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Indicator BacktesterOverview This professional-grade backtesting tool allows you to turn any indicator into a fully functional strategy without writing a single line of code. By using the "Source" inputs, you can link this backtester to the plots of your favorite indicators to analyze their historical performance, win rate, and drawdown. The standout feature of this tool is the Dynamic Risk-Based Position Sizing, which automatically calculates your trade quantity so that you lose a specific dollar amount (e.g., $50) if your Stop Loss is hit, regardless of how wide the gap is. How to Use Load your favorite indicator onto the chart. Load this Indicator Backtester strategy. In the "Settings" menu, map the Long/Short Entry Signals to the specific plots or "shapes" of your indicator. Choose your Exit Method and map the corresponding TP/SL levels or signals. Settings Breakdown 1. System Settings - Exit Method: - Price Levels: Uses specific price points for Take Profit and Stop Loss (ideal for indicators that plot target lines). - Signals: Uses trigger-based exits (ideal for indicators that show "Exit Now" shapes or color changes). 2. Risk Management - Use Risk-Based Sizing: - Enabled: The strategy calculates the quantity automatically. If your Stop Loss is 1% away or 10% away, your total loss will always equal the "Risk Amount." - Disabled: The strategy defaults to the quantity set in the "Properties" tab (e.g., % of Equity). - Risk Amount: The maximum amount of currency (e.g., USDT) you are willing to lose on a single trade. 3. Entries - Long Entry Signal: Select the indicator plot that triggers a buy. - Short Entry Signal: Select the indicator plot that triggers a sell. 4. Mode: Price Levels (Exit Method 1) - Long/Short TP Level: Select the plot representing your profit target price. - Long/Short SL Level: Select the plot representing your stop loss price. Note: These must be actual price values on the chart. 5. Mode: Signals (Exit Method 2) - Take Profit Signal: Select the plot that triggers a profit take. - Stop Loss Signal: Select the plot that triggers a stop loss exit.
Chiến lược Pine Script®
của imjayanth08
Swing Strategy Feature Set V [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set V includes concepts beginning with the letter "V" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Vertical Horizontal Filter Volume Positive Volume Index Negative Volume Index On-Balance Volume Price Volume Trend Volume Weighted Average Price Volume Zone Oscillator Vortex Indicator █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET V SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com As there are no built-in TradingView indicators for the VHF, VWAP and VZO values used in this script, code samples are provided in the relevant sections so that users can build their own Pine Script indicators. For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com Vertical Horizontal Filter (VHF) Filters As there is no built-in indicator for the VHF value used in this script, users can build their own VHF indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Vertical Horizontal Filter", shorttitle = "VHF", overlay = false) import TradingView/ta/12 as ta vhf_source = input.source(defval = close, title = 'VHF Source', group = 'Vertical Horizontal Filter (VHF)') vhf_length = input.int(defval = 28, minval = 1, title = 'VHF Length', group = 'Vertical Horizontal Filter (VHF)') vhf = ta.vhf(vhf_source, vhf_length) plot(vhf, color = color.blue) The VHF defaults are as follows: Source is set to "Close". Length is set to 28. Users can adjust the VHF inputs via strategy Settings/Inputs/VERTICAL HORIZONTAL FILTER (VHF). The VHF minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply VHF above-equal is set to false. VHF above-equal threshold is set to 0.0. Apply VHF below-equal is set to false. VHF below-equal threshold is set to 1.0. The VHF minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The VHF trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the VHF filters and adjust filter parameters via strategy Settings/Inputs/VHF FILTERS. Volume Filters The Volume minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The Volume trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the Volume filters and adjust filter parameters via strategy Settings/Inputs/VOLUME FILTERS. Positive Volume Index (PVI) Filters The PVI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PVI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PVI filters and adjust filter parameters via strategy Settings/Inputs/POSITIVE VOLUME INDEX (PVI) FILTERS. Negative Volume Index (NVI) Filters The NVI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The NVI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the NVI filters and adjust filter parameters via strategy Settings/Inputs/NEGATIVE VOLUME INDEX (NVI) FILTERS. On-Balance Volume (OBV) Filters The OBV minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The OBV trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the OBV filters and adjust filter parameters via strategy Settings/Inputs/ON-BALANCE VOLUME (OBV) FILTERS. Price Volume Trend (PVT) Filters The PVT minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PVT trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PVT filters and adjust filter parameters via strategy Settings/Inputs/PRICE VOLUME TREND (PVT) FILTERS. Volume Weighted Average Price (VWAP) Filters Although there is a built-in VWAP indicator, its output may differ from the calculation used in this script. As such, it is recommended that users build their own VWAP indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Volume Weighted Average Price", shorttitle = "VWAP", overlay = false) vwap_source = input.source(title = 'VWAP Source', defval = hlc3, group = 'Volume Weighted Average Price (VWAP)') vwap_anchor = input.bool(title = 'VWAP Anchor', defval = true, group = 'Volume Weighted Average Price (VWAP)') vwap = ta.vwap(vwap_source, vwap_anchor) plot(vwap, color = color.blue) The VWAP indicator defaults are as follows: Source is set to "HLC3". Anchor is set to true. Users can adjust the VWAP inputs via strategy Settings/Inputs/VOLUME WEIGHTED AVERAGE PRICE (VWAP). The default mode for the close above-equal/below VWAP filter (see generic filters section above) is set to "None". The default mode for the VWAP rejection filter (see generic filters section above) is set to "None". Users can apply the VWAP filters and adjust filter parameters via strategy Settings/Inputs/VWAP FILTERS. Volume Zone Oscillator (VZO) Filters As there is no built-in indicator for the VZO value used in this script, users can build their own VZO indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Volume Zone Oscillator", shorttitle = "VZO", overlay = false) import TradingView/ta/12 as ta vzo_length = input.int(defval = 14, minval = 1, title = 'VZO Length', group = 'Volume Zone Oscillator (VZO)') vzo = ta.vzo(vzo_length) plot(vzo, color = color.blue) The default length for the VZO is set to 14. Users can adjust the VZO length via strategy Settings/Inputs/VOLUME ZONE OSCILLATOR (VZO). The VZO minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply VZO above-equal is set to false. VZO above-equal threshold is set to -100. Apply VZO below-equal is set to false. VZO below-equal threshold is set to 100. The VZO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The VZO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the VZO filters and adjust filter parameters via strategy Settings/Inputs/VZO FILTERS. Vortex Indicator (VI) Filters The default length for the VI is set to 14. Users can adjust the VI length via strategy Settings/Inputs/VORTEX INDICATOR (VI). The VI above-equal/below VI signal filter is defined as an entry filter that evaluates the relative positioning of the VI value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the VI above-equal/below VI signal filter is set to "None". The VI bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the VI line and VI signal line is expanding or contracting over a configurable lookback period. The default VI bandwidth increasing/decreasing filter mode is set to "None". The default VI bandwidth increasing/decreasing lookback is set to 3. The VI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The VI signal minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The VI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The VI signal trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the VI filters and adjust filter parameters via strategy Settings/Inputs/VI FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set U [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set U includes concepts beginning with the letter "U" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Ulcer Index Ultimate Oscillator █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET U SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Ulcer Index (UI) Filters The UI indicator defaults are as follows: Source is set to "Close". Length is set to 14. Users can adjust the UI inputs via strategy Settings/Inputs/ULCER INDEX (UI). The UI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The UI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the UI filters and adjust filter parameters via strategy Settings/Inputs/UI FILTERS. Ultimate Oscillator (UO) Filters The UO indicator defaults are as follows: Fast length is set to 7. Medium length is set to 14. Slow length is set to 28. Users can adjust the Ultimate Oscillator inputs via strategy Settings/Inputs/ULTIMATE OSCILLATOR (UO). The UO minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply UO above-equal is set to false. UO above-equal threshold is set to 0. Apply UO below-equal is set to false. UO below-equal threshold is set to 100. The UO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The UO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the UO filters and adjust filter parameters via strategy Settings/Inputs/UO FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set T [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set T includes concepts beginning with the letter "T" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Tilson Moving Average Trend Trendline Triple Exponential Moving Average (TRIX) True Strength Index █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred indicator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Moving Average (MA) Double and Triple Trend Filters MA double and triple trend filters are defined as entry filters that evaluate the relative positioning of two or more MA values and invalidate trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when one MA is greater than or equal to another MA. "Below" returns true when one MA is less than another MA. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET T SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com As there are no built-in TradingView indicators for the TMA (T3) and TRIX values used in this script, code samples are provided in the relevant sections so that users can build their own Pine Script indicators. For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com Tilson Moving Average (TMA) Filters As there is no built-in indicator for the TMA (T3) value used in this script, users can build their own TMA (T3) indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Tilson Moving Average (T3)", shorttitle = "TMA (T3)", overlay = true) import TradingView/ta/12 as ta tma_1_source = input.source(title = 'TMA 1 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_1_length = input.int(title = 'TMA 1 Length', defval = 50, minval = 1, group = 'Tilson Moving Average (TMA)') vf_1 = input.float(title = 'TMA 1 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_1_colour = input.color(title = 'TMA 1 Colour', defval = color.green, group = 'Tilson Moving Average (TMA)') tma_2_source = input.source(title = 'TMA 2 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_2_length = input.int(title = 'TMA 2 Length', defval = 100, minval = 1, group = 'Tilson Moving Average (TMA)') vf_2 = input.float(title = 'TMA 2 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_2_colour = input.color(title = 'TMA 2 Colour', defval = color.orange, group = 'Tilson Moving Average (TMA)') tma_3_source = input.source(title = 'TMA 3 Source', defval = close, group = 'Tilson Moving Average (TMA)') tma_3_length = input.int(title = 'TMA 3 Length', defval = 200, minval = 1, group = 'Tilson Moving Average (TMA)') vf_3 = input.float(title = 'TMA 3 Volume Factor', defval = 0.7, minval = 0.0, maxval = 1.0, step = 0.05, group = 'Tilson Moving Average (TMA)') tma_3_colour = input.color(title = 'TMA 3 Colour', defval = color.red, group = 'Tilson Moving Average (TMA)') tma_1 = ta.t3(tma_1_source, tma_1_length, vf_1) tma_2 = ta.t3(tma_2_source, tma_2_length, vf_2) tma_3 = ta.t3(tma_3_source, tma_3_length, vf_3) plot(tma_1, color = tma_1_colour) plot(tma_2, color = tma_2_colour) plot(tma_3, color = tma_3_colour) Users can define up to three independent TMA (T3) series. The defaults are as follows: TMA 1: source = close, length = 50, volume factor = 0.7. TMA 2: source = close, length = 100, volume factor = 0.7. TMA 3: source = close, length = 200, volume factor = 0.7. Users can adjust the TMA inputs via strategy Settings/Inputs/TILSON MOVING AVERAGE (TMA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined TMA (T3). The default mode for all three TMA close above-equal/below filters is set to "None". Users can apply up to three independent TMA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: TMA 1 above-equal/below TMA 2 is set to "None". TMA 2 above-equal/below TMA 3 is set to "None". TMA 1 above-equal/below TMA 3 is set to "None". The TMA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined TMA is rejected exclusive of the other two TMAs. The default mode for the TMA rejection filter is set to "None". Users can apply the TMA filters and adjust filter parameters via strategy Settings/Inputs/TMA FILTERS. Trend Filters The trend filters in this section extend the generic basic and multi-part trend filters by applying the same logical framework to structurally defined peak and trough prices rather than to a continuous time-series. By operating on completed swing structures, these filters introduce an additional structural layer that differentiates between directional continuation and return line behaviour. This structural distinction necessitates the inclusion of return line variations alongside standard uptrend and downtrend conditions. Within this framework, peak-to-peak sequences define upper trend filters and trough-to-trough sequences define lower trend filters. A peak-to-peak upward structural progression is classified as a return line uptrend, while a peak-to-peak downward progression is classified as a downtrend. Conversely, a trough-to-trough upward structural progression is classified as an uptrend, while a trough-to-trough downward progression is classified as a return line downtrend. Upper trends include: Return line uptrends. Downtrends. Lower trends include: Uptrends. Return line downtrends. Below are links to my multi-part trend indicators, which can be used as visual aids for the relevant filter conditions included in this script: The upper and lower trend filter's defaults are as follows: Upper Trend mode is set to "None". Upper Trend count is set to 3. Lower Trend mode is set to "None". Lower Trend count is set to 3. When basic trend modes are selected, the trend count inputs are redundant and have no effect. Users can apply the trend filters via strategy Settings/Inputs/TREND FILTERS. Trendline Filters The trendline value calculations used in this script are based on those included in my trendlines indicator (link below for visual reference). Note that previous trendline values are not factored into the filter logic used in this script, only the most recent peak-to-peak (resistance) and trough-to-trough (support) lines are evaluated. The trendline rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined trendline value is rejected exclusive of the other trendline value. Four rejection modes are available: Support. Resistance. Support-turned-resistance. Resistance-turned-support. These operate asymmetrically depending on trade direction. For long entry conditions, the filter will only evaluate support and resistance-turned-support, both of which require a bullish rejection (i.e. price rejecting upward from the relevant trendline). For short entry conditions, the filter will only evaluate resistance and support-turned-resistance, both of which require a bearish rejection (i.e. price rejecting downward from the relevant trendline). The default trendline rejection filter mode is set to "None". Users can apply the trendline filter via strategy Settings/Inputs/TRENDLINE FILTERS. Triple Exponential Moving Average (TRIX) Filters As there is no built-in indicator for the TRIX values used in this script, users can build their own TRIX indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Triple Exponential Moving Average (TRIX)", shorttitle = "TRIX", overlay = false) import TradingView/ta/12 as ta trix_source = input.source(title = 'TRIX Source', defval = close, group = 'Triple Exponential Moving Average (TRIX)') trix_length = input.int(title = 'TRIX Length', defval = 14, minval = 1, group = 'Triple Exponential Moving Average (TRIX)') trix_signal_length = input.int(title = 'TRIX Signal Length', defval = 9, minval = 1, group = 'Triple Exponential Moving Average (TRIX)') trix_exponential = input.bool(title = 'TRIX Exponential', defval = true, group = 'Triple Exponential Moving Average (TRIX)') trix_colour = input.color(title = 'TRIX Colour', defval = color.yellow, group = 'Triple Exponential Moving Average (TRIX)') trix_sig_colour = input.color(title = 'TRIX Signal Colour', defval = color.blue, group = 'Triple Exponential Moving Average (TRIX)') trix_hist_pos_colour = input.color(title = 'TRIX Histogram Positive Colour', defval = color.rgb(76, 175, 79, 80) , group = 'Triple Exponential Moving Average (TRIX)') trix_neg_colour = input.color(title = 'TRIX Histogram Negative Colour', defval = color.rgb(255, 82, 82, 80), group = 'Triple Exponential Moving Average (TRIX)') = ta.trix(trix_source, trix_length, trix_signal_length, trix_exponential) plot(trix, color = trix_colour) plot(trix_signal, color = trix_sig_colour) plot(trix_hist, color = trix_hist >= 0 ? trix_hist_pos_colour : trix_neg_colour, style = plot.style_columns) The TRIX defaults are as follows: Source is set to "Close". Length is set to 14. Signal length is set to 9. Exponential mode is set to true. Users can adjust the TRIX inputs via strategy Settings/Inputs/TRIPLE EXPONENTIAL MOVING AVERAGE (TRIX). The TRIX above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the TRIX value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the TRIX above-equal/below signal filter is set to "None". The default mode for the TRIX Histogram above-equal/below zero filter (see generic filters section above) is set to "None". The TRIX Histogram minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The TRIX Histogram trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the TRIX filters and adjust filter parameters via strategy Settings/Inputs/TRIX FILTERS. True Strength Index (TSI) Filters The TSI defaults are as follows: Long length is set to 25. Short length is set to 13. Signal length is set to 13. Users can adjust the TSI inputs via strategy Settings/Inputs/TRUE STRENGTH INDEX (TSI). The TSI above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the TSI value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the TSI above-equal/below signal filter is set to "None". The default mode for the TSI above-equal/below zero filter (see generic filters section above) is set to "None". The default mode for the TSI Signal above-equal/below zero filter (see generic filters section above) is set to "None". The TSI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The TSI Signal minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The TSI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The TSI Signal trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the TSI filters and adjust filter parameters via strategy Settings/Inputs/TSI FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Voce Eterna - BTC Safe Final🚀 Strategic Trading Framework: The "Peak Reset" Logic We have engineered an advanced trading algorithm tailored for Bitcoin Futures, designed with a core focus on extreme capital protection. The following 10 keywords define the architecture of this strategy: High-Water Mark: The system continuously tracks the maximum equity value achieved, establishing a new baseline for protection at every peak. Capital Preservation: Our primary objective is to safeguard the initial €2,000 investment through rigorous risk controls. Risk Mitigation: Each trade is strictly managed to eliminate catastrophic losses and ensure long-term sustainability. Trend Filtering: By utilizing a 200-period SMA filter, the algorithm operates exclusively during confirmed Bull Market conditions. Trailing Stop: Profit is dynamically followed, allowing the strategy to capture the maximum upside of a trend before exiting. Profit Locking: Once a profit peak is established, the system secures gains by preventing the equity from retracing significantly. Dynamic Exit: Rather than relying on fixed targets, the algorithm exits positions based on real-time market exhaustion and trend decay. Whipsaw Protection: Optimized filters are in place to ignore "noise" and false signals common during sideways market volatility. Automated Reset: An autonomous "kill-switch" triggers if the equity drops below a specific percentage of the peak, halting all operations to save profit. Evidence-Based Backtesting: Rigorous analysis of 2026 data ensures the strategy remains resilient against the high volatility of the crypto market. The mission is clear: we do not aim to beat the market every single day, but rather to survive the downturns in order to thrive during the rallies. 📈🛡️
Chiến lược Pine Script®
của abcdddiego
Swing Strategy Feature Set S [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set S includes concepts beginning with the letter "S" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Schaff Trend Cycle Sentiment Zone Oscillator Stochastic Oscillator Stochastic Relative Strength Index Super Trend █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred indicator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET S SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com As there are no built-in TradingView indicators for the STC and SZO values used in this script, code samples are provided in the relevant sections so that users can build their own Pine Script indicators. For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com Schaff Trend Cycle (STC) Filters As there is no built-in indicator for the STC value used in this script, users can build their own STC indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Schaff Trend Cycle", shorttitle = "STC", overlay = false) import TradingView/ta/12 as ta stc_source = input.source(defval = close, title = 'STC Source', group = 'Schaff Trend Cycle (STC)') stc_fast_length = input.int(defval = 23, minval = 1, title = 'STC Fast Length', group = 'Schaff Trend Cycle (STC)') stc_slow_length = input.int(defval = 50, minval = 1, title = 'STC Slow Length', group = 'Schaff Trend Cycle (STC)') stc_cycle_length = input.int(defval = 10, minval = 1, title = 'STC Cycle Length', group = 'Schaff Trend Cycle (STC)') stc_d1_length = input.int(defval = 3, minval = 1, title = 'STC D1 Length', group = 'Schaff Trend Cycle (STC)') stc_d2_length = input.int(defval = 3, minval = 1, title = 'STC D2 Length', group = 'Schaff Trend Cycle (STC)') stc = ta.stc(stc_source, stc_fast_length, stc_slow_length, stc_cycle_length, stc_d1_length, stc_d2_length) plot(stc, color = color.blue) The STC indicator defaults are as follows: Source is set to "Close". Fast length is set to 23. Slow length is set to 50. Cycle length is set to 10. D1 length is set to 3. D2 length is set to 3. Users can adjust the STC inputs via strategy Settings/Inputs/SCHAFF TREND CYCLE (STC). The STC minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply STC above-equal is set to false. STC above-equal threshold is set to 0. Apply STC below-equal is set to false. STC below-equal threshold is set to 100. The STC minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The STC trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the STC filters and adjust filter parameters via strategy Settings/Inputs/STC FILTERS. Sentiment Zone Oscillator (SZO) Filters As there is no built-in indicator for the SZO value used in this script, users can build their own SZO indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Sentiment Zone Oscillator", shorttitle = "SZO", overlay = false) import TradingView/ta/12 as ta szo_source = input.source(defval = close, title = 'SZO Source', group = 'Sentiment Zone Oscillator (SZO)') szo_length = input.int(defval = 14, minval = 1, title = 'SZO Length', group = 'Sentiment Zone Oscillator (SZO)') szo = ta.szo(szo_source, szo_length) plot(szo, color = color.blue) The SZO indicator defaults are as follows: Source is set to "Close". Length is set to 14. 
Users can adjust the SZO inputs via strategy Settings/Inputs/SENTIMENT ZONE OSCILLATOR (SZO). The default mode for the SZO above-equal/below zero filter (see generic filters section above) is set to "None". The SZO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The SZO trend filter (see generic filters section above) defaults are as follows:
 Mode is set to "None". Trend count is set to 3. Users can apply the SZO filters and adjust filter parameters via strategy Settings/Inputs/SZO FILTERS. Stochastic Oscillator (SO) Filters The SO indicator defaults are as follows: Length is set to 14. %K smoothing is set to 1. %D smoothing is set to 3. 
Users can adjust the SO inputs via strategy Settings/Inputs/STOCHASTIC OSCILLATOR (SO). The SO %K above-equal/below %D filter is defined as an entry filter that evaluates the relative positioning of the SO %K and SO %D values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the SO %K above-equal/below %D filter is set to "None". The SO %K minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply SO %K above-equal is set to false. SO %K above-equal threshold is set to 0. Apply SO %K below-equal is set to false. SO %K below-equal threshold is set to 100. The SO %D minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply SO %D above-equal is set to false. SO %D above-equal threshold is set to 0. Apply SO %D below-equal is set to false. SO %D below-equal threshold is set to 100. The SO %K minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The SO %D minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The SO %K trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The SO %D trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the SO filters and adjust filter parameters via strategy Settings/Inputs/SO FILTERS. Stochastic Relative Strength Index (SRSI) Filters The SRSI indicator defaults are as follows: Source is set to "Close". RSI length is set to 14. Stoch length is set to 14. %K smoothing is set to 3. %D smoothing is set to 3. Users can adjust the SRSI inputs via strategy Settings/Inputs/STOCHASTIC RELATIVE STRENGTH INDEX (SRSI). The SRSI %K above-equal/below %D filter is defined as an entry filter that evaluates the relative positioning of the SRSI %K and SRSI %D values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the SRSI %K above-equal/below %D filter is set to "None". The SRSI %K minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply SRSI %K above-equal is set to false. SRSI %K above-equal threshold is set to 0. Apply SRSI %K below-equal is set to false. SRSI %K below-equal threshold is set to 100. The SRSI %D minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply SRSI %D above-equal is set to false. SRSI %D above-equal threshold is set to 0. Apply SRSI %D below-equal is set to false. SRSI %D below-equal threshold is set to 100. The SRSI %K minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows:
 Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The SRSI %D minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The SRSI %K trend filter (see generic filters section above) defaults are as follows:
 
 Mode is set to "None". Trend count is set to 3. The SRSI %D trend filter (see generic filters section above) defaults are as follows:
 
 Mode is set to "None". Trend count is set to 3. Users can apply the SRSI filters and adjust filter parameters via strategy Settings/Inputs/SRSI FILTERS. Super Trend (ST) Filters The ST indicator defaults are as follows: 
 ATR length is set to 10. Factor (ATR multiplier) is set to 3.0. 
 Users can adjust the ST inputs via strategy Settings/Inputs/SUPER TREND (ST). The default mode for the close above-equal/below ST filter (see generic filter section above) is set to "None". Users can apply the ST filters via strategy Settings/Inputs/ST FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Linda Bradford Raschke Quantitative Trading JLKJ Formula█ OVERVIEW This strategy implements a statistically-driven mean reversion system optimized for liquid instruments. It combines Bollinger Bands and Z-score analysis to identify statistically significant oversold/oversold conditions while employing institutional-grade risk management protocols. █ CONCEPTS The strategy operates on three core quantitative principles: 1 — Mean Reversion Detection: Identifies price extremes using a 20-period Bollinger Bands (2.0 std) combined with a Z-score threshold. Entries are triggered when price deviates beyond statistical norms. 2 — Adaptive Position Sizing: Implements a Kelly Criterion-based algorithm that dynamically adjusts exposure based on historical win rate, average win/loss ratio, and recent equity performance. 3 — Circuit Breakers: Features proprietary risk guards including Daily Loss Limits and Max Consecutive Losses. Trading automatically halts when predefined drawdown thresholds are met. █ FEATURES • Trend Filter: Optional EMA alignment (20/50) ensures mean reversion trades align with the broader trend. • Volatility Filter: Automatically filters low/high volatility environments using ATR%. • Dynamic Kelly Sizing: Starts conservatively (0.5% risk) and mathematically optimizes position size as trade history accumulates. • Real-Time Dashboard: Displays Z-Score, Kelly %, Win Rate, Daily Loss %, and System Status. • Compatibility: Works on all timeframes. Optimized for 5min–1h charts. █ HOW TO USE 1. Apply the strategy to your chart (default settings are conservative). 2. Monitor the statistics table in the top-right corner. 3. The system trades automatically. Do not manually override signals. 4. Review the "Trading Status" indicator; if status is "HALTED", the circuit breakers are active. █ LIMITATIONS • This is a mean reversion strategy. It underperforms in strongly trending, low-volatility environments without pullbacks. • Backtest results are hypothetical and do not guarantee future results. • Sufficient trade history (20+ trades) is required for the Kelly formula to reach optimal sizing. BACKTEST BEFORE USE.
Chiến lược Pine Script®
của uzair2join
Swing Strategy Feature Set R [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set R includes concepts beginning with the letter "R" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Random Walk Index Range Ratio Rank Correlation Index Rate of Change Relative Strength Index █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET R SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Random Walk Index (RWI) Filters As there is no built-in indicator for the RWI values used in this script, users can build their own RWI indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Random Walk Index", shorttitle = "RWI", overlay = false) import TradingView/ta/12 as ta rwi_length = input.int(title = 'RWI Length', defval = 14, minval = 1, group = 'Random Walk Index (RWI)') = ta.rwi(rwi_length) plot(rwi_high, color = color.green) plot(rwi_low, color = color.red) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com By default, the RWI length is set to 14. Users can adjust the RWI length via strategy Settings/Inputs/RANDOM WALK INDEX (RWI). The RWI high above-equal/below RWI low filter is defined as an entry filter that evaluates the relative positioning of the RWI high and RWI low values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the RWI high above-equal/below RWI low filter is set to "None". The RWI high above-equal/below zero filter is defined as an entry filter that evaluates the RWI high value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the RWI high above-equal/below zero filter is set to "None". The RWI low above-equal/below zero filter is defined as an entry filter that evaluates the RWI low value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the RWI low above-equal/below zero filter is set to "None". The RWI bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the RWI high and RWI low values is expanding or contracting over a configurable lookback period. The default mode for the RWI bandwidth increasing/decreasing filter is set to "None". The default RWI bandwidth increasing/decreasing lookback is set to 3. The RWI high minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The RWI low minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The RWI high trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The RWI low trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the RWI filters and adjust filter parameters via strategy Settings/Inputs/RWI FILTERS. Range Ratio Filters The range ratio value calculations used in this script are the same as those included in my retracement and extension ratios indicator. Link below: For long trades, the range ratio filters evaluate swing low range ratios. Conversely, for short trades, the range ratio filters evaluate swing high range ratios. The range ratio increasing/decreasing filter is defined as an entry filter that evaluates whether the most recent range ratio has expanded or contracted relative to the preceding value, invalidating trade signals that do not satisfy user-defined criteria. The default mode for the range ratio increasing/decreasing filter is set to "None". The range ratio minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply range ratio above-equal is set to false. Range ratio above-equal threshold is set to 0. Apply range ratio below-equal is set to false. Range ratio below-equal threshold is set to 100. Users can apply the range ratio filters and adjust filter parameters via strategy Settings/Inputs/RANGE RATIO FILTERS. Rank Correlation Index (RCI) Filters The RCI indicator defaults are as follows: Source is set to "Close". Length is set to 10. Users can adjust the RCI inputs via strategy Settings/Inputs/RANK CORRELATION INDEX (RCI). The RCI minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply RCI above-equal is set to false. RCI above-equal threshold is set to -100. Apply RCI below-equal is set to false. RCI below-equal threshold is set to 100. The RCI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The RCI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the RCI filters and adjust filter parameters via strategy Settings/Inputs/RCI FILTERS. Rate of Change (ROC) Filters The ROC indicator defaults are as follows: Source is set to "Close". Length is set to 9. Users can adjust the ROC inputs via strategy Settings/Inputs/RATE OF CHANGE (ROC). The ROC above-equal/below zero filter is defined as an entry filter that evaluates the ROC value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the ROC above-equal/below zero filter is set to "None". The ROC minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The ROC trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the ROC filters and adjust filter parameters via strategy Settings/Inputs/ROC FILTERS. Relative Strength Index (RSI) Filters The RSI indicator defaults are as follows: Source is set to "Close". Length is set to 14. Users can adjust the RSI inputs via strategy Settings/Inputs/RELATIVE STRENGTH INDEX (RSI). The RSI minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply RSI above-equal is set to false. RSI above-equal threshold is set to 0. Apply RSI below-equal is set to false. RSI below-equal threshold is set to 100. The RSI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The RSI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the RSI filters and adjust filter parameters via strategy Settings/Inputs/RSI FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set P [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set P includes concepts beginning with the letter "P" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Parabolic Stop and Reverse Peak/Trough Colour Percentage Price Oscillator Pivot Points Price Momentum Oscillator Price Zone Oscillator Pring's Special K █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred oscillator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET P SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Parabolic Stop and Reverse (PSAR) Filters The PSAR indicator defaults are as follows: Start is set to 0.02. Increment is set to 0.02. Maximum is set to 0.2. Users can adjust the PSAR inputs via strategy Settings/Inputs/PARABOLIC STOP AND REVERSE (PSAR). The default mode for the close above-equal/below PSAR filter (see generic filters section above) is set to "None". Users can apply the PSAR filters via strategy Settings/Inputs/PSAR FILTERS. Peak/Trough Colour Filters The peak/trough colour filter is an entry filter that evaluates the colour of the candle that forms the most recent peak or trough price and invalidates trade signals if the candle does not meet the user-defined colour criteria. For short trades, the candle forming the peak price is evaluated. Conversely, for long trades, the candle forming the trough price is evaluated. The default mode for the peak/trough colour filter is set to "None". Users can apply the peak/trough colour filter via strategy Settings/Inputs/PEAK TROUGH COLOUR FILTERS. Percentage Price Oscillator (PPO) Filters The PPO indicator defaults are as follows: Source is set to "Close". Fast length is set to 12. Slow length is set to 26. Signal length is set to 9. Users can adjust the PPO inputs via strategy Settings/Inputs/PERCENTAGE PRICE OSCILLATOR (PPO). The PPO above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the PPO value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the PPO above-equal/below signal filter is set to "None". The default mode for the PPO Histogram above-equal/below zero filter (see generic filters section above) is set to "None". The PPO Histogram minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PPO Histogram trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PPO filters and adjust filter parameters via strategy Settings/Inputs/PPO FILTERS. Pivot Points (PP) Filters The default type for the PP indicator is set to "Traditional". Users can adjust the PP type via strategy Settings/Inputs/PIVOT POINTS (PP). Users can apply up to eleven independent close above-equal/below filters (see generic filters section above), one for each PP value. The default mode for all eleven close above-equal/below PP filters is set to "None". The PP rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined PP value is rejected exclusive of the other PP values. The default PP rejection filter mode is set to "None". Users can apply the PP filters via strategy Settings/Inputs/PP FILTERS. Price Momentum Oscillator (PMO) Filters The PMO indicator defaults are as follows: Source is set to "Close". Fast length is set to 35. Slow length is set to 20. Signal length is set to 10. Users can adjust the PMO inputs via strategy Settings/Inputs/PRICE MOMENTUM OSCILLATOR (PMO). The PMO above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the PMO value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the PMO above-equal/below signal filter is set to "None". The default mode for the PMO above-equal/below zero filter (see generic filters section above) is set to "None". The default mode for the PMO Signal above-equal/below zero filter (see generic filters section above) is set to "None". The PMO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PMO signal minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PMO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The PMO signal trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PMO filters and adjust filter parameters via strategy Settings/Inputs/PMO FILTERS. Price Zone Oscillator (PZO) Filters As there is no built-in indicator for the PZO value used in this script, users can build their own PZO indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Price Zone Oscillator", shorttitle = "PZO", overlay = false) import TradingView/ta/12 as ta pzo_length = input.int(defval = 14, minval = 0, title = 'PZO Length', group = 'Price Zone Oscillator (PZO)') pzo = ta.pzo(pzo_length) plot(pzo) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The default PZO length is set to 14. Users can adjust the PZO length via strategy Settings/Inputs/PRICE ZONE OSCILLATOR (PZO). PZO minimum and maximum boundary filters (see generic filters section above) are included for the PZO value, the defaults are as follows: Apply PZO above-equal is set to false PZO above-equal threshold is set to -100. Apply PZO below-equal is set to false PZO below-equal threshold is set to 100. The PZO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PZO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PZO filters and adjust filter parameters via strategy Settings/Inputs/PZO FILTERS. Pring Special K (PSK) Filters The PSK indicator defaults are as follows: Source is set to "Close". Signal length 1 is set to 100. Signal length 2 is set to 100. Users can adjust the PSK inputs via strategy Settings/Inputs/PRING'S SPECIAL K (PSK). The PSK above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the PSK value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the PSK above-equal/below signal filter is set to "None". The default mode for the PSK above-equal/below zero filter (see generic filters section above) is set to "None". The default mode for the PSK Signal above-equal/below zero filter (see generic filters section above) is set to "None". The PSK minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PSK signal minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The PSK trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The PSK signal trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the PSK filters and adjust filter parameters via strategy Settings/Inputs/PSK FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set M [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set M includes concepts beginning with the letter "M" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Money Flow Index Momentum Moving Averages Moving Average Convergence Divergence Moving average types included in the feature set are as follows: Exponential Moving Average Fractal Adaptive Moving Average Moving Average Resting Point Relative Moving Average Simple Moving Average Triangular Moving Average Volume Weighted Moving Average Weighted Moving Average █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred oscillator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Moving Average (MA) Double and Triple Trend Filters MA double and triple trend filters are defined as entry filters that evaluate the relative positioning of two or more MA values and invalidate trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when one MA is greater than or equal to another MA. "Below" returns true when one MA is less than another MA. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET M SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Money Flow Index (MFI) Filters The default length for the MFI is set to 14. Users can adjust the MFI length via strategy Settings/Inputs/MONEY FLOW INDEX (MFI). MFI minimum and maximum boundary filters (see generic filters section above) are included for the MFI value, the defaults are as follows: Apply MFI above-equal is set to false MFI above-equal threshold is set to 0. Apply MFI below-equal is set to false MFI below-equal threshold is set to 100. The MFI minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The MFI trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the MFI filters and adjust filter parameters via strategy Settings/Inputs/MFI FILTERS. Momentum (MOM) Filters The MOM defaults are as follows: Source is set to "Close". Length is set to 10. Users can adjust the MOM inputs via strategy Settings/Inputs/MOMENTUM (MOM). The default mode for the MOM above-equal/below zero filter (see generic filters section above) is set to "None". The MOM minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The MOM trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the MOM filters and adjust filter parameters via strategy Settings/Inputs/MOM FILTERS. Moving Average (MA) Filters The Moving Average Resting Point (MARP) value calculations used in this script are the same as those included in my MARP indicator. Link below: As there is no built-in indicators for the FRAMA, RMA or TRIMA values used in this script, users can build their own indicators in Pine Script by copying the following code samples and pasting them into new indicators separately: //@version=6 indicator("Fractal Adaptive Moving Average", shorttitle = "FRAMA", overlay = true) import TradingView/ta/12 frama_source = input.source(close, 'FRAMA Source', group = 'Fractal Adaptive Moving Average (FRAMA)') frama_length = input.int(50, 'FRAMA Length', group = 'Fractal Adaptive Moving Average (FRAMA)') frama_colour = input.color(color.green, 'FRAMA Colour', group = 'Fractal Adaptive Moving Average (FRAMA)') frama = ta.frama(frama_source, frama_length) plot(frama, color = frama_colour) //@version=6 indicator("Relative Moving Average", shorttitle = "RMA", overlay = true) import TradingView/ta/12 rma_source = input.source(close, 'RMA Source', group = 'Relative Moving Average (RMA)') rma_length = input.int(50, 'RMA Length', group = 'Relative Moving Average (RMA)') rma_colour = input.color(color.green, 'RMA Colour', group = 'Relative Moving Average (RMA)') rma = ta.rma(rma_source, rma_length) plot(rma, color = rma_colour) //@version=6 indicator("Triangular Moving Average", shorttitle = "TRIMA", overlay = true) import TradingView/ta/12 trima_source = input.source(close, 'TRIMA Source', group = 'Triangular Moving Average (TRIMA)') trima_length = input.int(50, 'TRIMA Length', group = 'Triangular Moving Average (TRIMA)') trima_colour = input.color(color.green, 'TRIMA Colour', group = 'Triangular Moving Average (TRIMA)') trima = ta.trima(trima_source, trima_length) plot(trima, color = trima_colour) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com Users can define up to three independent MA series. The defaults are as follows: MA 1: type = EMA, source = close, length = 50. MA 2: type = EMA, source = close, length = 100. MA 3: type = EMA, source = close, length = 200. Source is redundant for MARP as the indicator uses peak and trough prices by default. Users can adjust the MA inputs via strategy Settings/Inputs/MOVING AVERAGE (MA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined MA. The default mode for all three close above-equal/below MA filters is set to "None". Users can apply up to three independent MA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: MA 1 above-equal/below MA 2 is set to "None". MA 2 above-equal/below MA 3 is set to "None". MA 1 above-equal/below MA 3 is set to "None". The MA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined MA is rejected exclusive of the other two MAs. The default MA rejection filter mode is set to "None". Users can apply the MA filters and adjust filter parameters via strategy Settings/Inputs/MA FILTERS. Moving Average Convergence Divergence (MACD) Filters The MACD defaults are as follows: Source is set to "Close". Fast length is set to 12. Slow length is set to 26. Signal length is set to 9. Users can adjust the MACD inputs via strategy Settings/Inputs/MOVING AVERAGE CONVERGENCE DIVERGENCE (MACD). The MACD above-equal/below signal filter is defined as an entry filter that evaluates the relative positioning of the MACD value and its signal line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the MACD above-equal/below signal filter is set to "None". The default mode for the MACD Histogram above-equal/below zero filter (see generic filters section above) is set to "None". The MACD Histogram minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The MACD Histogram trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the MACD filters and adjust filter parameters via strategy Settings/Inputs/MACD FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set L [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set L includes concepts beginning with the letter "L" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Linear Regression Curve █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET L SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Linear Regression Curve (LRC) As there is no built-in indicator for the LRC value used in this script, users can build their own LRC indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Linear Regression Curve", shorttitle = "LRC", overlay = true) lrc_source = input.source(close, 'LRC Source', group = 'Linear Regression Curve (LRC)') lrc_length = input.int(14, 'LRC Length', group = 'Linear Regression Curve (LRC)') lrc = ta.linreg(lrc_source, lrc_length, 0) plot(lrc) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The LRC defaults are as follows: Source is set to "Close". Length is set to 14. Users can adjust the LRC inputs via strategy Settings/Inputs/LINEAR REGRESSION CURVE (LRC).
 The default mode for the close above-equal/below LRC filter (see generic filters section above) is set to "None". The LRC minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. By default, the LRC basic rejection filter (see generic filters section above) is set to false. The LRC trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the LRC filters and adjust filter parameters via strategy Settings/Inputs/LRC FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set K [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set K includes concepts beginning with the letter "K" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Kaufman Adaptive Moving Average Kaufman Efficiency Ratio Keltner Channels Klinger Volume Oscillator █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Above-Equal/Below Zero Filter The above-equal/below zero filter is defined as an entry filter that evaluates zero centred oscillator values relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the oscillator value is greater than or equal to zero. "Below" returns true when the oscillator value is less than zero. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Moving Average (MA) Double and Triple Trend Filters MA double and triple trend filters are defined as entry filters that evaluate the relative positioning of two or more MA values and invalidate trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when one MA is greater than or equal to another MA. "Below" returns true when one MA is less than another MA. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET K SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Kaufman Adaptive Moving Average (KAMA) Filters Users can define up to three independent KAMA series. The defaults are as follows: KAMA 1: source = close, ER length = 50, fast length = 2, slow length = 30. KAMA 2: source = close, ER length = 100, fast length = 2, slow length = 30. KAMA 3: source = close, ER length = 200, fast length = 2, slow length = 30. Users can adjust the KAMA inputs via strategy Settings/Inputs/KAUFMAN ADAPTIVE MOVING AVERAGE (KAMA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined KAMA. The default mode for all three KAMA close above-equal/below filters is set to "None". Users can apply up to three independent KAMA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: KAMA 1 above-equal/below KAMA 2 is set to "None". KAMA 2 above-equal/below KAMA 3 is set to "None". KAMA 1 above-equal/below KAMA 3 is set to "None". The KAMA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined KAMA is rejected exclusive of the other two KAMAs. The default KAMA rejection filter mode is set to "None". Users can apply the KAMA filters and adjust filter parameters via strategy Settings/Inputs/KAMA FILTERS. Kaufman Efficiency Ratio (KER) Filters As there is no built-in indicator for the KER value used in this script, users can build their own KER indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Kaufman Efficiency Ratio", shorttitle = "KER", overlay = false) import TradingView/ta/12 as ta ker_source = input.source(close, 'KER Source', group = 'Kaufman Efficiency Ratio (KER)') ker_length = input.int(10, 'KER Length', group = 'Kaufman Efficiency Ratio (KER)') ker = ta.er(ker_source, ker_length) plot(ker) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com KER minimum and maximum boundary filters (see generic filters section above) are included for the KER value, the defaults are as follows: Apply KER above-equal is set to false KER above-equal threshold is set to 0. Apply KER below-equal is set to false KER below-equal threshold is set to 1. The KER minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The KER trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the KER filters and adjust filter parameters via strategy Settings/Inputs/KAUFMAN EFFICIENCY RATIO (KER) FILTERS. Keltner Channels (KC) Filters The KC bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the KC upper and lower values is expanding or contracting over a configurable lookback period. The default mode for the KC bandwidth increasing/decreasing filter is set to "None". The default KC bandwidth increasing/decreasing lookback is set to 3. Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each KC value (upper, middle and lower). The default mode for all three KC close above-equal/below filters is set to "None". The KC rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined KC value is rejected exclusive of the other KC values. The default KC rejection filter mode is set to "None". Users can apply the KC filters and adjust filter parameters via strategy Settings/Inputs/KELTNER CHANNELS (KC) FILTERS. Klinger Volume Oscillator (KVO) Filters As there is no built-in indicator for the KVO value used in this script, users can build their own KVO indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator(title = "Klinger Volume Oscillator", shorttitle = "KVO", overlay = false) import TradingView/ta/12 as ta = ta.kvo(34, 55, 13) plot(kvo) plot(kvo_trigger, color = color.green) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The KVO above-equal/below trigger filter is defined as an entry filter that evaluates the relative positioning of the KVO value and its trigger line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the KVO above-equal/below trigger filter is set to "None". The default mode for the KVO above-equal/below zero filter (see generic filters section above) is set to "None". The default mode for the KVO trigger above-equal/below zero filter (see generic filters section above) is set to "None". The KVO minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The KVO trigger minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The KVO trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. The KVO trigger trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the KVO filters and adjust filter parameters via strategy Settings/Inputs/KLINGER VOLUME OSCILLATOR (KVO) FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Yzkvng SMC Confirmations & webhookWhat PineScript Does Monitors price action Detects trading signals Sends alert() with JSON data What TradingView Does Shows popup notification Sends HTTP POST to webhook URL Stores in console logs What Your Backend Does Receives the POST request Logs the data Updates database Sends notifications Places trades (if automated) All Three Happen Together When PineScript detects a signal: Instantly: Popup appears on TradingView Instantly: HTTP request sent to backend Simultaneously: Both happen at the same time
Chiến lược Pine Script®
của mikecheq5
WarrIA Oracle - Predictive Probability SystemWarrIA Oracle - Predictive Probability System Complementary indicator of the WarrIA PRO Ecosystem. Advanced statistical system that analyzes similarity patterns and calculates the probability of success or loss for ongoing trades in real time. --- ⚙️ How It Works WarrIA Oracle uses historical pattern matching to evaluate the current open trade against a database of past trades executed by the WarrIA PRO Trade System. The system identifies statistically similar setups based on multiple dimensions and provides: ✦ Probability of success/loss for the current open position ✦ Statistical similarity scoring against historical trades ✦ Real-time predictive analysis that updates as market conditions evolve ✦ Complementary layer of confidence for trade management decisions WarrIA Oracle is designed to work in conjunction with the WarrIA PRO Institutional-Grade Trade System, providing an additional decision-support layer for position management. --- 💎 Part of the WarrIA PRO Ecosystem WarrIA Oracle is one of 4 proprietary technologies in the WarrIA PRO Ecosystem: ✦ WarrIA PRO Institutional-Grade Trade System - Core multidimensional trading platform integrating WarrIA Score System (7 dimensions), WarrIA Shield System (6 filters + 12 anti-trap metrics), WarrIA WSI Detection System, and WarrIA Institutional Risk Control System (WFO Panel + Risk Limits Panel). ✦ WarrIA Oracle - Predictive probability system for ongoing trades (this indicator). ✦ WarrIA Smart Money Narratives Autopilot - Real-time detection of direction and strength of Whale and Institutional movements. ✦ WarrIA Chart Patterns Analyzer - Chart and candlestick pattern identification based on specialized literature metrics (Bulkowski). --- 📊 Historical Backtesting Results (Internal Pre-Operational Audit) The following metrics are based on historical backtesting of the WarrIA PRO portfolio and do not guarantee future results: Total Trades Analyzed: 3,706 Average Win Rate: 97.83% Total Portfolio Return: +1,003.62% These results reflect backtesting conditions with specific parameters for demonstration purposes. Real trading results may differ significantly. --- 🔐 Registered and Protected Intellectual Properties INPI Brazil: BR512026000273-7 INPI Brazil: BR512026000286-9 U.S. Copyright: 1-15078649821 --- 🧠 Access the WarrIA PRO Ecosystem Free Trial, plans, personalized onboarding (100% guided by our AI Specialist), and full details: warria.io --- ⚠️ Risk Disclaimer Past performance does not guarantee future results. All metrics shown are based on historical backtesting with specific parameters for demonstration purposes only. This is an educational tool designed for knowledge and know-how transfer, not financial advice. Users are solely responsible for their own investment decisions. Never risk capital you cannot afford to lose. @ 2025 WarrIA PRO | All Rights Reserved | warria.io
Chiến lược Pine Script®
của marcus_loureiro
WarrIA PRO - Institutional-Grade Trade SystemWarrIA PRO - Institutional-Grade Trade System Institutional-grade multidimensional trading platform for the cryptocurrency market. Part of the WarrIA PRO Ecosystem - an algorithmic trading ecosystem designed to provide retail traders with institutional-level tools historically restricted to major market players. --- ⚙️ Proprietary Architecture The WarrIA PRO Institutional-Grade Trade System integrates 4 proprietary sub-systems into a single multidimensional platform: ✦ WarrIA Score System - Exclusive multidimensional scoring architecture. 7 integrated high-impact dimensions for real-time setup detection and validation: On-Chain, WSI Detection (Whale/Smart Money/Institutional), Market Structure and Profile, Money Flow Confluence, and other institutional-grade metrics. ✦ WarrIA Shield System - Protective architecture performing double-check validation of setups. 6 interdisciplinary filters composed of institutional-grade multidisciplinary metrics plus 12 institutional anti-trap metrics. Any single fail blocks the signal entirely. ✦ WarrIA WSI Detection System - Exclusive detection system. Identifies and measures, in real time, the direction and strength of activities from the Core Actors of the crypto market (Whales, Institutions, and Smart Money). Includes interactive WSI Activity Panel with consolidated scores, Z-Scores by actor, Status/Action/Method tracking, WSI Traps detection, and WSI Imbalance analysis. ✦ WarrIA Institutional Risk Control System - Robust statistical architecture composed of: - WFO Panel (Walk-Forward Optimization): Results segmented by month, quarter, and year. Integrated Advanced Risk Metrics: VaR, CVaR, Monte Carlo Simulation, Sharpe/Sortino/Calmar Ratios, and Kelly Criterion for Position Sizing. - Institutional Risk Limits Panel: Customizable cockpit for strict control of daily, weekly, monthly, and total (max DD) portfolio risk limits. Automatic system halt upon threshold breach. --- 💎 WarrIA PRO Ecosystem - Complementary Technologies The Trade System is the core platform of a broader ecosystem that also includes 3 complementary proprietary technologies (exclusive to PRO subscribers): ✦ WarrIA Oracle - Advanced statistical similarity analysis plus probability of success/loss for ongoing trades. ✦ WarrIA Smart Money Narratives Autopilot - Real-time detection of direction and strength of Whale and Institutional movements across the full portfolio. ✦ WarrIA Chart Patterns Analyzer - Identification and measurement of chart and candlestick patterns based on specialized literature metrics (Bulkowski). --- 📊 Historical Backtesting Results (Internal Pre-Operational Audit) The following metrics are based on historical backtesting and do not guarantee future results: Total Trades Analyzed: 3,706 Average Win Rate: 97.83% Total Portfolio Return: +1,003.62% Audit Parameters: Base Capital $20k (USD) | Risk Per Trade: 15% (BTC: 20%) These results reflect backtesting conditions with specific parameters for demonstration purposes. Real trading results may differ significantly. --- 🔐 Registered and Protected Intellectual Properties INPI Brazil: BR512026000273-7 INPI Brazil: BR512026000286-9 U.S. Copyright: 1-15078649821 --- 🧠 Access the WarrIA PRO Ecosystem Free Trial, plans, personalized onboarding (100% guided by our AI Specialist), and full details: warria.io --- ⚠️ Risk Disclaimer Past performance does not guarantee future results. All metrics shown are based on historical backtesting with specific parameters for demonstration purposes only. This is an educational tool designed for knowledge and know-how transfer, not financial advice. Users are solely responsible for their own investment decisions. Never risk capital you cannot afford to lose. @ 2026 WarrIA PRO | All Rights Reserved | warria.io
Chiến lược Pine Script®
của marcus_loureiro
Swing Strategy Feature Set I [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set I includes concepts beginning with the letter "I" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Ichimoku Cloud Intraday Highest High/Lowest Low Intraday Intensity Index █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET I SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Ichimoku Cloud Filters The Tenkan above-equal/below Kijun filter is defined as an entry filter that evaluates the relative positioning of the Tenkan and Kijun values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Tenkan above-equal/below Kijun filter is set to "None". The Tenkan above-equal/below Senkou A filter is defined as an entry filter that evaluates the relative positioning of the Tenkan and Senkou A values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Tenkan above-equal/below Senkou A filter is set to "None". The Tenkan above-equal/below Senkou B filter is defined as an entry filter that evaluates the relative positioning of the Tenkan and Senkou B values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Tenkan above-equal/below Senkou B filter is set to "None". The Tenkan above-equal/below Chikou filter is defined as an entry filter that evaluates the relative positioning of the Tenkan and Chikou values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Tenkan above-equal/below Chikou filter is set to "None". The Kijun above-equal/below Senkou A filter is defined as an entry filter that evaluates the relative positioning of the Kijun and Senkou A values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Kijun above-equal/below Senkou A filter is set to "None". The Kijun above-equal/below Senkou B filter is defined as an entry filter that evaluates the relative positioning of the Kijun and Senkou B values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Kijun above-equal/below Senkou B filter is set to "None". The Kijun above-equal/below Chikou filter is defined as an entry filter that evaluates the relative positioning of the Kijun and Chikou values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Kijun above-equal/below Chikou filter is set to "None". The Senkou A above-equal/below Senkou B filter is defined as an entry filter that evaluates the relative positioning of the Senkou A and Senkou B values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Senkou A above-equal/below Senkou B filter is set to "None". The Senkou A above-equal/below Chikou filter is defined as an entry filter that evaluates the relative positioning of the Senkou A and Chikou values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Senkou A above-equal/below Chikou filter is set to "None". The Senkou B above-equal/below Chikou filter is defined as an entry filter that evaluates the relative positioning of the Senkou B and Chikou values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the Senkou B above-equal/below Chikou filter is set to "None". The Tenkan and Kijun bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the Tenkan and Kijun values is expanding or contracting over a configurable lookback period. The default mode for the Tenkan and Kijun bandwidth increasing/decreasing filter is set to "None". The default Tenkan and Kijun bandwidth increasing/decreasing lookback is set to 3. The Senkou A and B bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the Senkou A and B values is expanding or contracting over a configurable lookback period. The default mode for the Senkou A and B bandwidth increasing/decreasing filter is set to "None". The default Senkou A and B bandwidth increasing/decreasing lookback is set to 3. Users can apply up to five independent close above-equal/below filters (see generic filters section above), one for each Ichimoku Cloud value. The default mode for all five Ichimoku Cloud close above-equal/below filters is set to "None". The Ichimoku Cloud rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined Ichimoku Cloud value is rejected exclusive of the other Ichimoku Cloud values. The default mode for the Ichimoku Cloud rejection filter is set to "None". Users can apply the Ichimoku Cloud filters and adjust filter parameters via strategy Settings/Inputs/ICHIMOKU CLOUD FILTERS. Intraday Highest High/Lowest Low (IHHLL) Filter The IHHLL filter is defined as an entry filter that validates trade signals based on whether or not the most recent peak or trough prices coincide with the current trading day’s intraday extremes. At the start of each new trading day, the filter identifies the first bar of the session and continuously tracks the highest high and lowest low formed since the start of the relevant symbol’s daily candle open time. These values update dynamically as new candles form throughout the session and reset automatically at the start of each new trading day. "IHH" will return true if the most recent peak set, or is equal to, the intraday highest high. "Not IHH" will return true if the most recent peak was below the intraday highest high. "ILL" will return true if the most recent trough set, or is equal to, the intraday lowest low. "Not ILL" will return true if the most recent trough was above the intraday lowest low. The default mode for the IHHLL filter is set to "None". Users can apply the IHHLL filter via strategy Settings/Inputs/INTRADAY HIGHEST HIGH/LOWEST LOW (IHHLL) FILTER. Intraday Intensity Index (III) Filters As there is no built-in indicator for the III value used in this script, users can build their own III indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator("Intraday Intensity Index", overlay = false) import TradingView/ta/12 as ta iii = ta.iii * 1000 plot(iii) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The III above-equal/below zero filter is defined as an entry filter that evaluates the III value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the III above-equal/below zero filter is set to "None". The III minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The III trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the III filters and adjust filter parameters via strategy Settings/Inputs/INTRADAY INTENSITY INDEX (III) FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
BTC 15m strat1 Inside BarThe strategy trades Bitcoin on the 15-minute chart using pullbacks to EMA20. Higher-timeframe SMAs define the main trend and filter out ranging periods. Entries occur only when price pulls back to EMA20 and then closes back in the trend direction. Additional confirmation comes from the daily SMA, EMA20 slope, and ADX strength (with a stricter threshold for shorts). Stop-loss is based on ATR, and take-profit is set as a fixed RR multiple. The strategy opens only one position per signal.
Chiến lược Pine Script®
của tem1ch
Swing Strategy Feature Set H [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set H includes concepts beginning with the letter "H" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Harmonic Patterns Hilbert Transform Hull Moving Average █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Moving Average (MA) Double and Triple Trend Filters MA double and triple trend filters are defined as entry filters that evaluate the relative positioning of two or more MA values and invalidate trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when one MA is greater than or equal to another MA. "Below" returns true when one MA is less than another MA. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET H SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Harmonic Pattern Filter The harmonic patterns used in this script are the same as those included in my patterns library and harmonic patterns indicator. Link below for library and indicator, respectively: The harmonic pattern filter is an entry filter that validates trade signals based on the presence of a user-selected harmonic pattern. Separate filters are provided for long and short entries. Each filter evaluates only patterns that are directionally compatible with the corresponding core entry condition. The default mode for the long and short harmonic pattern filters is set to "None". Users can apply the harmonic pattern filters via strategy Settings/Inputs/HARMONIC PATTERN FILTERS. Hilbert Transform (HT) Filters As there is no built-in indicator for the HT value used in this script, users can build their own HT indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator("Hilbert Transform", overlay = false) import TradingView/ta/12 as ta ht = ta.ht(close) plot(ht) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The HT above-equal/below zero filter is defined as an entry filter that evaluates the HT value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the HT above-equal/below zero filter is set to "None". The HT minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The HT trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the HT filters and adjust filter parameters via strategy Settings/Inputs/HILBERT TRANSFORM (HT) FILTERS. Hull Moving Average (HMA) Filters Users can define up to three independent HMA series. The defaults are as follows: HMA 1: source = close, length = 50. HMA 2: source = close, length = 100. HMA 3: source = close, length = 200. Users can adjust the HMA inputs via strategy Settings/Inputs/HULL MOVING AVERAGE (HMA). Users can apply up to three independent close above-equal/below filters (see generic filters section above), one for each user-defined HMA. The default mode for all three HMA close above-equal/below filters is set to "None". Users can apply up to three independent HMA double trend filters (see generic filters section above), one filter for each of the three possible configurations. The defaults are as follows: HMA 1 above-equal/below HMA 2 is set to "None". HMA 2 above-equal/below HMA 3 is set to "None". HMA 1 above-equal/below HMA 3 is set to "None". The HMA rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined HMA is rejected exclusive of the other two HMAs. The default mode for the HMA rejection filter is set to "None". 
Users can apply the HMA filters and adjust filter parameters via strategy Settings/Inputs/HMA FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set F [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set F includes concepts beginning with the letter "F" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Fibonacci Ratios Fisher Transform Inverse Fisher Transform █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Minimum and Maximum Boundary Filters Minimum and maximum boundary filters are defined as entry filters used to constrain time-series values to predefined minimum and/or maximum thresholds, invalidating trade signals that do not satisfy a user-defined threshold criteria. The filters consist of two independent threshold components, minimum (above-equal) and maximum (below-equal), which may be applied individually or together. When both components are applied simultaneously the filters act as a value range constraint, invalidating trade signals that fall outside of the specified bounds. "Above-Equal" returns true when the evaluated value is greater than or equal to the user-defined minimum boundary. "Below-Equal" returns true when the evaluated value is less than or equal to the user-defined maximum boundary. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET F SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Fibonacci Ratio (FR) Filters The Fibonacci ratios used in this script are the same as those in my Fibonacci ratios indicator, link below: The FR rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the user-defined FR value is rejected exclusive of the other FR values. The default mode for the FR rejection filter is set to "None". Fisher Transform (FT) Filters The default FT length is set to 9. Users can adjust the FT length via strategy Settings/Inputs/Fisher Transform (FT).
 The FT above-equal/below zero filter is defined as an entry filter that evaluates the FT value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the FT above-equal/below zero filter is set to "None". The FT trigger above-equal/below zero filter is defined as an entry filter that evaluates the FT trigger value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the FT trigger above-equal/below zero filter is set to "None". The FT and FT trigger minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The FT and FT trigger trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the FT filters and adjust filter parameters via strategy Settings/Inputs/FT FILTERS. Inverse Fisher Transform (IFT) Filters As there is no built-in indicator for the IFT values used in this script, users can build their own IFT indicator in Pine Script by copying the following code and pasting it into a new indicator: //@version=6 indicator("Inverse Fisher Transform", shorttitle = "IFT", overlay = false) import TradingView/ta/12 as ta ft_length = input.int(defval = 9, title = 'FT Length', minval = 1, group = 'Inverse Fisher Transform (IFT)') ft = ta.ft(hl2, ft_length) ift = ta.ift(ft) plot(ift) For further information on how to build Pine Script indicators, please refer to: www.tradingview.com www.tradingview.com The IFT minimum and maximum boundary filter (see generic filters section above) defaults are as follows: Apply above-equal filter is set to false. Above-equal threshold is set to -1. Apply below-equal filter is set to false. Below-equal threshold is set to 1. The IFT minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The IFT trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. 
Users can apply the IFT filters and adjust filter parameters via strategy Settings/Inputs/IFT FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set E [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set E includes concepts beginning with the letter "E" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Ease of Movement █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET E SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Ease of Movement (EOM) Filters The default EOM inputs are as follows: Length is set to 14. Divisor is set to 10000. Users can adjust the EOM inputs via strategy Settings/Inputs/Ease of Movement (EOM).
 The EOM above-equal/below zero filter is defined as an entry filter that evaluates the EOM value relative to the zero line and invalidates trade signals that do not satisfy a user-defined directional condition. The default EOM above-equal/below zero filter mode is set to "None". The EOM minimum percent change positive-flat/negative filter (see generic filters section above) defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The EOM trend filter (see generic filters section above) defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the EOM filters and adjust filter parameters via strategy Settings/Inputs/EOM FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
Chiến lược Pine Script®
của theEccentricTrader
Swing Strategy Feature Set D [theEccentricTrader]█   OVERVIEW This swing strategy is part of a broader research and exploration framework designed to encourage users to experiment with a variety of technical concepts and evaluate the comparative effectiveness of different strategy configurations. For example, users can first configure a core strategy as a benchmark, then iteratively test a range of feature configurations as additional entry conditions and compare their performance against one another and against the core strategy. Feature Set D includes concepts beginning with the letter "D" and forms part of a larger swing strategy suite that covers a wide range of technical concepts. The objective of the suite is not curve-fitting, but rather structured experimentation, exploration and statistical validation (or invalidation) of technical concepts. Concepts exclusive to the feature set are as follows: Day of Week Directional Movement Index Donchian Channel █   OPERATIONAL Initial Capital The initial capital is defined as a monetary value denominated in a given base currency. The default initial capital is set to 100,000. The default base currency is set to the selected symbol's default base currency. Users can adjust the initial capital and select an alternative base currency via strategy Settings/Properties. Risk as Percentage of Equity The equity is defined as the sum of initial capital, net profit and open profit. The risk is defined as a percentage of equity per-trade. As a result, net profit outcomes are subject to compounding effects over time. The default risk is set to 1% of equity. Users can adjust the strategy's per-trade risk via strategy Settings/Inputs/STRATEGY. For further information on how the risk is applied in practice, refer to the position sizing section below. Unit of Value The unit of value is defined as a decimal precision factor that converts user-defined point or pip distances into actual price units used by the selected symbol. Different symbols express price movement using different conventions. For example, some symbols are quoted directly in whole price points, while others use pips or fractional point increments. The unit of value provides a normalisation layer that allows all distance-based logic in the strategy to operate consistently across symbols. Examples: A unit of value of 1 corresponds to a price increment of 1.0. A unit of value of 10 corresponds to a price increment of 0.1. A unit of value of 100 corresponds to a price increment of 0.01. A unit of value of 1000 corresponds to a price increment of 0.001. A unit of value of 10000 corresponds to a price increment of 0.0001. Users should consult their broker’s published symbol specifications to confirm how price movement is defined for the symbols they intend to backtest. Incorrect configuration of the unit of value may result in misaligned stop distances, targets and/or risk calculations. The default unit of value is set to 1. Users can adjust the unit of value via strategy Settings/Inputs/STRATEGY. Stop Buffer The stop buffer is defined as the number of points or pips beyond a stop loss level required for the level to be considered clearly breached. The default stop buffer is set to 0 points/pips. Users can adjust the stop buffer via strategy Settings/Inputs/STRATEGY. Risk Range The risk range is defined as the difference between the entry price and the stop loss price (inclusive of the stop buffer) for any given trade. Position Sizing Position sizing determines the quantity of contracts, shares or units opened for each trade based on the user-defined risk and the selected symbol’s pricing structure. "syminfo.pointvalue" is a built-in Pine Script variable that defines the number of underlying units contained within a single contract for any given symbol, and is critical for accurate position size calculations. The position size is calculated as follows: The risk range is multiplied by the syminfo.pointvalue to convert the price movement into its monetary equivalent. The user-defined risk amount (expressed as a percentage of equity) is divided by this monetary risk per unit to determine the position size. This ensures that each trade risks a consistent proportion of account equity regardless of point or pip based quoting conventions, symbol price scale or contract specifications. While the strategy targets a fixed percentage of equity risk per-trade, the exact risk applied cannot always be matched precisely due to symbol-specific constraints such as contract sizing and margin requirements. In these cases, the strategy opens the largest permissible position that does not violate operational constraints, resulting in a realised risk that is as close as possible to the user-defined risk without exceeding it. For further information on the syminfo.pointvalue variable, please refer to: www.tradingview.com Margin The margin is defined as the minimum percentage of a position’s notional value that must be covered by the strategy’s available equity in order for TradingView's strategy tester to simulate opening and maintaining that position. For example, a margin setting of 25% means the simulated account must hold equity equal to at least 25% of the position’s notional value in order to enter or maintain that trade, the remaining 75% is considered provided by the simulated broker. A lower margin percentage allows the account to open larger positions relative to its equity, because the required equity portion is smaller. Conversely, a higher margin percentage demands more of the account's equity be committed to any given position. When the account’s equity falls below the required margin, the strategy tester emulates a margin call event, in which the broker emulator forcibly closes or reduces positions so that remaining positions no longer exceed available equity relative to the margin requirement. This behaviour is documented as part of TradingView’s margin/leverage feature for strategies. Margin settings in a strategy are used solely for simulation purposes and do not automatically match any broker’s real-world margin requirements (which can vary by broker, asset class and symbol). Users should consult their broker’s published specifications for further details. The default margin is set to 25% for both long and short positions. Users can adjust the margin for long and short positions independently via strategy Settings/Properties/MARGIN. For further information on the strategy tester's margin functionality, please refer to: www.tradingview.com www.tradingview.com Pyramiding The pyramiding count is defined as the maximum number of open positions permitted at any one time. TradingView's strategy tester does not facilitate hedging, as such, long entries will close any open short positions and short entries will close any open long positions. The default pyramiding count is set to 100. Users can adjust the pyramiding count via strategy Settings/Properties.
 For further information on TradingView's strategy tester and broker emulator, please refer to: www.tradingview.com Spread The spread is defined as the difference between a given symbol's bid (buy) price and ask (sell) price. Typical spreads vary by broker and symbol. Some brokers offer fixed spreads on certain symbols, while others offer variable spreads that fluctuate with market conditions. Users should consult their broker's published specifications for further details. Commission The commission is defined as a transaction cost applied by a broker and may be expressed as a percentage of position size, a per-contract fee or a fixed fee per-transaction. Commission structures vary by broker and symbol. Some brokers charge no explicit commission and instead generate revenue through the spread or other indirect sources, while others will typically apply one of the three aforementioned commission types, depending on the product offered. Users should consult their broker's published specifications for further details. The default commission is set to 0.005% of position size. Users can select and adjust the commission type via strategy Settings/Properties/COST SIMULATION. █   CORE STRATEGY Green and Red Candles A green candle is defined as a candle that closes at or above its open price and a red candle is defined as a candle that closes below its open price. Swing Highs and Swing Lows A swing high is defined as a green candle, or a series of consecutive green candles, followed by a single red candle that completes the swing and forms the peak. A swing low is defined as a red candle, or a series of consecutive red candles, followed by a single green candle that completes the swing and forms the trough. Peak and Trough Prices The peak price of a complete swing high is either the high of the red candle that completes the swing high or the high of the preceding green candle, depending on which is higher. The trough price of a complete swing low is either the low of the green candle that completes the swing low or the low of the preceding red candle, depending on which is lower. Fixed Reward-to-Risk Fixed reward-to-risk is defined as a user-defined reward multiple for a given unit of risk. Variable Reward-to-Risk Variable reward-to-risk is defined as a path-dependent reward multiple for a given unit of risk. Swing High Swing Low (SHSL) Strategy The SHSL strategy uses swing lows for core long entry conditions and swing highs for core short entry conditions. The strategy is designed for standard OHLC candlestick charts only and will not behave as intended on other chart types. All entries are processed at candle close and use the candle close price for the entry price. Long stop losses are anchored to the most recent trough and short stop losses are anchored to the most recent peak. Users can choose between long-only and short-only configurations, or alternatively simulate trades in both directions (long-short). However, when the "Both" option is selected, long entries will close any open short positions and short entries will close any open long positions (as mentioned in the pyramiding sub-section above). This can and will result in variable reward-to-risk outcomes. The default direction is set to "Long" for a long-only configuration. The default exit type is set to "Target" for a fixed reward-to-risk configuration. Long targets are determined by adding a user-defined multiple of the risk range to the entry price and short targets are determined by subtracting a user-defined multiple of the risk range from the entry price. Even when using a fixed reward-to-risk configuration, realised reward-to-risk outcomes may vary due to market gaps, particularly when positions are held across session boundaries or market closures. Gaps can cause stop losses or exits to be executed at prices materially different from those implied by the strategy’s static distance calculations. Users who wish to minimise gap-related variability may consider applying the close at end of session filter (see core filters section below), accepting that this introduces its own form of reward-to-risk variability. The default reward-to-risk is set to 1. Users can adjust strategy parameters via strategy Settings/Inputs/STRATEGY. Selecting a non-target exit type removes profit targets and renders the reward-to-risk input inactive. Trailing Stop Loss A trailing stop loss is defined as an exit type that dynamically moves a stop loss level in a favourable direction when a predefined condition is met. For example, a predefined point move or the formation of a higher trough or lower peak. Risk Range Trailing Stop Loss The risk range trailing stop loss is defined as a trailing stop mechanism that activates once price has moved favourably by one full risk range. Upon activation, the stop loss is moved to breakeven and subsequently trails favourable price movement by the risk range into profit. Users can apply this exit type by selecting "Trail" via strategy Settings/Inputs/STRATEGY. Trend Trailing Stop Loss The trend trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher troughs (for longs) or lower peaks (for shorts). Users can apply this exit type by selecting "Trend Trail" via strategy Settings/Inputs/STRATEGY. Candle Trailing Stop Loss The candle trailing stop loss is defined as a trailing stop mechanism that dynamically moves a stop loss level to newly formed higher candle lows (for longs) or lower candle highs (for shorts). Users can apply this exit type by selecting "Candle Trail" via strategy Settings/Inputs/STRATEGY. Opposing Candle Colour Close The opposing candle colour close exit type is defined as an exit condition that closes any long positions when a new red candle forms and closes any short positions when a new green candle forms. Users can apply this exit type by selecting "Opposing Candle" via strategy Settings/Inputs/STRATEGY. █   CORE FILTERS Minimum Risk Range Filter The minimum risk range filter is defined as an entry filter that invalidates trade signals with a risk range below a user-defined threshold. The default minimum risk range is set to 4 points/pips. Users can adjust the minimum risk range via strategy Settings/Inputs/RISK RANGE FILTER. It is recommended that users set the minimum risk range at least 1–2 points/pips above the selected symbol’s spread to invalidate trades that would be completely impractical under realistic trading conditions. Time Zone The time zone is defined using either an IANA region identifier (e.g. Europe/London, America/New_York) or a fixed UTC/GMT offset (e.g. UTC+1, GMT-05:30). Fixed offsets do not account for daylight saving time. The default time zone is set to Europe/London. Users can change the time zone via strategy Settings/Inputs/TIME ZONE. For further information on time zone configuration, please refer to: data.iana.org en.wikipedia.org Session Filter The session filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined intraday trading session, with session start and end times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, session boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered or held beyond the intended session end, users should configure the session end time at least one full timeframe period earlier than the desired practical session close. For example, on a 5-minute chart with a desired session end at 22:00, the session should typically be configured to end at 21:55. This ensures that no new trades are taken at the final session close and that any session-dependent exit logic is applied before the session ends in practice. When using custom or non-standard timeframes where the desired session end does not align cleanly with candle boundaries, it is recommended that users set the session end two full timeframe periods earlier than the desired session end. This provides an additional safety buffer, ensuring the strategy avoids taking trades near the session boundary. By default, the session filter is set to false and the default session is set to "2300-2155". Users can apply the session filter and adjust session boundaries via strategy Settings/Inputs/SESSION FILTER. Close At End of Session Filter The close at end of session filter is defined as an exit filter that closes all open positions when the active trading session ends, provided that the session filter is appropriately configured and applied. When enabled, the strategy monitors the session filter state and detects the transition from an active session to an inactive session. All open trades are closed on the first candle that falls outside the defined session window. This ensures that no positions are carried beyond the user-defined trading session. The close at end of session filter operates independently of entry conditions and other exit types. When enabled, it will force the closure of all open positions at session end regardless of the selected exit configuration. Enabling the close at end of session filter can result in variable reward-to-risk outcomes. Because positions are forcibly closed at session end regardless of stop loss or target placement, exits may occur at prices that differ from those implied by the fixed reward-to-risk configuration. This behaviour is intentional and reflects a design trade-off between enforcing strict session boundaries and allowing trades to reach their predefined directional objectives, regardless of how severely distorted the realised reward-to-risk outcomes could be in the event of price gaps. By default, the close at end of session filter is set to false. Users can apply the close at end of session filter via strategy Settings/Inputs/CLOSE AT END OF SESSION FILTER. Users should also ensure that the session filter is applied and that session boundaries are configured appropriately with respect to candle timestamp behaviour, as described in the session filter section above. Sample Period Filter The sample period filter is defined as an entry filter that invalidates trade signals that fall outside a user-defined date-time range, with start and end date-times bound to the strategy time zone. TradingView candle timestamps represent the candle open time, not the candle close time. As a result, sample period boundaries are evaluated based on when a candle opens, even though entries and exits are processed at candle close. To avoid trades being entered beyond the intended sample period end, users should configure the sample period end date-time at least one full timeframe period earlier than the desired practical sample period end date-time. For example, on a 5-minute chart with a desired end date-time of 01/01/2026 22:00, the end date-time should typically be configured to 01/01/2026 21:55. The default sample period start and end date-times are set to 01/01/1900 00:00 and 01/01/3000 00:00, respectively. Users can adjust the sample period via strategy Settings/Inputs/SAMPLE PERIOD FILTER. █   GENERIC FILTERS Generic Filter Behaviour Unless otherwise stated: "None" inputs return true. Filters return true only when their selected condition is satisfied. Close Above-Equal/Below Filter The close price above-equal/below filter is defined as an entry filter that evaluates the most recent candle close price relative to a given time-series value and invalidates trade signals that do not satisfy a user-defined directional condition. "Above-Equal" returns true when the most recent candle close price is greater than or equal to any given time-series value. "Below" returns true when the most recent candle close price is less than any given time-series value. Minimum Percentage Change Positive-Flat/Negative Filter The minimum percentage change filter is an entry filter that measures the relative change of a time-series value over a configurable historical window and applies a directional threshold condition, invalidating trade signals that do not meet the directional threshold criteria. The filter compares the current value to its value n bars ago and computes the percentage difference. A signal returns true only if this percentage change satisfies both: The selected directional requirement. The user-defined minimum percentage change magnitude. "Positive-Flat" direction logic: Accepts values that have increased or remained unchanged, provided the percentage change is greater than or equal to the minimum threshold. "Negative" direction logic: Accepts values that have decreased, provided the magnitude of the decrease meets or exceeds the minimum threshold. When the minimum threshold is set to 0%, the filter behaves as a pure directional check: "Positive-Flat" accepts ≥ 0% changes. "Negative" accepts < 0% changes only. Basic and Exclusive Rejection Filters The basic rejection filter is defined as an entry filter that evaluates swing-based wick or body rejections of a given price level and invalidates trade signals that do not satisfy the rejection criteria. For long trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is above a given rejection price. The trough price is less than or equal to a given rejection price. The green candle that completes the swing closes above a given rejection price. For short trades, "Rejection" returns true when all three of the following conditions are met: The previous candle open is below a given rejection price. The peak price is greater than or equal to a given rejection price. The red candle that completes the swing closes below a given rejection price. The exclusive rejection filter is defined as an entry filter that meets basic rejection filter criteria for only one user-defined price level from a set of given price levels. If the rejection criteria is met for more than one of the given price levels the filter will return false. Basic and Multi-Part Trend Filters Basic and multi-part trend filters are defined as entry filters that evaluate changes in time-series values from one period to the next and invalidate trade signals that do not satisfy a user-defined trend condition. Basic trends operate independently of prior trend state, whereas multi-part trends are defined by the presence or absence of preceding trend sequences. The multi-part trend states are distinguished numerically and the conditions are bound to a user-defined trend count. "Basic Uptrend" returns true when a time-series value is greater than the preceding value. For example, a basic volume uptrend filter returns true if the most recent candle's volume is greater than the preceding candle's volume. "Basic Downtrend" returns true when a time-series value is less than the preceding value. For example, a basic volume downtrend filter returns true if the most recent candle's volume is less than the preceding candle's volume. "Uptrend" returns true while a multi-part uptrend state is valid. The uptrend state begins when a new basic uptrend forms following a basic downtrend and remains valid until a new basic downtrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part uptrend conditions will return true. "Downtrend" returns true while a multi-part downtrend state is valid. The downtrend state begins when a new basic downtrend forms following a basic uptrend and remains valid until a new basic uptrend forms. The user-defined trend count will determine which multi-part trend condition is selected. For example, if the user-defined trend count is set to 3, then only 3-part downtrend conditions will return true. █   FEATURE SET D SPECIFIC FILTERS All feature set specific indicators use the same calculations as the built-in TradingView indicators unless otherwise stated in the relevant filter sub-section. While users do not need to apply the indicators for the strategy to function, they can of course apply the relevant indicators as visual aids if they so desire. For further information on how to apply built-in TradingView indicators, please refer to: www.tradingview.com Day of Week (DOW) Filter The DOW filter is defined as an entry filter that invalidates trade signals that fall outside of a user-defined day of the week (configured to the strategy's time zone). The default mode for the DOW filter is set to "None". Users can apply the DOW filter via strategy Settings/Inputs/DAY OF WEEK (DOW) FILTER. Directional Movement Index (DMI) Filters The default DMI inputs are as follows: DI length is set to 14. ADX smoothing length is set to 14. Users can adjust the DMI inputs via strategy Settings/Inputs/DIRECTIONAL MOVEMENT INDEX (DMI). The positive DMI above-equal/below negative DMI filter is an entry filter that evaluates the relative positioning of the positive and negative DMI values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the positive DMI above-equal/below negative DMI filter is set to "None". The positive DMI above-equal/below ADX filter is an entry filter that evaluates the relative positioning of the positive DMI and ADX values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the positive DMI above-equal/below ADX filter is set to "None". The negative DMI above-equal/below ADX filter is an entry filter that evaluates the relative positioning of the negative DMI and ADX values and invalidates trade signals that do not satisfy a user-defined directional condition. The default mode for the negative DMI above-equal/below ADX filter is set to "None". Users can apply up to three DMI minimum percent change and trend filters (see generic filters section above), one for each of the DMI values (positive, negative, adx). The minimum percent change positive-flat/negative filter defaults are as follows: Mode is set to "None". Minimum percent change is set to 0. Lookback is set to 3. The trend filter defaults are as follows: Mode is set to "None". Trend count is set to 3. Users can apply the DMI filters and adjust filter parameters via strategy Settings/Inputs/DMI FILTERS. Donchian Channel (DC) Filters The default DC length is set to 14. Users can adjust the DC length via strategy Settings/Inputs/DONCHIAN CHANNEL (DC). The DC bandwidth increasing/decreasing filter is defined as an entry filter that evaluates whether the distance between the DC high and DC low values is expanding or contracting over a configurable lookback period. The default mode for the DC bandwidth increasing/decreasing filter is set to "None". The default DC bandwidth increasing/decreasing lookback is set to 3. The default mode for the close above-equal/below DC median (see generic filters section above) filter is set to "None". The DC median rejection filter is defined as an exclusive rejection filter (see generic filters section above) that will only return true if the DC median value is rejected exclusive of the other two DC values. By default, the DC median rejection filter is set to false. Users can apply the DC filters and adjust filter parameters via strategy Settings/Inputs/DC FILTERS. █   ALERTS Users can set alerts for any given strategy configuration via the alerts dialogue box. Users must first ensure that the correct condition (the strategy title) is selected from the first drop-down list in the alert dialogue box's condition field. Default alert messages have been configured for both entries and exits so that users can more effectively distinguish between long and short entries and exits while using long-short configurations. To get alerts for both entries and exits the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "Order fills only". When using "Order fills only" with long-short configurations, it is recommended that users define their alert via the alert name field and use only the default {{strategy.order.alert_message}} call in the alert message field. Alert conditions generated by "Order fills only" are evaluated after entry conditions have been satisfied and operational constraints (risk, position size and margin requirements) have been applied. As such, trade signals that would result in position sizes exceeding the simulated account's margin constraints will not generate alerts. To get alerts for entries only the user should change the value in the condition field's second drop-down list from "Order fills only and alert() function calls" to "alert() function calls only". The default alert messages generated by "Order fills only" are as follows: "long entry". "long exit". "short entry". "short exit". The default alert messages generated by "alert() function calls only" are as follows: "long entry". "short entry". Alert conditions generated by "alert() function calls only" are operational-constraint-agnostic and will generate alerts whenever entry conditions are satisfied, regardless of the simulated account's margin constraints. For further information on setting and managing alerts, please refer to: www.tradingview.com www.tradingview.com www.tradingview.com █   LIMITATIONS AND CONSIDERATIONS Backtesting Backtest results should always be interpreted cautiously. Strategy performance can vary significantly across time periods and sample sets. While strong historical performance does not guarantee future results, poor historical performance reliably indicates a weak strategy when sample sizes are statistically meaningful. Statistical Significance and Path-Dependent Outcomes (Overfitting) In statistical practice, sample sizes of 100 observations are sometimes cited as a rough lower bound for certain forms of basic significance testing. In the context of trading strategy evaluation, such sample sizes are rarely sufficient to produce results that are meaningfully reliable or replicable. Based on practical experience, sample sizes closer to 1,000 observations or more are generally required before performance characteristics begin to stabilise. As a general rule, larger sample sizes increase the reliability and replicability of observed results. Path dependence refers to situations in which outcomes are determined not only by initial conditions, but by the specific and unique sequence of price movements over a given time period. Even with large sample sizes, favourable net profit outcomes should be interpreted with caution when they are primarily driven by either variable reward-to-risk configurations or fixed reward-to-risk configurations that employ unrealistically high reward multiples. In both cases, performance is often strongly influenced by path-dependent effects, making such outcomes less reliable and less replicable. Fixed reward-to-risk configurations are generally less susceptible to path dependence when the reward multiple is kept within reasonable bounds. However, empirical studies and practitioner research suggest that reward multiples above approximately 3:1 increasingly exhibit the same path-dependent characteristics observed in variable reward-to-risk strategies. Bar Magnifier Due to the limitations of OHLC data, intra-bar price movement cannot be precisely determined. When both stop loss and target levels are reached within the same candle, assumptions are made by the strategy tester. Pine Script's bar magnifier partially mitigates this limitation by evaluating lower-timeframe data. However, this feature is available only to TradingView Premium users and remains inherently limited. For further information on the bar magnifier functionality, please refer to: www.tradingview.com www.tradingview.com TradingView Premium users can enable bar magnifier via strategy Settings/Properties/FILL ORDERS. Processing Orders at Candle Close Backtests cannot accurately account for slippage between signal generation and trade execution. A practical mitigation is to use fixed-distance stop losses and targets rather than absolute price levels, a feature supported by many brokers and APIs. Empirical Probabilities Empirical probabilities are derived directly from observed outcomes rather than from theoretical models or assumed distributions. In the context of trading, they are calculated by measuring the relative frequency of events (such as wins and losses) across a large sample of historical trades. Unlike conditional or model-based probabilities, empirical probabilities make no assumptions. Their validity relies primarily on sample size and the consistency of the rules used to generate observations, making them particularly relevant for trading systems evaluated under the law of large numbers. Empirical probabilities are most useful for comparative analysis, such as assessing how different configurations, filters or exit mechanisms alter the statistical behaviour of a strategy under identical conditions. They are not intended to represent true predictive probabilities or to imply stable future performance. To study empirical probabilities for comparative purposes, it is recommended that users set commission and both long and short margin values to 0% in order to maximise sample size. However, users should not interpret any resulting profits as realistic. Setting commission and margin (in particular) to 0% produces highly distorted outcomes that are not representative of realistic live trading conditions. █   DISCLAIMER This Pine Script strategy is provided for educational purposes only and does not constitute financial advice in any form.
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70To see straight is to glimpse tomorrow, projecting a linear vision that does not fear time. But when the gaze curves toward the past, reality multiplies into reflected fires, distorting the truth through the filter of experience. At this intersection of intuition and analysis, our fund is born—a financial ecosystem where philosophy transforms into algorithm. The core of our strategy is not just profit, but Lucidity. Imagine starting with a capital of €50,000: from 2024 to the present, this plan has navigated the markets not as a gamble, but as a sensory mastery of the subject matter. The First Fire (F1 - The Voice): The predicate that breaks through the market's silence to capture the exact equity moment. The Second Fire (F2 - Management of the "Fault"): The awareness that prevents "paralysis by analysis," protecting capital when self-observation becomes excessive. The Third Fire (F3 - Vibrational Extraction): The ability to extract vibrational thought from the chaos of volatility, discerning the straight path. We have encoded this triad into a system that avoids boredom and overthinking, alternating the "senses" to maintain a perpetually fresh understanding. Choosing to participate in this project means investing not just in an asset, but in a method that balances passivity and activity, responding to market calls only when they coincide with a determined, lucid thought. Our projection, supported by a logic that scales leverage only when success is confirmed, aims for a growth that is not just numerical, but structural. It is time to move beyond the overlapping lenses that distort the truth of profit. We invite you to enter a world where every choice is the result of a balanced sequence, starting from objective data to dominate the most volatile sentiment. Investing with us means stopping looking at the reflection and starting to see, finally, tomorrow. 📈 Strategy Estimate (Based on your tests) Initial Capital: €50,000. Control Logic: "Obiettivo 70" (Target 70) strategy for solid and consistent growth. Protection: Active safety threshold to preserve the bulk of the capital in case of a market "fault."
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