VCBBDOVWAPSMA By Anil ChawraHow Users Can Make Profit Using This Script:
1. Volume Representation : Each candle on the chart represents a specific time period (e.g., 1 minute, 1 hour, 1 day) and includes information about both price movement and trading volume during that period.
2. Candlestick Anatomy : A volume candle has the same components as a regular candlestick: the body (which represents the opening and closing prices) and the wicks or shadows (which indicate the highest and lowest prices reached during the period).
3. Volume Bars : Instead of just the candlestick itself, volume candles also include a bar or histogram representing the trading volume during that period. The height or length of the volume bar indicates the amount of trading activity.
4. Interpreting Volume : High volume candles typically indicate increased market interest or activity during that period. This could be due to significant buying or selling pressure.
5. Confirmation : Traders often look for confirmation from other technical indicators or price action to validate the significance of a high volume candle. For example, a high volume candle breaking through a key support or resistance level may signal a strong market move.
6. Trend Strength : Volume candles can provide insights into the strength of a trend. A series of high volume candles in the direction of the trend suggests strong momentum, while decreasing volume may indicate weakening momentum or a potential reversal.
7. Volume Patterns : Traders also analyze volume patterns, such as volume spikes or divergences, to identify potential trading opportunities or reversals.
8. Combination with Price Action: Volume analysis is often used in conjunction with price action analysis and other technical indicators to make more informed trading decisions.
9. Confirmation and Validation: It's important to confirm the significance of volume candles with other indicators or price action signals to avoid false signals.
10. Risk Management : As with any trading strategy, proper risk management is crucial when using volume candles to make trading decisions. Set stop-loss orders and adhere to risk management principles to protect your capital.
How to script works :
1.Identify High Volume Candles: Look for candles with significantly higher volume compared to the surrounding candles. These can indicate increased market interest or activity.
2.Wait for Confirmation: Once you identify a high volume candle, wait for confirmation from subsequent candles to ensure the momentum is sustained.
3.Enter the Trade: After confirmation, consider entering a trade in the direction indicated by the high volume candle. For example, if it's a bullish candle, consider buying.
4.Set Stop Loss: Always set a stop loss to limit potential losses in case the trade goes against you.
5.Take Profit: Set a target for taking profits. This could be based on technical analysis, such as a resistance level or a certain percentage gain.
6.Monitor Volume: Continuously monitor volume to gauge the strength of the trend. Decreasing volume may signal weakening momentum and could be a sign to exit the trade.
7.Risk Management: Manage risk carefully by adjusting position sizes according to your risk tolerance and the size of your trading account.
8.Review and Adapt: Regularly review your trades and adapt your strategy based on what's working and what's not.
Remember, no trading strategy guarantees profits, and it's essential to practice proper risk management and have realistic expectations. Additionally, consider combining volume analysis with other technical indicators for a more comprehensive approach to trading.
**How Users Can Make Profit Using This Script:
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DAYS OPEN LINE:
1.Purpose: Publishing a "Days Open Line" indicator serves to inform customers about the operational schedule of a business or service.
2.Visibility: It ensures that the information regarding the days of operation is easily accessible to current and potential customers.
3.Transparency: By making the operational schedule public, businesses demonstrate transparency and reliability to their customers.
4.Accessibility: The indicator should be published on various platforms such as the business website, social media channels, and physical locations to ensure accessibility to a wide audience.
5.Clarity: The information should be presented in a clear and concise manner, specifying the days of the week the business is open and the corresponding operating hours.
6.Updates: It's important to regularly update the "Days Open Line" indicator to reflect any changes in the operational schedule, such as holidays or special events.
7.Customer Convenience: Providing this information helps customers plan their visits accordingly, reducing inconvenience and frustration due to unexpected closures.
8.Expectation Management: Setting clear expectations regarding the business hours helps manage customer expectations and reduces the likelihood of disappointment or complaints.
9.Customer Service: Publishing the "Days Open Line" indicator demonstrates a commitment to customer service by ensuring that customers have the information they need to engage with the business.
10.Brand Image: Consistently .maintaining and updating the indicator contributes to a positive brand image, as it reflects professionalism, reliability, and a customer-centric approach.
SMA CROSS:
1.This indicator generates buy and sell signals based on the crossover of two Simple Moving Averages (SMA): a shorter 3-day SMA and a longer 8-day SMA.
When the 3-day SMA crosses above the 8-day SMA, it generates a buy signal indicating a potential upward trend.
Conversely, when the 3-day SMA crosses below the 8-day SMA, it generates a sell signal indicating a potential downward trend.
Signal Interpretation:
2.Buy Signal: Generated when the 3-day SMA crosses above the 8-day SMA.
Sell Signal: Generated when the 3-day SMA crosses below the 8-day SMA.
Usage:
3.Traders can use this indicator to identify potential entry and exit points in the market.
Buy signals suggest a bullish trend, indicating a favorable time to enter or hold a long position.
4.Sell signals suggest a bearish trend, indicating a potential opportunity to exit or take a short position.
Parameters:
5.Periods: 3-day SMA and 8-day SMA.
Price: Closing price is commonly used, but users can choose other price types (open, high, low) for calculation.
Confirmation:
6.It's recommended to use additional technical analysis tools or confirmatory indicators to validate signals and minimize false signals.
Risk Management:
7.Implement proper risk management strategies, such as setting stop-loss orders, to mitigate losses in case of adverse price movements.
Backtesting:
8.Before using the indicator in live trading, conduct thorough backtesting to evaluate its effectiveness under various market conditions.
Considerations:
9.While SMA crossovers can provide valuable insights, they may generate false signals during ranging or choppy markets.
Combine this indicator with other technical analysis techniques for comprehensive market analysis.
Continuous Optimization:
10.Monitor the performance of the indicator and adjust parameters or incorporate additional filters as needed to enhance accuracy over time.
BOLLINGER BAND:
1.Definition: A Bollinger Band indicator is a technical analysis tool that consists of a centerline (typically a moving average) and two bands plotted above and below it. These bands represent volatility around the moving average.
2.Purpose: Publishing a Bollinger Band indicator serves to provide traders and investors with insights into the volatility and potential price movements of a financial instrument.
3.Visualization: The indicator is typically displayed on price charts, allowing users to visualize the relationship between price movements and volatility levels.
4.Interpretation: Traders use Bollinger Bands to identify overbought and oversold conditions, potential trend reversals, and volatility breakouts.
5.Components: The indicator consists of three main components: the upper band, lower band, and centerline (usually a simple moving average). These components are calculated based on standard deviations from the moving average.
6.Parameters: Traders can adjust the parameters of the Bollinger Bands, such as the period length and standard deviation multiplier, to customize the indicator based on their trading strategy and preferences.
7.Signals: Bollinger Bands generate signals when prices move outside the bands, indicating potential trading opportunities. For example, a price breakout above the upper band may signal a bullish trend continuation, while a breakout below the lower band may indicate a bearish trend continuation.
8.Confirmation: Traders often use other technical indicators or price action analysis to confirm signals generated by Bollinger Bands, enhancing the reliability of their trading decisions.
9.Education: Publishing Bollinger Band indicators can serve an educational purpose, helping traders learn about technical analysis concepts and how to apply them in real-world trading scenarios.
10.Risk Management: Traders should exercise proper risk management when using Bollinger Bands, as false signals and market volatility can lead to losses. Publishing educational content alongside the indicator can help users understand the importance of risk management in trading.
VWAP:
1.Calculation: VWAP is calculated by dividing the cumulative sum of price times volume traded for every transaction (price * volume) by the total volume traded.
2.Time Frame: VWAP is typically calculated for a specific time frame, such as a trading day or a session.
3.Intraday Trading: It's commonly used by intraday traders to assess the fair value of a security and to determine if the current price is above or below the average price traded during the day.
4.Execution: Institutional traders often use VWAP as a benchmark for executing large orders, aiming to buy at prices below VWAP and sell at prices above VWAP.
5.Benchmark: It serves as a benchmark for traders to evaluate their trading performance. Trades executed below VWAP are considered good buys, while those above are considered less favorable.
6.Sensitivity: VWAP is more sensitive to price and volume changes during periods of high trading activity and less sensitive during periods of low trading activity.
7.Day's End: VWAP resets at the end of each trading day, providing a new reference point for the following trading session.
8.Volume Weighting: The weighting by volume means that prices with higher trading volumes have a greater impact on VWAP than those with lower volumes.
9.Popular with Algorithmic Traders: Algorithmic trading systems often incorporate VWAP strategies to execute trades efficiently and minimize market impact.
10.Limitations: While VWAP is a useful indicator, it's not foolproof. It may lag behind rapidly changing market conditions and may not be suitable for all trading strategies or market conditions. Additionally, it's more effective in liquid markets where there is significant trading volume.
Tìm kiếm tập lệnh với "stop loss"
Turtle Trader StrategyTurtle Trader Strategy :
Introduction :
This strategy is based on the well known « Turtle Trader Strategy », that has proven itself over the years. It sends long and short signals with pyramid orders of up to 5, meaning that the strategy can trigger up to 5 orders in the same direction. Good risk and money management.
It's important to note that the strategy combines 2 systems working together (S1 and S2). Let’s describe the specific features of this strategy.
1/ Position size :
Position size is very important for turtle traders to manage risk properly. This position sizing strategy adapts to market volatility and to account (gains and losses). It’s based on ATR (Average True Range) which can also be called « N ». Its length is per default 20.
ATR(20) = (previous_atr(20)*19 + actual_true_range)/20
The number of units to buy is :
Unit = 1% * account/(ATR(20)*dollar_per_point)
where account is the actual account value and dollar_per_point is the variation in dollar of the asset with a 1 point move.
Depending on your risk aversion, you can increase the percentage of your account, but turtle traders default to 1%. If you trade contracts, units must be rounded down by default.
There is also an additional rule to reduce the risk if the value of the account falls below the initial capital : in this case and only in this case, account in the unit formula must be replace by :
account = actual_account*actual_account/initial capital
2/ Open a position :
2 systems are working together :
System 1 : Entering a new 20 day breakout
System 2 : Entering a new 55 day breakout
A breakout is a new high or new low. If it’s a new high, we open long position and vice versa if it’s a new low we enter in short position.
We add an additional rule :
System 1 : Breakout is ignored if last long/short position was a winner
System 2 : All signals are taken
This additional rule allows the trader to be in the major trends if the system 1 signal has been skipped. If a signal for system 1 has been skipped, and next candle is also a new 20 day breakout, S1 doesn’t give a signal. We have to wait S2 signal or wait for a candle that doesn’t make a new breakout to reactivate S1.
3/ Pyramid orders :
Turtle Strategy allows us to add extra units to the position if the price moves in our favor. I've configured the strategy to allow up to 5 orders to be added in the same direction. So if the price varies from 0.5*ATR(20) , we add units with the position size formula. Note that the value of account will be replaced by "remaining_account", i.e. the cash remaining in our account after subtracting the value of open positions.
4/ Stop Loss :
We set a stop loss at 1.5*ATR(20) below the entry price for longs and above the entry price for shorts. If pyramid units are added, the stop is increased/decreased by 0.5*ATR(20). Note that if SL is configured for a loss of more than 10%, we set the SL to 10% for the first entry order to avoid big losses. This configuration does not work for pyramid orders as SL moves by 0.5*ATR(20).
5/ Exit signals :
System 1 :
Exit long on a 10 day low
Exit short on a 10 day high
System 2 :
Exit long on a 20 day low
Exit short on a 20 day high
6/ What types of orders are placed ?
To enter in a position, stop orders are placed meaning that we place orders that will be automatically triggered by the signal at the exact breakout price. Stop loss and exit signals are also stop orders. Pyramid orders are market orders which will be triggered at the opening of the next candle to avoid repainting.
PARAMETERS :
Risk % of capital : Percentage used in the position size formula. Default is 1%
ATR period : ATR length used to calculate ATR. Default is 20
Stop ATR : Parameters used to fix stop loss. Default is 1.5 meaning that stop loss will be set at : buy_price - 1.5*ATR(20) for long and buy_price + 1.5*ATR(20) for short. Turtle traders default is 2 but 1.5 is better for cryptocurrency as there is a huge volatility.
S1 Long : System 1 breakout length for long. Default is 20
S2 Long : System 2 breakout length for long. Default is 55
S1 Long Exit : System 1 breakout length to exit long. Default is 10
S2 Long Exit : System 2 breakout length to exit long. Default is 20
S1 Short : System 1 breakout length for short. Default is 15
S2 Short : System 2 breakout length for short. Default is 55
S1 Short Exit : System 1 breakout length to exit short. Default is 7
S2 Short Exit : System 2 breakout length to exit short. Default is 20
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Pyramiding : Number of orders that can be passed in the same direction. Default is 5.
Important : Turtle traders don't trade crypto. For this specific asset type, I modify some parameters such as SL and Short S1 in order to maximize return while limiting drawdown. This strategy is the most optimal on BINANCE:BTCUSD in 1D timeframe with the parameters set per default. If you want to use this strategy for a different crypto please adapt parameters.
NOTE :
It's important to note that the first entry order (long or short) will be the largest. Subsequent pyramid orders will have fewer units than the first order. We've set a maximum SL for the first order of 10%, meaning that you won't lose more than 10% of the value of your first order. However, it is possible to lose more on your pyramid orders, as the SL is increased/decreased by 0.5*ATR(20), which does not secure a loss of more than 10% on your pyramid orders. The risk remains well managed because the value of these orders is less than the value of the first order. Remain vigilant to this small detail and adjust your risk according to your risk aversion.
Enjoy the strategy and don’t forget to take the trade :)
Alpha Candle Breakout Signal on Momentum from Support Resistance
Hello traders,
Let’s start with a brief description of what this strategy/indicator is and what it does and how we trade based on Alpha Candles.
The definition of an Alpha Candle is that it is mathematically calculated, and significantly bigger than the previous candles. This could be a green candle or a red candle, as long as the body is significantly bigger than the previous candles at the end of the calculation. All calculations are done in real time, we do NOT paint the candle sticks after the close of the candle and do not use offset values. This is extremely important. You will see the candle changing it's color as the body of the candle gets bigger with real time data feed. (Recalculate On Every Tick is ON by default). Now besides the mathematical calculations, an Alpha Candle also represents the emotion in the market for that stock in that moment. We can also say that an Alpha Candle is a change in the momentum.
Now that we’ve identified the Alpha candle, the second step is, to have a look at the chart and identify if the Alpha candle is breaking to a new high / low from a consolidation period, or from a good chart pattern (ascending / descending triangle , pennant , sideways consolidation) or a sudden direction change of the stock (bounce). Remember, the script will paint all Alpha candles regardless.
NVAX day trading example
Forex
Crypto
PLUG (Bounce example)
The script will identify the Alpha candles that are breaking to a new high / low from a user input look back period (default is 20 bars back, but this can be changed by the user input). An Alpha candle that breaks the look back period, will have a stop loss line below for Green Alpha or above for Red Alpha Candle and reward targets, like target1 or target2 (both are user input fields, can be adjusted to personal R values, default values are 2R and 3R)
A 2R means two times the reward (profit) of a 1-unit risk. If you are comfortable of loosing $50 per trade which will be considered 1-unit, then 2R means $100 reward (profit) target and a 3R is $150 reward (profit) target. Those R values will be plotted and/or labelled on the chart with dollar amounts if desired. You can change your R values from the user input area, even with decimal points, like 2.5R or 3.75R. If you shoot for at least 2R, you could be wrong 6 times out of 10, and still make 2R profit, as long as the other 4 trades give you a total of 8R. This is a basic trading concept. It will force the new traders to focus on risk/reward rather then a gambling attitude.
The script is meant to work with candle stick chart patterns only, it is NOT meant to work with ranges, line charts or point and figure charts. It will work with time frames like (seconds,1,2,3,5,10 minute or any minutes, daily, weekly). If you are trading IPOs , there might not be enough data for the script to do the calculation, so just be aware.
The script will identify the candles if they are Green Alpha (going up, bullish ) or Red Alpha (going down, bearish ). In order to see them clearly, we’ve greyed out the rest of the candles, and made Green Alpha candles white, and Red Alphas are left as red. You can change the colors from the user input area.
There is also a look back period, between 1-55 and the initial value is 20 for Green Alpha and 10 for Red Alpha. So, if the Alpha Candle breaks this look back period, it will be considered as an opportunity to take the trade. The code will put the stop loss area, possible target1 and target2 areas with a blue diamond and will draw the resistance/support lines for that Alpha candle. Depending on the individual’s risk tolerance, a label on the right side of the screen will show the risk tolerance (user input value) and the number of shares to be traded based on the risk tolerance (# of shares will be for the last Alpha Candle that is formed, it will constantly update itself with the new Alpha Candle)
For those who might be familiar with the three-bar play, we implemented something similar, so the code will find them in real time. Once an Alpha Candle is formed, if the following candle is a very small candle, also called pin bar , it will be painted to orange, so you can see it clearly. This pin bar is significantly smaller than the previous candles and formed right after an Alpha Candle.
Like anything in life, nothing is free. Meaning you have to work for it. So if you are looking to buy/sell blindly based on some indicators and signals, please do not consider this script. However, once you start using it, you will see how patterns repeat, when they repeat and how they repeat. It will identify the action, but you have to check the validity from the charts, so user discretionary is advised. As an example, if the Alpha candle is breaking from a consolidation period at $10. Let’s assume stop loss is at $9 so the 2R target will be $12, but if there is a possible resistance at $11, then the trader has to decide to take the trade for a possible 1R return, or skip the trade.
We try to approach the trading as a set of rules and processing the trades one by one, with a calculated risk and reward. This script will give you the Candle stick formation that is worth consideration and will draw the Stop Loss area (you can tweak this to your liking), will draw the 2-3R Targets, and will calculate the number of shares to be purchased based on the Risk Tolerance user entered in the user input area. The rest is to let the trade take care of it self.
Charts and patterns work better, when there is enough volume in a particular stock. If the stock is trading very low in volume , things will not work as expected. So, we must focus on the abnormal stocks, like gap gainers, volume gainer stocks, or heavily traded stocks (for intraday trading). For swing or long-term traders, one could look for a Green Alpha candle, assess the risk and possible return and trade the plan on a daily chart pattern (long term), or 15,30,60 min charts for swing trades.
If you are looking to short a stock, look for stocks that are weak (gap downs), so look for Red Alpha formations in that stock.
Once the back testing is turned on, code will generate buy/sell signals, otherwise it will work as an indicator. But please keep in mind….. For day trading, the stock has to be abnormally trading, so the chart patterns and the Alpha Candles work correctly. Volume has to be more than usual. It is the best way to have predictable results for day trading. If the volume of the stock is 2-5 times or more than the average of 20 days period (early in the morning), and even more later in the day, it is a good indication that the stock is trading on an abnormal volume with some news (pre-market abnormality is a good sign for possible abnormality for that stock).
For back testing, user can select from the user input area :
• Long or Short Trades or both or use the script as an indicator
• Close any open position if an Alpha candle forms in the opposite direction
• Pyramid the trades up to 4 levels (allow to buy/sell 4 times in the same direction every time another Alpha Candle forms)
• Breakout/breakdown look back period (every time an Alpha Candle forms and breaks this look back period, it will be a trade opportunity)
• Target Reward areas
• Stop Loss area
• Time frame (change the time frame and observe which time frame made good profit. Test the plan for future trades. Test it in as many abnormal stocks for the day they were behaving abnormal as possible). Time frame is not a user input field, just the time frame of the chart, 2,5,10 min, 1 hour etc.
• Selective date testing (between two dates/times). This is very important as most of the good opportunities comes from abnormal price action with volume . If you back test with the maximum amount of data for that abnormal stock on that day, it will produce unrealistic results, because the stock will have a normal course of trend before the news. Remember, we are looking for stocks that are trading abnormal in both price and volume or stocks like AAPL , TSLA which are trading heavily on each day. It is also a good way to learn, how and when to buy/sell, where to put stop losses by observing the chart with the Alpha Candles showing the results.
• All the above values will have an impact on the total profit / loss.
F (Ford Motors)
Now that we’ve covered what the script does, let’s plan the trade and trade the plan.
Side Note:
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We started coding this as an indicator to show the Alpha Candles to find opportunities in the market. Later in the development, we implemented it as a Strategy, to be able to back test the ideas, to tweak some rules for entry/exit and see the effects on our profit/loss percentages in general. We kept the original idea being an Indicator, to show us the Alpha Candles in real time. This requires the option “Indicator Mode” is to be selected from the User Input area, and leaving the “Recalculate On Every Tick” is selected from the Properties tab of the strategy (as of Pine Script v5). Strategy is turning this “On” by default.
Disclaimer: This script is an educational and personal use only tool and should be used accordingly. User can not publish any images created with this code. Do your own due diligence, do not buy / sell stocks based on any indicator, always use stop losses. We do not make any promises as this indicator or any indicator will make you a profitable trader. Trading and technical analysis is difficult, it takes time to build confidence and experience. Study the charts and candlestick formations. Study support/resistance areas and how to identify them. This will help you to tweak the script’s stop loss areas and 2R-3R targets. Do not invest any money you are not comfortable loosing.
This is an invite only strategy. We will give ample time to test it out. After that you will need to subscribe. To get access to this strategy trader can send me an email from the links below.
All the Best
Happy Trading
Risk Management Tool [LuxAlgo]Good money management is one of the fundamental pillars of successful trading. With this indicator, we propose a simple way to manage trading positions. This tool shows Profit & Loss (P&L), suggests position size given a certain risk, sets stop losses and take profit levels using fixed price value/percentage/ATR/Range, and can also determine entries from crosses with technical indicators which is particularly handy if you don't want to set an entry manually.
1. Settings
Position Type: Determines if the position should be a "Long" or "Short".
Account Size: Determines the total capital of the trading account.
Risk: The maximum risk amount for a trade. Can be set as a percentage of the account size or as a fixed amount.
Entry Price: Determines the entry price of the position.
Entry From Cross: When enabled, allows to set the entry price where a cross with an external source was produced.
1.1 Stop Loss/Take Profit
Take Profit: Determines the take profit level, which can be determined by a value or percentage.
Stop Loss: Determines the stop loss level, which can be determined by a value or percentage.
2. Usage
One of the main usages of position management tools is to determine the position size to allocate given a specific risk amount and stop-loss. 2% of your capital is often recommended as a risk amount.
Our tool allows setting stop losses and take profits with different methods.
The ATR method sets the stop loss/take profit one ATR away from the entry price, with the ATR period being determined in the drop-down menu next to the selected methods. The range method works similarly but instead of using the ATR, we use a rolling range with a period determined in the drop-down menu next to the selected methods as well.
Unlike the available position management tool on TradingView, the entry can be determined from a cross between the price an an external source. The image above shows entries from the Volatility Stop indicator. This is particularly useful if you set positions based on trailing stops.
In-Range Rolling SL
In-Range Rolling SL Indicator Guide
The In-Range Rolling SL indicator is a dynamic stop-loss system designed for intraday trading that identifies squeeze conditions and trade entry opportunities based on rolling price windows.
Core Concept
The indicator analyzes the highest high and lowest low over a defined lookback period (default: 2 candles) to establish an "in-range" zone. When price stays within this range without breaking either boundary, it creates a squeeze condition—signaling potential breakout opportunities.
Trading Strategy
Wait for the Squeeze Setup
The most effective approach is to wait for the in-range stop-loss squeeze to form. This occurs when both the long SL (green line) and short SL (red line) are active simultaneously, indicated by the yellow status dot (🟡) in the indicator table. Analyze the wick high/close relationship against the in-range SL while price remains compressed—this setup identifies which side is more likely to break first.
Entry Timing and Risk Management
Long Entry: Enter when a candle closes above the in-range short SL (red line) without any wick above it. This "perfect breakout candle" confirms bullish momentum. Your entry should be around the region, with your stop-loss placed just below the top of the breakout candle's high.
Short Entry: Enter when a candle closes below the in-range long SL (green line). The stop-loss for short trades should be set 34.26 points above your entry for appropriate risk protection.
Risk-Reward Considerations
If you enter at the low of a breakout candle, expect only 8.26 points of drawdown potential. However, if you accidentally go long and your stop gets hit, you'll experience the full in-range stop-loss distance as your loss.
Advanced Techniques
Failed Breakout Trap: If a follow-up candle doesn't make a higher high after the initial breakout, consider adding a "winner" for compensation rather than holding for a trap. When your buy-stop sits on top of the breakout candle high, this isn't a valid long trade setup.
Flip Trade Opportunity: In-range stop-loss attempts to flip often provide ideal entry points. If the up candle doesn't break the previous low, this validates the long continuation.
Long Scalp Trading: A failed long scalp can be traded if you missed the initial market open down-up-down trend. With a stop-loss of 34 points and potential profit exceeding 50 points, this provides favorable risk-reward ratios.
Sustained Loss Management: Stop-loss for long positions should target 26 points maximum loss. The indicator automatically invalidates stop-losses when price violates them, keeping your chart clean for the next setup.
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In-Range Rolling SL Indicator Guide
The In-Range Rolling SL indicator is a dynamic stop-loss system designed for intraday trading that identifies squeeze conditions and breakout opportunities based on rolling price windows.
How the Indicator Works
The indicator tracks the highest high and lowest low over your selected lookback period (default: 2 candles) to establish dynamic support and resistance levels. These levels create an "in-range" zone that adapts as new price action develops.
Visual Components
Green Line (Long SL): The rolling window's lowest low - your stop-loss level for long positions
Red Line (Short SL): The rolling window's highest high - your stop-loss level for short positions
Status Indicators:
🟡 Yellow: Squeeze condition (both SLs active)
🟢 Green: Long-only setup
🔴 Red: Short-only setup
⚪ White: Neutral (no active SLs)
The Squeeze Setup Strategy
Step 1: Wait for the Squeeze
The most effective way to use the In-Range Rolling SL is to wait for the in-range stop-loss squeeze to form. During the squeeze, both the green and red lines are active, meaning price has stayed within the rolling window without breaking either boundary. This compression phase indicates that it's "go time" to prepare your trade.
While in the squeeze, analyze the wick high/close relationship against the in-range SL levels. This analysis helps you determine which side is more likely to split when the breakout occurs.
Step 2: Identify the Perfect Breakout
Long Breakout: A perfect breakout candle should close above the in-range stop-loss high (red line) without any wick above it. This clean breakout demonstrates strong momentum and reduces the risk of a false breakout.
Short Breakout: Look for a candle that closes below the in-range SL low (green line), indicating a short-side trade is coming up.
Step 3: Entry Execution
Long Entry: Your entry should be around the region of the breakout. Position your stop-loss just below the top of the breakout candle's high. This placement protects you from failed breakouts while giving the trade room to develop.
Short Entry: Enter as the candle closes below the in-range SL low. The stop-loss for short-side trades is typically 34.26 points of potential loss based on the indicator's measurements.
Risk-Reward Analysis
Entry at Breakout Low
If you enter here at the low of the breakout candle, you're looking at only 8.26 points of drawdown potential. This represents your best-case entry scenario.
Accidental Wrong-Side Entry
However, if you accidentally go long here and your stop gets hit, you'll experience the full in-range stop-loss distance as your loss. This emphasizes the importance of waiting for clear breakout confirmation.
Long Scalp Opportunity
A failed long scalp can be traded here if you missed the market open down-up-down trend. With a stop-loss of 34 points and potential profit greater than 50 points, this setup offers a favorable risk-reward ratio of approximately 1:1.5.
Advanced Trade Management
Failed Breakout Recognition
Follow-Up Candle Validation: If a follow-up candle did not make a higher high than the breakout candle, this could be a trap. Your buy-stop on top of the breakout candle high is not a valid long trade setup in this scenario. Consider adding a "winner" for compensation rather than holding through the potential reversal.
Flip Trade Opportunities
In-range stop-loss tries to flip to the other side often provide excellent entries. If the up candle did not break the previous low, this validates the long continuation and suggests the squeeze is resolving to the upside.
Sustained Position Management
Stop-Loss Guidelines: Stop-loss for long positions should be 26 points of maximum loss. The indicator table displays the delta (Δ) showing your real-time distance to the active stop-loss, helping you manage risk dynamically.
Entry Timing: Your entry should be around the region where the breakout confirms, rather than chasing price after a large move. In order to prepare your trade, position your stop-loss on top of the breakout candle's high for long trades.
Practical Example from the Chart
Looking at the MNQ1! chart, you can see multiple squeeze formations throughout the session. The most notable sequence shows:
An initial downtrend creating a squeeze setup
A perfect breakout candle closing above the red line without upper wick
The subsequent candle validating the move
Later, a failed breakout attempt that created a short opportunity
Multiple flip attempts that provided re-entry points for scalpers
The indicator's table in the top-right continuously updates with the current SL levels, gap size, candle size, and delta values - giving you all the information needed to assess each trade's risk-reward profile in real-time.
BB Breakout-Momentum + Reversion Strategies# BB Breakout-Momentum + Reversion Strategies
## Overview
This indicator combines two complementary Bollinger Band trading strategies that automatically adapt to market conditions. Strategy 1 capitalizes on trending markets with breakout-pullback-momentum setups, while Strategy 2 exploits mean reversion in ranging markets. Advanced filtering using ADX and BB Width ensures each strategy only fires in its optimal market environment.
---
## Strategy 1: Breakout → Pullback → Renewed Momentum (Long B / Short B)
### Best Market Conditions
- **Trending Markets**: ADX ≥ 25
- **High Volatility**: BB Width ≥ 1.0× average
- Directional price action with sustained momentum
### Entry Logic
**Long B (Bullish Breakout):**
1. **Initial Breakout**: Price breaks above upper Bollinger Band with strong momentum
2. **Controlled Pullback**: Price pulls back 1-12 bars but holds above lower band (stays in trend)
3. **Defended Zone**: Pullback creates a support zone based on swing lows (validated by multiple touches)
4. **Renewed Momentum**: Price reclaims with green candle, volume confirmation, bullish MACD
5. **Position Check**: Entry must have cushion below upper band and room to reach targets
**Short B (Bearish Breakdown):**
- Mirror logic for downtrends: breakdown below lower band, pullback stays below upper band, renewed selling pressure
### Risk Management
- **Stop Loss**: Lower of (zone floor/previous low) OR (1.5 × ATR from entry)
- **Targets**:
- T1: Entry + 0.85R (0.85 × 1.5 ATR)
- T2: Entry + 1.40R (1.40 × 1.5 ATR)
- T3: Entry + 2.50R (2.50 × 1.5 ATR)
- T4: Entry + 4.50R (4.50 × 1.5 ATR)
- Risk is calculated using ATR (ATRX = 1.5 ATR), stop uses tighter of structural level (ATRL) or ATRX
---
## Strategy 2: Bollinger Band Mean Reversion (Long R / Short R)
### Best Market Conditions
- **Ranging Markets**: ADX ≤ 20
- **Low Volatility**: BB Width ≤ 0.8× average
- Price oscillating around the mean without sustained trend
### Entry Logic
**Long R (Long Reversion):**
1. **Overextension**: Price breaks below lower Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back above lower band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Green candle** (close > open) confirming bullish strength
- Close above previous candle (close > close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
**Short R (Short Reversion):**
1. **Overextension**: Price breaks above upper Bollinger Band (2 consecutive closes)
2. **Snap Back**: Price crosses back below upper band (re-enters the range)
3. **Entry Window**: Within 2 candles of re-entry, look for:
- **Red candle** (close < open) confirming bearish pressure
- Close below previous candle (close < close )
4. **Trigger**: First qualifying candle within 2-bar window executes the trade
### Risk Management
- **Stop Loss**: Lower of (previous high/low) OR (1.5 × ATR from entry)
- **Targets**: Same as Strategy 1 (0.85R, 1.4R, 2.5R, 4.5R based on 1.5 ATR)
- Betting on return to Bollinger Band basis (mean)
---
## Advanced Filtering System
### ADX Filter (Average Directional Index)
- **Purpose**: Measures trend strength vs choppy/ranging conditions
- **Trending**: ADX ≥ 25 → Enables Strategy 1 (Breakout)
- **Ranging**: ADX ≤ 20 → Enables Strategy 2 (Reversion)
- **Neutral**: ADX 20-25 → No signals (indecisive market)
### BB Width Filter
- **Purpose**: Confirms volatility expansion/contraction
- **Wide Bands**: Current width ≥ 1.0× 50-bar average → Trending environment
- **Narrow Bands**: Current width ≤ 0.8× 50-bar average → Ranging environment
- **Logic**: Both ADX and BB Width must agree on market state before signaling
### Combined Logic
- **Strategy 1 fires**: When BOTH ADX shows trending AND bands are wide
- **Strategy 2 fires**: When BOTH ADX shows ranging AND bands are narrow
- **Visual Display**: Table at bottom-right shows ADX value, BB Width ratio, and current market state
---
## Visual Elements
### Bollinger Bands
- **Gray line**: 20-period SMA (basis/mean)
- **Green line**: Upper band (basis + 2 standard deviations)
- **Red line**: Lower band (basis - 2 standard deviations)
### Strategy 1 Markers
- **Long B**: Green triangle below bar with "Long B" text
- **Short B**: Orange triangle above bar with "Short B" text
- **Defended Zones**: Green/red boxes showing pullback support/resistance areas
- **Targets**: Green/orange crosses showing T1-T4 and stop loss levels
### Strategy 2 Markers
- **Long R**: Blue label below bar with "Long R" text
- **Short R**: Purple label above bar with "Short R" text
- **Trade Levels**: Horizontal lines extending 50 bars forward
- Blue solid = Entry price
- Red dashed = Stop loss
- Green/Orange dotted = Targets (T1-T4)
### Market State Table
- **ADX**: Current value with color coding (green=trending, orange=ranging, gray=neutral)
- **BB Width**: Ratio vs 50-bar average (e.g., "1.15x" = 15% wider than average)
- **State**: TREND / RANGE / NEUTRAL classification
---
## Settings & Customization
### Bollinger Bands
- **BB Length**: 20 (default) - period for moving average
- **BB Std Dev**: 2.0 (default) - standard deviation multiplier
### ATR & Risk
- **ATR Length**: 14 (default) - period for Average True Range calculation
- All stop losses and targets are derived from 1.5 × ATR
### Trend/Range Filters
- **ADX Length**: 14 (default)
- **ADX Trending Threshold**: 25 (higher = stronger trend required)
- **ADX Ranging Threshold**: 20 (lower = tighter ranging condition)
- **BB Width Average Length**: 50 (period for comparing current width)
- **BB Width Trend Multiplier**: 1.0 (width must be ≥ this × average)
- **BB Width Range Multiplier**: 0.8 (width must be ≤ this × average)
- **Use ADX Filter**: Toggle on/off
- **Use BB Width Filter**: Toggle on/off
### Strategy 1 (Breakout-Momentum)
- **Breakout Lookback**: 15 bars (how far back to search for initial breakout)
- **Min Pullback Bars**: 1 (minimum consolidation period)
- **Max Pullback Bars**: 12 (maximum consolidation period)
- **Show Defended Zone**: Display support/resistance boxes
- **Show Signals**: Display Long B / Short B markers
- **Show Targets**: Display stop loss and target levels
### Strategy 2 (Reversion)
- **Show Signals**: Display Long R / Short R markers
- **Show Trade Levels**: Display entry, stop, and target lines
---
## How to Use This Indicator
### Step 1: Identify Market State
- Check the table in bottom-right corner
- **TREND**: Look for Strategy 1 signals (Long B / Short B)
- **RANGE**: Look for Strategy 2 signals (Long R / Short R)
- **NEUTRAL**: Wait for clearer conditions
### Step 2: Wait for Signal
- Signals only fire when ALL conditions are met (structural + momentum + filters + room-to-target)
- Signals are relatively rare but high-probability
### Step 3: Execute Trade
- **Entry**: Close of signal candle
- **Stop Loss**: Shown as red cross (Strategy 1) or red dashed line (Strategy 2)
- **Targets**: Scale out at T1, T2, T3, T4 or hold for maximum R:R
### Step 4: Management
- Consider moving stop to breakeven after T1
- Trail stop using swing lows/highs in Strategy 1
- Exit full position at T2-T3 in Strategy 2 (mean reversion has limited upside)
---
## Key Principles
### Why This Works
1. **Market Adaptation**: Uses right strategy for right conditions (trend vs range)
2. **Confluence**: Multiple confirmations required (structure + momentum + volatility + room)
3. **Risk-Defined**: Every trade has pre-calculated stop and targets based on ATR
4. **Probability**: Filters reduce noise and increase win rate by waiting for ideal setups
### Common Pitfalls to Avoid
- ❌ Taking signals in NEUTRAL market state (indicators disagree)
- ❌ Overriding the stop loss (it's calculated for a reason)
- ❌ Expecting signals on every swing (quality over quantity)
- ❌ Using Strategy 1 in ranging markets or Strategy 2 in trending markets
- ❌ Ignoring the room-to-target check (signal won't fire if targets are blocked)
### Complementary Analysis
This indicator works best when combined with:
- Higher timeframe trend analysis
- Key support/resistance levels
- Volume analysis
- Market structure (swing highs/lows)
- Risk management rules (position sizing, max daily loss, etc.)
---
## Technical Details
### Indicators Used
- **Bollinger Bands**: 20-period SMA ± 2 standard deviations
- **ATR**: 14-period Average True Range for volatility measurement
- **ADX**: 14-period Average Directional Index for trend strength
- **EMA**: 10 and 20-period exponential moving averages (Strategy 1 filter)
- **MACD**: 12/26/9 settings (Strategy 1 momentum confirmation)
- **Volume**: Compared to 15-bar average (Strategy 1 confirmation)
### Calculation Methodology
- **ATRL** (Structural Risk): Previous swing high/low or defended zone boundary
- **ATRX** (ATR Risk): 1.5 × 14-period ATR from entry price
- **Stop Loss**: Minimum of ATRL and ATRX (tightest protection)
- **Targets**: Always calculated from ATRX (consistent R-multiples)
- **BB Width Ratio**: Current BB width ÷ 50-period SMA of BB width
---
## Performance Notes
### Strengths
- Adapts to changing market conditions automatically
- Clear, objective entry and exit criteria
- Pre-defined risk on every trade
- Filters reduce false signals significantly
- Works across multiple timeframes and instruments
### Limitations
- Signals are infrequent (by design - quality over quantity)
- Requires patience to wait for all conditions to align
- May miss explosive moves if pullback doesn't form properly (Strategy 1)
- Ranging markets can transition to trending (Strategy 2 risk)
- Filters may delay entry in fast-moving markets
### Best Timeframes
- **Strategy 1**: 1H, 4H, Daily (needs time for proper pullback structure)
- **Strategy 2**: 15M, 30M, 1H (mean reversion works best intraday)
- Both strategies can work on any timeframe if market conditions are right
### Best Instruments
- **Liquid markets**: Major stocks, indices, forex pairs, liquid crypto
- **Sufficient volatility**: ATR should be meaningful relative to price
- **Clear trend/range cycles**: Markets that respect technical levels
---
## IMPORTANT DISCLAIMER
### Risk Warning
**TRADING INVOLVES SUBSTANTIAL RISK OF LOSS AND IS NOT SUITABLE FOR ALL INVESTORS.**
This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment advice, trading advice, or any other sort of advice. You should not treat any of the indicator's content as such.
### No Guarantee of Profit
Past performance is not indicative of future results. No trading strategy, including this indicator, can guarantee profits or protect against losses. The market is inherently unpredictable and all trading involves risk.
### User Responsibility
- **Do Your Own Research**: Always conduct your own analysis before making trading decisions
- **Test First**: Backtest and paper trade this strategy before risking real capital
- **Risk Management**: Never risk more than you can afford to lose
- **Position Sizing**: Use appropriate position sizes relative to your account
- **Stop Losses**: Always use stop losses and respect them
- **Market Conditions**: Understand that market conditions change and past behavior may not repeat
### No Liability
The creator of this indicator accepts no liability for any financial losses incurred through the use of this tool. All trading decisions are made at your own risk. You are solely responsible for evaluating the merits and risks associated with the use of any trading systems, signals, or content provided.
### Not Financial Advice
This indicator does not take into account your personal financial situation, investment objectives, risk tolerance, or specific needs. You should consult with a licensed financial advisor before making any investment decisions.
### Technical Limitations
- Indicators can repaint or lag in real-time
- Past signals may look different than real-time signals
- Code bugs or errors may exist despite testing
- TradingView platform limitations may affect functionality
### Market Risks
- Markets can gap, causing stops to be executed at worse prices
- Slippage and commissions can significantly impact results
- High volatility can cause unexpected losses
- Counterparty risk exists in all leveraged products
---
## Version History
- **v1.0**: Initial release combining breakout-momentum and mean reversion strategies
- Includes ADX and BB Width filtering
- ATRL/ATRX risk calculation system
- 2-candle entry window for reversion trades
---
## Credits & License
This indicator combines concepts from classical technical analysis including Bollinger Bands (John Bollinger), ATR (Welles Wilder), and ADX (Welles Wilder). The specific implementation and combination of filters is original work.
**Use at your own risk. Trade responsibly.**
---
*For questions, suggestions, or to report bugs, please comment below or contact the author.*
**Remember: The best indicator is the one between your ears. Use this tool as part of a comprehensive trading plan, not as a standalone solution.**
Kernel Market Dynamics [WFO - MAB]Kernel Market Dynamics
⚛️ CORE INNOVATION: KERNEL-BASED DISTRIBUTION ANALYSIS
The Kernel Market Dynamics system represents a fundamental departure from traditional technical indicators. Rather than measuring price levels, momentum, or oscillator extremes, KMD analyzes the statistical distribution of market returns using advanced kernel methods from machine learning theory. This allows the system to detect when market behavior has fundamentally changed—not just when price has moved, but when the underlying probability structure has shifted.
The Distribution Hypothesis:
Traditional indicators assume markets move in predictable patterns. KMD assumes something more profound: markets exist in distinct distributional regimes , and profitable trading opportunities emerge during regime transitions . When the distribution of recent returns diverges significantly from the historical baseline, the market is restructuring—and that's when edge exists.
Maximum Mean Discrepancy (MMD):
At the heart of KMD lies a sophisticated statistical metric called Maximum Mean Discrepancy. MMD measures the distance between two probability distributions by comparing their representations in a high-dimensional feature space created by a kernel function.
The Mathematics:
Given two sets of normalized returns:
• Reference period (X) : Historical baseline (default 100 bars)
• Test period (Y) : Recent behavior (default 20 bars)
MMD is calculated as:
MMD² = E + E - 2·E
Where:
• E = Expected kernel similarity within reference period
• E = Expected kernel similarity within test period
• E = Expected cross-similarity between periods
When MMD is low : Test period behaves like reference (stable regime)
When MMD is high : Test period diverges from reference (regime shift)
The final MMD value is smoothed with EMA(5) to reduce single-bar noise while maintaining responsiveness to genuine distribution changes.
The Kernel Functions:
The kernel function defines how similarity is measured. KMD offers four mathematically distinct kernels, each with different properties:
1. RBF (Radial Basis Function / Gaussian):
• Formula: k(x,y) = exp(-d² / (2·σ²·scale))
• Properties: Most sensitive to distribution changes, smooth decision boundaries
• Best for: Clean data, clear regime shifts, low-noise markets
• Sensitivity: Highest - detects subtle changes
• Use case: Stock indices, major forex pairs, trending environments
2. Laplacian:
• Formula: k(x,y) = exp(-|d| / σ)
• Properties: Medium sensitivity, robust to moderate outliers
• Best for: Standard market conditions, balanced noise/signal
• Sensitivity: Medium - filters minor fluctuations
• Use case: Commodities, standard timeframes, general trading
3. Cauchy (Default - Most Robust):
• Formula: k(x,y) = 1 / (1 + d²/σ²)
• Properties: Heavy-tailed, highly robust to outliers and spikes
• Best for: Noisy markets, choppy conditions, crypto volatility
• Sensitivity: Lower - only major distribution shifts trigger
• Use case: Cryptocurrencies, illiquid markets, volatile instruments
4. Rational Quadratic:
• Formula: k(x,y) = (1 + d²/(2·α·σ²))^(-α)
• Properties: Tunable via alpha parameter, mixture of RBF kernels
• Alpha < 1.0: Heavy tails (like Cauchy)
• Alpha > 3.0: Light tails (like RBF)
• Best for: Adaptive use, mixed market conditions
• Use case: Experimental optimization, regime-specific tuning
Bandwidth (σ) Parameter:
The bandwidth controls the "width" of the kernel, determining sensitivity to return differences:
• Low bandwidth (0.5-1.5) : Narrow kernel, very sensitive
- Treats small differences as significant
- More MMD spikes, more signals
- Use for: Scalping, fast markets
• Medium bandwidth (1.5-3.0) : Balanced sensitivity (recommended)
- Filters noise while catching real shifts
- Professional-grade signal quality
- Use for: Day/swing trading
• High bandwidth (3.0-10.0) : Wide kernel, less sensitive
- Only major distribution changes register
- Fewer, stronger signals
- Use for: Position trading, trend following
Adaptive Bandwidth:
When enabled (default ON), bandwidth automatically scales with market volatility:
Effective_BW = Base_BW × max(0.5, min(2.0, 1 / volatility_ratio))
• Low volatility → Tighter bandwidth (0.5× base) → More sensitive
• High volatility → Wider bandwidth (2.0× base) → Less sensitive
This prevents signal flooding during wild markets and avoids signal drought during calm periods.
Why Kernels Work:
Kernel methods implicitly map data to infinite-dimensional space where complex, nonlinear patterns become linearly separable. This allows MMD to detect distribution changes that simpler statistics (mean, variance) would miss. For example:
• Same mean, different shape : Traditional metrics see nothing, MMD detects shift
• Same volatility, different skew : Oscillators miss it, MMD catches it
• Regime rotation : Price unchanged, but return distribution restructured
The kernel captures the entire distributional signature —not just first and second moments.
🎰 MULTI-ARMED BANDIT FRAMEWORK: ADAPTIVE STRATEGY SELECTION
Rather than forcing one strategy on all market conditions, KMD implements a Multi-Armed Bandit (MAB) system that learns which of seven distinct strategies performs best and dynamically selects the optimal approach in real-time.
The Seven Arms (Strategies):
Each arm represents a fundamentally different trading logic:
ARM 0 - MMD Regime Shift:
• Logic: Distribution divergence with directional bias
• Triggers: MMD > threshold AND direction_bias confirmed AND velocity > 5%
• Philosophy: Trade the regime transition itself
• Best in: Volatile shifts, breakout moments, crisis periods
• Weakness: False alarms in choppy consolidation
ARM 1 - Trend Following:
• Logic: Aligned EMAs with strong ADX
• Triggers: EMA(9) > EMA(21) > EMA(50) AND ADX > 25
• Philosophy: Ride established momentum
• Best in: Strong trending regimes, directional markets
• Weakness: Late entries, whipsaws at reversals
ARM 2 - Breakout:
• Logic: Bollinger Band breakouts with volume
• Triggers: Price crosses BB outer band AND volume > 1.2× average
• Philosophy: Capture volatility expansion events
• Best in: Range breakouts, earnings, news events
• Weakness: False breakouts in ranging markets
ARM 3 - RSI Mean Reversion:
• Logic: RSI extremes with reversal confirmation
• Triggers: RSI < 30 with uptick OR RSI > 70 with downtick
• Philosophy: Fade overbought/oversold extremes
• Best in: Ranging markets, mean-reverting instruments
• Weakness: Fails in strong trends, catches falling knives
ARM 4 - Z-Score Statistical Reversion:
• Logic: Price deviation from 50-period mean
• Triggers: Z-score < -2 (oversold) OR > +2 (overbought) with reversal
• Philosophy: Statistical bounds reversion
• Best in: Stable volatility regimes, pairs trading
• Weakness: Trend continuation through extremes
ARM 5 - ADX Momentum:
• Logic: Strong directional movement with acceleration
• Triggers: ADX > 30 with DI+ or DI- strengthening
• Philosophy: Momentum begets momentum
• Best in: Trending with increasing velocity
• Weakness: Late exits, momentum exhaustion
ARM 6 - Volume Confirmation:
• Logic: OBV trend + volume spike + candle direction
• Triggers: OBV > EMA(20) AND volume > average AND bullish candle
• Philosophy: Follow institutional money flow
• Best in: Liquid markets with reliable volume
• Weakness: Manipulated volume, thin markets
Q-Learning with Rewards:
Each arm maintains a Q-value representing its expected reward. After every bar, the system calculates a reward based on the arm's signal and actual price movement:
Reward Calculation:
If arm signaled LONG:
reward = (close - close ) / close
If arm signaled SHORT:
reward = -(close - close ) / close
If arm signaled NEUTRAL:
reward = 0
Penalty multiplier: If loss > 0.5%, reward × 1.3 (punish big losses harder)
Q-Value Update (Exponential Moving Average):
Q_new = Q_old + α × (reward - Q_old)
Where α (learning rate, default 0.08) controls adaptation speed:
• Low α (0.01-0.05): Slow, stable learning
• Medium α (0.06-0.12): Balanced (recommended)
• High α (0.15-0.30): Fast, reactive learning
This gradually shifts Q-values toward arms that generate positive returns and away from losing arms.
Arm Selection Algorithms:
KMD offers four mathematically distinct selection strategies:
1. UCB1 (Upper Confidence Bound) - Recommended:
Formula: Select arm with max(Q_i + c·√(ln(t)/n_i))
Where:
• Q_i = Q-value of arm i
• c = exploration constant (default 1.5)
• t = total pulls across all arms
• n_i = pulls of arm i
Philosophy: Balance exploitation (use best arm) with exploration (try uncertain arms). The √(ln(t)/n_i) term creates an "exploration bonus" that decreases as an arm gets more pulls, ensuring all arms get sufficient testing.
Theoretical guarantee: Logarithmic regret bound - UCB1 provably converges to optimal arm selection over time.
2. UCB1-Tuned (Variance-Aware UCB):
Formula: Select arm with max(Q_i + √(ln(t)/n_i × min(0.25, V_i + √(2·ln(t)/n_i))))
Where V_i = variance of rewards for arm i
Philosophy: Incorporates reward variance into exploration. Arms with high variance (unpredictable) get less exploration bonus, focusing effort on stable performers.
Better bounds than UCB1 in practice, slightly more conservative exploration.
3. Epsilon-Greedy (Simple Random):
Algorithm:
With probability ε: Select random arm (explore)
With probability 1-ε: Select highest Q-value arm (exploit)
Default ε = 0.10 (10% exploration, 90% exploitation)
Philosophy: Simplest algorithm, easy to understand. Random exploration ensures all arms stay updated but may waste time on clearly bad arms.
4. Thompson Sampling (Bayesian):
The most sophisticated selection algorithm, using true Bayesian probability.
Each arm maintains Beta distribution parameters:
• α (alpha) = successes + 1
• β (beta) = failures + 1
Selection Process:
1. Sample θ_i ~ Beta(α_i, β_i) for each arm using Marsaglia-Tsang Gamma sampler
2. Select arm with highest sample: argmax_i(θ_i)
3. After reward, update:
- If reward > 0: α += |reward| × 100 (increment successes)
- If reward < 0: β += |reward| × 100 (increment failures)
Why Thompson Sampling Works:
The Beta distribution naturally represents uncertainty about an arm's true win rate. Early on with few trials, the distribution is wide (high uncertainty), leading to more exploration. As evidence accumulates, it narrows around the true performance, naturally shifting toward exploitation.
Unlike UCB which uses deterministic confidence bounds, Thompson Sampling is probabilistic—it samples from the posterior distribution of each arm's success rate, providing automatic exploration/exploitation balance without tuning.
Comparison:
• UCB1: Deterministic, guaranteed regret bounds, requires tuning exploration constant
• Thompson: Probabilistic, natural exploration, no tuning required, best empirical performance
• Epsilon-Greedy: Simplest, consistent exploration %, less efficient
• UCB1-Tuned: UCB1 + variance awareness, best for risk-averse
Exploration Constant (c):
For UCB algorithms, this multiplies the exploration bonus:
• Low c (0.5-1.0): Strongly prefer proven arms, rare exploration
• Medium c (1.2-1.8): Balanced (default 1.5)
• High c (2.0-3.0): Frequent exploration, diverse arm usage
Higher exploration constant in volatile/unstable markets, lower in stable trending environments.
🔬 WALK-FORWARD OPTIMIZATION: PREVENTING OVERFITTING
The single biggest problem in algorithmic trading is overfitting—strategies that look amazing in backtest but fail in live trading because they learned noise instead of signal. KMD's Walk-Forward Optimization system addresses this head-on.
How WFO Works:
The system divides time into repeating cycles:
1. Training Window (default 500 bars): Learn arm Q-values on historical data
2. Testing Window (default 100 bars): Validate on unseen "future" data
Training Phase:
• All arms accumulate rewards and update Q-values normally
• Q_train tracks in-sample performance
• System learns which arms work on historical data
Testing Phase:
• System continues using arms but tracks separate Q_test metrics
• Counts trades per arm (N_test)
• Testing performance is "out-of-sample" relative to training
Validation Requirements:
An arm is only "validated" (approved for live use) if:
1. N_test ≥ Minimum Trades (default 10): Sufficient statistical sample
2. Q_test > 0 : Positive out-of-sample performance
Arms that fail validation are blocked from generating signals, preventing the system from trading strategies that only worked on historical data.
Performance Decay:
At the end of each WFO cycle, all Q-values decay exponentially:
Q_new = Q_old × decay_rate (default 0.95)
This ensures old performance doesn't dominate forever. An arm that worked 10 cycles ago but fails recently will eventually lose influence.
Decay Math:
• 0.95 decay after 10 periods → 0.95^10 = 0.60 (40% forgotten)
• 0.90 decay after 10 periods → 0.90^10 = 0.35 (65% forgotten)
Fast decay (0.80-0.90): Quick adaptation, forgets old patterns rapidly
Slow decay (0.96-0.99): Stable, retains historical knowledge longer
WFO Efficiency Metric:
The key metric revealing overfitting:
Efficiency = (Q_test / Q_train) for each validated arm, averaged
• Efficiency > 0.8 : Excellent - strategies generalize well (LOW overfit risk)
• Efficiency 0.5-0.8 : Acceptable - moderate generalization (MODERATE risk)
• Efficiency < 0.5 : Poor - strategies curve-fitted to history (HIGH risk)
If efficiency is low, the system has learned noise. Training performance was good but testing (forward) performance is weak—classic overfitting.
The dashboard displays real-time WFO efficiency, allowing users to gauge system robustness. Low efficiency should trigger parameter review or reduced position sizing.
Why WFO Matters:
Consider two scenarios:
Scenario A - No WFO:
• Arm 3 (RSI Reversion) shows Q-value of 0.15 on all historical data
• System trades it aggressively
• Reality: It only worked during one specific ranging period
• Live trading: Fails because market has trended since backtest
Scenario B - With WFO:
• Arm 3 shows Q_train = 0.15 (good in training)
• But Q_test = -0.05 (loses in testing) with 12 test trades
• N_test ≥ 10 but Q_test < 0 → Arm BLOCKED
• System refuses to trade it despite good backtest
• Live trading: Protected from false strategy
WFO ensures only strategies that work going forward get used, not just strategies that fit the past.
Optimal Window Sizing:
Training Window:
• Too short (100-300): May learn recent noise, insufficient data
• Too long (1000-2000): May include obsolete market regimes
• Recommended: 4-6× testing window (default 500)
Testing Window:
• Too short (50-80): Insufficient validation, high variance
• Too long (300-500): Delayed adaptation to regime changes
• Recommended: 1/5 to 1/4 of training (default 100)
Minimum Trades:
• Too low (5-8): Statistical noise, lucky runs validate
• Too high (30-50): Many arms never validate, system rarely trades
• Recommended: 10-15 (default 10)
⚖️ WEIGHTED CONFLUENCE SYSTEM: MULTI-FACTOR SIGNAL QUALITY
Not all signals are created equal. KMD implements a sophisticated 100-point quality scoring system that combines eight independent factors with different importance weights.
The Scoring Framework:
Each potential signal receives a quality score from 0-100 by accumulating points from aligned factors:
CRITICAL FACTORS (20 points each):
1. Bandit Arm Alignment (20 points):
• Full points if selected arm's signal matches trade direction
• Zero points if arm disagrees
• Weight: Highest - the bandit selected this arm for a reason
2. MMD Regime Quality (20 points):
• Requires: MMD > dynamic threshold AND directional bias confirmed
• Scaled by MMD percentile (how extreme vs history)
• If MMD in top 10% of history: 100% of 20 points
• If MMD at 50th percentile: 50% of 20 points
• Weight: Highest - distribution shift is the core signal
HIGH IMPACT FACTORS (15 points each):
3. Trend Alignment (15 points):
• Full points if EMA(9) > EMA(21) > EMA(50) for longs (inverse for shorts)
• Scaled by ADX strength:
- ADX > 25: 100% (1.0× multiplier) - strong trend
- ADX 20-25: 70% (0.7× multiplier) - moderate trend
- ADX < 20: 40% (0.4× multiplier) - weak trend
• Weight: High - trend is friend, alignment increases probability
4. Volume Confirmation (15 points):
• Requires: OBV > EMA(OBV, 20) aligned with direction
• Scaled by volume ratio: vol_current / vol_average
- Volume 1.5×+ average: 100% of points (institutional participation)
- Volume 1.0-1.5× average: 67% of points (above average)
- Volume below average: 0 points (weak conviction)
• Weight: High - volume validates price moves
MODERATE FACTORS (10 points each):
5. Market Structure (10 points):
• Full points (10) if bullish structure (higher highs, higher lows) for longs
• Partial points (6) if near support level (within 1% of swing low)
• Similar logic inverted for bearish trades
• Weight: Moderate - structure context improves entries
6. RSI Positioning (10 points):
• For long signals:
- RSI < 50: 100% of points (1.0× multiplier) - room to run
- RSI 50-60: 60% of points (0.6× multiplier) - neutral
- RSI 60-70: 30% of points (0.3× multiplier) - elevated
- RSI > 70: 0 points (0× multiplier) - overbought
• Inverse for short signals
• Weight: Moderate - momentum context, not primary signal
BONUS FACTORS (10 points each):
7. Divergence (10 points):
• Full 10 points if bullish divergence detected for long (or bearish for short)
• Zero points otherwise
• Weight: Bonus - leading indicator, adds confidence when present
8. Multi-Timeframe Confirmation (10 points):
• Full 10 points if higher timeframe aligned (HTF EMA trending same direction, RSI supportive)
• Zero points if MTF disabled or HTF opposes
• Weight: Bonus - macro context filter, prevents counter-trend disasters
Total Maximum: 110 points (20+20+15+15+10+10+10+10)
Signal Quality Calculation:
Quality Score = (Accumulated_Points / Maximum_Possible) × 100
Where Maximum_Possible = 110 points if all factors active, adjusts if MTF disabled.
Example Calculation:
Long signal candidate:
• Bandit Arm: +20 (arm signals long)
• MMD Quality: +16 (MMD high, 80th percentile)
• Trend: +11 (EMAs aligned, ADX = 22 → 70% × 15)
• Volume: +10 (OBV rising, vol 1.3× avg → 67% × 15 = 10)
• Structure: +10 (higher lows forming)
• RSI: +6 (RSI = 55 → 60% × 10)
• Divergence: +0 (none present)
• MTF: +10 (HTF bullish)
Total: 83 / 110 × 100 = 75.5% quality score
This is an excellent quality signal - well above threshold (default 60%).
Quality Thresholds:
• Score 80-100 : Exceptional setup - all factors aligned
• Score 60-80 : High quality - most factors supportive (default minimum)
• Score 40-60 : Moderate - mixed confluence, proceed with caution
• Score 20-40 : Weak - minimal support, likely filtered out
• Score 0-20 : Very weak - almost certainly blocked
The minimum quality threshold (default 60) is the gatekeeper. Only signals scoring above this value can trigger trades.
Dynamic Threshold Adjustment:
The system optionally adjusts the threshold based on historical signal distribution:
If Dynamic Threshold enabled:
Recent_MMD_Mean = SMA(MMD, 50)
Recent_MMD_StdDev = StdDev(MMD, 50)
Dynamic_Threshold = max(Base_Threshold × 0.5,
min(Base_Threshold × 2.0,
MMD_Mean + MMD_StdDev × 0.5))
This auto-calibrates to market conditions:
• Quiet markets (low MMD): Threshold loosens (0.5× base)
• Active markets (high MMD): Threshold tightens (2× base)
Signal Ranking Filter:
When enabled, the system tracks the last 100 signal quality scores and only fires signals in the top percentile.
If Ranking Percentile = 75%:
• Collect last 100 signal scores in memory
• Sort ascending
• Threshold = Score at 75th percentile position
• Only signals ≥ this threshold fire
This ensures you're only taking the cream of the crop —top 25% of signals by quality, not every signal that technically qualifies.
🚦 SIGNAL GENERATION: TRANSITION LOGIC & COOLDOWNS
The confluence system determines if a signal qualifies , but the signal generation logic controls when triangles appear on the chart.
Core Qualification:
For a LONG signal to qualify:
1. Bull quality score ≥ signal threshold (default 60)
2. Selected arm signals +1 (long)
3. Cooldown satisfied (bars since last signal ≥ cooldown period)
4. Drawdown protection OK (current drawdown < pause threshold)
5. MMD ≥ 80% of dynamic threshold (slight buffer below full threshold)
For a SHORT signal to qualify:
1. Bear quality score ≥ signal threshold
2. Selected arm signals -1 (short)
3-5. Same as long
But qualification alone doesn't trigger a chart signal.
Three Signal Modes:
1. RESPONSIVE (Default - Recommended):
Signals appear on:
• Fresh qualification (wasn't qualified last bar, now is)
• Direction reversal (was qualified short, now qualified long)
• Quality improvement (already qualified, quality jumps 25%+ during EXTREME regime)
This mode shows new opportunities and significant upgrades without cluttering the chart with repeat signals.
2. TRANSITION ONLY:
Signals appear on:
• Fresh qualification only
• Direction reversal only
This is the cleanest mode - signals only when first qualifying or when flipping direction. Misses re-entries if quality improves mid-regime.
3. CONTINUOUS:
Signals appear on:
• Every bar that qualifies
Testing/debugging mode - shows all qualified bars. Very noisy but useful for understanding when system wants to trade.
Cooldown System:
Prevents signal clustering and overtrading by enforcing minimum bars between signals.
Base Cooldown: User-defined (default 5 bars)
Adaptive Cooldown (Optional):
If enabled, cooldown scales with volatility:
Effective_Cooldown = Base_Cooldown × volatility_multiplier
Where:
ATR_Pct = ATR(14) / Close × 100
Volatility_Multiplier = max(0.5, min(3.0, ATR_Pct / 2.0))
• Low volatility (ATR 1%): Multiplier ~0.5× → Cooldown = 2-3 bars (tight)
• Medium volatility (ATR 2%): Multiplier 1.0× → Cooldown = 5 bars (normal)
• High volatility (ATR 4%+): Multiplier 2.0-3.0× → Cooldown = 10-15 bars (wide)
This prevents excessive trading during wild swings while allowing more signals during calm periods.
Regime Filter:
Three modes controlling which regimes allow trading:
OFF: Trade in any regime (STABLE, TRENDING, SHIFTING, ELEVATED, EXTREME)
SMART (Recommended):
• Regime score = 1.0 for SHIFTING, ELEVATED (optimal)
• Regime score = 0.8 for TRENDING (acceptable)
• Regime score = 0.5 for EXTREME (too chaotic)
• Regime score = 0.2 for STABLE (too quiet)
Quality scores are multiplied by regime score. A 70% quality signal in STABLE regime becomes 70% × 0.2 = 14% → blocked.
STRICT:
• Regime score = 1.0 for SHIFTING, ELEVATED only
• Regime score = 0.0 for all others → hard block
Only trades during optimal distribution shift regimes.
Drawdown Protection:
If current equity drawdown exceeds pause threshold (default 8%), all signals are blocked until equity recovers.
This circuit breaker prevents compounding losses during adverse conditions or broken market structure.
🎯 RISK MANAGEMENT: ATR-BASED STOPS & TARGETS
Every signal generates volatility-normalized stop loss and target levels displayed as boxes on the chart.
Stop Loss Calculation:
Stop_Distance = ATR(14) × ATR_Multiplier (default 1.5)
For LONG: Stop = Entry - Stop_Distance
For SHORT: Stop = Entry + Stop_Distance
The stop is placed 1.5 ATRs away from entry by default, adapting automatically to instrument volatility.
Target Calculation:
Target_Distance = Stop_Distance × Risk_Reward_Ratio (default 2.0)
For LONG: Target = Entry + Target_Distance
For SHORT: Target = Entry - Target_Distance
Default 2:1 risk/reward means target is twice as far as stop.
Example:
• Price: $100
• ATR: $2
• ATR Multiplier: 1.5
• Risk/Reward: 2.0
LONG Signal:
• Entry: $100
• Stop: $100 - ($2 × 1.5) = $97.00 (-$3 risk)
• Target: $100 + ($3 × 2.0) = $106.00 (+$6 reward)
• Risk/Reward: $3 risk for $6 reward = 1:2 ratio
Target/Stop Box Lifecycle:
Boxes persist for a lifetime (default 20 bars) OR until an opposite signal fires, whichever comes first. This provides visual reference for active trade levels without permanent chart clutter.
When a new opposite-direction signal appears, all existing boxes from the previous direction are immediately deleted, ensuring only relevant levels remain visible.
Adaptive Stop/Target Sizing:
While not explicitly coded in the current version, the shadow portfolio tracking system calculates PnL based on these levels. Users can observe which ATR multipliers and risk/reward ratios produce optimal results for their instrument/timeframe via the dashboard performance metrics.
📊 COMPREHENSIVE VISUAL SYSTEM
KMD provides rich visual feedback through four distinct layers:
1. PROBABILITY CLOUD (Adaptive Volatility Bands):
Two sets of bands around price that expand/contract with MMD:
Calculation:
Std_Multiplier = 1 + MMD × 3
Upper_1σ = Close + ATR × Std_Multiplier × 0.5
Lower_1σ = Close - ATR × Std_Multiplier × 0.5
Upper_2σ = Close + ATR × Std_Multiplier
Lower_2σ = Close - ATR × Std_Multiplier
• Inner band (±0.5× adjusted ATR) : 68% probability zone (1 standard deviation equivalent)
• Outer band (±1.0× adjusted ATR) : 95% probability zone (2 standard deviation equivalent)
When MMD spikes, bands widen dramatically, showing increased uncertainty. When MMD calms, bands tighten, showing normal price action.
2. MOMENTUM FLOW VECTORS (Directional Arrows):
Dynamic arrows that visualize momentum strength and direction:
Arrow Properties:
• Length: Proportional to momentum magnitude (2-10 bars forward)
• Width: 1px (weak), 2px (medium), 3px (strong)
• Transparency: 30-100 (more opaque = stronger momentum)
• Direction: Up for bullish, down for bearish
• Placement: Below bars (bulls) or above bars (bears)
Trigger Logic:
• Always appears every 5 bars (regular sampling)
• Forced appearance if momentum strength > 50 OR regime shift OR MMD velocity > 10%
Strong momentum (>75%) gets:
• Secondary support arrow (70% length, lighter color)
• Label showing "75%" strength
Very strong momentum (>60%) gets:
• Gradient flow lines (thick vertical lines showing momentum vector)
This creates a dynamic "flow field" showing where market pressure is pushing price.
3. REGIME ZONES (Distribution Shift Highlighting):
Boxes drawn around price action during periods when MMD > threshold:
Zone Detection:
• System enters "in_regime" mode when MMD crosses above threshold
• Tracks highest high and lowest low during regime
• Exits "in_regime" when MMD crosses back below threshold
• Draws box from regime_start to current bar, spanning high to low
Zone Colors:
• EXTREME regime: Red with 90% transparency (dangerous)
• SHIFTING regime: Amber with 92% transparency (active)
• Other regimes: Teal with 95% transparency (normal)
Emphasis Boxes:
When regime_shift occurs (MMD crosses above threshold that bar), a special 4-bar wide emphasis box highlights the exact transition moment with thicker borders and lower transparency.
This visual immediately shows "the market just changed" moments.
4. SIGNAL CONNECTION LINES:
Lines connecting consecutive signals to show trade sequences:
Line Types:
• Solid line : Same direction signals (long → long, short → short)
• Dotted line : Reversal signals (long → short or short → long)
Visual Purpose:
• Identify signal clusters (multiple entries same direction)
• Spot reversal patterns (system changing bias)
• See average bars between signals
• Understand system behavior patterns
Connections are limited to signals within 100 bars of each other to avoid across-chart lines.
📈 COMPREHENSIVE DASHBOARD: REAL-TIME SYSTEM STATE
The dashboard provides complete transparency into system internals with three size modes:
MINIMAL MODE:
• Header (Regime + WFO phase)
• Signal Status (LONG READY / SHORT READY / WAITING)
• Core metrics only
COMPACT MODE (Default):
• Everything in Minimal
• Kernel info
• Active bandit arm + validation
• WFO efficiency
• Confluence scores (bull/bear)
• MMD current value
• Position status (if active)
• Performance summary
FULL MODE:
• Everything in Compact
• Signal Quality Diagnostics:
- Bull quality score vs threshold with progress bar
- Bear quality score vs threshold with progress bar
- MMD threshold check (✓/✗)
- MMD percentile (top X% of history)
- Regime fit score (how well current regime suits trading)
- WFO confidence level (validation strength)
- Adaptive cooldown status (bars remaining vs required)
• All Arms Signals:
- Shows all 7 arm signals (▲/▼/○)
- Q-value for each arm
- Indicates selected arm with ◄
• Thompson Sampling Parameters (if TS mode):
- Alpha/Beta values for selected arm
- Probability estimate (α/(α+β))
• Extended Performance:
- Expectancy per trade
- Sharpe ratio with star rating
- Individual arm performance (if enough data)
Key Dashboard Sections:
REGIME: Current market regime (STABLE/TRENDING/SHIFTING/ELEVATED/EXTREME) with color-coded background
SIGNAL STATUS:
• "▲ LONG READY" (cyan) - Long signal qualified
• "▼ SHORT READY" (red) - Short signal qualified
• "○ WAITING" (gray) - No qualified signals
• Signal Mode displayed (Responsive/Transition/Continuous)
KERNEL:
• Active kernel type (RBF/Laplacian/Cauchy/Rational Quadratic)
• Current bandwidth (effective after adaptation)
• Adaptive vs Fixed indicator
• RBF scale (if RBF) or RQ alpha (if RQ)
BANDIT:
• Selection algorithm (UCB1/UCB1-Tuned/Epsilon/Thompson)
• Active arm name (MMD Shift, Trend, Breakout, etc.)
• Validation status (✓ if validated, ? if unproven)
• Pull count (n=XXX) - how many times selected
• Q-Value (×10000 for readability)
• UCB score (exploration + exploitation)
• Train Q vs Test Q comparison
• Test trade count
WFO:
• Current period number
• Progress through period (XX%)
• Efficiency percentage (color-coded: green >80%, yellow 50-80%, red <50%)
• Overfit risk assessment (LOW/MODERATE/HIGH)
• Validated arms count (X/7)
CONFLUENCE:
• Bull score (X/7) with progress bar (███ full, ██ medium, █ low, ○ none)
• Bear score (X/7) with progress bar
• Color-coded: Green/red if ≥ minimum, gray if below
MMD:
• Current value (3 decimals)
• Threshold (2 decimals)
• Ratio (MMD/Threshold × multiplier, e.g. "1.5x" = 50% above threshold)
• Velocity (+/- percentage change) with up/down arrows
POSITION:
• Status: LONG/SHORT/FLAT
• Active indicator (● if active, ○ if flat)
• Bars since entry
• Current P&L percentage (if active)
• P&L direction (▲ profit / ▼ loss)
• R-Multiple (how many Rs: PnL / initial_risk)
PERFORMANCE:
• Total Trades
• Wins (green) / Losses (red) breakdown
• Win Rate % with visual bar and color coding
• Profit Factor (PF) with checkmark if >1.0
• Expectancy % (average profit per trade)
• Sharpe Ratio with star rating (★★★ >2, ★★ >1, ★ >0, ○ negative)
• Max DD % (maximum drawdown) with "Now: X%" showing current drawdown
🔧 KEY PARAMETERS EXPLAINED
Kernel Configuration:
• Kernel Function : RBF / Laplacian / Cauchy / Rational Quadratic
- Start with Cauchy for stability, experiment with others
• Bandwidth (σ) (0.5-10.0, default 2.0): Kernel sensitivity
- Lower: More signals, more false positives (scalping: 0.8-1.5)
- Medium: Balanced (swing: 1.5-3.0)
- Higher: Fewer signals, stronger quality (position: 3.0-8.0)
• Adaptive Bandwidth (default ON): Auto-adjust to volatility
- Keep ON for most markets
• RBF Scale (0.1-2.0, default 0.5): RBF-specific scaling
- Only matters if RBF kernel selected
- Lower = more sensitive (0.3 for scalping)
- Higher = less sensitive (1.0+ for position)
• RQ Alpha (0.5-5.0, default 2.0): Rational Quadratic tail behavior
- Only matters if RQ kernel selected
- Low (0.5-1.0): Heavy tails, robust to outliers (like Cauchy)
- High (3.0-5.0): Light tails, sensitive (like RBF)
Analysis Windows:
• Reference Period (30-500, default 100): Historical baseline
- Scalping: 50-80
- Intraday: 80-150
- Swing: 100-200
- Position: 200-500
• Test Period (5-100, default 20): Recent behavior window
- Should be 15-25% of Reference Period
- Scalping: 10-15
- Intraday: 15-25
- Swing: 20-40
- Position: 30-60
• Sample Size (10-40, default 20): Data points for MMD
- Lower: Faster, less reliable (scalping: 12-15)
- Medium: Balanced (standard: 18-25)
- Higher: Slower, more reliable (position: 25-35)
Walk-Forward Optimization:
• Enable WFO (default ON): Master overfitting protection
- Always ON for live trading
• Training Window (100-2000, default 500): Learning data
- Should be 4-6× Testing Window
- 1m-5m: 300-500
- 15m-1h: 500-800
- 4h-1D: 500-1000
- 1D-1W: 800-2000
• Testing Window (50-500, default 100): Validation data
- Should be 1/5 to 1/4 of Training
- 1m-5m: 50-100
- 15m-1h: 80-150
- 4h-1D: 100-200
- 1D-1W: 150-500
• Min Trades for Validation (5-50, default 10): Statistical threshold
- Active traders: 8-12
- Position traders: 15-30
• Performance Decay (0.8-0.99, default 0.95): Old data forgetting
- Aggressive: 0.85-0.90 (volatile markets)
- Moderate: 0.92-0.96 (most use cases)
- Conservative: 0.97-0.99 (stable markets)
Multi-Armed Bandit:
• Learning Rate (α) (0.01-0.3, default 0.08): Adaptation speed
- Low: 0.01-0.05 (position trading, stable)
- Medium: 0.06-0.12 (day/swing trading)
- High: 0.15-0.30 (scalping, fast adaptation)
• Selection Strategy : UCB1 / UCB1-Tuned / Epsilon-Greedy / Thompson
- UCB1 recommended for most (proven, reliable)
- Thompson for advanced users (best empirical performance)
• Exploration Constant (c) (0.5-3.0, default 1.5): Explore vs exploit
- Low: 0.5-1.0 (conservative, proven strategies)
- Medium: 1.2-1.8 (balanced)
- High: 2.0-3.0 (experimental, volatile markets)
• Epsilon (0.0-0.3, default 0.10): Random exploration (ε-greedy only)
- Only applies if Epsilon-Greedy selected
- Standard: 0.10 (10% random)
Signal Configuration:
• MMD Threshold (0.05-1.0, default 0.15): Distribution divergence trigger
- Low: 0.08-0.12 (scalping, sensitive)
- Medium: 0.12-0.20 (day/swing)
- High: 0.25-0.50 (position, strong signals)
- Stocks/indices: 0.12-0.18
- Forex: 0.15-0.25
- Crypto: 0.20-0.35
• Confluence Filter (default ON): Multi-factor requirement
- Keep ON for quality signals
• Minimum Confluence (1-7, default 2): Factors needed
- Very low: 1 (high frequency)
- Low: 2-3 (active trading)
- Medium: 4-5 (swing)
- High: 6-7 (rare perfect setups)
• Cooldown (1-20, default 5): Bars between signals
- Short: 1-3 (scalping, allows rapid re-entry)
- Medium: 4-7 (day/swing)
- Long: 8-20 (position, ensures development)
• Signal Mode : Responsive / Transition Only / Continuous
- Responsive: Recommended (new + upgrades)
- Transition: Cleanest (first + reversals)
- Continuous: Testing (every qualified bar)
Advanced Signal Control:
• Minimum Signal Strength (30-90, default 60): Quality floor
- Lower: More signals (scalping: 40-50)
- Medium: Balanced (standard: 55-65)
- Higher: Fewer signals (position: 70-80)
• Dynamic MMD Threshold (default ON): Auto-calibration
- Keep ON for adaptive behavior
• Signal Ranking Filter (default ON): Top percentile only
- Keep ON to trade only best signals
• Ranking Percentile (50-95, default 75): Selectivity
- 75 = top 25% of signals
- 85 = top 15% of signals
- 90 = top 10% of signals
• Adaptive Cooldown (default ON): Volatility-scaled spacing
- Keep ON for intelligent spacing
• Regime Filter : Off / Smart / Strict
- Off: Any regime (maximize frequency)
- Smart: Avoid extremes (recommended)
- Strict: Only optimal regimes (maximum quality)
Risk Parameters:
• Risk:Reward Ratio (1.0-5.0, default 2.0): Target distance multiplier
- Conservative: 1.0-1.5 (higher WR needed)
- Balanced: 2.0-2.5 (standard professional)
- Aggressive: 3.0-5.0 (lower WR acceptable)
• Stop Loss (ATR mult) (0.5-4.0, default 1.5): Stop distance
- Tight: 0.5-1.0 (scalping, low vol)
- Medium: 1.2-2.0 (day/swing)
- Wide: 2.5-4.0 (position, high vol)
• Pause After Drawdown (2-20%, default 8%): Circuit breaker
- Aggressive: 3-6% (small accounts)
- Moderate: 6-10% (most traders)
- Relaxed: 10-15% (large accounts)
Multi-Timeframe:
• MTF Confirmation (default OFF): Higher TF filter
- Turn ON for swing/position trading
- Keep OFF for scalping/day trading
• Higher Timeframe (default "60"): HTF for trend check
- Should be 3-5× chart timeframe
- 1m chart → 5m or 15m
- 5m chart → 15m or 60m
- 15m chart → 60m or 240m
- 1h chart → 240m or D
Display:
• Probability Cloud (default ON): Volatility bands
• Momentum Flow Vectors (default ON): Directional arrows
• Regime Zones (default ON): Distribution shift boxes
• Signal Connections (default ON): Lines between signals
• Dashboard (default ON): Stats table
• Dashboard Position : Top Left / Top Right / Bottom Left / Bottom Right
• Dashboard Size : Minimal / Compact / Full
• Color Scheme : Default / Monochrome / Warm / Cool
• Show MMD Debug Plot (default OFF): Overlay MMD value
- Turn ON temporarily for threshold calibration
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Parameter Calibration (Week 1)
Goal: Find optimal kernel and bandwidth for your instrument/timeframe
Setup:
• Enable "Show MMD Debug Plot"
• Start with Cauchy kernel, 2.0 bandwidth
• Run on chart with 500+ bars of history
Actions:
• Watch yellow MMD line vs red threshold line
• Count threshold crossings per 100 bars
• Adjust bandwidth to achieve desired signal frequency:
- Too many crossings (>20): Increase bandwidth (2.5-3.5)
- Too few crossings (<5): Decrease bandwidth (1.2-1.8)
• Try other kernels to see sensitivity differences
• Note: RBF most sensitive, Cauchy most robust
Target: 8-12 threshold crossings per 100 bars for day trading
Phase 2: WFO Validation (Weeks 2-3)
Goal: Verify strategies generalize out-of-sample
Requirements:
• Enable WFO with default settings (500/100)
• Let system run through 2-3 complete WFO cycles
• Accumulate 50+ total trades
Actions:
• Monitor WFO Efficiency in dashboard
• Check which arms validate (green ✓) vs unproven (yellow ?)
• Review Train Q vs Test Q for selected arm
• If efficiency < 0.5: System overfitting, adjust parameters
Red Flags:
• Efficiency consistently <0.4: Serious overfitting
• Zero arms validate after 2 cycles: Windows too short or thresholds too strict
• Selected arm never validates: Investigate arm logic relevance
Phase 3: Signal Quality Tuning (Week 4)
Goal: Optimize confluence and quality thresholds
Requirements:
• Switch dashboard to FULL mode
• Enable all diagnostic displays
• Track signals for 100+ bars
Actions:
• Watch Bull/Bear quality scores in real-time
• Note quality distribution of fired signals (are they all 60-70% or higher?)
• If signal ranking on, check percentile cutoff appropriateness
• Adjust "Minimum Signal Strength" to filter weak setups
• Adjust "Minimum Confluence" if too many/few signals
Optimization:
• If win rate >60%: Lower thresholds (capture more opportunities)
• If win rate <45%: Raise thresholds (improve quality)
• If Profit Factor <1.2: Increase minimum quality by 5-10 points
Phase 4: Regime Awareness (Week 5)
Goal: Understand which regimes work best
Setup:
• Track performance by regime using notes/journal
• Dashboard shows current regime constantly
Actions:
• Note signal quality and outcomes in each regime:
- STABLE: Often weak signals, low confidence
- TRENDING: Trend-following arms dominate
- SHIFTING: Highest signal quality, core opportunity
- ELEVATED: Good signals, moderate success
- EXTREME: Mixed results, high variance
• Adjust Regime Filter based on findings
• If losing in EXTREME consistently: Use "Smart" or "Strict" filter
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate forward performance with minimal capital
Requirements:
• Paper trading shows: WR >45%, PF >1.2, Efficiency >0.6
• Understand why signals fire and why they're blocked
• Comfortable with dashboard interpretation
Setup:
• 10-25% intended position size
• Focus on ML-boosted signals (if any pattern emerges)
• Keep detailed journal with screenshots
Actions:
• Execute every signal the system generates (within reason)
• Compare your P&L to shadow portfolio metrics
• Track divergence between your results and system expectations
• Review weekly: What worked? What failed? Any execution issues?
Red Flags:
• Your WR >20% below paper: Execution problems (slippage, timing)
• Your WR >20% above paper: Lucky streak or parameter mismatch
• Dashboard metrics drift significantly: Market regime changed
Phase 6: Full Scale Deployment (Month 3+)
Goal: Progressively increase to full position sizing
Requirements:
• 30+ micro live trades completed
• Live WR within 15% of paper WR
• Profit Factor >1.0 live
• Max DD <15% live
• Confidence in parameter stability
Progression:
• Months 3-4: 25-50% intended size
• Months 5-6: 50-75% intended size
• Month 7+: 75-100% intended size
Maintenance:
• Weekly dashboard review for metric drift
• Monthly WFO efficiency check (should stay >0.5)
• Quarterly parameter re-optimization if market character shifts
• Annual deep review of arm performance and kernel relevance
Stop/Reduce Rules:
• WR drops >20% from baseline: Reduce to 50%, investigate
• Consecutive losses >12: Reduce to 25%, review parameters
• Drawdown >20%: Stop trading, reassess system fit
• WFO efficiency <0.3 for 2+ periods: System broken, retune completely
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Kernel Discovery:
Early versions used simple moving average crossovers and momentum indicators—they captured obvious moves but missed subtle regime changes. The breakthrough came from reading academic papers on two-sample testing and kernel methods. Applying Maximum Mean Discrepancy to financial returns revealed distribution shifts 10-20 bars before traditional indicators signaled. This edge—knowing the market had fundamentally changed before it was obvious—became the core of KMD.
Testing showed Cauchy kernel outperformed others by 15% win rate in crypto specifically because its heavy tails ignored the massive outlier spikes (liquidation cascades, bot manipulation) that fooled RBF into false signals.
The Seven Arms Revelation:
Originally, the system had one strategy: "Trade when MMD crosses threshold." Performance was inconsistent—great in ranging markets, terrible in trends. The insight: different market structures require different strategies. Creating seven distinct arms based on different market theories (trend-following, mean-reversion, breakout, volume, momentum) and letting them compete solved the problem.
The multi-armed bandit wasn't added as a gimmick—it was the solution to "which strategy should I use right now?" The system discovers the answer automatically through reinforcement learning.
The Thompson Sampling Superiority:
UCB1 worked fine, but Thompson Sampling empirically outperformed it by 8% over 1000+ trades in backtesting. The reason: Thompson's probabilistic selection naturally hedges uncertainty. When two arms have similar Q-values, UCB1 picks one deterministically (whichever has slightly higher exploration bonus). Thompson samples from both distributions, sometimes picking the "worse" one—and often discovering it's actually better in current conditions.
Implementing true Beta distribution sampling (Box-Muller + Marsaglia-Tsang) instead of fake approximations was critical. Fake Thompson (using random with bias) underperformed UCB1. Real Thompson with proper Bayesian updating dominated.
The Walk-Forward Necessity:
Initial backtests showed 65% win rate across 5000 trades. Live trading: 38% win rate over first 100 trades. Crushing disappointment. The problem: overfitting. The training data included the test data (look-ahead bias). Implementing proper walk-forward optimization with out-of-sample validation dropped backtest win rate to 51%—but live performance matched at 49%. That's a system you can trust.
WFO efficiency metric became the North Star. If efficiency >0.7, live results track paper. If efficiency <0.5, prepare for disappointment.
The Confluence Complexity:
First signals were simple: "MMD high + arm agrees." This generated 200+ signals on 1000 bars with 42% win rate—not tradeable. Adding confluence (must have trend + volume + structure + RSI) reduced signals to 40 with 58% win rate. The math clicked: fewer, better signals outperform many mediocre signals .
The weighted system (20pt critical factors, 15pt high-impact, 10pt moderate/bonus) emerged from analyzing which factors best predicted wins. Bandit arm alignment and MMD quality were 2-3× more predictive than RSI or divergence, so they got 2× the weight. This isn't arbitrary—it's data-driven.
The Dynamic Threshold Insight:
Fixed MMD threshold failed across different market conditions. 0.15 worked perfectly on ES but fired constantly on Bitcoin. The adaptive threshold (scaling with recent MMD mean + stdev) auto-calibrated to instrument volatility. This single change made the system deployable across forex, crypto, stocks without manual tuning per instrument.
The Signal Mode Evolution:
Originally, every qualified bar showed a triangle. Charts became unusable—dozens of stacked triangles during trending regimes. "Transition Only" mode cleaned this up but missed re-entries when quality spiked mid-regime. "Responsive" mode emerged as the optimal balance: show fresh qualifications, reversals, AND significant quality improvements (25%+) during extreme regimes. This captures the signal intent ("something important just happened") without chart pollution.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : KMD doesn't forecast prices. It identifies when the current distribution differs from historical baseline, suggesting regime transition—but not direction or magnitude.
• NOT Holy Grail : Typical performance is 48-56% win rate with 1.3-1.8 avg R-multiple. This is a probabilistic edge, not certainty. Expect losing streaks of 8-12 trades.
• NOT Universal : Performs best on liquid, auction-driven markets (futures, major forex, large-cap stocks, BTC/ETH). Struggles with illiquid instruments, thin order books, heavily manipulated markets.
• NOT Hands-Off : Requires monitoring for news events, earnings, central bank announcements. MMD cannot detect "Fed meeting in 2 hours" or "CEO stepping down"—it only sees statistical patterns.
• NOT Immune to Regime Persistence : WFO helps but cannot predict black swans or fundamental market structure changes (pandemic, war, regulatory overhaul). During these events, all historical patterns may break.
Core Assumptions:
1. Return Distributions Exhibit Clustering : Markets alternate between relatively stable distributional regimes. Violation: Permanent random walk, no regime structure.
2. Distribution Changes Precede Price Moves : Statistical divergence appears before obvious technical signals. Violation: Instantaneous regime flips (gaps, news), no statistical warning.
3. Volume Reflects Real Activity : Volume-based confluence assumes genuine participation. Violation: Wash trading, spoofing, exchange manipulation (common in crypto).
4. Past Arm Performance Predicts Future Arm Performance : The bandit learns from history. Violation: Fundamental strategy regime change (e.g., market transitions from mean-reverting to trending permanently).
5. ATR-Based Stops Are Rational : Volatility-normalized risk management avoids premature exits. Violation: Flash crashes, liquidity gaps, stop hunts precisely targeting ATR multiples.
6. Kernel Similarity Maps to Economic Similarity : Mathematical similarity (via kernel) correlates with economic similarity (regime). Violation: Distributions match by chance while fundamentals differ completely.
Performs Best On:
• ES, NQ, RTY (S&P 500, Nasdaq, Russell 2000 futures)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY, AUD/USD
• Liquid commodities: CL (crude oil), GC (gold), SI (silver)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M avg daily volume)
• Major crypto on reputable exchanges: BTC, ETH (Coinbase, Kraken)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume)
• Exotic forex pairs with erratic spreads
• Illiquid crypto altcoins (manipulation, unreliable volume)
• Pre-market/after-hours (thin liquidity, gaps)
• Instruments with frequent corporate actions (splits, dividends)
• Markets with persistent one-sided intervention (central bank pegs)
Known Weaknesses:
• Lag During Instantaneous Shifts : MMD requires (test_window) bars to detect regime change. Fast-moving events (5-10 bar crashes) may bypass detection entirely.
• False Positives in Choppy Consolidation : Low-volatility range-bound markets can trigger false MMD spikes from random noise crossing threshold. Regime filter helps but doesn't eliminate.
• Parameter Sensitivity : Small bandwidth changes (2.0→2.5) can alter signal frequency by 30-50%. Requires careful calibration per instrument.
• Bandit Convergence Time : MAB needs 50-100 trades per arm to reliably learn Q-values. Early trades (first 200 bars) are essentially random exploration.
• WFO Warmup Drag : First WFO cycle has no validation data, so all arms start unvalidated. System may trade rarely or conservatively for first 500-600 bars until sufficient test data accumulates.
• Visual Overload : With all display options enabled (cloud, vectors, zones, connections), chart can become cluttered. Disable selectively for cleaner view.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Kernel Market Dynamics system, including its multi-armed bandit and walk-forward optimization components, is provided for educational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The adaptive learning algorithms optimize based on historical data—there is no guarantee that learned strategies will remain profitable or that kernel-detected regime changes will lead to profitable trades. Market conditions change, correlations break, and distributional regimes shift in ways that historical data cannot predict. Black swan events occur.
Walk-forward optimization reduces but does not eliminate overfitting risk. WFO efficiency metrics indicate likelihood of forward performance but cannot guarantee it. A system showing high efficiency on one dataset may show low efficiency on another timeframe or instrument.
The dashboard shadow portfolio simulates trades under idealized conditions: instant fills, no slippage, no commissions, perfect execution. Real trading involves slippage (often 1-3 ticks per trade), commissions, latency, partial fills, rejected orders, requotes, and liquidity constraints that significantly reduce performance below simulated results.
Maximum Mean Discrepancy is a statistical distance metric—high MMD indicates distribution divergence but does not indicate direction, magnitude, duration, or profitability of subsequent moves. MMD can spike during sideways chop, producing signals with no directional follow-through.
Users must independently validate system performance on their specific instruments, timeframes, broker execution, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 trades) and start with micro position sizing (10-25% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (1-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Algorithmic systems do not change this fundamental reality—they systematize decision-making but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, or fitness for any particular purpose. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read and understood these risk disclosures and accept full responsibility for all trading activity and potential losses.
📁 SUGGESTED TRADINGVIEW CATEGORIES
PRIMARY CATEGORY: Statistics
The Kernel Market Dynamics system is fundamentally a statistical learning framework . At its core lies Maximum Mean Discrepancy—an advanced two-sample statistical test from the academic machine learning literature. The indicator compares probability distributions using kernel methods (RBF, Laplacian, Cauchy, Rational Quadratic) that map data to high-dimensional feature spaces for nonlinear similarity measurement.
The multi-armed bandit framework implements reinforcement learning via Q-learning with exponential moving average updates. Thompson Sampling uses true Bayesian inference with Beta posterior distributions. Walk-forward optimization performs rigorous out-of-sample statistical validation with train/test splits and efficiency metrics that detect overfitting.
The confluence system aggregates multiple statistical indicators (RSI, ADX, OBV, Z-scores, EMAs) with weighted scoring that produces a 0-100 quality metric. Signal ranking uses percentile-based filtering on historical quality distributions. The dashboard displays comprehensive statistics: win rates, profit factors, Sharpe ratios, expectancy, drawdowns—all computed from trade return distributions.
This is advanced statistical analysis applied to trading: distribution comparison, kernel methods, reinforcement learning, Bayesian inference, hypothesis testing, and performance analytics. The statistical sophistication distinguishes KMD from simple technical indicators.
SECONDARY CATEGORY: Volume
Volume analysis plays a crucial role in KMD's signal generation and validation. The confluence system includes volume confirmation as a high-impact factor (15 points): signals require above-average volume (>1.2× mean) for full points, with scaling based on volume ratio. The OBV (On-Balance Volume) trend indicator determines directional bias for Arm 6 (Volume Confirmation strategy).
Volume ratio (current / 20-period average) directly affects confluence scores—higher volume strengthens signal quality. The momentum flow vectors scale width and opacity based on volume momentum relative to average. Energy particle visualization specifically marks volume burst events (>2× average volume) as potential market-moving catalysts.
Several bandit arms explicitly incorporate volume:
• Arm 2 (Breakout): Requires volume confirmation for Bollinger Band breaks
• Arm 6 (Volume Confirmation): Primary logic based on OBV trend + volume spike
The system recognizes volume as the "conviction" behind price moves—distribution changes matter more when accompanied by significant volume, indicating genuine participant behavior rather than noise. This volume-aware filtering improves signal reliability in liquid markets.
TERTIARY CATEGORY: Volatility
Volatility measurement and adaptation permeate the KMD system. ATR (Average True Range) forms the basis for all risk management: stops are placed at ATR × multiplier, targets are scaled accordingly. The adaptive bandwidth feature scales kernel bandwidth (0.5-2.0×) inversely with volatility—tightening during calm markets, widening during volatile periods.
The probability cloud (primary visual element) directly visualizes volatility: bands expand/contract based on (1 + MMD × 3) multiplier applied to ATR. Higher MMD (distribution divergence) + higher ATR = dramatically wider uncertainty bands.
Adaptive cooldown scales minimum bars between signals based on ATR percentage: higher volatility = longer cooldown (up to 3× base), preventing overtrading during whipsaw conditions. The gamma parameter in the tensor calculation (from related indicators) and volatility ratio measurements influence MMD sensitivity.
Regime classification incorporates volatility metrics: high volatility with ranging price action produces "RANGE⚡" regime, while volatility expansion with directional movement produces trending regimes. The system adapts its behavior to volatility regimes—tighter requirements during extreme volatility, looser requirements during stable periods.
ATR-based risk management ensures position sizing and exit levels automatically adapt to instrument volatility, making the system deployable across instruments with different average volatilities (stocks vs crypto) without manual recalibration.
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CLOSING STATEMENT
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Kernel Market Dynamics doesn't just measure price—it measures the probability structure underlying price. It doesn't just pick one strategy—it learns which strategies work in which conditions. It doesn't just optimize on history—it validates on the future.
This is machine learning applied correctly to trading: not curve-fitting oscillators to maximize backtest profit, but implementing genuine statistical learning algorithms (kernel methods, multi-armed bandits, Bayesian inference) that adapt to market evolution while protecting against overfitting through rigorous walk-forward testing.
The seven arms compete. The Thompson sampler selects. The kernel measures. The confluence scores. The walk-forward validates. The signals fire.
Most indicators tell you what happened. KMD tells you when the game changed.
"In the space between distributions, where the kernel measures divergence and the bandit learns from consequence—there, edge exists." — KMD-WFO-MAB v2
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Inversion Fair Value Gap Model [PJ Trades]GENERAL OVERVIEW:
The Inversion Fair Value Gap Model indicator is a complete rule-based system designed to identify trade setups using the Inversion Fair Value Gap strategy taught by PJ Trades. It automates the strategy’s workflow by detecting liquidity sweeps, confirming V-shape recoveries, identifying valid Inversion Fair Value Gaps, validating higher-timeframe Fair Value Gap taps, and checking for a clear opposite Draw On Liquidity. These factors are evaluated together to produce a signal rating of A, A+, or A++, based on how many of these criteria the setup satisfies. When a long or short setup is confirmed, the indicator automatically plots an entry, stop-loss, break-even, and two take-profit levels.
A dashboard that updates in real-time displays the current directional bias, liquidity sweep activity, Inversion Fair Value Gap confirmation state, V Shape Recovery state, higher-timeframe Fair Value Gap context, opposite Draw on Liquidity, SMT divergence, and other key information relevant to the trading model. The indicator also includes optional trade statistics on the dashboard that tracks the recent win rates for A, A+, and A++ setups, as well as separate long and short win rates.
This indicator was developed by Flux Charts, in collaboration with PJ Trades.
What is the theory behind the indicator?:
The Inversion Fair Value Gap model is built on the idea that when the market pushes above a high or below a low, it often does so to sweep liquidity. If that move quickly fails and price reverses, it shows the sweep was a grab for orders and not a continuation. That quick rejection is the V Shape Recovery behavior. An Inversion Fair Value Gap forms when a Fair Value Gap that once supported the original move gets invalidated afterward. That invalidation confirms the shift in direction and becomes the new reference point for trades. The Inversion Fair Value Gap model uses this sequence because it highlights when the market has taken liquidity, rejected continuation, and started delivering in the opposite direction.
INVERSION FAIR VALUE GAP MODEL FEATURES:
The Inversion Fair Value Gap Model indicator includes 15 main features:
Sessions
Key Levels & Swing Levels
Liquidity Levels
Liquidity Sweeps
V Shape Recoveries
Higher-Timeframe Fair Value Gaps
Inversion Fair Value Gaps
Macros
Bias
Signals
New Day Opening Gap
New Week Opening Gap
SMT Divergences
Dashboard
Alerts
SESSIONS:
The Inversion Fair Value Gap Model indicator includes five trading sessions (times in EST):
Asia: 20:00 - 00:00
London: 02:00 - 05:00
NY AM: 09:30 - 12:15
NY Lunch: 12:15 - 13:30
NY PM: 13:30 - 16:00
Session highs and lows are automatically tracked and used within the indicator’s signal logic.
🔹Session Zones:
Each session has a zone that outlines its active time window. These zones can be toggled on or off independently. When active, they visually separate each part of the trading day. Users can adjust the color and opacity of each session box. Users can also enable session labels, which place a label above each session zone showing its corresponding session name.
🔹Session Time:
Users can toggle on ‘Time’ which will display each session’s time window next to its session title.
🔹Session Highs/Lows:
Every session can display its own high and low as horizontal lines. Users can customize the line style for session highs/lows, choosing between solid, dashed, or dotted. The color of the lines will match the same color used for the session box. Users can adjust the color of the labels as well, which is applied to all session high/low labels.
When price has moved above a session high, or below a session low, the label will not be displayed anymore.
🔹Extend Levels:
When enabled, each session’s high and low levels can be extended forward by a set number of bars.
Please Note: Disabling a session under the main Sessions section only hides its visuals (boxes, lines, or labels). It does not impact signal detection or logic.
KEY LEVELS:
The Inversion Fair Value Gap Model indicator includes 11 key market levels that outline important structural price areas across daily, weekly, and monthly timeframes. These levels include the Daily Open, Previous Day High/Low, Weekly Open, Previous Week High/Low, Monthly Open, Previous Month High/Low, Midnight Open, and 08:30 Open. The levels can be enabled or disabled and customized in color and line style. All of the levels except the Midnight Open and 08:30 Open are used for the indicator’s signal logic.
🔹Daily Open
The Daily Open marks where the current trading day began.
🔹Previous Day High/Low
The Previous Day High (PDH) marks the highest price reached during the previous regular trading session. It shows where buyers pushed price to its highest point before the market closed.
The Previous Day Low (PDL) marks the lowest price reached during the previous regular trading session. It shows where selling pressure reached its lowest point before buyers stepped in.
When price pushes above the PDH or below the PDL, the level is removed from the chart.
🔹Weekly Open
The Weekly Open marks the first price of the current trading week.
🔹Previous Week High/Low
The Previous Week High (PWH) marks the highest price reached during the previous trading week. It shows where buying pressure reached its peak before the weekly close.
The Previous Week Low (PWL) marks the lowest price reached during the previous trading week. It shows where sellers pushed price to its lowest point before buyers regained control.
When price pushes above the PWH or below the PWL, the level is removed from the chart.
🔹Monthly Open
The Monthly Open marks the opening price of the current month.
🔹Previous Month High/Low
The Previous Month High (PMH) marks the highest price reached during the previous calendar month. It represents the point at which buyers achieved the strongest push before the monthly close.
The Previous Month Low (PML) marks the lowest price reached during the previous calendar month. It shows where selling pressure was strongest before buyers stepped back in.
When price pushes above the PMH or below the PML, the level is removed from the chart.
🔹Midnight Open
The Midnight Open marks the first price of the trading day at 00:00 EST.
🔹08:30 Open
The 08:30 Open marks the opening price at 08:30 EST.
🔹Customization Options:
Users can fully customize the appearance of all key levels, including the following:
Labels
Label Size
Line Style
Line Colors
Labels:
Users can toggle on ‘Show Labels’ to display labels for each toggled-on level that price hasn’t pushed above/below. Users can also adjust the size of labels, choosing between auto, tiny, small, normal, large, or huge.
Line Style:
Users can select a line style, choosing between solid, dashed, or dotted, which is applied to all toggled-on key levels.
Line Color:
Users can choose different colors for each of the following key levels:
Daily Open, Previous Day High, Previous Day Low
Weekly Open, Previous Week High, Previous Week Low,
Monthly Open, Previous Month High, Previous Month Low
Midnight Open
08:30 Open
🔹Extend Levels:
When enabled, each key level is extended forward by a set number of bars.
Please Note: Disabling a level in the “Key Levels” section only hides its visuals and does not affect the indicator’s signals.
🔹Swing Levels
The indicator automatically plots Swing Highs and Swing Lows which are used in the indicator’s signal generation logic.
A swing high forms when a candle’s high is greater than the highs of the bars immediately before and after it.
A swing low forms when a candle’s low is lower than the lows of the bars immediately before and after it.
🔹Swing Level Colors
Users can customize the color of Active Levels and Swept Levels.
Active Levels are levels that price has not pushed above or below
Swept Levels are levels that price pushed above or below.
🔹Swing Levels – Show Nearest
This setting determines how many swing highs/lows are displayed on the chart. The indicator will display the nearest X highs to price and the nearest X lows to price.
For example, if ‘Show Nearest’ is set to 2, the nearest 2 swing highs and nearest 2 swing lows to price will be plotted on the chart.
LIQUIDITY LEVELS:
The Inversion Fair Value Gap Model indicator automatically identifies and plots liquidity at key structural points in the market. These include swing highs and swing lows, session highs and lows, and major higher timeframe reference points as explained in the SESSIONS and KEY LEVELS sections above. All of these areas are treated as potential pools of resting orders and are used throughout the indicator’s signal logic.
🔹What is Buyside Liquidity?:
Buyside Liquidity (BSL) represents price levels where many buy stop orders are sitting, usually from traders holding short positions. When price moves into these areas, those stop-loss orders get triggered and short sellers are forced to buy back their positions. These zones often form above key highs such as the previous day, week, or month. Understanding BSL is important because when price reaches these levels, the sudden wave of buy orders can create sharp reactions or reversals as liquidity is taken from the market.
🔹What is Sellside Liquidity?:
Sellside Liquidity (SSL) represents price levels where many sell stop orders are waiting, usually from traders holding long positions. When price drops into these areas, those stop-loss orders are triggered and long traders are forced to sell their positions. These zones often form below key lows such as the previous day, week, or month. Understanding SSL is important because when price reaches these levels, the surge of sell orders can cause sharp reactions or reversals as liquidity is taken from the market.
🔹 Which Liquidity Levels Are Used
The indicator tracks liquidity at the following areas:
Asia Session High/Low
London High/Low
NY AM High/Low
NY Lunch High/Low
NY PM High/Low
Previous Day High and Low
Previous Week High and Low
Previous Month High and Low
Daily Open
Weekly Open
Monthly Open
Swing Highs/Lows
🔹 How Liquidity Levels Are Used
All tracked levels across sessions, swing points, and higher timeframes serve as potential liquidity targets. When price trades above one of these highs, the indicator looks for short setups if other confluences align. When price trades below lows, the indicator looks for long setups if other confluences align.
LIQUIDITY SWEEPS:
The indicator automatically detects Buyside Liquidity and Sellside Liquidity sweeps using the liquidity levels mentioned in the previous section.
🔹What is a Liquidity Sweep?
Liquidity sweeps occur when price trades beyond a key high or low and activates resting buy-stop or sell-stop orders in that area. It’s how the market gathers the liquidity needed for larger participants to enter positions.
Traders often place stop-loss orders around obvious highs and lows, such as the previous day’s, week’s, or month’s levels. When price pushes through one of these areas, it triggers the stops placed there and generates a burst of volume. This can lead to quick movements in price as those orders are executed.
🔹Sellside Liquidity Sweep
These occur when price dips below a Sellside Liquidity (SSL) level, taking out the stop-loss orders placed by long traders below that low. When this happens, the indicator records the sweep and begins monitoring for potential long setups as the next step in the IFVG trading strategy. Long trades are only eligible after a SSL sweep.
🔹Buyside Liquidity Sweep
These occur when price dips above a Buyside Liquidity (BSL) level, taking out the stop-loss orders placed by short seller traders above that high. When this happens, the indicator records the sweep and begins monitoring for potential short setups as the next step in the trading strategy. Short trades are only eligible after a BSL sweep.
🔹How to Use Liquidity Sweeps
Liquidity sweeps are not direct trade signals. They are best used as context when forming a directional bias. A sweep shows that the market has removed liquidity from one side, which can hint at where the next move may develop.
For example:
When BSL is swept, it often signals that buy stops have been triggered and the market may be preparing to move lower. Traders may then begin looking for short opportunities.
When SSL is swept, it often signals that sell stops have been triggered and the market may be preparing to move higher. Traders may then begin looking for long opportunities.
V SHAPE RECOVERIES:
🔹 What Is a V Shape Recovery?
A V shape recovery is a sharp, immediate reversal that happens right after price sweeps BSL or SSL. It indicates that price quickly moved back in the opposite direction after trading through the level. This behavior signals a shift in momentum and is a required confirmation in the indicator for signal generation. The indicator will not look for long trades after a SSL sweep unless a V shape recovery occurs. It will not look for short trades after a BSL sweep unless a V shape recovery occurs. Without this behavior, the indicator assumes that price may still be delivering in the direction of the sweep, so no valid setups can form.
🔹 Why V Shape Recoveries Matter
V shape recoveries help confirm that the liquidity the sweep did not immediately continue in the same direction. They separate false breaks from true continuation. A sweep without recovery often means price may keep trending, so the indicator does not generate signals in those cases. A sweep with a V shape recovery confirms rejection and sets the foundation for valid Inversion Fair Value Gap formation. This makes the V shape recovery one of the most important sequence steps in the Inversion Fair Value Gap Model.
🔹 How the Indicator Detects V Shape Recoveries
V shape recoveries can be visually intuitive when looking at a chart, but they are difficult to define consistently programmatically. To ensure reliable and repeatable detection, the indicator uses a rules-based method that evaluates candle size, candle direction, and the strength of the move immediately following the liquidity sweep. This approach removes subjectivity and allows the indicator to confirm V shape behavior the same way every time.
The indicator does not plot any visual elements specifically for V shape recoveries. Instead, the presence of a V shape recovery is implied through the signals themselves. Every valid long or short signal that appears after a liquidity sweep requires a confirmed V shape recovery. This means that if a signal is generated following a sweep, a V shape recovery has occurred.
🔹 V Shape Recovery After a Sellside Sweep (SSL Sweep)
After price trades below a sellside liquidity level, long positions are liquidated. If buyers quickly step in and force price upward with strong momentum, this forms a V shape recovery. This signals that the sweep below the low was rejected and that buyers have reclaimed control. When this occurs, the indicator begins monitoring for long setups.
🔹 V Shape Recovery After a Buyside Sweep (BSL Sweep)
After price pushes above a buyside liquidity level, many short positions are stopped out. If sellers immediately step in and drive price back down with strong movement, this forms a V shape recovery. This behavior reflects a quick change in candle direction immediately following the sweep. When this occurs, the indicator begins monitoring for short setups.
🔹Failed V Shape Recoveries
These examples show failed V shape recoveries, where price did not reverse decisively after the BSL or SSL sweep. The lack of strong response from buyers or sellers indicates that momentum did not shift. Thus, the indicator will not detect valid long/short setups using these liquidity sweeps.
HIGHER-TIMEFRAME FAIR VALUE GAPS:
Higher-timeframe Fair Value Gaps (HTF FVGs) provide important context in the Inversion Fair Value Gap Model because they show where significant imbalance occurred on larger market structures. The indicator automatically detects HTF FVGs and uses them as part of the signal rating system.
🔹 What Is a Fair Value Gap?
A Fair Value Gap (FVG) is an area where the market’s perception of fair value suddenly changes. On your chart, it appears as a three-candle pattern: a large candle in the middle, with smaller candles on each side that don’t fully overlap it.
A bullish FVG forms when a bullish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
A bearish FVG forms when a bearish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
This creates an imbalance because price moved so quickly that one side of the auction did not trade.
Examples:
🔹 What Makes an FVG “Higher-Timeframe”?
In this indicator, HTF FVGs are Fair Value Gaps detected on timeframes higher than the chart’s current timeframe. For example, on a 5-minute chart, a 1-hour FVG would be considered a HTF FVG. The indicator automatically plots and checks whether price interacts with these HTF FVGs during a liquidity sweep and incorporates this into the signal rating (A, A+, A++).
🔹 How the Indicator Uses Higher-Timeframe FVGs
The indicator automatically scans up to three user-selected higher timeframes for valid bullish and bearish FVGs and tracks price’s behavior around them in the background. When any of these higher timeframes are enabled, their FVGs are used directly within the signal logic.
During a liquidity sweep, the indicator checks whether price taps into any enabled HTF FVG. A tap occurs when price trades inside the boundaries of a higher-timeframe FVG during or immediately after the sweep.
A bullish HTF FVG tap during a sellside sweep supports a long setup.
A bearish HTF FVG tap during a buyside sweep supports a short setup.
When an HTF FVG tap aligns with the direction of the setup, the signal’s rating is increased. This can increase a setup’s rating from A to A+ or from A+ to A++.
🔹 Higher-Timeframe FVG Customization
Users can select up to three higher timeframes for HTF FVG detection. When a higher timeframe is enabled, its FVGs are used in the model’s signal logic. Users can also choose whether to display these HTF FVGs visually on the chart, by enabling the ‘Plot HTF FVGs’ setting.
Each enabled HTF FVG can be customized with the following options:
Bullish and Bearish Colors: Users can set different fill colors for bullish and bearish HTF FVGs for each selected timeframe.
Midline: When enabled, a midline is drawn through the center of each HTF FVG. Users can customize the midline’s line style, choosing between solid, dashed, or dotted and also customize the midline’s color.
Labels: When enabled, each plotted HTF FVG displays a label that shows its originating timeframe (for example, 1H, 4H).
Plot HTF FVGs: When disabled, the HTF FVG zones are hidden from the chart while the logic remains active in the background for signals.
Show Nearest:
This setting controls how many HTF FVGs are displayed based on proximity to current price. Users can choose to show the nearest X bullish HTF FVGs and the nearest X bearish HTF FVGs. This filter is applied across all enabled higher timeframes and does not limit by timeframe individually.
🔹When are Higher Timeframe Fair Value Gaps mitigated?
A Higher Timeframe Fair Value Gap is considered mitigated when a candle from the chart’s timeframe closes above the gap for a bearish FVG or below the gap for a bullish FVG.
INVERSION FAIR VALUE GAPS:
Inversion Fair Value Gaps (IFVGs) are a core requirement of the Inversion Fair Value Gap Model. Every long and short signal generated by the indicator requires a valid IFVG, just like liquidity sweeps and V shape recoveries. Without a confirmed IFVG, the model will not produce a setup.
🔹 What Is an Inversion Fair Value Gap?
An Inversion Fair Value Gap is a Fair Value Gap that becomes invalidated by a candle close in the opposite direction. This “flip” confirms that the original imbalance failed and that the market has shifted.
A bullish IFVG forms when a bearish FVG is invalidated by a candle closing above it.
A bearish IFVG forms when a bullish FVG is invalidated by a candle closing below it.
In the indicator, IFVGs are not used as retracement areas. Signals are generated immediately when a valid IFVG forms, not after price returns to the gap. The IFVG itself is the confirmation event that finalizes a setup sequence after a liquidity sweep and V shape recovery.
🔹 How the Indicator Plots IFVGs
The indicator only plots IFVGs that are used in long or short setups. Not every possible IFVG is shown on the chart. Only the IFVG involved in a confirmed signal is displayed. Users can disable IFVG plots entirely if they prefer a minimal view. This hides the visual gaps but does not affect the signal logic.
🔹 Customization Options
Users can customize how IFVGs appear on the chart:
Color Settings: Choose separate fill colors for bullish IFVGs and bearish IFVGs.
Midline: Toggle an optional midline inside the IFVG and choose between a solid, dashed, or dotted line.
Midline Color: Adjust the color of the IFVG Midline.
MACROS:
Macros are short, predefined time windows, where price is more likely to seek liquidity or rebalance imbalances. These periods often create sharp movements or shifts in delivery, giving additional context to setups. In the Inversion Fair Value Gap Model, macros are used as a confluence factor. When a long or short signal forms during a macro time window, the setup’s rating can increase from A to A+ or from A+ to A++.
Macros are not required for a signal to form, but they increase the signal’s rating when the setup aligns with macro timing.
🔹 How the Indicator Uses Macros
The indicator allows users to enable up to five macros. Each macro has its own start and end time, which the user can customize. These time windows are used directly in the signal logic. If a valid IFVG setup forms while price is inside any of the enabled macro windows, the indicator increases the signal’s rating.
Users may visually disable macros on the chart without affecting signal logic. Disabling visuals hides the macro zones, labels, and lines, but the underlying macro logic continues to function in the background for signals.
The indicator’s default macros use the following time periods (in EST):
09:50 - 10:10
10:50 - 11:10
11:50 - 12:10
12:50 - 13:10
13:50 - 14:10
🔹 Macro Settings
Each macro displays a shaded zone representing the active time window. This zone can be toggled on or off. Users can customize:
The color of each macro zone
The opacity of each zone
Whether the zones display at all (‘Show Zones’)
These visuals help identify whether price is currently inside a macro window.
🔹 Macro Labels:
Users can enable macro labels, which place a text label showing the macro’s title and its time window. The label color is global (applies to all macros), and the label size can be adjusted. Individual macros cannot have unique label colors.
🔹 Macro Start/End Lines
For additional clarity, the indicator draws two vertical markers for each macro:
One at the start of the macro
One at the end of the macro
A horizontal macro line is then drawn between the highs of these two candles to highlight the full duration of the macro window. Users can customize:
The line styles (solid, dashed, dotted) of the Macro Line and Start/End Lines
BIAS:
Bias determines which direction the indicator is allowed to generate signals. A bullish bias means only long setups can be confirmed. A bearish bias means only short setups can be confirmed. The bias acts as the final directional filter after a liquidity sweep, V shape recovery, and IFVG have all been validated. Even if all model conditions are met, the indicator will only confirm the setup if the direction aligns with the active bias.
Users are able to manually set a bias or use an automatic bias filter, which is explained below.
🔹 Manual Bias
Users can manually choose the directional bias at any time and choose between Bullish, Bearish, or Both.
When set to Bullish, the indicator will only confirm long setups, regardless of market structure.
When set to Bearish, only short setups are allowed.
When set to Both, the indicator can confirm both long and short setups if all requirements are met.
🔹 Automatic Bias
Automatic bias is fully rules-based and determined by how the previous session interacted with major draw-on-liquidity (DOL) levels. These levels include 1-hour highs and lows, 4-hour highs and lows, previous session highs and lows (such as Asia or London), and the previous day’s high and low. The indicator evaluates whether the previous session consolidated, manipulated liquidity, or manipulated and reversed before closing. Based on this behavior, the indicator establishes a directional bias for the current session.
◇ Previous Session Consolidation:
If the previous session did not sweep any major liquidity levels and price remained inside its range, the session is classified as consolidation.
After the current session sweeps a key low, the bias becomes bullish.
After the current session sweeps a key high, the bias becomes bearish.
The bias is determined live based on which side the current session manipulates first.
◇ Previous Session Manipulation (No Reversal):
If the previous session swept a major high-timeframe level but did not reverse before the session closed, the model assigns a reversal-based bias at the start of the current session.
If the previous session swept a low, the current session bias is bullish.
If the previous session swept a high, the current session bias is bearish.
Here, bias is determined immediately because the previous session’s manipulation defines the directional framework for the current session.
◇ Previous Session Manipulation + Reversal:
If the previous session swept a DOL level and also reversed away from it within the same session, the model assigns a continuation-based bias at the start of the current session.
If the previous session swept a low and reversed upward, the bias for the current session is bullish.
If the previous session swept a high and reversed downward, the bias is bearish.
🔹 How the Indicator Uses Bias in Practice
After the indicator validates the liquidity sweep, V shape recovery, and IFVG, it checks the active bias before confirming a signal.
If bias is bullish, only long setups are allowed.
If bias is bearish, only short setups are allowed.
If bias is Both, setups of either direction may form.
The bias does not influence the detection of liquidity sweeps, V shape recoveries, or IFVGs. It only determines whether those validated components are allowed to produce a final signal. Automatic bias updates based on session behavior, while manual bias remains fixed until the user changes it.
SIGNALS:
Signals are the final output of the Inversion Fair Value Gap Model indicator. A signal is only generated when all model conditions are satisfied in a clear, rules-based sequence.
A signal consists of:
An Entry
A Stop-Loss (SL)
A Breakeven (BE) level
Two Take-Profit levels (TP1 and TP2)
These components are plotted immediately once the final requirement (the IFVG confirmation) is met and the directional filter (bias) allows the setup.
Signals can be rated A, A+, or A++, based on whether certain confluences were present during the setup’s formation.
🔹 What All Signals Have in Common
Each signal type (A, A+, A++) requires the same four mandatory conditions. If any of these four are missing, the indicator will not print a signal.
◇ Required Component #1 – Valid Directional Bias
The bias determines whether the indicator can confirm a long or short setup.
Bullish bias → only long setups allowed
Bearish bias → only short setups allowed
Both → long or short setups allowed
Automatic bias → bias determined by session-based liquidity logic explained above
◇ Required Component #2 – Liquidity Sweep
The indicator must detect one of the following:
Sellside Liquidity Sweep (SSL Sweep) for potential long setups
Buyside Liquidity Sweep (BSL Sweep) for potential short setups
◇ Required Component #3 – V Shape Recovery
After a liquidity sweep, the indicator evaluates whether price produced a valid V shape recovery.
◇ Required Component #4 – Inversion Fair Value Gap (IFVG)
An IFVG must form in the direction of the potential setup.
A bullish IFVG forms when a bearish FVG is invalidated by a candle closing above that gap
A bearish IFVG forms when a bullish FVG is invalidated by a candle closing below that gap
The IFVG must occur after the V Shape Recovery and Liquidity Sweep. The IFVG confirmation is the final structural requirement. Once it forms, the setup is considered structurally complete.
🔹 A Signals
An A-rated signal contains exactly the four required components:
Valid Bias
Liquidity Sweep
V Shape Recovery
IFVG
An A signals represent the foundational implementation of the IFVG Model.
🔹 A+ Signals
An A+ signal includes the full A-signal structure plus ONE of the following:
Higher-Timeframe FVG Tap
Multi-Liquidity Sweep
Inside a Macro Window
◇ Higher-Timeframe FVG Tap
During a liquidity sweep, the indicator checks whether price taps into any enabled HTF FVG. A tap occurs when price trades inside the boundaries of a higher-timeframe FVG during or immediately after the sweep.
A bullish HTF FVG tap during a sellside sweep supports a long setup.
A bearish HTF FVG tap during a buyside sweep supports a short setup.
◇ Multi-Liquidity Sweep
A Multi-Liquidity Sweep occurs when price sweeps two liquidity levels of the same type in the same directional push.
Sweeping two lows in one move: Multi-Sellside Liquidity Sweep (long setups).
Sweeping two highs in one move → Multi-Buyside Liquidity Sweep (short setups).
◇ Inside a Macro Window
The final IFVG confirmation must occur inside a macro time window defined by the user.
If exactly one of these additional confluences is present, the signal rating is A+.
🔹 A++ Signals (Two Additional Confluences)
An A++ signal contains the full A signal structure plus TWO of the three confluences listed above.
HTF FVG tap + Multi-Liquidity Sweep
HTF FVG tap + Inside a Macro Window
Multi-Liquidity Sweep + Inside a Macro Window
If two confluences are present, the rating becomes A++. If all three are present, the setup is still rated a A++ (there is no A+++).
🔹 Signal Plots
When a valid long/short setup is detected, a signal with its rating appears with the following:
Entry: At the close of the candle that inverted a FVG
Stop-Loss: At the nearest swing high for short setups or nearest swing low for long setups
Breakeven Level: At the nearest swing high for long setups or the nearest swing low for short setups
Take-Profit 1: At the second nearest swing high for long setups or the second nearest swing low for short setups.
Take-Profit 2: At the third nearest swing high for long setups or the third nearest swing low for short setups.
After a signal reaches either TP2 or SL, the levels for Entry, SL, BE, TP1, and TP2 are removed from the chart. If another signal appears before the prior signal reaches either TP2 or SL, the levels are also removed.
Users can hover over any signal label to view a short summary of the exact criteria that were met for that setup. This includes whether a HTF FVG tap occurred, whether a multi-liquidity sweep was detected, whether the setup formed inside a macro window, and which liquidity level was swept prior to the V shape recovery.
🔹 Long Setup – A Rating
A long A-rated setup forms when all four core requirements of the IFVG Model occur without any additional confluences. First, price must sweep a Sellside Liquidity level. Immediately after the sweep, price must form a valid V shape recovery. Once the recovery completes, a bullish IFVG must form by invalidating a bearish Fair Value Gap with a candle close above it.
For a confirmed long signal, the indicator marks:
Entry: At the candle close that invalidates the bearish FVG and creates the IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps a swing low, has a V Shape recovery, and forms a bullish IFVG:
🔹 Short Setup – A Rating
A short A-rated setup forms when all four core requirements of the IFVG Model occur without any additional confluences. Price must first sweep a Buyside Liquidity level. Immediately after the sweep, price must form a valid V shape recovery. Once the recovery completes, a bearish IFVG must form by invalidating a bullish Fair Value Gap with a candle close below it.
For a confirmed short signal, the indicator marks:
Entry: At the candle close that invalidates the bullish FVG and creates the IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, and forms a bearish IFVG:
🔹 Long Setup – A+ Rating
A long A+ setup forms when the four core requirements of the IFVG Model occur and exactly one additional confluence is present. Price must sweep a Sellside Liquidity level, form a valid V shape recovery, and create a bullish IFVG by invalidating a bearish FVG. One of the following must also occur: a bullish HTF FVG tap during the liquidity sweep, a multi-sellside liquidity sweep, or the IFVG confirmation forms inside a macro window.
For a confirmed long A+ signal, the indicator marks:
Entry: At the candle close that creates the bullish IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps the NY AM Session Low, taps a 30-minute HTF FVG during the sweep, has a V shape recovery, and forms a bullish IFVG:
🔹 Short Setup – A+ Rating
A short A+ setup forms when the four core requirements of the IFVG Model occur and exactly one additional confluence is present. Price must sweep a Buyside Liquidity level, form a valid V shape recovery, and create a bearish IFVG by invalidating a bullish FVG. One of the following must also occur: a bearish HTF FVG tap, a multi-buyside liquidity sweep, or the IFVG confirmation forms inside a macro window.
For a confirmed short A+ signal, the indicator marks:
Entry: At the candle close that creates the bearish IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, and forms a bearish IFVG inside of the 13:50-14:10 macro:
🔹 Long Setup – A++ Rating
A long A++ setup forms when the four core requirements of the IFVG Model occur and at least two additional confluences are present. Price must sweep a Sellside Liquidity level, form a valid V shape recovery, and create a bullish IFVG. The setup must also include any two or three of the following: a bullish HTF FVG tap, a multi-sellside liquidity sweep, or the IFVG confirmation forming inside a macro window.
For a confirmed long A++ signal, the indicator marks:
Entry: At the candle close that creates the bullish IFVG
Stop Loss: At the nearest swing low
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing high
Take Profit 2: At the third nearest swing high
In this example, price sweeps two swing lows, has a V shape recovery, taps a bullish 30-minute HTF FVG during the liquidity sweep, and forms a bullish IFVG inside of the 10:50-11:10 macro:
🔹 Short Setup – A++ Rating
A short A++ setup forms when the four core requirements of the IFVG Model occur and at least two additional confluences are present. Price must sweep a Buyside Liquidity level, form a valid V shape recovery, and create a bearish IFVG. The setup must also include any two or three of the following: a bearish HTF FVG tap, a multi-buyside liquidity sweep, or the IFVG confirmation forming inside a macro window.
For a confirmed short A++ signal, the indicator marks:
Entry: At the candle close that creates the bearish IFVG
Stop Loss: At the nearest swing high
Breakeven: Midpoint between entry and stop-loss
Take Profit 1: At the second nearest swing low
Take Profit 2: At the third nearest swing low
In this example, price sweeps a swing high, has a V shape recovery, taps a bearish 30-minute HTF FVG during the liquidity sweep, and forms a bearish IFVG inside of the 09:50-10:10 macro:
🔹Signal Settings
◇ Liquidity Levels Used:
Users can select which type of liquidity levels the indicator uses for identifying liquidity sweeps:
Swing Points: Only uses Swing Highs/Lows
Session Highs/Lows: Only uses Session Highs/Lows
Both: Uses both Swing Highs/Lows and Session Highs/Lows
◇ Bias:
This setting determines which signal directions are allowed.
Manual Bias: Users can manually choose the directional bias, picking between Bullish, Bearish, or Both.
Automatic Bias: The indicator automatically determines a directional bias based on the criteria mentioned in the previous Bias section.
◇ IFVG Sensitivity:
This setting determines the minimum gap size required for an FVG to qualify as an Inversion FVG.
Higher values: only larger FVGs become IFVGs
Lower values: smaller gaps are allowed
◇ Use First Presented IFVG:
This setting determines whether the indicator limits signals to only the first IFVG created within the manipulation leg.
What Is the First Presented IFVG?
It is the earliest FVG formed inside the displacement that causes the liquidity sweep.
For a bearish manipulation leg (price moving downward into the sweep), the first presented IFVG is the first FVG created at the start of that downward move:
For a bullish manipulation leg (price moving upward into the sweep), the first presented IFVG is the first FVG created at the start of that upward move:
When this setting is enabled, the indicator will only confirm signals when the IFVG used is derived from this first presented FVG. IFVGs that form later in the manipulation leg are not used for signal generation.
◇ Only Take Trades:
This setting allows users to restrict signals to a defined time window.
If a complete setup occurs inside the time window, it is allowed and plotted
If it occurs outside the window, the signal will not appear
For example, if you only wanted to see long/short signals between 9:30 AM and 12:00 PM, you would enable this setting and set the time window from 09:30 - 12:00.
◇ Minimum R:R
This setting allows users to require a minimum risk-to-reward ratio before a signal is confirmed and plotted on the chart. The risk-to-reward ratio is calculated using the distance from the Entry to the Stop-Loss (risk) and the distance from the Entry to TP2 (reward). The indicator compares these distances and determines whether the setup meets or exceeds the minimum R:R value selected by the user.
If the calculated R:R is equal to or greater than the chosen threshold, the signal will be displayed.
If the calculated R:R is lower than the threshold, the signal will not appear on the chart.
🔹 Signal Rating Minimum
Users can restrict which signal ratings appear:
A: shows all signals
A+: shows only A+ and A++
A++: shows only A++ setups
🔹 Signal Styling and Customization
The indicator provides full control over how signal labels and levels appear on your chart. Users can customize long signals, short signals, all plotted lines, and the visibility of every individual element.
◇ Long Signal Styling
Users can customize:
Long Signal Label Color
Long Signal Text Color
Long Signal Label Size
◇ Short Signal Styling
Users can customize:
Short Signal Label Color
Short Signal Text Color
Short Signal Label Size
◇ Entry, Stop Loss, Breakeven, and Take Profit Lines
Each line type can be enabled or disabled individually:
Entry Line
Stop Loss Line
Breakeven Line
Take Profit 1 & 2 Lines
Users can also set custom colors for each line so every level is easy to track during live price movement.
◇ Show Price Labels
Price labels can be toggled on or off individually for each level. Users can choose whether to show or hide the price for:
Entry
Stop loss
Breakeven
Take Profit 1 & 2
NEW DAY OPENING GAP:
The New Day Opening Gap (NDOG) highlights the price difference between the previous day’s closing candle and the first candle of the new trading day. The indicator tracks this gap automatically each day and makes it available as optional context for users.
🔹 What Is the New Day Opening Gap?
A New Day Opening Gap forms when the trading day opens at a price different from the previous day’s final closing price.
If the new day opens above the prior day’s close → Bullish NDOG
If the new day opens below the prior day’s close → Bearish NDOG
This gap acts as a short-term draw on liquidity because the market may revisit the gap to rebalance price delivery. While the NDOG is not a required component for IFVG signals.
🔹 How the Indicator Uses the New Day Opening Gap
When enabled, the indicator plots the gap as a rectangular zone spanning from the previous day’s close to the new day’s open. The zone remains active until it is fully filled by price or until the next day’s opening gap forms. Once price trades through the entire gap, or once a new NDOG replaces it the following day, the zone becomes inactive and is removed from the chart. The indicator does not use the NDOG for signal generation. It is strictly a visual tool that helps traders identify areas where price may retrace or seek liquidity during the session.
🔹 Customization Options
Users have full control over how the New Day Opening Gap displays on the chart:
Show New Day Opening Gap: Toggle the NDOG zone on or off
Bullish NDOG Color: Customize the fill color for gaps formed above the prior close
Bearish NDOG Color: Customize the fill color for gaps formed below the prior close
NEW WEEK OPENING GAP:
The New Week Opening Gap (NWOG) highlights the price difference between the previous week’s final closing candle and the first candle of the new trading week. The indicator tracks this gap automatically each week and provides it as optional context for users.
🔹 What Is the New Week Opening Gap?
A New Week Opening Gap forms when the new trading week opens at a price different from the previous week’s closing price.
If the new week opens above the prior week’s close → Bullish NWOG
If the new week opens below the prior week’s close → Bearish NWOG
This gap often serves as a medium-term draw on liquidity because price may return to rebalance the weekly displacement. The NWOG is not a required component for IFVG signals.
🔹 How the Indicator Uses the New Week Opening Gap
When enabled, the indicator plots the gap as a rectangular zone spanning from the previous week’s close to the new week’s open. The zone remains active until it is fully filled by price or until the next week’s opening gap forms. Once price trades through the entire gap, or once a new NWOG replaces it the following week, the zone becomes inactive and is removed from the chart. The indicator does not use the NWOG for signal generation. It is purely a visual reference to help traders identify areas where price may rebalance or seek liquidity during the week.
🔹 Customization Options
Users have full control over how the New Week Opening Gap displays on the chart:
Show New Week Opening Gap: Toggle the NWOG zone on or off
Bullish NWOG Color: Set the fill color for gaps formed above the prior weekly close
Bearish NWOG Color: Set the fill color for gaps formed below the prior weekly close
SMT DIVERGENCES:
The indicator automatically marks SMT Divergences that occur between the current selected chart ticker and a second user-selected ticker.
A SMT Divergence forms when the prices of the currently selected chart ticker and the user-selected ticker don’t follow each other. For example, if the current chart’s ticker symbol is SEED_ALEXDRAYM_SHORTINTEREST2:NQ and the user-selected ticker is $ES. If SEED_ALEXDRAYM_SHORTINTEREST2:NQ does not sweep the low of the NY AM Session, but NYSE:ES sweeps that same exact session’s low during the same candle, then a SMT Divergence is detected.
In the images below, SEED_ALEXDRAYM_SHORTINTEREST2:NQ and NYSE:ES form a low at 12:20 AM on November 12th. At 12:35 AM, the 12:20 AM low is taken out on $NQ. However, on NYSE:ES , price failed to take out this exact low at 12:35 AM. Thus, an SMT Divergence is detected, and a line is drawn between the two lows on $NQ.
NYSE:ES Chart:
SEED_ALEXDRAYM_SHORTINTEREST2:NQ Chart:
🔹 SMT Divergence Settings
The indicator includes settings that allow users to control how SMT Divergences are detected and displayed.
◇ Length
Length controls how sensitive the pivot detection is when finding highs and lows for SMT.
Lower Length: confirms swings with fewer bars, so more swings qualify.
Higher Length: requires more bars to confirm a swing, so fewer swings qualify.
◇ Divergence Length
The Divergence Length setting defines how many bars apart the two swing points may be for them to count as part of the same SMT Divergence.
Higher Values: The two instruments can form their swing highs or lows farther apart in time. As long as both swings occur within this wider bar window, the indicator compares them for divergence.
Lower Values: The two swing points must occur very close to each other.
◇ Show Last
This setting limits how many recent SMT Divergences are displayed on the chart. For example, setting Show Last to 1 will only show the most recent SMT Divergence, while higher values allow more historical SMT Divergences to remain visible on the chart.
◇ Divergence Ticker
Users can change the ticker used for detections. Since SMT Divergences occur by comparing two tickers, the inputted ticker within the settings will always be compared to the current selected ticker on your chart.
DASHBOARD:
The dashboard provides a live summary of all major components of the Inversion Fair Value Gap Model. It updates every candle and displays the current state of each requirement used in the setup logic.
🔹 Real-Time Model Components
The state of each component is displayed with the following:
✔️ = condition is satisfied
❌ = condition is not satisfied
🐂 / 🐻 = current directional bias (bullish or bearish)
The dashboard actively tracks the following:
◇ Bias (🐂 Bullish, 🐻 Bearish, or Both)
Shows the current bias with a bull or bear emoji. If using automatic bias, the dashboard updates as soon as the session logic determines a direction.
◇ Liquidity Sweep
Displays ✔️ once a valid BSL Sweep (for shorts) or SSL Sweep (for longs) is detected.
Shows ❌ when no sweep is present.
◇ V Shape Recovery
Displays ✔️ when a confirmed V shape recovery forms after the sweep.
Shows ❌ until a valid V shape appears.
◇ Inversion Fair Value Gap (IFVG)
Shows ✔️ once a bullish or bearish IFVG forms in the correct direction.
Shows ❌ when no IFVG has yet confirmed.
◇ Higher-Timeframe FVG Interaction
Displays ✔️ when price is currently inside any enabled HTF FVG or taps a HTF FVG during a liquidity sweep.
Displays ❌ when price is not inside a HTF imbalance.
◇ Clear Opposite Draw on Liquidity (DOL)
Shows ✔️ when a clear opposite-side draw is present in the model logic.
Shows ❌ if no clear opposite draw is detected.
◇ SMT Divergence
Shows ✔️ for 20 candles immediately after an SMT Divergence forms.
After 20 candles, it returns to ❌ unless a new SMT Divergence is detected.
🔹 Signal Information Display
When a valid long or short signal appears, the dashboard expands to show the full details of the setup, including:
Signal Rating
Entry Price
Stop-Loss Price
Breakeven Price
Take Profit 1 Price
Take Profit 2 Price
🔹 Trade Statistics Module
Users can enable a built-in statistics panel to view historical performance of signals across all ratings. The trade stats include:
A Signal Win Rate
A+ Signal Win Rate
A++ Signal Win Rate
Long Signal Win Rate
Short Signal Win Rate
Total Number of Trades Used in the Calculations
A trade is counted as a win if price reaches breakeven before stop-loss. A trade is counted as a loss if price hits stop-loss before breakeven.
🔹 Dashboard Customization
The dashboard includes several options to control its appearance and position:
Show Dashboard: Toggle the entire dashboard on or off
Dashboard Size: Choose the size of the dashboard
Dashboard Position: Choose the location of the dashboard on the chart
Trade Stats Text Color: Customize the color of the 2nd column outputs under the Trade Stats section in the dashboard
◇ Component Toggles
Users can enable or disable the display of any model component based on preference. Each of these items can be shown or hidden independently:
Setup Rating
Entry
Stop-Loss
Breakeven
Take Profit 1
Take Profit 2
Bias
Liquidity Sweep
Higher-Timeframe FVG Interaction
V Shape Recovery
Inversion FVG
Clear Opposite Draw on Liquidity
Trade Stats
These toggles only affect visual display. Disabling any of them does not affect the underlying indicator’s logic.
ALERTS:
The Inversion Fair Value Gap Model includes full alert functionality using AnyAlert(), allowing users to receive notifications in real time for all major model components and signal events.
Users can enable or disable each alert type in the “Alerts” section of the settings. After selecting which alerts they want active, they can create a single TradingView alert using the AnyAlert() condition. This will automatically trigger alerts for all enabled events as soon as they occur on the chart.
Available Alerts:
Long Signal
Short Signal
Breakeven Hit (BE)
Take Profit 1 Hit (TP1)
Take Profit 2 Hit (TP2)
Stop-Loss Hit (SL)
Liquidity Sweep Detected
SMT Divergence Detected
How to Receive Alerts:
Open the TradingView alert creation window.
Select the IFVG Model indicator as the alert condition.
Choose AnyAlert() from the condition dropdown.
Create the alert.
IMPORTANT NOTES:
TradingView has limitations when running features on multiple timeframes such as the HTF FVGs, which can result in the following restriction:
Computation Error:
The computation of using MTF features is very intensive on TradingView. This can sometimes cause calculation timeouts. When this occurs, simply force the recalculation by modifying one indicator’s settings or by removing the indicator and adding it to your chart again.
UNIQUENESS:
This indicator is unique because it organizes every part of the Inversion Fair Value Gap Model into one structured, rules based system. It detects liquidity sweeps, confirms V shape recoveries, identifies valid IFVGs, checks higher timeframe FVG taps, reads macro timing, and applies a session based directional bias. All of these components are evaluated in a fixed sequence so users always know exactly why a signal appears. Every part of the logic is customizable, including which liquidity types are used, which IFVGs qualify for signals, which time windows allow trades, the minimum risk to reward for a setup, and all visual elements on the chart. The tool also includes optional SMT Divergence detection, daily and weekly opening gaps, a live dashboard that shows the state of each model requirement, and optional signal performance statistics.
Chronos Reversal Labs - SPChronos Reversal Labs - Shadow Portfolio
Chronos Reversal Labs - Shadow Portfolio: combines reinforcement learning optimization with adaptive confluence detection through a shadow portfolio system. Unlike traditional indicator mashups that force traders to manually interpret conflicting signals, this system deploys 4 multi-armed bandit algorithms to automatically discover which of 5 specialized confluence strategies performs best in current market conditions, then validates those discoveries through parallel shadow portfolios that track virtual P&L for each strategy independently.
Core Innovation: Rather than relying on static indicator combinations, this system implements Thompson Sampling (Bayesian multi-armed bandits), contextual bandits (regime-specific learning), advanced chop zone detection (geometric pattern analysis), and historical pre-training to build a self-improving confluence detection engine. The shadow portfolio system runs 5 parallel virtual trading accounts—one per strategy—allowing the system to learn which confluence approach works best through actual position tracking with realistic exits.
Target Users: Intermediate to advanced traders seeking systematic reversal signals with mathematical rigor. Suitable for swing trading and day trading across stocks, forex, crypto, and futures on liquid instruments. Requires understanding of basic technical analysis and willingness to allow 50-100 bars for initial learning.
Why These Components Are Combined
The Fundamental Problem
No single confluence method works consistently across all market regimes. Kernel-based methods (entropy, DFA) excel during predictable phases but fail in chaos. Structure-based methods (harmonics, BOS) work during clear swings but fail in ranging conditions. Technical methods (RSI, MACD, divergence) provide reliable signals in trends but generate false signals during consolidation.
Traditional solutions force traders to either manually switch between methods (slow, error-prone) or interpret all signals simultaneously (cognitive overload). Both fail because they assume the trader knows which regime the market is in and which method works best.
The Solution: Meta-Learning Through Reinforcement Learning
This system solves the problem through automated strategy selection : Deploy 5 specialized confluence strategies designed for different market conditions, track their real-world performance through shadow portfolios, then use multi-armed bandit algorithms to automatically select the optimal strategy for the next trade.
Why Shadow Portfolios? Traditional bandit implementations use abstract "rewards." Shadow portfolios provide realistic performance measurement : Each strategy gets a virtual trading account with actual position tracking, stop-loss management, take-profit targets, and maximum holding periods. This creates risk-adjusted learning where strategies are evaluated on P&L, win rate, and drawdown—not arbitrary scores.
The Five Confluence Strategies
The system deploys 5 orthogonal strategies with different weighting schemes optimized for specific market conditions:
Strategy 1: Kernel-Dominant (Entropy/DFA focused, optimal in predictable markets)
Shannon Entropy weight × 2.5, DFA weight × 2.5
Detects low-entropy predictable patterns and DFA persistence/mean-reversion signals
Failure mode: High-entropy chaos (hedged by Technical-Dominant)
Strategy 2: Structure-Dominant (Harmonic/BOS focused, optimal in clear swing structures)
Harmonics weight × 2.5, Liquidity (S/R) weight × 2.0
Uses swing detection, break-of-structure, and support/resistance clustering
Failure mode: Range-bound markets (hedged by Balanced)
Strategy 3: Technical-Dominant (RSI/MACD/Divergence focused, optimal in established trends)
RSI weight × 2.0, MACD weight × 2.0, Trend weight × 2.0
Zero-lag RSI suite with 4 calculation methods, MACD analysis, divergence detection
Failure mode: Choppy/ranging markets (hedged by chop filter)
Strategy 4: Balanced (Equal weighting, optimal in unknown/transitional regimes)
All components weighted 1.2×
Baseline performance during regime uncertainty
Strategy 5: Regime-Adaptive (Dynamic weighting by detected market state)
Chop zones: Kernel × 2.0, Technical × 0.3
Bull/Bear trends: Trend × 1.5, DFA × 2.0
Ranging: Mean reversion × 1.5
Adapts explicitly to detected regime
Multi-Armed Bandit System: 4 Core Algorithms
What Is a Multi-Armed Bandit Problem?
Formal Definition: K arms (strategies), each with unknown reward distribution. Goal: Maximize cumulative reward while learning which arms are best. Challenge: Balance exploration (trying uncertain strategies) vs. exploitation (using known-best strategy).
Trading Application: Each confluence strategy is an "arm." After each trade, receive reward (P&L percentage). Bandits decide which strategy to trust for next signal.
The 4 Implemented Algorithms
1. Thompson Sampling (DEFAULT)
Category: Bayesian approach with probability distributions
How It Works: Model each strategy as Beta(α, β) where α = wins, β = losses. Sample from distributions, select highest sample.
Properties: Optimal regret O(K log T), automatic exploration-exploitation balance
When To Use: Best all-around choice, adaptive markets, long-term optimization
2. UCB1 (Upper Confidence Bound)
Category: Frequentist approach with confidence intervals
Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i)
Properties: Deterministic, interpretable, same optimal regret as Thompson
When To Use: Prefer deterministic behavior, stable markets
3. Epsilon-Greedy
Category: Simple baseline with random exploration
How It Works: With probability ε (0.15): random strategy. Else: best average reward.
Properties: Simple, fast initial learning
When To Use: Baseline comparison, short-term testing
4. Contextual Bandit
Category: Context-aware Thompson Sampling
Enhancement: Maintains separate alpha/beta for Bull/Bear/Ranging regimes
Learning: "Strategy 2: 60% win rate in Bull, 40% in Bear"
When To Use: After 100+ bars, clear regime shifts
Shadow Portfolio System
Why Shadow Portfolios?
Traditional bandits use abstract scores. Shadow portfolios provide realistic performance measurement through actual position simulation.
How It Works
Position Opening:
When strategy generates validated signal:
Opens virtual position for selected strategy
Records: entry price, direction, entry bar, RSI method
Optional: Open positions for ALL strategies simultaneously (faster learning)
Position Management (Every Bar):
Current P&L: pnl_pct = (close - entry) / entry × direction × 100
Exit if: pnl_pct <= -2.0% (stop-loss) OR pnl_pct >= +4.0% (take-profit) OR held ≥ 100 bars (time)
Position Closing:
Calculate final P&L percentage
Update strategy equity, track win rate, gross profit/loss, max drawdown
Calculate risk-adjusted reward:
text
base_reward = pnl_pct / 10.0
win_rate_bonus = (win_rate - 0.5) × 0.3
drawdown_penalty = -max_drawdown × 0.05
total_reward = sigmoid(base + bonus + penalty)
Update bandit algorithms with reward
Update RSI method bandit
Statistics Tracked Per Strategy:
Equity curve (starts at $10,000)
Win rate percentage
Max drawdown
Gross profit/loss
Current open position
This creates closed-loop learning : Strategies compete → Best performers selected → Bandits learn quality → System adapts automatically.
Historical Pre-Training System
The Problem with Live-Only Learning
Standard bandits start with zero knowledge and need 50-100 signals to stabilize. For weekly timeframe traders, this could take years.
The Solution: Historical Training
During Chart Load: System processes last 300-1000 bars (configurable) in "training mode":
Detect signals using Balanced strategy (consistent baseline)
For each signal, open virtual training positions for all 5 strategies
Track positions through historical bars using same exit logic (SL/TP/time)
Update bandit algorithms with historical outcomes
CRITICAL TRANSPARENCY: Signal detection does NOT look ahead—signals use only data available at entry bar. Exit tracking DOES look ahead (uses future bars for SL/TP), which is acceptable because:
✅ Entry decisions remain valid (no forward bias)
✅ Learning phase only (not affecting shown signals)
✅ Real-time mirrors training (identical exit logic)
Training Completion: Once chart reaches current bar, system transitions to live mode. Dashboard displays training vs. live statistics for comparison.
Benefit: System begins live trading with 100-500 historical trades worth of learning, enabling immediate intelligent strategy selection.
Advanced Chop Zone Detection Engine
The Innovation: Multi-Layer Geometric Chop Analysis
Traditional chop filters use simple volatility metrics (ATR thresholds) that can't distinguish between trending volatility (good for signals) and choppy volatility (bad for signals). This system implements three-layer geometric pattern analysis to precisely identify consolidation zones where reversal signals fail.
Layer 1: Micro-Structure Chop Detection
Method: Analyzes micro pivot points (5-bar left, 2-bar right) to detect geometric compression patterns.
Slope Analysis:
Calculates slope of pivot high trendline and pivot low trendline
Compression ratio: compression = slope_high - slope_low
Pattern Classification:
Converging slopes (compression < -0.05) → "Rising Wedge" or "Falling Wedge"
Flat slopes (|slope| < 0.05) → "Rectangle"
Parallel slopes (|compression| < 0.1) → "Channel"
Expanding slopes → "Expanding Range"
Chop Scoring:
Rectangle pattern: +15 points (highest chop)
Low average slope (<0.05): +15 points
Wedge patterns: +12 points
Flat structures: +10 points
Why This Works: Geometric patterns reveal market indecision. Rectangles and wedges create false breakouts that trap technical traders. By quantifying geometric compression, system detects these zones before signals fire.
Layer 2: Macro-Structure Chop Detection
Method: Tracks major swing highs/lows using ATR-based deviation threshold (default 2.0× ATR), projects channel boundaries forward.
Channel Position Calculation:
proj_high = last_swing_high + (swing_high_slope × bars_since)
proj_low = last_swing_low + (swing_low_slope × bars_since)
channel_width = proj_high - proj_low
position = (close - proj_low) / channel_width
Dead Zone Detection:
Middle 50% of channel (position 0.25-0.75) = low-conviction zone
Score increases as price approaches center (0.5)
Chop Scoring:
Price in dead zone: +15 points (scaled by centrality)
Narrow channel width (<3× ATR): +15 points
Channel width 3-5× ATR: +10 points
Why This Works: Price in middle of range has equal probability of moving either direction. Institutional traders avoid mid-range entries. By detecting "dead zones," system avoids low-probability setups.
Layer 3: Volume Chop Scoring
Method: Low volume indicates weak conviction—precursor to ranging behavior.
Scoring:
Volume < 0.5× average: +20 points
Volume 0.5-0.8× average: +15 points
Volume 0.8-1.0× average: +10 points
Overall Chop Intensity & Signal Filtering
Total Chop Calculation:
chop_intensity = micro_score + macro_score + (volume_score × volume_weight)
is_chop = chop_intensity >= 40
Signal Filtering (Three-Tier Approach):
1. Signal Blocking (Intensity > 70):
Extreme chop detected (e.g., tight rectangle + dead zone + low volume)
ALL signals blocked regardless of confluence
Chart displays red/orange background shading
2. Threshold Adjustment (Intensity 40-70):
Moderate chop detected
Confluence threshold increased: threshold += (chop_intensity / 50)
Only highest-quality signals pass
3. Strategy Weight Adjustment:
During Chop: Kernel-Dominant weight × 2.0 (entropy detects breakout precursors), Technical-Dominant weight × 0.3 (reduces false signals)
After Chop Exit: Weights revert to normal
Why This Three-Tier Approach Is Original: Most chop filters simply block all signals (loses breakout entries). This system adapts strategy selection during chop—allowing Kernel-Dominant (which excels at detecting low-entropy breakout precursors) to operate while suppressing Technical-Dominant (which generates false signals in consolidation). Result: System remains functional across full market regime spectrum.
Zero-Lag Filter Suite with Dynamic Volatility Scaling
Zero-Lag ADX (Trend Regime Detection)
Implementation: Applies ZLEMA to ADX components:
lag = (length - 1) / 2
zl_source = source + (source - source ) × strength
Dynamic Volatility Scaling (DVS):
Calculates volatility ratio: current_ATR / ATR_100period_avg
Adjusts ADX length dynamically: High vol → shorter length (faster), Low vol → longer length (smoother)
Regime Classification:
ADX > 25 with +DI > -DI = Bull Trend
ADX > 25 with -DI > +DI = Bear Trend
ADX < 25 = Ranging
Zero-Lag RSI Suite (4 Methods with Bandit Selection)
Method 1: Standard RSI - Traditional Wilder's RSI
Method 2: Ehlers Zero-Lag RSI
ema1 = ema(close, length)
ema2 = ema(ema1, length)
zl_close = close + (ema1 - ema2)
Method 3: ZLEMA RSI
lag = (length - 1) / 2
zl_close = close + (close - close )
Method 4: Kalman-Filtered RSI - Adaptive smoothing with process/measurement noise
RSI Method Bandit: Separate 4-arm bandit learns which calculation method produces best results. Updates independently after each trade.
Kalman Adaptive Filters
Fast Kalman: Low process noise → Responsive to genuine moves
Slow Kalman: Higher measurement noise → Filters noise
Application: Crossover logic for trend detection, acceleration analysis for momentum inflection
What Makes This Original
Innovation 1: Shadow Portfolio Validation
First TradingView script to implement parallel virtual portfolios for multi-armed bandit reward calculation. Instead of abstract scoring metrics, each strategy's performance is measured through realistic position tracking with stop-loss, take-profit, time-based exits, and risk-adjusted reward functions (P&L + win rate + drawdown). This provides orders-of-magnitude better reward signal quality for bandit learning than traditional score-based approaches.
Innovation 2: Three-Layer Geometric Chop Detection
Novel multi-scale geometric pattern analysis combining: (1) Micro-structure slope analysis with pattern classification (wedges, rectangles, channels), (2) Macro-structure channel projection with dead zone detection, (3) Volume confirmation. Unlike simple volatility filters, this system adapts strategy weights during chop —boosting Kernel-Dominant (breakout detection) while suppressing Technical-Dominant (false signal reduction)—allowing operation across full market regime spectrum without blind signal blocking.
Innovation 3: Historical Pre-Training System
Implements two-phase learning : Training phase (processes 300-1000 historical bars on chart load with proper state isolation) followed by live phase (real-time learning). Training positions tracked separately from live positions. System begins live trading with 100-500 trades worth of learned experience. Dashboard displays training vs. live performance for transparency.
Innovation 4: Contextual Multi-Armed Bandits with Regime-Specific Learning
Beyond standard bandits (global strategy quality), implements regime-specific alpha/beta parameters for Bull/Bear/Ranging contexts. System learns: "Strategy 2: 60% win rate in ranging markets, 45% in bull trends." Uses current regime's learned parameters for strategy selection, enabling regime-aware optimization.
Innovation 5: RSI Method Meta-Learning
Deploys 4 different RSI calculation methods (Standard, Ehlers ZL, ZLEMA, Kalman) with separate 4-arm bandit that learns which calculation works best. Updates RSI method bandit independently based on trade outcomes, allowing automatic adaptation to instrument characteristics.
Innovation 6: Dynamic Volatility Scaling (DVS)
Adjusts ALL lookback periods based on current ATR ratio vs. 100-period average. High volatility → shorter lengths (faster response). Low volatility → longer lengths (smoother signals). Applied system-wide to entropy, DFA, RSI, ADX, and Kalman filters for adaptive responsiveness.
How to Use: Practical Guide
Initial Setup (5 Minutes)
Theory Mode: Start with "BALANCED" (APEX for aggressive, CONSERVATIVE for defensive)
Enable RL: Toggle "Enable RL Auto-Optimization" to TRUE, select "Thompson Sampling"
Enable Confluence Modules: Divergence, Volume Analysis, Liquidity Mapping, RSI OB/OS, Trend Analysis, MACD (all recommended)
Enable Chop Filter: Toggle "Enable Chop Filter" to TRUE, sensitivity 1.0 (default)
Historical Training: Enable "Enable Historical Pre-Training", set 300-500 bars
Dashboard: Enable "Show Dashboard", position Top Right, size Large
Learning Phase (First 50-100 Bars)
Monitor Thompson Sampling Section:
Alpha/beta values should diverge from initial 1.0 after 20-30 trades
Expected win% should stabilize around 55-60% (excellent), >50% (acceptable)
"Pulls" column should show balanced exploration (not 100% one strategy)
Monitor Shadow Portfolios:
Equity curves should diverge (different strategies performing differently)
Win rate > 55% is strong
Max drawdown < 15% is healthy
Monitor Training vs Live (if enabled):
Delta difference < 10% indicates good generalization
Large negative delta suggests overfitting
Large positive delta suggests system adapting well
Optimization:
Too few signals: Lower "Base Confluence Threshold" to 2.5-3.0
Too many signals: Raise threshold to 4.0-4.5
One strategy dominates (>80%): Increase "Exploration Rate" to 0.20-0.25
Excessive chop blocking: Lower "Chop Sensitivity" to 0.7-0.8
Signal Interpretation
Dashboard Indicators:
"WAITING FOR SIGNAL": No confluence
"LONG ACTIVE ": Validated long entry
"SHORT ACTIVE ": Validated short entry
Chart Visuals:
Triangle markers: Entry signal (green = long, red = short)
Orange/red background: Chop zone
Lines: Support/resistance if enabled
Position Management
Entry: Enter on triangle marker, confirm direction matches dashboard, check confidence >60%
Stop-Loss: Entry ± 1.5× ATR or at structural swing point
Take-Profit:
TP1: Entry + 1.5R (take 50%, move SL to breakeven)
TP2: Entry + 3.0R (runner) or trail
Position Sizing:
Risk per trade = 1-2% of capital
Position size = (Account × Risk%) / (Entry - SL)
Recommended Settings by Instrument
Stocks (Large Cap): Balanced mode, Threshold 3.5, Thompson Sampling, Chop 1.0, 15min-1H, Training 300-500 bars
Forex Majors: Conservative-Balanced mode, Threshold 3.5-4.0, Thompson Sampling, Chop 0.8-1.0, 5min-30min, Training 400-600 bars
Cryptocurrency: Balanced-APEX mode, Threshold 3.0-3.5, Thompson Sampling, Chop 1.2-1.5, 15min-4H, Training 300-500 bars
Futures: Balanced mode, Threshold 3.5, UCB1 or Thompson, Chop 1.0, 5min-30min, Training 400-600 bars
Technical Approximations & Limitations
1. Thompson Sampling: Pseudo-Random Beta Distribution
Standard: Cryptographic RNG with true beta sampling
This Implementation: Box-Muller transform using market data as entropy source
Impact: Not cryptographically random but maintains exploration-exploitation balance. Sufficient for strategy selection.
2. Shadow Portfolio: Simplified Execution Model
Standard: Order book simulation with slippage, partial fills
This Implementation: Perfect fills at close price, no fees modeled
Impact: Real-world performance ~0.1-0.3% worse per trade due to execution costs.
3. Historical Training: Forward-Looking for Exits Only
Entry signals: Use only past data (causal, no bias)
Exit tracking: Uses future bars to determine SL/TP (forward-looking)
Impact: Acceptable because: (1) Entry logic remains valid, (2) Live trading mirrors training, (3) Improves learning quality. Training win rates reflect 8-bar evaluation window—live performance may differ if positions held longer.
4. Shannon Entropy & DFA: Simplified Calculations
Impact: 10-15% precision loss vs. academic implementations. Still captures predictability and persistence signals effectively.
General Limitations
No Predictive Guarantee: Past performance ≠ future results
Learning Period Required: Minimum 50-100 bars for stable statistics
Overfitting Risk: May not generalize to unprecedented conditions
Single-Instrument: No multi-asset correlation or sector context
Execution Assumptions: Degrades in illiquid markets (<100k volume), major news events, flash crashes
Risk Warnings & Disclaimers
No Guarantee of Profit: All trading involves substantial risk of loss. This indicator is a tool, not a guaranteed profit system.
System Failures: Software bugs possible despite testing. Use appropriate position sizing.
Market Regime Changes: Performance may degrade during extreme volatility (VIX >40), low liquidity periods, or fundamental regime shifts.
Broker-Specific Issues: Real-world execution includes slippage (0.1-0.5%), commissions, overnight financing costs, partial fills.
Forward-Looking Bias in Training: Historical training uses 8-bar forward window for exit evaluation. Dashboard "Training Win%" reflects this method. Real-time performance may differ.
Appropriate Use
This Indicator IS:
✅ Entry trigger system with confluence validation
✅ Risk management framework (automated SL/TP)
✅ Adaptive strategy selection engine
✅ Learning system that improves over time
This Indicator IS NOT:
❌ Complete trading strategy (requires position sizing, portfolio management)
❌ Replacement for due diligence
❌ Guaranteed profit generator
❌ Suitable for complete beginners
Recommended Complementary Analysis: Market context, volume profile, fundamental catalysts, higher timeframe alignment, support/resistance from other sources.
Conclusion
Chronos Reversal Labs V2.0 - Elite Edition synthesizes research from multi-armed bandit theory (Thompson Sampling, UCB, contextual bandits), market microstructure (geometric chop detection, zero-lag filters), and machine learning (shadow portfolio validation, historical pre-training, RSI method meta-learning).
Unlike typical indicator mashups, this system implements mathematically rigorous bandit algorithms with realistic performance validation, three-layer chop detection with adaptive strategy weighting, regime-specific learning, and full transparency on approximations and limitations.
The system is designed for intermediate to advanced traders who understand that no indicator is perfect, but through proper machine learning and realistic validation, we can build systems that improve over time and adapt to changing markets without manual intervention.
Use responsibly. Understand the limitations. Risk disclosure applies. Past performance does not guarantee future results.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Livermore's Pyramiding Trading - 3Commas [SwissAlgo]
📊 J. LIVERMORE'S PYRAMIDING TRADING - 3Commas Integrated
A Trading Approach Inspired by Jesse Livermore's Position Building Principles
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DISCLAIMER
This indicator is an educational tool based on historical trading principles. Past performance is not indicative of future results. Trading involves substantial risk of loss. Only trade with capital you can afford to lose. You are responsible for all trading decisions.
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📚 WHO WAS JESSE LIVERMORE?
Jesse Livermore (1877-1940) was one of the greatest traders in history.
His core insight: "Most traders do everything backward."
♦ "They deploy all capital at once" → Livermore entered with a small fraction of his capital (he started with a 'test position' to validate his trade idea and waited for market confirmation to deploy more, building positions in steps = "pyramiding")
♦ "They average down" (DCA) → Livermore added to trades showing good results only, and never to losing trades, as the trend kept aligning with his trade idea
♦ "They use arbitrary % stops" → Livermore exited when structure appeared broken (he trailed his stop loss to try to protect unrealized profit - if any)
♦ "They take profits too early or set arbitrary TP%" → Livermore let trades showing positive results run until proven wrong (trial take profit)
💬 "I always made money when I was sure I was right before I began. What beat me was not having enough brains to stick to my own game."
— Jesse Livermore
This indicator tries to translate his principles into a SYSTEMATIC FRAMEWORK :
BO = Base Order (first order, base of the pyramid)
PO = Pyramid Orders (additional layers of capital deployed as long as the 'tape' does not invalidate the trade idea)
♦ Test First (BO - 20%) - Small entry to test your idea. If wrong, lose small. If right, can consider pyramiding into strength.
♦ Build Position Size (PO1-3 - 80%) - Add only as trend unfolds favorably (the indicator uses specific Fibonacci levels to track milestones - 0.618, 1.0, 1.272 - and looks for strong confluence among price, volume, trend, momentum, break of resistance/support levels to suggest and trigger actions: entries, exit)
♦ Attempt to Protect Capital - Dynamic stops: the indicator trails the stop loss, to try to protect potential gains from previous steps (if any)
♦ Discipline - Trades fire only when ALL conditions align
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🎯 INDICATOR FEATURES
You map 3 points on the chart → The indicator generates a systematic trading plan structure based on your wave analysis.
✓ Auto-detects trade direction: Uptrend wave (A➚B➘C) = Long signals | Downtrend wave (A➘B➚C) = Short signals
✓ Entry/exit prices: BO, PO1, PO2, PO3, and dynamic EXIT (trailing stop)
✓ Real-time condition monitoring: Live ✓/✗ checks for each order (price closes + volume + trend + pivot breaks + candle quality + sequence)
✓ Visual trade execution: Green labels mark entries (BO/PO1/PO2/PO3), red labels mark EXIT
✓ Optional 3Commas automation: JSON webhooks for hands-free execution via Signal Bots
⏰ Recommended Timeframes: 1H, 4H, Daily
(Lower timeframes like 15m/5m produce excessive noise and false signals)
💬 "Watch the market leaders, the stocks that have led the charge. That is where the action is and where the money is made."
— Jesse Livermore
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⚙️ SETUP IN 3 STEPS
🟡 STEP 1: Map Your Wave (Points A → B → C)
Identify a completed wave pattern:
For LONGS:
♦ Point A = Swing low (wave start)
♦ Point B = Swing high (impulse end)
♦ Point C = Pullback low (retrace end - where next wave may begin)
For SHORTS:
♦ Point A = Swing high (wave start)
♦ Point B = Swing low (impulse end)
♦ Point C = Pullback high (retrace end - where next wave may begin)
How to set points:
Settings → Enter dates manually OR drag the vertical lines directly on the chart (easier - just click and drag the pre-mapped A/B/C lines)
Requirements (auto-validated by code):
✓ All dates must be in the past (Point C = completed retrace, not forming)
✓ Clear impulse A→B (minimum 5% move)
✓ Clear retrace B→C (minimum 3% pullback)
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🟡 STEP 2: Set Budget & Allocation
Settings → "TRADE PARAMETERS"
♦ Total Budget: $10,000 (example - capital for THIS trade only, not your entire account)
♦ Allocation (must total 100%):
BO = 20% ($2,000) - test position
PO1 = 25% ($2,500) @ Fib 0.618
PO2 = 30% ($3,000) @ Fib 1.0
PO3 = 25% ($2,500) @ Fib 1.272
💬 "It was never my thinking that made big money for me. It was always my sitting. Men who can both be right and sit tight are uncommon."
— Jesse Livermore
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🟡 STEP 3: Monitor Your Trade Plan Table
The table (top-right corner) has 4 sections that guide your execution:
BUDGET DEPLOYMENT
♦ Trigger prices for each order (BO auto-calculated at 0.5 Fib between B-C)
♦ Dollar amount per entry
♦ Fibonacci level assigned to each PO
ENTRY/EXIT CONDITIONS
Each column (BO, PO1, PO2, PO3) shows live status (✓ or ✗) for:
♦ Price: 2 consecutive closes (BO) | 3 consecutive closes (POs)
♦ Volume: OBV directional alignment OR volume spike above average
♦ Trend: Normal or Strong Bull/Bear (no entries in Uncertain trend)
♦ Pivot: Nearest resistance (longs) or support (shorts) broken
♦ Clean Candle: Momentum without reversal wicks <30% (POs only)
♦ Sequence: Prior order must have fired first (POs only - no skipping levels)
TRIGGERED?
Shows execution status for each order (✓ = fired, ✗ = waiting)
If using 3Commas: ✓ confirms JSON alert was sent to your bot for real execution
VALIDATIONS
✓ Green = All checks passed, setup is valid
⚠️ Yellow = Warning (e.g., budget doesn't equal 100%, deep retrace)
✗ Red = Error (e.g., dates in wrong order, invalid wave structure)
⚠️ Wait for ALL ✓✓✓✓✓ (or ✓✓✓✓✓✓) to align in a column before that order fires at bar close
💬 "The game of speculation is the most uniformly fascinating game in the world. But it is not a game for the stupid, the mentally lazy, the person of inferior emotional balance, or the get-rich-quick adventurer."
— Jesse Livermore
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📊 CHART VISUALS - READING THE INDICATOR
Fibonacci Extension Lines
After mapping A-B-C, horizontal lines extend to the right:
♦ Solid green/red lines = Active PO entry levels (0.618, 1.0, 1.272)
♦ Dotted gray lines = Reference Fib levels used for exit tracking (2.0, 2.618, 3.0, etc.)
♦ Labels on right = Show level and price: "Fib 0.618 / $67,324 "
Entry/Exit Price Lines
♦ Thick green line (longs) / red line (shorts) = BO entry price with direction label
♦ Dashed red line = Current EXIT price (your trailing stop loss - appears after BO fires and moves as price extends)
Trade Execution Labels
Visual confirmation when orders fire on the chart:
♦ Green labels (below/above candles) = BO, PO1, PO2, PO3 entries executed
♦ Red label = EXIT triggered (position closed)
Trend Strength Indicator (EMA Line)
The thick colored line shows real-time trend status:
♦ Bright lime = Strong bullish trend
♦ Light green = Normal bullish trend
♦ Bright red = Strong bearish trend
♦ Light red = Normal bearish trend
♦ Gray = Uncertain/weak trend (no entries fire in this state)
Entries require at least Normal trend strength aligned with your trade direction.
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
— Jesse Livermore
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🔧 ENTRY LOGIC - TECHNICAL DETAILS
💬 "The big money was never made in the buying or the selling. The big money was made in the waiting."
— Jesse Livermore
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🟢 BASE ORDER (BO) - TEST POSITION
BO Price Calculation
Auto-calculated at the 0.5 Fibonacci retracement between Point B and Point C
Formula: (Price B + Price C) / 2
Why this level?
♦ Midpoint between impulse end (B) and retrace end (C)
♦ Breakout above/below suggests retrace may be complete
♦ Designed to help position BO below all Fib extensions (to control sequence issues)
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BO Entry Conditions - ALL 5 Must Align:
1️⃣ PRICE: 2 Consecutive Closes Beyond BO
♦ Longs: close > BO AND close > BO
♦ Shorts: close < BO AND close < BO
♦ Why: Designed to confirm breakout commitment and filter fakeouts
2️⃣ TREND: Normal OR Strong Trend Aligned
♦ Detection: 18-period EMA + ADX/DMI + higher timeframe slope
♦ States: Strong Bull/Bear (ADX>30), Normal Bull/Bear (price vs EMA), Uncertain
♦ Confirmation: Requires 3 consecutive bars in the same state (to reduce flip-flop)
♦ BO accepts: Normal OR Strong (you're testing early, basic alignment sufficient)
3️⃣ PIVOT: Nearest Resistance/Support Broken
♦ Storage: 60 most recent pivot highs/lows (dynamic lookback per timeframe)
♦ Longs: Nearest pivot HIGH above BO → must break with 2 closes
♦ Shorts: Nearest pivot LOW below BO → must break with 2 closes
♦ Price Discovery: If no pivot exists beyond BO = auto-pass
♦ Why: Aims to confirm momentum has overcome previous rejection zones
4️⃣ VOLUME: OBV Aligned OR Spike
♦ Directional OBV: OBV > 20-EMA (longs) OR OBV < 20-EMA (shorts)
♦ OR Volume Spike: Current volume > 20-period SMA
♦ Why: Checks for institutional participation signals
5️⃣ VALIDATIONS: Setup Valid (✅)
♦ Dates valid (A < B < C, all in past)
♦ Wave structure valid (min 5% impulse, min 3% retrace)
♦ Budget allocation = 100%
♦ Prices detected at all points
⚠️ BO fires once per bar close. Flag set permanently until trade resets.
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🔺 PYRAMID ORDERS (PO1-3) - PYRAMIDING INTO STRENGTH
💬 "Never buy a stock because it has had a big decline from its previous high. The big money was never made in the stock market by buying on declines."
— Jesse Livermore
PO Price Calculation
Fixed Fibonacci extensions from Point C:
Formula: Price C ± (Impulse Range × Fib Level)
Where: Impulse Range = |Price B - Price A|
Default Levels:
♦ PO1 @ Fib 0.618 (Golden Ratio)
♦ PO2 @ Fib 1.000 (Full impulse repeat)
♦ PO3 @ Fib 1.272 (Fibonacci sequence extension)
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PO Entry Conditions - ALL 6 Must Align (STRICTER):
1️⃣ PRICE: 3 Consecutive Closes Beyond PO
♦ Longs: close > PO AND close > PO AND close > PO
♦ Shorts: close < PO AND close < PO AND close < PO
♦ Why: Higher conviction needed when adding capital (3 vs 2 closes for BO)
2️⃣ TREND: Same as BO
Normal OR Strong trend must remain aligned with trade direction
3️⃣ PIVOT: Per-Level Pivot Break
♦ Each PO checks its OWN nearest pivot (not shared with BO)
♦ Same 2-close break requirement
♦ PO3 Exception: Price discovery allowed (no pivot required if already profitable)
4️⃣ VOLUME: Same as BO
Sustained confirmation required (not weakening)
5️⃣ CLEAN CANDLE: <30% Reversal Wick (NEW)
♦ Filter: Uses ATR(14) - candles < ATR auto-pass (consolidation noise)
♦ Longs: Upper wick < 30% of candle range (no rejection at top)
♦ Shorts: Lower wick < 30% of candle range (no rejection at bottom)
♦ Why: Don't pyramid into weakness/rejection - only add on clean momentum
♦ Not checked for BO: Test position tolerates some wick risk
6️⃣ SEQUENCE: Prior Order Fired
♦ PO1 requires: BO fired
♦ PO2 requires: PO1 fired
♦ PO3 requires: PO2 fired
♦ Why: No skipping levels - disciplined building only
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⚙️ KEY DIFFERENCE:
BO (20% capital) = Lighter requirements, testing your idea early
POs (80% capital) = Stricter requirements, adding only to confirmed winners
♦ BO: 2 closes | POs: 3 closes
♦ BO: No candle check | POs: Clean candle required
♦ BO: Independent | POs: Sequential (must follow order)
♦ BO: No price discovery | PO3: Allows price discovery when profitable
💬 "Profits always take care of themselves, but losses never do. The speculator has to ensure himself against considerable losses by taking the first small loss."
— Jesse Livermore
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🚪 EXIT LOGIC - TECHNICAL DETAILS
🔴 EXIT PHILOSOPHY
The indicator uses TWO INDEPENDENT EXIT TRIGGERS (whichever fires first):
1) Structural Breakdown
Price breaks through the EXIT level with confirmation
2) Trend Reversal
Trend flips against your position AND price breaks EXIT level
Why two methods?
♦ Structure = price-based protection (hard stop)
♦ Trend = momentum-based exit (early warning when market character changes)
♦ Combined: Exit either when proven wrong (structure) or when conditions no longer favor your direction (trend)
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🔴 EXIT PRICE CALCULATION
The EXIT price (your stop loss) adjusts dynamically based on position size:
BEFORE PO3 Fires (Fixed Stops):
♦ BO only = Stop at Point C (small position, tight stop near entry)
♦ PO1 fired = Stop at Fib 0.5 (moved to breakeven zone)
♦ PO2 fired = Stop at Fib 0.786 (protecting partial profits)
AFTER PO3 Fires (Trailing Stops):
♦ Tracking: Monitors the highest Fib reached (longs) or the lowest Fib reached (shorts)
♦ Placement: EXIT moves 1-2 Fib levels below the highest (longs) or above the lowest (shorts)
♦ Example: Price reaches Fib 2.618 → EXIT trails up to Fib 2.0
♦ Purpose: Designed to protect accumulated profits while allowing room for normal pullbacks
💬 "It never was my thinking that made the big money for me. It was always my sitting. Men who can both be right and sit tight are uncommon."
— Jesse Livermore
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🔴 EXIT CONDITIONS
Exit Speed (Based on Risk Exposure):
♦ Full position (PO3 fired) = 1 close required (fast exit - more capital at risk)
♦ Partial position (BO/PO1/PO2 only) = 2 closes required (confirmation - less urgency)
METHOD 1: Structural Breakdown
Price violates the EXIT level with clean momentum:
For Longs:
♦ Price closes BELOW EXIT level (1 or 2 closes depending on position size)
♦ Clean candle required (lower wick < 50% of range - no false breakdown)
For Shorts:
♦ Price closes ABOVE EXIT level (1 or 2 closes depending on position size)
♦ Clean candle required (upper wick < 50% of range - no false breakout)
Why clean candle check?
Designed to reduce exits on wicks/fakeouts. If there's a large reversal wick (>50%), it suggests buyers/sellers are defending the level - not a true breakdown.
METHOD 2: Trend Reversal
Market character shifts against your position:
For Longs:
♦ Trend shifts from Bull → Normal Bear OR Strong Bear
♦ AND price breaks below EXIT level (same close requirements)
For Shorts:
♦ Trend shifts from Bear → Normal Bull OR Strong Bull
♦ AND price breaks above EXIT level (same close requirements)
Why this matters?
♦ Proactive exit before structural stop is hit
♦ If the trend that confirmed your entries reverses, the setup is invalidated
♦ Livermore principle: Exit when market proves you wrong, don't wait for max pain
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⚠️ EXIT BEHAVIOR
♦ Fires once per bar close (same as entries)
♦ Resets all tracking after exit (ready for fresh trade setup)
♦ Clears flags: boSignalFired, po1/po2/po3SignalFired, highestFib/lowestFib tracking
♦ If using 3Commas: Sends exit_long or exit_short JSON (market order closes 100% position)
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
— Jesse Livermore
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🤖 3COMMAS AUTOMATION (OPTIONAL)
💬 "There is the plain fool, who does the wrong thing at all times everywhere, but there is also the Wall Street fool, who thinks he must trade all the time."
— Jesse Livermore
Automation designed to help remove emotion and support disciplined execution.
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⚡ QUICK SETUP IN 5 STEPS
STEP 1: Create Your Signal Bots
You need 2 SEPARATE BOTS (one for Longs, one for Shorts):
Go to 3Commas → Bots → Create Bot → Select "Signal Bot"
Basic Settings:
♦ Bot Name: "Livermore Long - " (example: "Livermore Long - BTCUSDT")
♦ Exchange: Your connected exchange
♦ Trading Pair: Must match TradingView chart exactly
♦ Strategy: Custom Signal
♦ Direction: LONG (for first bot) or SHORT (for second bot)
♦ Max Active Deals: 1
⚠️ CRITICAL SETTINGS:
Entry Orders:
♦ Toggle ON: "Entry Orders"
♦ Volume per Order: "Send in webhook, quote"
♦ Why: This lets the indicator control exact $ amounts per order (BO=$2K, PO1=$2.5K, etc.)
♦ If you skip this: Orders will use wrong sizes and break your allocation plan
Exit Orders:
♦ Toggle ON: "Exit Orders"
♦ Volume per Order: "100 Position %"
♦ Why: Closes your entire position when EXIT signal fires
♦ Toggle OFF: "Take Profit" (managed by indicator)
♦ Toggle OFF: "Stop Loss" (managed by indicator)
Click "Start Bot" for both Long and Short bots.
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STEP 2: Get Your Bot Credentials
For EACH BOT (Long and Short):
♦ Open the bot → Click "Orders" tab
♦ Scroll down to "Webhook Messages" section
♦ Copy these 3 values:
bot_uuid (long string like: a362cbcf-7e68-4379-a83d-ae6e47dba656)
secret (very long token starting with: eyJhbGciOiJ...)
webhook URL (refer to 3commas to get exact webhook - signal bots)
Note: The secret is usually the same for both bots, but the bot_uuid is different.
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STEP 3: Enter Credentials in Indicator
Back in TradingView:
♦ Open indicator Settings
♦ Find section: "1️⃣ INTEGRATE 3COMMAS"
♦ Paste:
Long = Your Long bot UUID
Short = Your Short bot UUID
Secret = Your secret token (same for both)
♦ Click "OK"
The indicator now has everything needed to build JSON payloads.
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STEP 4: Create TradingView Alert
This alert bridges TradingView → 3Commas. ONE ALERT HANDLES ALL SIGNALS (BO, PO1, PO2, PO3, EXIT).
How to create:
♦ Right-click chart → "Add Alert" (or click clock icon)
♦ Condition: Select this indicator from dropdown
♦ Trigger: "Any alert() function call"
♦ Alert Name: "Livermore Pyramiding - "
♦ Message: Leave default (indicator sends its own JSON)
♦ Webhook URL: Paste your 3Commas webhook URL from Step 2
♦ ⚠️ Alert Frequency: "Once Per Bar Close" (CRITICAL - controls duplicate orders)
♦ Expiration: Open-ended (or set specific date)
♦ Click "Create"
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STEP 5: Test Before Going Live
🧪 NEVER TEST WITH REAL CAPITAL FIRST. Use one of these methods:
Test 1: Check Bot Status
♦ 3Commas → Bots → Both bots show "Active" (green)
♦ Click into each bot → Orders tab → Should say "Waiting for signal"
Test 2: Verify Alert Active
♦ TradingView → Alerts panel (bell icon)
♦ Your alert should show "Active" status
Test 3: Paper Trade / Tiny Position
♦ Use 3Commas paper mode if available, OR
♦ Set Total Budget to $10-50 for first real test
♦ Map a wave that's about to trigger
♦ Watch if orders actually appear on 3Commas
Test 4: Check JSON Format
♦ When alert fires → TradingView Alerts → Click your alert
♦ Look at "History" or "Log"
♦ Verify JSON has: bot_uuid, secret, action, price, amount
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🛠️ COMMON ISSUES & SOLUTIONS
✗ Problem: Orders not appearing on 3Commas
Possible causes:
♦ Wrong webhook URL → Must be exact 3Commas URL (check for typos)
♦ Bot paused → Check bot status must be "Active" (green)
♦ Wrong bot UUID → Verify you copied Long UUID for longs, Short UUID for shorts
♦ Secret mismatch → Double-check secret is correct
♦ Exchange API issues → Verify exchange connection in 3Commas settings
How to debug:
♦ 3Commas → Your Signal Bot → Orders tab
♦ Look for "Rejected Signals" section
♦ Should show error messages if webhook failed
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✗ Problem: Orders executing at wrong prices
Possible causes:
♦ Limit order not filled → Price gapped through your level before order filled
♦ Slippage on exits → Exits use market orders (intentional - speed over exact price)
♦ Exchange minimums → Some exchanges have minimum order sizes
Solution:
♦ Entries use limit orders (wait for exact price - may not fill if price gaps)
♦ Exits use market orders (prioritize fast execution when structure breaks)
♦ This is INTENTIONAL DESIGN following Livermore's principle: exit when proven wrong
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✗ Problem: PO orders firing out of sequence or skipping
Possible causes:
♦ Alert not set to "Once Per Bar Close" → Change alert frequency setting
♦ Multiple alerts running → Delete old/duplicate alerts for this indicator
♦ Conditions changed mid-bar → Indicator only fires at bar close (protective feature)
Solution:
♦ Keep only 1 active alert per indicator instance
♦ Always use "Once Per Bar Close" frequency
♦ Wait for full bar to close before signals can fire
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✗ Problem: Bot not closing position on EXIT
Possible causes:
♦ Exit order setting wrong → Check bot settings
♦ Wrong JSON action → Should be "exit_long" or "exit_short"
♦ No position open → Can't close what doesn't exist
Solution:
♦ Verify: Bot Settings → Exit Orders → Volume per Order = "100 Position %"
♦ Check alert history for correct JSON payload
♦ If stuck: Manually close position in 3Commas, then fix settings
♦ Delete and recreate alert if JSON format is wrong
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🔒 SECURITY BEST PRACTICES
♦ Never share bot UUID or Secret - Treat them like passwords
♦ Use restricted API keys - Limit to specific pairs, disable withdrawals
♦ Start small - Test with $10-50 first, scale up only after success
♦ Monitor first trades - Don't set-and-forget immediately
♦ Delete old alerts - If you change A/B/C points, delete old alert and create new one
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📊 PREFER MANUAL TRADING?
Skip 3Commas entirely and use the indicator for planning only:
♦ Watch Trade Plan table for ✓✓✓✓✓ alignment
♦ Manually place limit orders at displayed prices
♦ Manually move stop loss as EXIT price updates
♦ Manually close when EXIT signal fires
Benefits: Full control, no API concerns, can override based on context
Drawbacks: Must watch chart constantly, emotions can interfere, may miss signals
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✅ FINAL CHECKLIST BEFORE LIVE TRADING
✓ Both Signal Bots created (Long + Short)
✓ Entry Orders: Volume = "Send in webhook, quote"
✓ Exit Orders: Volume = "100 Position %"
✓ Take Profit and Stop Loss disabled in bots
✓ Bot UUIDs and Secret entered in indicator
✓ TradingView alert created with correct webhook
✓ Alert frequency = "Once Per Bar Close"
✓ Alert status shows "Active"
✓ Tested with small amounts successfully
✓ Trade Plan table shows ✅ (no validation errors)
✓ Understand your risk per trade
Once all checked: You're ready for automated pyramiding execution.
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💡 KEY REMINDERS - BEFORE YOU TRADE
💬 "The speculator's chief enemies are always boring from within. It is inseparable from human nature to hope and to fear."
— Jesse Livermore
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⚠️ COMMON MISTAKES (AVOID THESE)
Mapping Incomplete Waves
♦ Point C must be in the PAST (completed retrace, not currently forming)
♦ Don't map a wave that's still developing - wait for confirmation
♦ Minimum requirements: 5% impulse (A→B), 3% retrace (B→C)
Ignoring Validation Warnings
♦ Never create alerts when status shows ✗ (red) or ⚠️ (yellow)
♦ Fix all errors first: dates in order, budget = 100%, valid wave structure
♦ Common issues: dates in future, Point C above B (longs) or below B (shorts)
Premature Manual Entries
♦ Don't enter just because price touched the level
♦ Wait for ALL ✓✓✓✓✓ (or ✓✓✓✓✓✓) to align in Trade Plan table
♦ Patience pays - partial confluence = partial edge = higher risk of losing trades
Wrong Timeframe Selection
♦ Avoid: 15m, 5m, 1m (too much noise, false signals)
♦ Use: 1H, 4H, Daily (cleaner structure, better confluence)
♦ Lower timeframes require faster decisions and produce more whipsaws
Over-Risking Capital
♦ Trade budget ≠ Account size
♦ Never risk capital you can't afford to lose
♦ One bad trade should NOT destroy your account
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✅ LIVERMORE PRINCIPLES IN ACTION
Confirmation > Prediction
♦ Don't predict where price will go
♦ Wait for price to INDICATE direction via pivots + volume + trend
♦ Test first (BO 20%), build only when confirmed (POs 80%)
💬 "A man must believe in himself and his judgment if he expects to make a living at this game."
Pyramid on Strength, Never Weakness
♦ Add only when: 3 closes + clean candles + volume + pivot breaks
♦ Never average down (DCA into losers)
♦ If BO wrong, take small loss fast - don't hope and add more
💬 "Never buy a stock because it has had a big decline from its previous high."
Respect Market Structure
♦ Pivots = where smart money previously acted (support/resistance)
♦ Breaking them = momentum overcoming barriers
♦ Entering before pivot break = entering into known rejection zones
Trend is Your Friend
♦ Never pyramid against the trend
♦ If trend shifts to Uncertain or reverses → no new entries
♦ Exit when trend proves you wrong (don't fight it)
💬 "I never argue with the tape. Getting sore at the market doesn't get you anywhere."
Discipline > Emotion
♦ Can't "almost" have all conditions met
♦ Either 100% aligned (all ✓) or you wait
♦ No exceptions, no "this time is different"
♦ Automation designed to help remove emotion - consider using 3Commas
💬 "It never was my thinking that made the big money for me. It always was my sitting."
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🎯 FINAL THOUGHT
This indicator is a SYSTEMATIC FRAMEWORK, not a magic solution. It translates Livermore's century-old principles into actionable rules:
♦ Test small, build big
♦ Add to winners, cut losers fast
♦ Let structure guide exits
♦ Stay disciplined when emotions scream
The market will test your patience, discipline, and conviction. The indicator aims to reduce guesswork - but YOU still need to:
♦ Find valid wave structures
♦ Choose appropriate market conditions
♦ Size positions properly
♦ Accept losses as part of the game
💬 "The game of speculation is the most uniformly fascinating game in the world. But it is not a game for the stupid, the mentally lazy, the person of inferior emotional balance, or the get-rich-quick adventurer."
— Jesse Livermore
Breakouts with Trailing Stops V6 + AlertsBreakouts with Trailing Stops in Trading
Breakout trading is a strategy where traders aim to profit from an asset's price moving outside a defined support or resistance level, signaling a potential new trend. Trailing stops are a key risk management tool often used with breakouts to protect profits and limit potential losses.
What is a breakout?
A breakout occurs when an asset's price moves decisively above a resistance level (for a bullish breakout) or below a support level (for a bearish breakdown). This often signals increased momentum and potential for a significant price movement in the direction of the breakout.
Why use trailing stops with breakouts?
Trailing stops are particularly useful in breakout trading because they allow traders to capture potential profits as the price moves in their favor, while automatically adjusting to protect against sudden reversals.
How do trailing stops work with breakouts?
Initial Stop-Loss: When entering a breakout trade, a traditional stop-loss order is placed at a predetermined level to limit potential losses if the price reverses. For example, in a long position after a resistance breakout, the initial stop-loss might be placed below the former resistance level (which can now act as support).
Trailing Stop Activation: Once the price moves a favorable distance beyond the entry point, the trailing stop loss is activated. As highlighted by StoneX, it is a dynamic order that follows the price as it continues to move in the desired direction, maintaining a set distance below (for a long position) or above (for a short position) the current market price.
Profit Locking: If the price continues to rise (or fall for a short position), the trailing stop will move with it, "locking in" profits by raising the stop-loss level.
Exit Strategy: If the price reverses and hits the trailing stop, the position is automatically closed, ensuring that the trader retains a portion of the gains made while in the trade.
Advantages of using trailing stops with breakouts:
Locks in profits: Trailing stops help protect profits generated from successful breakout trades.
Automates exits: They automate the exit process, helping traders avoid emotional decision-making when the price reverses.
Allows for potential gains: They allow traders to stay in profitable trades as long as the trend continues.
Disadvantages of using trailing stops with breakouts:
Whipsaw risk: In volatile markets, the trailing stop may be triggered prematurely by minor price fluctuations.
Potential for missed gains: If the trailing stop is set too tightly, it may prevent the trader from capturing the maximum potential gains if the price experiences a minor pullback before continuing in the desired direction.
Tips for using trailing stops with breakouts:
Consider the asset's volatility: Adjust the trailing stop distance based on the asset's volatility to minimize the risk of premature stops.
Test different trailing stop methods: Experiment with different trailing stop methods to find what works best for your trading style and the specific asset you are trading.
Backtest your strategy: Before applying a trailing stop strategy to live trading, backtest it on historical data to evaluate its performance under different market conditions.
Combine with other indicators: Use other technical indicators, such as volume or momentum oscillators, to confirm the validity of breakouts and improve the effectiveness of your trailing stop strategy.
By carefully considering the market dynamics, using appropriate indicators, and implementing proper risk management techniques, traders can effectively utilize trailing stops with breakouts to capture potential profits while minimizing risk.
Have a good trade.
Canuck Trading Trader StrategyCanuck Trading Trader Strategy
Overview
The Canuck Trading Trader Strategy is a high-performance, trend-following trading system designed for NASDAQ:TSLA on a 15-minute timeframe. Optimized for precision and profitability, this strategy leverages short-term price trends to capture consistent gains while maintaining robust risk management. Ideal for traders seeking an automated, data-driven approach to trading Tesla’s volatile market, it delivers strong returns with controlled drawdowns.
Key Features
Trend-Based Entries: Identifies short-term trends using a 2-candle lookback period and a minimum trend strength of 0.2%, ensuring responsive trade signals.
Risk Management: Includes a configurable 3.0% stop-loss to cap losses and a 2.0% take-profit to lock in gains, balancing risk and reward.
High Precision: Utilizes bar magnification for accurate backtesting, reflecting realistic trade execution with 1-tick slippage and 0.1 commission.
Clean Interface: No on-chart indicators, providing a distraction-free trading experience focused on performance.
Flexible Sizing: Allocates 10% of equity per trade with support for up to 2 simultaneous positions (pyramiding).
Performance Highlights
Backtested from March 1, 2024, to June 20, 2025, on NASDAQ:TSLA (15-minute timeframe) with $1,000,000 initial capital:
Net Profit: $2,279,888.08 (227.99%)
Win Rate: 52.94% (3,039 winning trades out of 5,741)
Profit Factor: 3.495
Max Drawdown: 2.20%
Average Winning Trade: $1,050.91 (0.55%)
Average Losing Trade: $338.20 (0.18%)
Sharpe Ratio: 2.468
Note: Past performance is not indicative of future results. Always validate with your own backtesting and forward testing.
Usage Instructions
Setup:
Apply the strategy to a NASDAQ:TSLA 15-minute chart.
Ensure your TradingView account supports bar magnification for accurate results.
Configuration:
Lookback Candles: Default is 2 (recommended).
Min Trend Strength: Set to 0.2% for optimal trade frequency.
Stop Loss: Default 3.0% to cap losses.
Take Profit: Default 2.0% to secure gains.
Order Size: 10% of equity per trade.
Pyramiding: Allows up to 2 orders.
Commission: Set to 0.1.
Slippage: Set to 1 tick.
Enable "Recalculate After Order is Filled" and "Recalculate on Every Tick" in backtest settings.
Backtesting:
Run backtests over March 1, 2024, to June 20, 2025, to verify performance.
Adjust stop-loss (e.g., 2.5%) or take-profit (e.g., 1–3%) to suit your risk tolerance.
Live Trading:
Use with a compatible broker or TradingView alerts for automated execution.
Monitor execution for slippage or latency, especially given the high trade frequency (5,741 trades).
Validate in a demo account before deploying with real capital.
Risk Disclosure
Trading involves significant risk and may result in losses exceeding your initial capital. The Canuck Trading Trader Strategy is provided for educational and informational purposes only. Users are responsible for their own trading decisions and should conduct thorough testing before using in live markets. The strategy’s high trade frequency requires reliable execution infrastructure to minimize slippage and latency.
Long/Short/Exit/Risk management Strategy # LongShortExit Strategy Documentation
## Overview
The LongShortExit strategy is a versatile trading system for TradingView that provides complete control over entry, exit, and risk management parameters. It features a sophisticated framework for managing long and short positions with customizable profit targets, stop-loss mechanisms, partial profit-taking, and trailing stops. The strategy can be enhanced with continuous position signals for visual feedback on the current trading state.
## Key Features
### General Settings
- **Trading Direction**: Choose to trade long positions only, short positions only, or both.
- **Max Trades Per Day**: Limit the number of trades per day to prevent overtrading.
- **Bars Between Trades**: Enforce a minimum number of bars between consecutive trades.
### Session Management
- **Session Control**: Restrict trading to specific times of the day.
- **Time Zone**: Specify the time zone for session calculations.
- **Expiration**: Optionally set a date when the strategy should stop executing.
### Contract Settings
- **Contract Type**: Select from common futures contracts (MNQ, MES, NQ, ES) or custom values.
- **Point Value**: Define the dollar value per point movement.
- **Tick Size**: Set the minimum price movement for accurate calculations.
### Visual Signals
- **Continuous Position Signals**: Implement 0 to 1 visual signals to track position states.
- **Signal Plotting**: Customize color and appearance of position signals.
- **Clear Visual Feedback**: Instantly see when entry conditions are triggered.
### Risk Management
#### Stop Loss and Take Profit
- **Risk Type**: Choose between percentage-based, ATR-based, or points-based risk management.
- **Percentage Mode**: Set SL/TP as a percentage of entry price.
- **ATR Mode**: Set SL/TP as a multiple of the Average True Range.
- **Points Mode**: Set SL/TP as a fixed number of points from entry.
#### Advanced Exit Features
- **Break-Even**: Automatically move stop-loss to break-even after reaching specified profit threshold.
- **Trailing Stop**: Implement a trailing stop-loss that follows price movement at a defined distance.
- **Partial Profit Taking**: Take partial profits at predetermined price levels:
- Set first partial exit point and percentage of position to close
- Set second partial exit point and percentage of position to close
- **Time-Based Exit**: Automatically exit a position after a specified number of bars.
#### Win/Loss Streak Management
- **Streak Cutoff**: Automatically pause trading after a series of consecutive wins or losses.
- **Daily Reset**: Option to reset streak counters at the start of each day.
### Entry Conditions
- **Source and Value**: Define the exact price source and value that triggers entries.
- **Equals Condition**: Entry signals occur when the source exactly matches the specified value.
### Performance Analytics
- **Real-Time Stats**: Track important performance metrics like win rate, P&L, and largest wins/losses.
- **Visual Feedback**: On-chart markers for entries, exits, and important events.
### External Integration
- **Webhook Support**: Compatible with TradingView's webhook alerts for automated trading.
- **Cross-Platform**: Connect to external trading systems and notification platforms.
- **Custom Order Execution**: Implement advanced order flows through external services.
## How to Use
### Setup Instructions
1. Add the script to your TradingView chart.
2. Configure the general settings based on your trading preferences.
3. Set session trading hours if you only want to trade specific times.
4. Select your contract specifications or customize for your instrument.
5. Configure risk parameters:
- Choose your preferred risk management approach
- Set appropriate stop-loss and take-profit levels
- Enable advanced features like break-even, trailing stops, or partial profit taking as needed
6. Define entry conditions:
- Select the price source (such as close, open, high, or an indicator)
- Set the specific value that should trigger entries
### Entry Condition Examples
- **Example 1**: To enter when price closes exactly at a whole number:
- Long Source: close
- Long Value: 4200 (for instance, to enter when price closes exactly at 4200)
- **Example 2**: To enter when an indicator reaches a specific value:
- Long Source: ta.rsi(close, 14)
- Long Value: 30 (triggers when RSI equals exactly 30)
### Best Practices
1. **Always backtest thoroughly** before using in live trading.
2. **Start with conservative risk settings**:
- Small position sizes
- Reasonable stop-loss distances
- Limited trades per day
3. **Monitor and adjust**:
- Use the performance table to track results
- Adjust parameters based on how the strategy performs
4. **Consider market volatility**:
- Use ATR-based stops during volatile periods
- Use fixed points during stable markets
## Continuous Position Signals Implementation
The LongShortExit strategy can be enhanced with continuous position signals to provide visual feedback about the current position state. These signals can help you track when the strategy is in a long or short position.
### Adding Continuous Position Signals
Add the following code to implement continuous position signals (0 to 1):
```pine
// Continuous position signals (0 to 1)
var float longSignal = 0.0
var float shortSignal = 0.0
// Update position signals based on your indicator's conditions
longSignal := longCondition ? 1.0 : 0.0
shortSignal := shortCondition ? 1.0 : 0.0
// Plot continuous signals
plot(longSignal, title="Long Signal", color=#00FF00, linewidth=2, transp=0, style=plot.style_line)
plot(shortSignal, title="Short Signal", color=#FF0000, linewidth=2, transp=0, style=plot.style_line)
```
### Benefits of Continuous Position Signals
- Provides clear visual feedback of current position state (long/short)
- Signal values stay consistent (0 or 1) until condition changes
- Can be used for additional calculations or alert conditions
- Makes it easier to track when entry conditions are triggered
### Using with Custom Indicators
You can adapt the continuous position signals to work with any custom indicator by replacing the condition with your indicator's logic:
```pine
// Example with moving average crossover
longSignal := fastMA > slowMA ? 1.0 : 0.0
shortSignal := fastMA < slowMA ? 1.0 : 0.0
```
## Webhook Integration
The LongShortExit strategy is fully compatible with TradingView's webhook alerts, allowing you to connect your strategy to external trading platforms, brokers, or custom applications for automated trading execution.
### Setting Up Webhooks
1. Create an alert on your chart with the LongShortExit strategy
2. Enable the "Webhook URL" option in the alert dialog
3. Enter your webhook endpoint URL (from your broker or custom trading system)
4. Customize the alert message with relevant information using TradingView variables
### Webhook Message Format Example
```json
{
"strategy": "LongShortExit",
"action": "{{strategy.order.action}}",
"price": "{{strategy.order.price}}",
"quantity": "{{strategy.position_size}}",
"time": "{{time}}",
"ticker": "{{ticker}}",
"position_size": "{{strategy.position_size}}",
"position_value": "{{strategy.position_value}}",
"order_id": "{{strategy.order.id}}",
"order_comment": "{{strategy.order.comment}}"
}
```
### TradingView Alert Condition Examples
For effective webhook automation, set up these alert conditions:
#### Entry Alert
```
{{strategy.position_size}} != {{strategy.position_size}}
```
#### Exit Alert
```
{{strategy.position_size}} < {{strategy.position_size}} or {{strategy.position_size}} > {{strategy.position_size}}
```
#### Partial Take Profit Alert
```
strategy.order.comment contains "Partial TP"
```
### Benefits of Webhook Integration
- **Automated Trading**: Execute trades automatically through supported brokers
- **Cross-Platform**: Connect to custom trading bots and applications
- **Real-Time Notifications**: Receive trade signals on external platforms
- **Data Collection**: Log trade data for further analysis
- **Custom Order Management**: Implement advanced order types not available in TradingView
### Compatible External Applications
- Trading bots and algorithmic trading software
- Custom order execution systems
- Discord, Telegram, or Slack notification systems
- Trade journaling applications
- Risk management platforms
### Implementation Recommendations
- Test webhook delivery using a free service like webhook.site before connecting to your actual trading system
- Include authentication tokens or API keys in your webhook URL or payload when required by your external service
- Consider implementing confirmation mechanisms to verify trade execution
- Log all webhook activities for troubleshooting and performance tracking
## Strategy Customization Tips
### For Scalping
- Set smaller profit targets (1-3 points)
- Use tighter stop-losses
- Enable break-even feature after small profit
- Set higher max trades per day
### For Day Trading
- Use moderate profit targets
- Implement partial profit taking
- Enable trailing stops
- Set reasonable session trading hours
### For Swing Trading
- Use longer-term charts
- Set wider stops (ATR-based often works well)
- Use higher profit targets
- Disable daily streak reset
## Common Troubleshooting
### Low Win Rate
- Consider widening stop-losses
- Verify that entry conditions aren't triggering too frequently
- Check if the equals condition is too restrictive; consider small tolerances
### Missing Obvious Trades
- The equals condition is extremely precise. Price must exactly match the specified value.
- Consider using floating-point precision for more reliable triggers
### Frequent Stop-Outs
- Try ATR-based stops instead of fixed points
- Increase the stop-loss distance
- Enable break-even feature to protect profits
## Important Notes
- The exact equals condition is strict and may result in fewer trade signals compared to other conditions.
- For instruments with decimal prices, exact equality might be rare. Consider the precision of your value.
- Break-even and trailing stop calculations are based on points, not percentage.
- Partial take-profit levels are defined in points distance from entry.
- The continuous position signals (0 to 1) provide valuable visual feedback but don't affect the strategy's trading logic directly.
- When implementing continuous signals, ensure they're aligned with the actual entry conditions used by the strategy.
---
*This strategy is for educational and informational purposes only. Always test thoroughly before using with real funds.*
magic wand STSM"Magic Wand STSM" Strategy: Trend-Following with Dynamic Risk Management
Overview:
The "Magic Wand STSM" (Supertrend & SMA Momentum) is an automated trading strategy designed to identify and capitalize on sustained trends in the market. It combines a multi-timeframe Supertrend for trend direction and potential reversal signals, along with a 200-period Simple Moving Average (SMA) for overall market bias. A key feature of this strategy is its dynamic position sizing based on a user-defined risk percentage per trade, and a built-in daily and monthly profit/loss tracking system to manage overall exposure and prevent overtrading.
How it Works (Underlying Concepts):
Multi-Timeframe Trend Confirmation (Supertrend):
The strategy uses two Supertrend indicators: one on the current chart timeframe and another on a higher timeframe (e.g., if your chart is 5-minute, the higher timeframe Supertrend might be 15-minute).
Trend Identification: The Supertrend's direction output is crucial. A negative direction indicates a bearish trend (price below Supertrend), while a positive direction indicates a bullish trend (price above Supertrend).
Confirmation: A core principle is that trades are only considered when the Supertrend on both the current and the higher timeframe align in the same direction. This helps to filter out noise and focus on stronger, more confirmed trends. For example, for a long trade, both Supertrends must be indicating a bearish trend (price below Supertrend line, implying an uptrend context where price is expected to stay above/rebound from Supertrend). Similarly, for short trades, both must be indicating a bullish trend (price above Supertrend line, implying a downtrend context where price is expected to stay below/retest Supertrend).
Trend "Readiness": The strategy specifically looks for situations where the Supertrend has been stable for a few bars (checking barssince the last direction change).
Long-Term Market Bias (200 SMA):
A 200-period Simple Moving Average is plotted on the chart.
Filter: For long trades, the price must be above the 200 SMA, confirming an overall bullish bias. For short trades, the price must be below the 200 SMA, confirming an overall bearish bias. This acts as a macro filter, ensuring trades are taken in alignment with the broader market direction.
"Lowest/Highest Value" Pullback Entries:
The strategy employs custom functions (LowestValueAndBar, HighestValueAndBar) to identify specific price action within the recent trend:
For Long Entries: It looks for a "buy ready" condition where the price has found a recent lowest point within a specific number of bars since the Supertrend turned bearish (indicating an uptrend). This suggests a potential pullback or consolidation before continuation. The entry trigger is a close above the open of this identified lowest bar, and also above the current bar's open.
For Short Entries: It looks for a "sell ready" condition where the price has found a recent highest point within a specific number of bars since the Supertrend turned bullish (indicating a downtrend). This suggests a potential rally or consolidation before continuation downwards. The entry trigger is a close below the open of this identified highest bar, and also below the current bar's open.
Candle Confirmation: The strategy also incorporates a check on the candle type at the "lowest/highest value" bar (e.g., closevalue_b < openvalue_b for buy signals, meaning a bearish candle at the low, suggesting a potential reversal before a buy).
Risk Management and Position Sizing:
Dynamic Lot Sizing: The lotsvalue function calculates the appropriate position size based on your Your Equity input, the Risk to Reward ratio, and your risk percentage for your balance % input. This ensures that the capital risked per trade remains consistent as a percentage of your equity, regardless of the instrument's volatility or price. The stop loss distance is directly used in this calculation.
Fixed Risk Reward: All trades are entered with a predefined Risk to Reward ratio (default 2.0). This means for every unit of risk (stop loss distance), the target profit is rr times that distance.
Daily and Monthly Performance Monitoring:
The strategy tracks todaysWins, todaysLosses, and res (daily net result) in real-time.
A "daily profit target" is implemented (day_profit): If the daily net result is very favorable (e.g., res >= 4 with todaysLosses >= 2 or todaysWins + todaysLosses >= 8), the strategy may temporarily halt trading for the remainder of the session to "lock in" profits and prevent overtrading during volatile periods.
A "monthly stop-out" (monthly_trade) is implemented: If the lres (overall net result from all closed trades) falls below a certain threshold (e.g., -12), the strategy will stop trading for a set period (one week in this case) to protect capital during prolonged drawdowns.
Trade Execution:
Entry Triggers: Trades are entered when all buy/sell conditions (Supertrend alignment, SMA filter, "buy/sell situation" candle confirmation, and risk management checks) are met, and there are no open positions.
Stop Loss and Take Profit:
Stop Loss: The stop loss is dynamically placed at the upTrendValue for long trades and downTrendValue for short trades. These values are derived from the Supertrend indicator, which naturally adjusts to market volatility.
Take Profit: The take profit is calculated based on the entry price, the stop loss, and the Risk to Reward ratio (rr).
Position Locks: lock_long and lock_short variables prevent immediate re-entry into the same direction once a trade is initiated, or after a trend reversal based on Supertrend changes.
Visual Elements:
The 200 SMA is plotted in yellow.
Entry, Stop Loss, and Take Profit lines are plotted in white, red, and green respectively when a trade is active, with shaded areas between them to visually represent risk and reward.
Diamond shapes are plotted at the bottom of the chart (green for potential buy signals, red for potential sell signals) to visually indicate when the buy_sit or sell_sit conditions are met, along with other key filters.
A comprehensive trade statistics table is displayed on the chart, showing daily wins/losses, daily profit, total deals, and overall profit/loss.
A background color indicates the active trading session.
Ideal Usage:
This strategy is best applied to instruments with clear trends and sufficient liquidity. Users should carefully adjust the Your Equity, Risk to Reward, and risk percentage inputs to align with their individual risk tolerance and capital. Experimentation with different ATR Length and Factor values for the Supertrend might be beneficial depending on the asset and timeframe.
PRO Strategy 3TP (v2.1.1)
English Version
PRO Strategy 3TP (v2.1.1) — Comprehensive Guide for TradingView
Strategy Concept & Uniqueness
The PRO Strategy 3TP is a trading system designed to follow market trends using a combination of tools that check trends across different timeframes, measure momentum, and manage risks smartly. Its standout feature is a three-step profit-taking system (hence "3TP") and its ability to adjust to market ups and downs, helping traders make the most of strong trends while keeping losses low in choppy markets.
Why It’s Special:
✅ Three Profit Levels: Takes profit in stages—33% at the first target (TP1), 33% at the second (TP2), and 34% at the third (TP3)—so you lock in gains gradually.
✅ Risk-Free After TP1: Once the first profit target is hit, the stop-loss moves to your entry price, meaning no more risk on the trade.
✅ Smarter Signals: Uses data from a higher timeframe (like 1-hour) to filter out false moves on your chart (like 15-minutes).
How It Works
The strategy uses four main tools to decide when to enter and exit trades. Here’s what they do in simple terms:
Trend Tools (EMA, HMA, SMA)
EMA (Exponential Moving Average): A line that tracks the price trend, reacting quickly to recent changes. Think of it as a fast guide to where the market’s heading.
Default: EMA 100 (looks at the last 100 bars).
HMA (Hull Moving Average): A smoother, faster-moving line that spots trend shifts earlier than most averages.
Default: HMA 50 (looks at the last 50 bars).
SMA (Simple Moving Average): A basic average of prices over time, great for seeing the big picture (bull or bear market).
Default: SMA 200 (looks at the last 200 bars).
How It Helps: These lines work together to make sure the trend is real across short, medium, and long terms.
Momentum Tool (CCI)
CCI (Commodity Channel Index): Tells you if the market is “overbought” (too high, ready to drop) or “oversold” (too low, ready to rise).
Buy when CCI < -100 (oversold).
Sell when CCI > +100 (overbought).
How It Helps: It picks the best moments to jump into a trade when prices are at extremes.
Trend Strength Tool (ADX)
ADX (Average Directional Index): Measures how strong a trend is. Higher numbers mean a stronger trend.
Default: ADX > 26 (only trades when the trend is strong enough).
How It Helps: Keeps you out of flat, boring markets where prices don’t move much.
Volatility Tool (ATR)
ATR (Average True Range): Shows how much the price typically moves up or down. It’s like a ruler for market “wiggle room.”
Default: ATR over 19 bars, used to set stop-loss (5x ATR) and profit targets (1x, 1.3x, 1.7x ATR).
How It Helps: Adjusts your trade exits based on how wild or calm the market is.
Entry Rules
Buy (Long): Price is above EMA, HMA, and SMA (checked on a higher timeframe) + CCI < -100 + ADX > 26.
Sell (Short): Price is below EMA, HMA, and SMA + CCI > +100 + ADX > 26.
Exit Rules
Stop-Loss: Set at 5x ATR away from your entry (e.g., if ATR is 10 points, stop-loss is 50 points away).
Breakeven: After TP1 is hit, stop-loss moves to your entry price—no more risk!
Profit Targets:
TP1: 1x ATR (closes 33% of your position).
TP2: 1.3x ATR (closes 33%).
TP3: 1.7x ATR (closes 34%).
Why This Mix Works
Fewer Mistakes: Checking trends on multiple timeframes cuts out 60-70% of bad signals (based on tests).
Adapts to the Market: ATR adjusts your stops and targets as the market changes—super useful for volatile assets like crypto.
Balanced Wins: The three-step profit system locks in gains early but lets you ride big trends too.
Setup Guide
Settings for Different Styles
Parameter Scalping (1-15M) Swing (1H-4H) Position (Daily)
EMA/HMA/SMA 50/20/Off 100/50/200 Off/Off/200
ADX Threshold 20 26 25
ATR Multipliers SL=3x, TP3=2x SL=5x SL=6x
Position Size
Formula: Contracts = Risk Amount / (Stop-Loss Distance × Value per Point)
Example: Risking $100, stop-loss is 50 points, each point = $2 → Trade 1 contract.
Multi-Timeframe Tip
Chart: 15-minute
Indicators: 1-hour
Rule: Only trade if the 15-minute price matches the 1-hour trend.
Why Use It?
Proven Results: 58-62% win rate on assets like Bitcoin, Ethereum, and S&P 500 (tested 2020-2023). Risk-to-reward ratio of 1.8-2.3.
Saves Time: Alerts tell you when to enter or exit—no need to watch the screen all day.
Flexible: Works for fast scalping, medium swing trades, or long-term positions.
FAQ
Why no trailing stop?
Trailing stops cut profits by 15-20% in tests because they exit too early. The breakeven stop protects your money better.
What about news events?
Use a bigger ATR (e.g., 50) and wider stop-loss (6x ATR) when markets get crazy.
Can I trade forex?
Yes! Try EMA=50, HMA=20, ATR=14 on EUR/USD 15-minute charts.
Risk Management
Risk per Trade: Stick to 1-2% of your account.
Weekly Check: Adjust ATR and stop-loss every Friday to match market conditions.
Emergency Plan: Manually move your stop-loss if something wild (like a “black swan” event) happens.
⚠️ Warning: Trading is risky. This strategy doesn’t promise profits. Always use a stop-loss.
Русская версия
Стратегия PRO 3TP (v2.1.1) — Полное руководство для TradingView
Концепция и уникальность
PRO Strategy 3TP — это система, которая следует за трендами на рынке, используя проверку трендов на разных таймфреймах, измерение импульса и умное управление рисками. Главная фишка — трехступенчатая фиксация прибыли (поэтому "3TP") и адаптация к изменениям на рынке, чтобы зарабатывать больше в сильных трендах и терять меньше в нестабильные времена.
Почему она особенная:
✅ Три уровня прибыли: Закрывает 33% на первом уровне (TP1), 33% на втором (TP2) и 34% на третьем (TP3) — прибыль фиксируется постепенно.
✅ Без риска после TP1: После первого уровня стоп-лосс сдвигается на точку входа — дальше риска нет.
✅ Умные сигналы: Использует данные с более старшего таймфрейма (например, 1 час) для фильтрации шума на вашем графике (например, 15 минут).
Как это работает
Стратегия использует четыре основных инструмента для входа и выхода из сделок. Вот что они значат простыми словами:
Инструменты тренда (EMA, HMA, SMA)
EMA (Экспоненциальная скользящая средняя) : Линия, которая следит за трендом и быстро реагирует на последние цены. Это как быстрый указатель направления рынка.
По умолчанию: EMA 100 (смотрит на последние 100 баров).
HMA (Скользящая средняя Халла): Более плавная и быстрая линия, которая раньше замечает смену тренда.
По умолчанию: HMA 50 (смотрит на последние 50 баров).
SMA (Простая скользящая средняя) : Просто средняя цена за период, показывает общую картину (быки или медведи).
По умолчанию: SMA 200 (смотрит на последние 200 баров).
Зачем это нужно: Эти линии вместе проверяют, что тренд настоящий на коротких, средних и длинных периодах.
Инструмент импульса (CCI)
CCI (Индекс товарного канала): Показывает, когда рынок “перекуплен” (слишком высоко, готов упасть) или “перепродан” (слишком низко, готов расти).
Покупка: CCI < -100 (перепродан).
Продажа: CCI > +100 (перекуплен).
Зачем это нужно: Помогает выбрать лучшее время для входа, когда цены на крайних значениях.
Инструмент силы тренда (ADX)
ADX (Индекс среднего направленного движения): Измеряет, насколько силен тренд. Чем выше число, тем сильнее движение.
По умолчанию: ADX > 26 (торгуем, только если тренд сильный).
Зачем это нужно: Не дает торговать, когда рынок стоит на месте и скучный.
Инструмент волатильности (ATR)
ATR (Средний истинный диапазон): Показывает, насколько сильно цена обычно “гуляет” вверх-вниз. Это как линейка для рыночных колебаний.
По умолчанию: ATR за 19 баров, стоп-лосс = 5x ATR, цели прибыли = 1x, 1.3x, 1.7x ATR.
Зачем это нужно: Настраивает выход из сделки в зависимости от того, насколько рынок спокоен или хаотичен.
Правила входа
Покупка (Лонг): Цена выше EMA, HMA и SMA (проверяется на старшем таймфрейме) + CCI < -100 + ADX > 26.
Продажа (Шорт): Цена ниже EMA, HMA и SMA + CCI > +100 + ADX > 26.
Правила выхода
Стоп-лосс: Устанавливается на 5x ATR от входа (например, если ATR = 10 пунктов, стоп = 50 пунктов).
Безубыток: После TP1 стоп-лосс сдвигается на цену входа — риска больше нет!
Цели прибыли:
TP1: 1x ATR (закрывает 33% позиции).
TP2: 1.3x ATR (закрывает 33%).
TP3: 1.7x ATR (закрывает 34%).
Почему эта комбинация работает
Меньше ошибок: Проверка тренда на разных таймфреймах убирает 60-70% ложных сигналов (по тестам).
Подстраивается под рынок: ATR меняет стопы и цели в зависимости от условий — важно для активов вроде крипты.
Умная прибыль: Трехступенчатая система фиксирует выгоду рано, но оставляет шанс заработать на большом тренде.
Как настроить
Настройки для разных стилей
Параметр Скальпинг (1-15М) Свинг (1H-4H) Долгосрок (Daily)
EMA/HMA/SMA 50/20/Выкл 100/50/200 Выкл/Выкл/200
Порог ADX 20 26 25
Множители ATR SL=3x, TP3=2x SL=5x SL=6x
Размер позиции
Формула: Контракты = Риск / (Расстояние до стоп-лосса × Стоимость пункта)
Пример: Риск $100, стоп-лосс 50 пунктов, 1 пункт = $2 → 1 контракт.
Совет по таймфреймам
График: 15 минут
Индикаторы: 1 час
Правило: Торгуй, только если тренд на 15 минутах совпадает с 1 часом.
Зачем это использовать?
Проверено: 58-62% успешных сделок на BTC, ETH, S&P 500 (тесты 2020-2023). Соотношение риск/прибыль 1.8-2.3.
Экономит время: Оповещения скажут, когда входить и выходить — не надо сидеть у экрана.
Гибкость: Подходит для быстрой торговли, среднесрочной и долгосрочной.
Часто задаваемые вопросы
Почему нет трейлинг-стопа?
Тесты показали, что он снижает прибыль на 15-20%, потому что выходит слишком рано. Безубыток лучше защищает деньги.
Что делать с новостями?
Увеличьте ATR (например, до 50) и стоп-лосс (6x ATR), когда рынок штормит.
Можно торговать форекс?
Да! Используйте EMA=50, HMA=20, ATR=14 для EUR/USD на 15 минутах.
Управление рисками
Риск на сделку: Не больше 1-2% от депозита.
Проверка раз в неделю: Обновляйте ATR и стоп-лосс каждую пятницу под рынок.
План на экстрим: Если происходит что-то необычное (например, “черный лебедь”), вручную двигайте стоп-лосс.
⚠️ Предупреждение: Торговля — это риск. Стратегия не гарантирует прибыль. Всегда ставьте стоп-лосс.
Fibonacci Swing Trading BotStrategy Overview for "Fibonacci Swing Trading Bot"
Strategy Name: Fibonacci Swing Trading Bot
Version: Pine Script v5
Purpose: This strategy is designed for swing traders who want to leverage Fibonacci retracement levels and candlestick patterns to enter and exit trades on higher time frames.
Key Components:
1. Multiple Timeframe Analysis:
The strategy uses a customizable timeframe for analysis. You can choose between 4hour, daily, weekly, or monthly time frames to fit your preferred trading horizon. The high and low-price data is retrieved from the selected timeframe to identify swing points.
2. Fibonacci Retracement Levels:
The script calculates two key Fibonacci retracement levels:
0.618: A common level where price often retraces before resuming its trend.
0.786: A deeper retracement level, often used to identify stronger support/resistance areas.
These levels are dynamically plotted on the chart based on the highest high and lowest low over the last 50 bars of the selected timeframe.
3. Candlestick Based Entry Signals:
The strategy uses candlestick patterns as the only indicator for trade entries:
Bullish Candle: A green candle (close > open) that forms between the 0.618 retracement level and the swing high.
Bearish Candle: A red candle (close < open) that forms between the 0.786 retracement level and the swing low.
When these candlestick patterns align with the Fibonacci levels, the script triggers buy or sell signals.
4. Risk Management:
Stop Loss: The stop loss is set at 1% below the entry price for long trades and 1% above the entry price for short trades. This tight risk management ensures controlled losses.
Take Profit: The strategy uses a 2:1 risk-to-reward ratio. The take profit is automatically calculated based on this ratio relative to the stop loss.
5. Buy/Sell Logic:
Buy Signal: Triggered when a bullish candle forms above the 0.618 retracement level and below the swing high. The bot then places a long position.
Sell Signal: Triggered when a bearish candle forms below the 0.786 retracement level and above the swing low. The bot then places a short position.
The stop loss and take profit levels are automatically managed once the trade is placed.
Strengths of This Strategy:
Swing Trading Focus: The strategy is ideal for swing traders, targeting longer-term price moves that can take days or weeks to play out.
Simple Yet Effective Indicators: By only relying on Fibonacci retracement levels and basic candlestick patterns, the strategy avoids complexity while capitalizing on well-known support and resistance zones.
Automated Risk Management: The built-in stop loss and take profit mechanism ensures trades are protected, adhering to a strict 2:1 risk/reward ratio.
Multiple Timeframe Analysis: The script adapts to various market conditions by allowing users to switch between different timeframes (4hour, daily, weekly, monthly), giving traders flexibility.
Strategy Use Cases:
Retracement Traders: Traders who focus on entering the market at key retracement levels (0.618 and 0.786) will find this strategy especially useful.
Trend Reversal Traders: The strategy’s reliance on candlestick formations at Fibonacci levels helps traders spot potential reversals in price trends.
Risk Conscious Traders: With its 1% risk per trade and 2:1 risk/reward ratio, the strategy is ideal for traders who prioritize risk management in their trades.
Dow Theory based Strategy (Markttechnik)What makes this script unique?
calculates two trends at the same time: a big one for the overall strong trend - and a small one to trigger a trade after a small correction within the big trend
only if both trends (the small and the big trend) are in an uptrend, a buy signal is created: this prevents a buy signal from being generated in a falling market just because an upward movement begins in a small trend
the exit strategy can be configured very flexibly and individually: use the last low as stop loss and automatically switch to a trialing stop loss as soon as the take profit is reached (instead of finishing the trade)
the take profit strategy can also be configured - e.g. use the last high, a fixed percentage or a combination of it
plots each trade in detail on the chart - e.g. inner candles or the exact progression of the stop loss over the entire duration of the trade to allow you to analyze each trade precisely
What does the script do and how?
In this strategy an intact upward trend is characterized by higher highs and lower lows only if the big trend and the small trend are in an upward trend at the same time.
The following describes how the script calculates a buy signal. Every step is drawn to the chart immediately - see example chart above:
1. the stock rises in the big trend - i.e. in a longer time frame
2. a correction takes place (the share price falls) - but does not create a new low
3. the stock rises again in the big trend and creates a new high
From now on, the big trend is in an intact upward trend (until it falls below its last low).
This is drawn to the chart as 3 bold green zigzag lines.
But we do not buy right now! Instead, we want to wait for a correction in the big trend and for the start of a small upward trend.
4. a correction takes place (not below the low from 2.)
Now, the script also starts to calculate the small trend:
5. the stock rises in the small trend - i.e. in a shorter time frame
6. a small correction takes place (not below the low from 4.)
7. the stock rises above the high from 5.: a new high in the shorter time frame
Now, both trends are in an intact upward trend.
A buy signal is created and both the minor and major trend are colored green on the chart.
Now, the trade is active and:
the stop loss is calculated and drawn for each candle
the take profit is calculated and drawn to the chart
as soon as the price reaches the take profit or the stop loss, the trade is closed
Features and functionalities
Uptrend : An intact upward trend is characterized by higher highs and lower lows. Uptrends are shown in green on the chart.
The beginning of an uptrend is numbered 1, each subsequent high is numbered 2, and each low is numbered 3.
Downtrend: An intact downtrend is characterized by lower highs and lower lows. Downtrends are displayed in red on the chart.
Note that our indicator does not show the numbering of the points of the downtrend.
Trendless phases: If there is no intact trend, we are in a trendless phase. Trendless phases are shown in blue on the chart.
This occurs after an uptrend, when a lower low or a lower high is formed. Or after a downtrend, when a higher low or a higher high is formed.
Buy signals
A buy signal is generated as soon as a new upward trend has been formed or a new high has been established in an intact upward trend.
But even before a buy signal is generated, this strategy anticipates a possible emerging trend and draws the next possible trading opportunity to the chart.
In addition to the (not yet reached) buy price, the risk-reward ratio, the StopLoss and the TakeProfit price is shown.
With this information, you can already enter a StopBuy order, which is thus triggered directly with the then created buy signal.
You can configure, if a buy signal shall be created while the big trend is an uptrend, a downtrend and/or trendless.
Exit strategy
With this strategy, you have multiple possibilities to close your position. All of them can be configured within the settings. In general, you can combine a take profit strategy with a stop loss strategy.
The take profit price will be calculated once for each trade. It will be drawn to the chart for active trade.
Depending on your configuration, this can be the last high (which is often a resistance level), a fixed percentage added to the buy price or the maximum of both.
You can also configure that a trailing stop loss is used as soon as the take profit price is reached once.
The stop loss gets recalculated with each candle and is displayed and plotted for each active and finished trade. With this, you can easily check how the stop loss changed during your trades.
The stop loss can be configured flexibly:
Use the classic "trailing stop loss" that follows the price from below.
Set the stop loss to the last low and tighten it every time the small trend marks a new local low.
Confiure that the stop loss is tightened as soon as the break even is reached. Nothing is more annoying than a trade turning from a win to a loss.
Ignore inside candles (see description below) and relax the stop loss to use the outside candle for its calculation.
Inner candles
Inner candles are created when the candle body is within the maximum values of a previous candle (the outer candle). There can be any number of consecutive inner candles. As soon as you have activated the "Check inner candles" setting, all consecutive inner candles will be highlighted in yellow on the chart.
Prices during an inner candle scenario might be irrelevant for trading and can be interpreted as fluctuations within the outside candle. For this reason, the trailing stop loss should not be aligned with inner candles. Therefore, as soon as an inner candle occurs, the stop loss is reset and the low at the time of the outside candle is used as the calculation for the trailing stop loss. This will all be plotted for you on the chart.
Display of the trades:
All active and closed trades of the last 5 years are displayed in the chart with buy signal, sell, stop loss history, inside candles and statistics.
Backtesting:
The strategy can be simulated for each stock over the period of the last 5 years. Each individual trade is recorded and can be traced and analyzed in the chart including stop loss history. Detailed evaluations and statistics are available to evaluate the performance of the strategy.
Additional Statistics
This strategy immediately displays a statistic table to the chart area giving you an overview of its performance over the last years for the given chart.
This includes:
The total win/loss in $ and %
The win/loss per year in %
The active investment time in days and % (e.g. invested 10 of 100 trading days -> 10%)
The total win/loss in %, extrapolated to 100% equity usage: Only with this value can strategies really be compared. Because you are not invested between the trades and could invest in other stocks during this time. This value indicates how much profit you would have made if you had been invested 100% of the time - or to put it another way - if you had been invested 100% of the time in stocks with exactly the same performance. Let's say you had only one trade in the last 5 years that lasted, say, only one month and made 5% profit. This would be significantly better than a strategy with which you were invested for, say, 5 years and made 10% profit.
The total profit/loss per year in %, extrapolated to 100% equity usage
Notifications (alerts):
Get alerted before a new buy signal emerges to create an order if necessary and not miss a trade. You can also be notified when the stop loss needs to be adjusted. The notification can be done in different ways, e.g. by Mail, PopUp or App-Notification. This saves them the annoying, time-consuming and error-prone "click through" all the charts.
Settings: Display Settings
With these settings, you have the possibility to:
Show the small or the big trend as a background color
Configure if the numbers (1-2-3-2-3) shall be shown at all or only for the small, the big trend or both
Settings: Trend calculation - fine tuning
Drawing trend lines on a chart is not an exact science. Some highs and lows are not very clear or significant. And so it will always happen that 2 different people would draw different trendlines for the same chart. Unfortunately, there is no exact "right" or "wrong" here.
With the options under "Trend Calculation - Fine Tuning" you have the possibility to influence the drawing in of trends and to adapt it to your personal taste.
Small Trend, Big Trend : With these settings you can influence how significant a high or low has to be to recognize them as an independent high or low. The larger the values, the more significant a high or low must be to be recognized as such.
High and low recognition : With this setting you can influence when two adjacent, almost identical highs or lows should be recognized as independent highs or lows. The higher the value, the more different "similar" highs or lows must be in order to be recognized as such.
Which default settings were selected and why
Show Trades: true - its often useful to see all recent trades in the chart
Time Frame: 1 day - most common time frame (except for day traders)
Take Profit: combined 10% - the last high is taken as take profit because the trend often changes there, but only if there is at least 10% profit to ensure we do not risk money for a tiny profit
Stop Loss: combined - the last low is used as stop loss because the trend would break there and switch to a trailing stop loss as soon as our take profit is reached to let our profits run without risking them anymore
Stop Loss distance: 3% - we are giving the price 3% air (below the last low) to avoid being stopped out due to a short price drop
Trailing Stop Loss: 2% - we have to give the stop loss some room to avoid being stopped out prematurely; this is a value that is well balanced between a certain downside distance and the profit-taking ratio
Set Stop Loss to break even: true, 2% - once we reached the break even, it is a common practice to not risk our money anymore, the value is set to the same value as the trailing stop loss
Trade Filter: Uptrend - we only start trades if the big trend is an uptrend in the expectation that it will continue after a small correction
Display settings: those will not influence the trades, feel free to change them to your needs
Trend calculation - Fine Tuning: 1/1,5/0,05; influences the internal calculation for highs and lows and how significant they need to be to be considered a new high or low; the default values will provide you nicely calculated trends in the daily time frame; if there are too many or too few lows and highs according to your taste, feel free to play around and immediately see the result drawn to the chart; read the manual for a detailed description of this values
Note that you can (and should) configure the general trading properties like your initial capital, order size, slippage and commission.
BBTrend w SuperTrend decision - Strategy [presentTrading]This strategy aims to improve upon the performance of Traidngview's newly published "BB Trend" indicator by incorporating the SuperTrend for better trade execution and risk management. Enjoy :)
█Introduction and How it is Different
The "BBTrend w SuperTrend decision - Strategy " is a trading strategy designed to identify market trends using Bollinger Bands and SuperTrend indicators. What sets this strategy apart is its use of two Bollinger Bands with different lengths to capture both short-term and long-term market trends, providing a more comprehensive view of market dynamics. Additionally, the strategy includes customizable take profit (TP) and stop loss (SL) settings, allowing traders to tailor their risk management according to their preferences.
BTCUSD 4h Long Performance
█ Strategy, How It Works: Detailed Explanation
The BBTrend strategy employs two key indicators: Bollinger Bands and SuperTrend.
🔶 Bollinger Bands Calculation:
- Short Bollinger Bands**: Calculated using a shorter period (default 20).
- Long Bollinger Bands**: Calculated using a longer period (default 50).
- Bollinger Bands use the standard deviation of price data to create upper and lower bands around a moving average.
Upper Band = Middle Band + (k * Standard Deviation)
Lower Band = Middle Band - (k * Standard Deviation)
🔶 BBTrend Indicator:
- The BBTrend indicator is derived from the absolute differences between the short and long Bollinger Bands' lower and upper values.
BBTrend = (|Short Lower - Long Lower| - |Short Upper - Long Upper|) / Short Middle * 100
🔶 SuperTrend Indicator:
- The SuperTrend indicator is calculated using the average true range (ATR) and a multiplier. It helps identify the market trend direction by plotting levels above and below the price, which act as dynamic support and resistance levels. * @EliCobra makes the SuperTrend Toolkit. He is GOAT.
SuperTrend Upper = HL2 + (Factor * ATR)
SuperTrend Lower = HL2 - (Factor * ATR)
The strategy determines market trends by checking if the close price is above or below the SuperTrend values:
- Uptrend: Close price is above the SuperTrend lower band.
- Downtrend: Close price is below the SuperTrend upper band.
Short: 10 Long: 20 std 2
Short: 20 Long: 40 std 2
Short: 20 Long: 40 std 4
█ Trade Direction
The strategy allows traders to choose their trading direction:
- Long: Enter long positions only.
- Short: Enter short positions only.
- Both: Enter both long and short positions based on market conditions.
█ Usage
To use the "BBTrend - Strategy " effectively:
1. Configure Inputs: Adjust the Bollinger Bands lengths, standard deviation multiplier, and SuperTrend settings.
2. Set TPSL Conditions: Choose the take profit and stop loss percentages to manage risk.
3. Choose Trade Direction: Decide whether to trade long, short, or both directions.
4. Apply Strategy: Apply the strategy to your chart and monitor the signals for potential trades.
█ Default Settings
The default settings are designed to provide a balance between sensitivity and stability:
- Short BB Length (20): Captures short-term market trends.
- Long BB Length (50): Captures long-term market trends.
- StdDev (2.0): Determines the width of the Bollinger Bands.
- SuperTrend Length (10): Period for calculating the ATR.
- SuperTrend Factor (12): Multiplier for the ATR to adjust the SuperTrend sensitivity.
- Take Profit (30%): Sets the level at which profits are taken.
- Stop Loss (20%): Sets the level at which losses are cut to manage risk.
Effect on Performance
- Short BB Length: A shorter length makes the strategy more responsive to recent price changes but can generate more false signals.
- Long BB Length: A longer length provides smoother trend signals but may be slower to react to price changes.
- StdDev: Higher values create wider bands, reducing the frequency of signals but increasing their reliability.
- SuperTrend Length and Factor: Shorter lengths and higher factors make the SuperTrend more sensitive, providing quicker signals but potentially more noise.
- Take Profit and Stop Loss: Adjusting these levels affects the risk-reward ratio. Higher take profit percentages can increase gains but may result in fewer closed trades, while higher stop loss percentages can decrease the likelihood of being stopped out but increase potential losses.
[TTI] High Volume Close (HVC) Setup📜 ––––HISTORY & CREDITS––––
The High Volume Close (HVC) Setup is a specialised indicator designed for the TradingView platform used to identify specific bar. This tool was developed with the objective of identifying a technical pattern that trades have claimed is significant trading opportunities through a unique blend of volume analysis and price action strategies. It is based on the premise that high-volume bars, when combined with specific price action criteria, can signal key market movements.
The HVC is applicable both for swing and longer term trading and as a technical tool it can be used by traders of any asset type (stocks, ETF, crypto, forex etc).
🦄 –––UNIQUENESS–––
The uniqueness of the HVC Setup lies in its flexibility to determine an important price level based on historically important bar. The idea is to identify significant bars (e.g. those who have created the HIGHEST VOLUME: Ever, Yearly, Quarterly and meet additional criteria from the settings) and plot on the chart the close on that day as a significant level as well as theoretical stop loss and target levels. This approach allows traders to discern high volume bars that are contextually significant — a method not commonly found in standard trading tools.
🎯 ––––WHAT IT DOES––––
The HVC Setup indicator performs a series of calculations to identify high volume close bars/bar (HVC bars) based on the user requirements.
These bars are determined based on the highest volume recorded within a user-inputs:
👉 Period (Ever, Yearly, Quarterly) and must meet additional criteria such as:
👉 a minimum percentage Price Change (change is calculated based on a close/close) and
👉 specific Closing Range requirements for the HVC da.
The theory is that this is a significant bar that is important to know where it is on the chart.
The script includes a comparative analysis of the HVC bar's price against historical price highs (all-time, yearly, quarterly), which provides further context and significance to the identified bars. All of these USER input requirement are then taken into account as a condition to identity the High Volume Close Bar (HVC).
The visual representation includes color-coded bar (default is yellow) and lines to delineate these key trading signals. It then draws a blue line for the place where the close ofthe bar is, a red line that would signify a stop loss and 2 target profit levels equal to 2R and 3R of the risked level (close-stop loss). Additional lines can be turned on/off with their coresponding checkboxes in the settings.
If the user chooses "Ever" for Period - the script will look at the first available bar ever in Tradingview - this is generally the IPO bar;
If the users chooses "Yearly" - the script would look at the highest available bar for a completed year;
If the users chooses "Quarterly" - it would do the same for the quarter. (works on daily timeframe only);
While we have not backtested the performance of the script, this methodology has been widely publicised.
🛠️ ––––HOW TO USE IT––––
To utilize the HVC Setup effectively:
👉Customize Input Settings: Choose the HVC period, percentage change threshold, closing range, stop loss distance, and target multiples according to your trading strategy. Use the tick boxes to enable and disable if a given condition is used within the calculation.
👉Identify HVC Bars: The script highlights HVC bars, indicating potential opportunities based on volume and price action analysis.
👉Interpret Targets and Stop Losses: Use the color-coded lines (green for targets, red for stop losses) to guide your trade entries and exits.
👉Contextual Analysis: Always consider the HVC bar signals in conjunction with overall market trends and additional technical indicators for comprehensive trading decisions.
This script is designed to assist traders in identifying high-potential trading setups by using a combination of volume and price analysis, enhancing traditional methods with a unique, algorithmically driven approach.
Luxmi AI Directional Option Buying (Long Only)Introduction:
"Option premium charts typically exhibit a predisposition towards bearish sentiment in higher timeframes"
In the dynamic world of options trading, navigating through the complexities of market trends and price movements is essential for making informed decisions. Among the arsenal of tools available to traders, option premium charts stand out as a pivotal source of insight, particularly in higher timeframes. However, their inherent bearish inclination in such timeframes necessitates a keen eye for identifying bullish pullbacks, especially in lower timeframes, to optimize buying strategies effectively.
Understanding the interplay between different data points becomes paramount in this endeavor. Traders embark on a journey of analysis, delving into metrics such as Implementation Shortfall, the performance of underlying index constituents, and bullish trends observed in lower timeframes like the 1-minute and 3-minute charts. These data points serve as guiding beacons, illuminating potential opportunities amidst the market's ever-shifting landscape.
Using this indicator, we will dissect the significance of option premium charts and their nuanced portrayal of market sentiment. Furthermore, we will unveil the art of discerning bullish pullbacks in lower timeframes, leveraging a multifaceted approach that amalgamates quantitative analysis with qualitative insights. Through this holistic perspective, traders can refine their decision-making processes, striving towards efficiency and efficacy in their options trading endeavors.
Major Features:
Implementation Shortfall (IS) Candles:
Working Principle:
TWAP (Time-Weighted Average Price) and EMA (Exponential Moving Average) are both commonly used in calculating Implementation Shortfall, a metric that measures the difference between the actual execution price of a trade and the benchmark price.
TWAP calculates the average price of a security over a specified time period, giving equal weight to each interval. On the other hand, EMA places more weight on recent prices, making it more responsive to current market conditions.
To calculate Implementation Shortfall using TWAP, the difference between the average execution price and the benchmark price is determined over the trading period. Similarly, with EMA, the difference is calculated using the exponential moving average price instead of a simple average.
By employing TWAP and EMA, traders can gauge the effectiveness of their trading strategies and identify areas for improvement in executing trades relative to a benchmark.
Benefits of using Implementation Shortfall:
By visualizing the implementation shortfall and its comparison with the EMA on the chart, traders can quickly assess whether current trading activity is deviating from recent trends.
Green bars suggest potential buying opportunities or bullish sentiment, while red bars suggest potential selling opportunities or bearish sentiment.
Traders can use this visualization to make more informed decisions about their trading strategies, such as adjusting position sizes, entering or exiting trades, or managing risk based on the observed deviations from the moving average.
How to use this feature:
This feature calculates Implementation Shortfall (IS) and visually represents it by coloring the candles in either bullish (green) or bearish (red) hues. This color-coding system provides traders with a quick and intuitive way to assess market sentiment and potential entry points. Specifically, a long entry is signaled when both the candle color and the trend cloud color align as green, indicating a bullish market outlook. This integrated approach enables traders to make informed decisions, leveraging IS insights alongside visual cues for more effective trading strategies.
Micro Trend Candles:
Working Principle:
This feature begins by initializing variables to determine trend channel width and track price movements. Average True Range (ATR) is then calculated to measure market volatility, influencing the channel's size. Highs and lows are identified within a specified range, and trends are assessed based on price breaches, with potential changes signaled accordingly. The price channel is continually updated to adapt to market shifts, and arrows are placed to indicate potential entry points. Colors are assigned to represent bullish and bearish trends, dynamically adjusting based on current market conditions. Finally, candles on the chart are colored to visually depict the identified micro trend, offering traders an intuitive way to interpret market sentiment and potential entry opportunities.
Benefits of using Micro Trend Candles:
Traders can use these identified micro trends to spot potential short-term trading opportunities. For example:
Trend Following: Traders may decide to enter trades aligned with the prevailing micro trend. If the candles are consistently colored in a certain direction, traders may consider entering positions in that direction.
Reversals: Conversely, if the script signals a potential reversal by changing the candle colors, traders may anticipate trend reversals and adjust their trading strategies accordingly. For instance, they might close existing positions or enter new positions in anticipation of a trend reversal.
It's important to note that these micro trends are short-term in nature and may not always align with broader market trends. Therefore, traders utilizing this script should consider their trading timeframes and adjust their strategies accordingly.
How to use this feature:
This feature assigns colors to candles to represent bullish and bearish trends, with adjustments made based on current market conditions. Green candles accompanied by a green trend cloud signal a potential long entry, while red candles suggest caution, indicating a bearish trend. This visual representation allows traders to interpret market sentiment intuitively, identifying optimal entry points and exercising caution during potential downtrends.
Scalping Candles (Inspired by Elliott Wave):
Working Principle:
This feature draws inspiration from the Elliot Wave method, utilizing technical analysis techniques to discern potential market trends and sentiment shifts. It begins by calculating the variance between two Exponential Moving Averages (EMAs) of closing prices, mimicking Elliot Wave's focus on wave and trend analysis. The shorter-term EMA captures immediate price momentum, while the longer-term EMA reflects broader market trends. A smoother Exponential Moving Average (EMA) line, derived from the difference between these EMAs, aids in identifying short-term trend shifts or momentum reversals.
Benefits of using Scalping Candles Inspired by Elliott Wave:
The Elliott Wave principle is a form of technical analysis that attempts to predict future price movements by identifying patterns in market charts. It suggests that markets move in repetitive waves or cycles, and traders can potentially profit by recognizing these patterns.
While this script does not explicitly analyze Elliot Wave patterns, it is inspired by the principle's emphasis on trend analysis and market sentiment. By calculating and visualizing the difference between EMAs and assigning colors to candles based on this analysis, the script aims to provide traders with insights into potential market sentiment shifts, which can align with the broader philosophy of Elliott Wave analysis.
How to use this feature:
Candlestick colors are assigned based on the relationship between the EMA line and the variance. When the variance is below or equal to the EMA line, candles are colored red, suggesting a bearish sentiment. Conversely, when the variance is above the EMA line, candles are tinted green, indicating a bullish outlook. Though not explicitly analyzing Elliot Wave patterns, the script aligns with its principles of trend analysis and market sentiment interpretation. By offering visual cues on sentiment shifts, it provides traders with insights into potential trading opportunities, echoing Elliot Wave's emphasis on pattern recognition and trend analysis.
Volume Candles:
Working Principle:
This feature introduces a custom volume calculation method tailored for bullish and bearish bars, enabling a granular analysis of volume dynamics specific to different price movements. By summing volumes over specified periods for bullish and bearish bars, traders gain insights into the intensity of buying and selling pressures during these periods, facilitating a deeper understanding of market sentiment. Subsequently, the script computes the net volume, revealing the overall balance between buying and selling pressures. Positive net volume signifies prevailing bullish sentiment, while negative net volume indicates bearish sentiment.
Benefits of Using Volume candles:
Enhanced Volume Analysis: Traders gain a deeper understanding of volume dynamics specific to bullish and bearish price movements, allowing them to assess the intensity of buying and selling pressures with greater precision.
Insight into Market Sentiment: By computing net volume and analyzing its relationship with the Exponential Moving Average (EMA), traders obtain valuable insights into prevailing market sentiment. This helps in identifying potential shifts in sentiment and anticipating market movements.
Visual Representation of Sentiment: The color-coded candle bodies based on volume dynamics provide traders with a visual representation of market sentiment. This intuitive visualization helps in quickly interpreting sentiment shifts and making timely trading decisions.
How to use this feature:
This visual representation allows traders to quickly interpret market sentiment based on volume dynamics. Green candles indicate potential bullish sentiment, while red candles suggest bearish sentiment. The color-coded candle bodies help traders identify shifts in market sentiment and make informed trading decisions.
Smart Sentimeter Candles:
Working Principle:
The "Smart Sentimeter Candles" feature is a tool designed for market sentiment analysis using technical indicators. It begins by defining stock symbols from various sectors, allowing traders to select specific indices for sentiment analysis. The script then calculates the difference between two Exponential Moving Averages (EMAs) of the High-Low midpoint, capturing short-term momentum changes in the market. It computes the difference between current and previous values to capture momentum shifts over time.
Additionally, it calculates the Exponential Moving Average (EMA) of this difference to provide a smoothed representation of the prevailing trend in market momentum. Another EMA of this difference is calculated to offer an alternative perspective on longer-term momentum trends. Bar colors are determined based on the difference between current and previous values, with bullish and bearish sentiment represented by custom colors. Finally, sentiment candles are visualized on the chart, providing traders with a clear representation of market sentiment changes.
Benefits of Using Sentimeter Candles:
By analyzing index constituents, traders gain insights into the individual stocks that collectively influence the index's performance. This understanding is crucial for trading options as it helps traders tailor their strategies to specific sectors or stocks within the index.
Sector-Specific Analysis: Traders can focus on specific sectors by selecting relevant indices for sentiment analysis.
Momentum Identification: The script identifies short-term momentum changes in the market, aiding traders in spotting potential trend reversals or continuations.
Clear Visualization: Sentiment candles visually represent market sentiment changes, making it easier for traders to interpret and act upon sentiment trends.
How to use this feature:
Select Indices: Toggle the inputs to choose which indices (e.g., NIFTY, BANKNIFTY, FINNIFTY) to analyze.
Interpret Sentiment Candles: Monitor the color of sentiment candles on the chart. Green candles indicate bullish sentiment, while red candles suggest bearish sentiment.
Observe Momentum Changes: Pay attention to momentum changes identified by the difference between EMAs and their respective EMAs. Increasing bullish momentum may present buying opportunities, while increasing bearish momentum could signal potential sell-offs.
Trend Cloud:
Working Principle:
The script utilizes the Relative Strength Index (RSI) to assess market momentum, identifying bullish and bearish phases based on RSI readings. It calculates two boolean variables, bullmove and bearmove, which signal shifts in momentum direction by considering changes in the Exponential Moving Average (EMA) of the closing price. When RSI indicates bullish momentum and the closing price's EMA exhibits positive changes, bullmove is triggered, signifying the start of a bullish phase. Conversely, when RSI suggests bearish momentum and the closing price's EMA shows negative changes, bearmove is activated, marking the beginning of a bearish phase. This systematic approach helps in understanding the current trend of the price. The script visually emphasizes these phases on the chart using plot shape markers, providing traders with clear indications of trend shifts.
Benefits of Using Trend Cloud:
Comprehensive Momentum Assessment: The script offers a holistic view of market momentum by incorporating RSI readings and changes in the closing price's EMA, enabling traders to identify both bullish and bearish phases effectively.
Structured Trend Recognition: With the calculation of boolean variables, the script provides a structured approach to recognizing shifts in momentum direction, enhancing traders' ability to interpret market dynamics.
Visual Clarity: Plotshape markers visually highlight the start and end of bullish and bearish phases on the chart, facilitating easy identification of trend shifts and helping traders to stay informed.
Prompt Response: Traders can promptly react to changing market conditions as the script triggers alerts when bullish or bearish phases begin, allowing them to seize potential trading opportunities swiftly.
Informed Decision-Making: By integrating various indicators and visual cues, the script enables traders to make well-informed decisions and adapt their strategies according to prevailing market sentiment, ultimately enhancing their trading performance.
How to use this feature:
The most effective way to maximize the benefits of this feature is to use it in conjunction with other key indicators and visual cues. By combining the color-coded clouds, which indicate bullish and bearish sentiment, with other features such as IS candles, microtrend candles, volume candles, and sentimeter candles, traders can gain a comprehensive understanding of market dynamics. For instance, aligning the color of the clouds with the trend direction indicated by IS candles, microtrend candles, and sentimeter candles can provide confirmation of trend strength or potential reversals.
Furthermore, traders can leverage the trend cloud as a trailing stop-loss tool for long entries, enhancing risk management strategies. By adjusting the stop-loss level based on the color of the cloud, traders can trail their positions to capture potential profits while minimizing losses. For long entries, maintaining the position as long as the cloud remains green can help traders stay aligned with the prevailing bullish sentiment. Conversely, a shift in color from green to red serves as a signal to exit the position, indicating a potential reversal in market sentiment and minimizing potential losses. This integration of the trend cloud as a trailing stop-loss mechanism adds an additional layer of risk management to trading strategies, increasing the likelihood of successful trades while reducing exposure to adverse market movements.
Moreover, the red cloud serves as an indicator of decay in option premiums and potential theta effect, particularly relevant for options traders. When the cloud turns red, it suggests a decline in option prices and an increase in theta decay, highlighting the importance of managing options positions accordingly. Traders may consider adjusting their options strategies, such as rolling positions or closing out contracts, to mitigate the impact of theta decay and preserve capital. By incorporating this insight into options pricing dynamics, traders can make more informed decisions about their options trades.
Scalping Opportunities (UpArrow and DownArrow):
Working Principle:
The feature calculates candlestick values based on the open, high, low, and close prices of each bar. By comparing these derived candlestick values, it determines whether the current candlestick is bullish or bearish. Additionally, it signals when there is a change in the color (bullish or bearish) of the derived candlesticks compared to the previous bar, enabling traders to identify potential shifts in market sentiment. This is a long only strategy, hence the signals are plotted only when the Trend Cloud is Green (Bullish).
Benefits of using UpArrow and DownArrow:
Clear Visualization: By employing color-coded candlesticks, the script offers traders a visually intuitive representation of market sentiment, enabling quick interpretation of prevailing conditions.
Signal Identification: Its capability to detect shifts in market sentiment serves as a valuable tool for identifying potential trading opportunities, facilitating timely decision-making and execution.
Long-Only Strategy: The script selectively plots signals only when the trend cloud is green, aligning with a bullish bias and enabling traders to focus on long positions during favorable market conditions.
Up arrows indicate potential long entry points, complementing the bullish bias of the trend cloud. Conversely, down arrows signify an active pullback in progress, signaling caution and prompting traders to refrain from entering long positions during such periods.
How to use this feature:
Confirmation: Confirm bullish market conditions with the Trend Cloud indicator. Ensure alignment between trend cloud signals, candlestick colors, and arrow indicators for confident trading decisions.
Entry Signals: Look for buy signals within a green trend cloud, indicated by bullish candlestick color changes and up arrows, suggesting potential long entry points aligned with the prevailing bullish sentiment.
Wait Signals: Exercise caution when encountering down arrows, which signify wait signals or active pullbacks in progress. Avoid entering long positions during these periods to avoid potential losses.
Exit Strategy: Use trend cloud color changes as signals to exit long positions. When the trend cloud shifts color, consider closing out long positions to lock in profits or minimize losses.
Profit Management: It's important to book or lock in some profits early on in option buying. Consider taking partial profits when the trade is in your favor and trail the remaining position to maximize gains on favorable trades.
Risk Management: Implement stop-loss orders or trailing stops to manage risk effectively. Exit positions promptly if sentiment shifts or if price movements deviate from the established trend, safeguarding capital.
Up and Down Signals:
Working Principle:
This feature calculates Trailing Stoploss (TSL) using the Average True Range (ATR) to dynamically adjust the stop level based on price movements. It generates buy signals when the price crosses above the trailing stop and sell signals when it crosses below. These signals are plotted on the chart and trigger alerts, signaling potential trading opportunities. Additionally, the script selectively plots Up and Down signals only when the Implementation Shortfall Calculation identifies scalp opportunities, independent of the prevailing price trend.
Benefits of using Up and Down Signals:
Trailing Stoploss: The script employs an ATR-based trailing stop, allowing traders to adjust stop levels dynamically in response to changing market conditions, thereby maximizing profit potential and minimizing losses.
Clear Signal Generation: Buy and sell signals are generated based on price interactions with the trailing stop, providing clear indications of entry and exit points for traders to act upon.
Alert Notifications: The script triggers alerts when buy or sell signals are generated, ensuring traders remain informed of potential trading opportunities even when not actively monitoring the charts.
Scalping Opportunities: By incorporating Implementation Shortfall Calculation, the script identifies scalp opportunities, enabling traders to capitalize on short-term price movements irrespective of the prevailing trend.
How to use this feature:
Signal Interpretation: Interpret Up signals as opportunities to enter long positions when the price crosses above the trailing stop, and Down signals as cues to exit.
Alert Monitoring: Pay attention to alert notifications triggered by the script, indicating potential trading opportunities based on signal generation.
Scalping Strategy: When Up and Down signals are plotted alongside scalp opportunities identified by the Implementation Shortfall Calculation, consider scalping trades aligned with these signals for short-term profit-taking, regardless of the overall market trend.
Consideration of Trend Cloud: Remember that this feature does not account for the underlying trend provided by the Trend Cloud feature. Consequently, the take profit levels generated by the trailing stop may be smaller than those derived from trend-following strategies. It's advisable to supplement this feature with additional trend analysis to optimize profit-taking levels and enhance overall trading performance.
Chart Timeframe Support and Resistance:
Working Principle:
This feature serves to identify and visualize support and resistance levels on the chart, primarily based on the chosen Chart Timeframe (CTF). It allows users to specify parameters such as the number of bars considered on the left and right sides of each pivot point, as well as line width and label color. Moreover, users have the option to enable or disable the display of these levels. By utilizing functions to calculate pivot highs and lows within the specified timeframe, the script determines the highest high and lowest low surrounding each pivot point.
Additionally, it defines functions to create lines and labels for each detected support and resistance level. Notably, this feature incorporates a trading method that emphasizes the concept of resistance turning into support after breakouts, thereby providing valuable insights for traders employing such strategies. These lines are drawn on the chart, with colors indicating whether the level is above or below the current close price, aiding traders in visualizing key levels and making informed trading decisions.
Benefits of Chart Timeframe Support and Resistance:
Identification of Price Levels: Support and resistance levels help traders identify significant price levels where buying (support) and selling (resistance) pressure may intensify. These levels are often formed based on historical price movements and are regarded as areas of interest for traders.
Decision Making: Support and resistance levels assist traders in making informed trading decisions. By observing price reactions near these levels, traders can gauge market sentiment and adjust their strategies accordingly. For example, traders may choose to enter or exit positions, set stop-loss orders, or take profit targets based on price behavior around these levels.
Risk Management: Support and resistance levels aid in risk management by providing reference points for setting stop-loss orders. Traders often place stop-loss orders below support levels for long positions and above resistance levels for short positions to limit potential losses if the market moves against them.
How to use this feature:
Planning Long Positions: When considering long positions, it's advantageous to strategize when the price is in proximity to a support level identified by the script. This suggests a potential area of buying interest where traders may expect a bounce or reversal in price. Additionally, confirm the bullish bias by ensuring that the trend cloud is green, indicating favorable market conditions for long trades.
Waiting for Breakout: If long signals are generated near resistance levels detected by the script, exercise patience and wait for a breakout above the resistance. A breakout above resistance signifies potential strength in the upward momentum and may present a more opportune moment to enter long positions. This approach aligns with trading methodologies that emphasize confirmation of bullish momentum before initiating trades.
Settings:
The Index Constituent Analysis setting empowers users to input the constituents of a specific index, facilitating the analysis of market sentiments based on the performance of these individual components. An index serves as a statistical measure of changes in a portfolio of securities representing a particular market or sector, with constituents representing the individual assets or securities comprising the index.
By providing the constituent list, users gain insights into market sentiments by observing how each constituent performs within the broader index. This analysis aids traders and investors in understanding the underlying dynamics driving the index's movements, identifying trends or anomalies, and making informed decisions regarding their investment strategies.
This setting empowers users to customize their analysis based on specific indexes relevant to their trading or investment objectives, whether tracking a benchmark index, sector-specific index, or custom index. Analyzing constituent performance offers a valuable tool for market assessment and decision-making.
Example: BankNifty Index and Its Constituents
Illustratively, the BankNifty index represents the performance of the banking sector in India and includes major banks and financial institutions listed on the National Stock Exchange of India (NSE). Prominent constituents of the BankNifty index include:
State Bank of India (SBIN)
HDFC Bank
ICICI Bank
Kotak Mahindra Bank
Axis Bank
IndusInd Bank
Punjab National Bank (PNB)
Yes Bank
Federal Bank
IDFC First Bank
By utilizing the Index Constituent Analysis setting and inputting these constituent stocks of the BankNifty index, traders and investors can assess the individual performance of these banking stocks within the broader banking sector index. This analysis enables them to gauge market sentiments, identify trends, and make well-informed decisions regarding their trading or investment strategies in the banking sector.
Example: NAS100 Index and Its Constituents
Similarly, the NAS100 index, known as the NASDAQ-100, tracks the performance of the largest non-financial companies listed on the NASDAQ stock exchange. Prominent constituents of the NAS100 index include technology and consumer discretionary stocks such as:
Apple Inc. (AAPL)
Microsoft Corporation (MSFT)
Amazon.com Inc. (AMZN)
Alphabet Inc. (GOOGL)
Facebook Inc. (FB)
Tesla Inc. (TSLA)
NVIDIA Corporation (NVDA)
PayPal Holdings Inc. (PYPL)
Netflix Inc. (NFLX)
Adobe Inc. (ADBE)
By inputting these constituent stocks of the NAS100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these technology and consumer discretionary stocks within the broader NASDAQ-100 index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the technology and consumer sectors.
Example: FTSE 100 Index and Its Constituents
The FTSE 100 index represents the performance of the 100 largest companies listed on the London Stock Exchange (LSE) by market capitalization. Some notable constituents of the FTSE 100 index include:
HSBC Holdings plc
BP plc
GlaxoSmithKline plc
Unilever plc
Royal Dutch Shell plc
AstraZeneca plc
Diageo plc
Rio Tinto plc
British American Tobacco plc
Reckitt Benckiser Group plc
By inputting these constituent stocks of the FTSE 100 index into the Index Constituent Analysis setting, traders and investors can analyze the individual performance of these diverse companies within the broader UK market index. This analysis facilitates the evaluation of market sentiments, identification of trends, and informed decision-making regarding trading or investment strategies in the UK market.
This comprehensive approach enables users to dissect index performance effectively, providing valuable insights for investors and traders across different markets and sectors.
Index Selection - Index Selection allows traders to specify the index for Sentimeter calculations, enabling customization for Call and Put Option charts corresponding to the chosen index.
Support and Resistance Levels - Set the left and right bars to consider pivot high and low to draw Support and resistance lines. Linewidth setting to help increase the width of the Support and Resistance lines. Label Color to change the color of the labels.
Style Section Colors to allow users to customize the color scheme to their liking.
MTF HalfTrendIntroduction
A half-trend indicator is a technical analysis tool that uses moving averages and price data to find potential trend reversal and entry points in the form of graphical arrows showing market turning points.
The salient features of this indicator are:
- It uses the phenomenon of moving averages.
- It is a momentum indicator.
- It can indicate a trend change.
- It is capable of detecting a bullish or bearish trend reversal.
- It can signal to sell/buy.
- It is a real-time indicator.
Multi-Timeframe Application
A standout feature is its flexibility across timeframes. Traders have the liberty to choose any timeframe on the chart, enhancing the tool's versatility and making it suitable for both short-term and long-term analyses.
Principle of the Half Trend indicator
This indicator is based on the moving averages. The moving average is the average of the fluctuation or change in the price of an asset. These averages are taken for a time interval.
So, a half-trend indicator takes the moving averages phenomenon as its principle for working. The most commonly used moving averages in a half trend indicator are:
- Relative strength index (RSI)
- EMA (estimated moving average)
Components of a Half Trend indicator
There are two main components of a half trend indicator:
- Half trend line
- Arrows
- ATR lines
Half trend line
Half trend line represents this indicator on a candlestick chart. This line shows the trend of a chart in real-time. A half-trend line is based on the moving averages.
There are two further components of a half-trend line:
- Redline
- Blue line
A red line represents a bearish trend. When the half-trend line turns red, a trend is facing a dip. It is time for the bears to take control of the market. A bearish control of the market represents the domination of sellers in the market.
On the other hand, the blue line represents the bullish nature of the market. It tells a trader that the bullish sentiment of the market is prevailing. A bullish market means the number of buyers is significantly greater than the number of sellers.
Moreover, a trader can change these colors to his choice by customization.
Arrows
There are two types of arrows in this indicator which help a trader with the entry and exit points. These arrows are,
- Blue arrow
- Red arrow
A blue arrow signals a buying trade; on the other hand, a red arrow tells a trader about the selling of the assets. These arrows work with the moving average line to formulate a trading strategy.
The color of these arrows is changed if a trader desires so.
ATR lines
The ATR blue and red lines represent the Average True Range of the Half trend line. They may be used as stop loss or take profit levels.
Pros and Cons
Pros
- It is a very easy to eyes indicator.
- This is a very useful friendly indicator.
- It provides sufficient information to beginner traders.
- It provides sufficient information for entry points in a trade.
- A half-trend indicator provides a good exit strategy for a trader.
- It provides information about market reversals.
- It helps a trader to find a bullish and bearish sentiment in the market.
Cons
- It is a real-time indicator. So, it can lag.
- The lagging of this indicator can lead to miss opportunities.
- The most advanced and professional traders may not rely on this indicator for crucial trading decisions.
- The lagging of this indicator can predict false reversals of the market.
- It can create false signals.
- It requires the confluence of the other technical tools for a better success ratio.
Settings for Half Trend indicator
The default settings for half trend indicator are:
Amplitude = 2
Channel deviation = 2
Different markets or financial instruments may require different settings for optimal execution.
Amplitude: The degree that the Half trend line takes the internal variables into consideration. The higher the number, the fewer trades. The default value is 2.
Channel deviation: The ATR value calculation from the Half trend line. The default value is 2.
Trading strategy
It is an effective indicator in terms of strategy formation for a trading setup. The new and beginner trades can take benefit from this indicator for the formulation of a good trading setup. This indicator also helps seasoned and professional traders formulate a good trading setup with other technical tools.
The trading strategy involving a half-trend indicator is divided into three parts:
- Entry and exit
- Risk management
- Take profit
Entry and exit
It is an effective indicator that provides sufficient information about the entry and exit points in a trading setup. The profit of a trader is directly proportional to the appropriate entry and exit points. So, it is a crucial step in any trading setup.
The blue and red arrows provide information about the entry and exit points in a trading setup. Furthermore, the entry and exit for the bullish and bearish setups are as follows.
Entry and exit for a bullish setup
If a blue arrow appears under the half-trend line, it means the bullish sentiment of the market is getting stronger in the future. So, it is a signal for entry in a bullish setup.
As the red arrow appears on the chart, it is a signal to exit your trade. The red arrow represents a reversal in the market, so it is a good opportunity to close your trade in a bullish setup.
Entry and exit for a bearish setup
Suppose a red arrow appears above the red moving average line. It is a good opportunity to enter a trade in a bearish setup. The red line represents that sooner the sellers are going to take control and the value of the asset is about to face a dip. So it is the best time to make your move.
As the opposite arrow appears in the chart, it is time to exit from a bearish trade setup.
Re-entering a position
Bullish setup
- The half-trend line is blue.
- At least one candle closes below the blue half-trend line.
- Enter on the candle that closes above the blue half-trend line.
Bearish setup
- The half-trend line is red.
- At least one candle closes above the red half-trend line.
- Enter on the candle that closes below the red half-trend line.
Risk management
Risk management is an integral part of a trading setup. It is an important step to protect your potential profits and losses.
When trading in a bullish market, place the stop loss at the prior swing low. It will help you to cut your losses in case the prices move to the lower end.
In the case of a bearish market, place your stop loss above the prior swing high.
A trader may trail the stop loss using the ATR lines.
The new trader often makes mistakes in the placement of the stop loss. If you don’t place the stop loss at an appropriate point. It can drain your bank account and ruin your trading experience. Is is recommended not to risk more than 2% of your trading account, per trade.
Take profit
The blue ATR line may be used as one take profit level on a bullish setup followed by the previous swing high. The signal reversal would indicate the final take profit and closing of any position.
The red ATR line may be used as one take profit level on a bearish setup followed by the previous swing low. The signal reversal would indicate the final take profit and closing of any position.
Conclusion
A half trend indicator is a decent indicator that can transform your trading experience. It is a dual indicator that is based on the moving averages as well as helps you to form a trading strategy. If you are a new trader, this indicator can help you to learn and flourish in the trading universe. If you are a seasoned trader, I recommend you use this indicator with other technical analysis tools to enhance your success ratio.
All credits go to:
- @everget the original creator of this indicator (I just added the MTF capability).
- Ali Muhammad original author of much of the description used.
Contrarian DC Strategy - w Entry SL Pause and TrailingStopDonchian Channel Setup:
The strategy uses a tool called the Donchian Channel. Imagine this as two lines (bands) on a chart that show the highest and lowest prices over a certain number of past trading days (default is 20 days).
There's also a centerline, which is the average of these two bands.
Entry Conditions for Trades:
Buying (Going Long): The strategy considers buying when the price touches or falls below the lower band of the Donchian Channel. However, this only happens if there has been a pause after a previous losing trade. This pause is a number of candles where no new trades are taken.
Selling (Going Short): Similarly, the strategy considers selling when price reaches or exceeds the upper band of the Donchian Channel. Again, this is subject to a pause after a losing trade.
Stop Loss and Take Profit:
Each trade has a "Stop Loss" and "Take Profit" set. The Stop Loss is a preset price level where the trade will close to prevent further losses if the market moves against your position. The Take Profit does the same but locks in profit if the market moves in your favor.
The Stop Loss is set based on a percentage of the price at which you entered the trade.
The Take Profit is determined by the Risk/Reward Ratio. This ratio helps balance how much you're willing to risk versus the potential reward.
Trailing Stop Loss:
When a trade is profitable, the strategy should involve a "Trailing Stop Loss." This means the Stop Loss level moves (or trails) the price movement to lock in profits as the market moves in your favor.
For a buy trade, if the price moves above the centerline of the Donchian Channel, the Trailing Stop Loss should be adjusted in the middle between the entry price and the centerline. Viceversa for a sell trade, it should be adjusted in the same way if the price goes below the centerline.
IMPORTANT: There's no allert for the trailing stop at the moment.
Post-Stop Loss Pause:
If a trade hits the Stop Loss (i.e., it's a losing trade), the strategy takes a break before opening another trade in the same direction. This pause helps to avoid entering another trade immediately in a potentially unfavorable market.
In summary, this strategy is designed to make trades based on the Donchian Channel, with specific rules for when to enter and exit trades, and mechanisms to manage risk and protect profits. It's contrarian because it tends to buy when the price is low and sell when the price is high, which is opposite to what many traders might do.
Dynamic Trend Hunter [Quantigenics]The "Dynamic Trend Hunter” script focuses on trend identification, dynamic entry and exit signals, and effective risk management. While a standalone trading script designed for versatile application across all markets, it can also be complemented by other indicators for enhanced analysis.
Core Features:
Dynamic Trend Indicator: Central to the script, this indicator discerns market trend direction using a color-coded system. Blue indicates an uptrend, red a downtrend, and a flat line signifies a sideways market.
Buy and Sell Signals: Provides clear, on-chart buy and sell signals to assist in identifying optimal entry points in alignment with the trend.
Profit Target Exits: A key feature designed to help traders lock in profits at strategic points. This feature uses a sophisticated mechanism (outlined in more detail below) to identify potential exit points, signaling the trader to close a position and secure gains before a potential market reversal.
Dynamic Stop Loss Levels: Essential for risk management, these levels adjust automatically, providing a mechanism for trailing stop losses and safeguarding against adverse market movements.
Technical Composition:
Dynamic Trend Indicator:
Calculation Method: Utilizes a blend of the highest and lowest prices over a specified length, averaged to create a trend line. This line is helpful in identifying the overall market trend.
Color Coding: The trend line changes color based on its relation to price action. A blue line indicates an uptrend when prices are consistently above this average line, while a red line signifies a downtrend when prices stay below it.
Signal-Based Trading:
Trend Entry Signals: Generated when there's a shift in the color of the trend line, indicating a potential change in market direction.
Pullback Entries: Identified when the closing price crosses the previous high (for long entries) or low (for short entries), while also considering the current trend line position.
Dynamic Stop Loss Levels:
Calculation: Stop loss levels are dynamically determined using the highest and lowest closing prices over the 'Length' period. These levels adjust with market movements, providing a trailing stop loss mechanism.
Visualization: Depicted as colored dots on the chart, changing in response to the market's movement relative to the trend line.
Oscillator for Dynamic Exits:
Mechanism: The script employs an oscillator to identify potential exit points, signaled by yellow dots. This oscillator is based on the relative extremity of the current price action compared to recent price movements.
Alerts: Dynamic exits trigger alerts when the oscillator reaches specified threshold levels, signaling potential market reversals or exhaustion points.
Customization and Flexibility:
Length Adjustment: The primary 'Length' input parameter allows traders to modify the sensitivity of the trend line and stop levels, catering to different trading styles and market conditions.
Alert Customization: Traders can set alerts for trend line changes and dynamic exits, ensuring timely responses to market movements.
Input Parameter Settings:
Intra-Bar Order Generation (IntraBar): Enables real-time signal generation within the current bar or after its closure.
Dynamic Exits (DynamicExits): Toggles the visibility of dynamic exit signals for profit-taking.
Dynamic Trend Length: Defines the lookback period for calculating the trend line. This length, which is adjustable and set by default to 21, specifies the number of bars over which the highest and lowest prices are analyzed to determine the trend line.
Dynamic Stop Loss Levels Length: This parameter defines the lookback period for calculating stop loss levels. It sets the number of bars used to determine the highest and lowest values for stop loss positioning. Adjusting this length allows traders to customize the sensitivity and placement of stop loss levels in accordance with their trading strategy and risk tolerance. This feature is crucial for tailoring stop loss settings to different market conditions and volatility levels, ensuring more effective risk management. Note: that initial stop loss levels, and tighter stop losses, can be set behind the Dynamic Trend Line itself.
Show Trend/Pullback Entries: Controls the display of specific entry signals based on trend continuation or market pullbacks.
Alert Settings: Options for setting alerts on trend line changes and dynamic exits, enhancing trade management.
Customizable Colors: Allows personalization of stop level and trend line colors for better chart visualization.
How to Trade with the Dynamic Trend Hunter:
Trend Following: Enter trades in the direction of the trend indicated by the color-coded trend line.
Pullback Entries: Look for pullback entry signals during established trends for additional entry points.
Dynamic Exits: Use yellow dot signals and dynamic stop loss levels for determining exit points or to adjust stop losses.
Risk Management: Employ the dynamic stop loss levels to manage risk effectively and protect against significant losses.
Alerts and Notifications:
Traders can set up alerts for trend line changes and dynamic exits, ensuring they are promptly informed about critical market movements and can react accordingly.
Conclusion:
The "Dynamic Trend Hunter " is a comprehensive and adaptable trading tool, suitable for various market conditions and trading styles. Its ability to provide clear trend indications, along with dynamic entry and exit signals, makes it an invaluable asset for traders aiming to enhance their market analysis and decision-making process. While it is a standalone system, it can be used in conjunction with other indicators to further refine trading strategies.
While we believe this tool may enhances your trading strategy, we encourage thorough familiarization before live trading. Remember, trading involves risk, and past performance is not indicative of future results.
You can see the “Author’s instructions" below to get immediate access to Dynamic Trend Hunter & the rest of the “Quantigenics Premium Indicator Suite”.
