Price and OI ChangePrice and OI Change
Description:
The "Price and OI Change" indicator provides insights into market dynamics by analyzing the price and open interest (OI) changes over a 7-day period. This indicator is designed for use with both spot and futures markets, including cryptocurrencies.
Key Features:
Price and OI Change Calculation: Computes the 7-day change in price and open interest to help identify market trends and shifts.
Market Conditions Visualization: Differentiates market conditions by changing the background color based on:
Leverage-Driven Market: Blue background indicates increasing prices and OI, suggesting a bullish trend driven by leverage.
Spot-Driven Market: Green background shows increasing prices but decreasing OI, indicating a bullish trend driven by spot market activity.
Leverage Sell-Off: Orange background reveals decreasing prices with increasing OI, signaling a potential liquidation phase.
Deleveraging Sell-Off: Red background reflects decreasing prices and OI, indicating a bearish market with reduced leverage.
Top 3 BTC Futures Average OI: Displays the average open interest for the top 3 BTC futures contracts from major exchanges (Binance, OKX, Bybit). This helps gauge overall market sentiment and liquidity.
Visualization Tools: Includes optional plotting of open interest data and average OI for better visualization of market conditions.
Usage:
Traders and Analysts: Use the background color changes and average OI to make informed decisions about market entry and exit points.
Futures Traders: Track OI changes in major BTC futures to assess market strength and potential liquidity issues.
Tìm kiếm tập lệnh với "liquidity"
Relative Equal Highs/LowsThis Pine script indicator is designed to create a visual representation of the relative equal highs & lows formed and automatically removed mitigated ones. Unlike indicators designed to show exact equal high/lows this indicator allows a small, configurable degree of variance between price to identify areas where price stops.
Relevance:
Relative Equal highs and lows can serve as valuable tools in identifying potential shifts in trend direction. They come into play when the price hits a support or resistance level and can’t advance further, signaling a possible reversal or pivot point. When the price sufficiently retreats from these levels, relative equal highs and lows can also indicate liquidity draws where buy/sell stops might be positioned, in accordance with SMC/ICT concepts.
How It Works:
The indicator tracks all unmitigated highs & lows within the chart’s present timeframe, limited to the user-defined max bars lookback for optimal performance. If the prices are within the configured variance they are marked as relatively equal and at that point are visually identified by a horizontal line, which connects the two (or more) points of price. Depending on configuration of the indicator, a line is rendered from the 1st, last or both values within the relatively equal range of price. A unique feature of this indicator is its ability to remove the line once the price mitigates the relative equal high/low by falling below the lows or rising above highs. This ensures the chart remains uncluttered and highlights only the currently relevant levels, setting it apart from other indicators providing similar functionality.
Configurability:
The indicator offers five style settings for complete customization of the lines that represent equal highs/lows. These settings include line style, color, and width, along with an option to extend the lines to the right of the chart for enhanced visibility of equal high/low levels. To optimize performance, the indicator allows users to configure the lookback length, determining how far back the price history should be examined. In most instances, the default setting of 500 bars proves more than adequate. Additionally, you can set thresholds via separate configs for stocks & indices that will determine if the price is relatively equal and lastly allow you to configure where the indicator line should be drawn, the first, last or all the values.
Additional notes:
This uses a different approach then my “equal highs/lows” indicator to identify price levels and because it focuses specifically on relative as opposed to exact values it is entirely different and may show “weaker”, but still important levels of liquidity. This indicator is more suited for analysis of stocks and indices or higher-timeframes where price-action rarely forms exact equal values instead more frequently forming almost equal values. My other indicator is more suited for smaller (15m or less) timeframe on indices where exact equal prices are often identical. Depending on situation different indicators should be used.
Open Intrest / Volume / Liquidations (Suite) [BigBeluga]This indicator is a suite of tools that aims to provide traders with efficient metrics to analyze the market in a different way, such as various types of Open Interest, Intraday Volume, and Liquidations.
This indicator can both save time and also provide a different approach to the usual price action trading style.
🔶 FEATURES
The indicator contains the following features:
Open Interest Suite
- Delta OI
- Net longs and shorts
- OI Relative Strength Index
Intraday Volume Suite
- Bullish and Bearish LTF Volume
- CVD
- Delta Volume
Liquidations Suite
- Long and Short Liquidations
- Cumulative Liquidations
🔶 EXAMPLE OF SUITE
In the example above, we can see how we can plot long and short positions, both opening and closing out.
This can give a unique way to view which side is the strongest but also which side has the most resting liquidity.
For example, if more longs are entering the market, it also means more liquidity for longs and vice versa.
Or, for example, plotting the delta OI will allow the user to see big percentages in change and spot big areas of position closing out.
This presents a fascinating method for observing numerous positions closing out in conjunction with a surge of liquidations, which could indicate a potential reversal in price.
Here, we can see a basic example of using intraday volume on a 1m LTF.
With this, we are able to see both bullish and bearish volume of the same candle, very useful to see both volumes traded in the same candle.
Using the CVD to see the overall direction based purely on the volume and spot divergence, for example, the price in an uptrend but CVD going down, indicating weak shorts in the market or trapped shorts.
Or simply view liquidations happening in the market in a very different way, both long and short liquidation at the same time + the option to use multi-timeframe liquidations.
🔶 CONCLUSION
The idea of this script is to provide a set of tools in a unique script to optimize time and analyze the market in both a quick way and in a different way than usual.
Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Temporary imbalances 2.0 This indicator attempts to calculate potential points of imbalance and equilibrium based on VWAPs and modified moving averages. The idea is to determine if there has been a change in volume and perform the calculation from that point It uses the standard deviation to determine the significant imbalance threshold. Candles with bullish imbalances are highlighted in green, while candles with bearish imbalances are highlighted in red.
"It also features a set of VWAPs and modified moving averages that you can enable or disable."
When you activate the 'Show Anchor VWAP' option, it will add five modified VWAPs.
Practical Significance:
The Anchored VWAP is a volume-weighted average price that serves as a dynamic reference to assess the average price during specific moments of market imbalance.
During a bullish imbalance, the anchor_vwap reflects the VWAP at that moment, emphasizing price behavior during that specific period.
Similarly, in a bearish imbalance, the anchor_vwap provides the associated VWAP for that condition, highlighting price movements during the imbalance phase.
How to Use:
The anchor_vwap can be employed to contextualize the volume-weighted average price during critical moments associated with significant changes in market imbalance.
By analyzing price behavior during and after periods of imbalance, the Anchored VWAP can help better understand market dynamics and identify potential areas of support or resistance.
Show VWAP Percent Imbalance"
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The "showDeltaVWAP" is a toggleable setting that you can turn on or off. When activated, it displays special lines on the chart. Let's understand what these lines represent:
Delta Anchor VWAP:
A green line (Delta Anchor VWAP) represents a measure of market volume imbalance.
Delta2 Anchor VWAP:
A red line (Delta2 Anchor VWAP) shows another perspective of volume imbalance.
VWAP Delta Volume:
A light blue line (VWAP Delta Volume) displays a volume-weighted average of price.
VWAP Delta Volume2:
An orange line (VWAP Delta Volume2) shows another view of the volume-weighted average of price.
Delta3 Anchor VWAP:
A light blue line (Delta3 Anchor VWAP) represents a combination of the previous measures.
Delta4 Anchor VWAP:
A purple line (Delta4 Anchor VWAP) is another combination, providing an overall view.
These lines are based on different conditions and calculations related to trading volume. When you activate "showDeltaVWAP," these lines appear on the chart, aiding in better understanding market behavior.
"Show Faster Volatility" is an option that you can enable or disable. When activated (set to true), it displays special lines on the chart called "Faster Volatility VWAP," "Faster Volatility VWAP2," and "Faster Volatility VWAP3." Let's understand what these lines represent:
Faster Volatility VWAP:
A purple line (Faster Volatility VWAP) is a Volume Weighted Average Price (VWAP) that is calculated more quickly based on short-term price reversal patterns.
Faster Volatility VWAP2:
A light gray line (Faster Volatility VWAP2) is another Volume Weighted Average Price (VWAP) that is calculated even more quickly based on even shorter-term price reversal patterns.
Faster Volatility VWAP3:
A purple line (Faster Volatility VWAP3) is another Volume Weighted Average Price (VWAP) calculated rapidly based on even shorter-term price reversal patterns.
These lines are designed to indicate moments of possible exhaustion of volatility in the market, suggesting that there may be a subsequent increase in volatility. When you activate "Show Faster Volatility," these lines are displayed on the chart.
"Show Average VWAPs Imbalance" displays weighted averages of different Volume Weighted Average Prices (VWAPs) in relation to specific market conditions. Here's an explanation of each component:
Standard VWAP:
The blue line represents the standard VWAP, a volume-weighted average of asset prices over a specific period.
VWAP with Added Imbalance (avg_vwap2):
The pink line is a weighted average that adds an imbalance value to the standard VWAP. This component highlights periods of market imbalance.
VWAP with Balance (avg_vwap3):
The lilac line is a weighted average that adds balance based on the imbalance between uptrend and downtrend, reflecting changes in volume. This provides insights into supply and demand dynamics.
Overall Average of VWAPs (avg_vwaptl):
The violet line is a weighted average that incorporates both standard and adjusted VWAPs, offering an overview of market behavior under different considered conditions.
Visual Customization (Show Average VWAPs Imbalance):
Users have the option to show or hide these average lines on the chart, allowing for a clear visualization of market trends.
"Show Min Variation VWAP" is associated with the calculation and display of a smoothed version of the Volume Weighted Average Price (VWAP), taking into account the minimum price variation over a specific period.
"How Imbalance Anchor VWAP Calculated as the smoothed relationship between liquidity difference and maximum VWAP equilibrium" is associated with the calculation and display of a smoothed version of the Imbalance Anchor VWAP. Here is a detailed explanation:
Calculations and Smoothing:
The variable "smoothed_difference" represents the exponential moving average (EMA) of the difference between two variables related to liquidity.
"smoothed_difference2" is the division of "smoothed_difference" by the maximum variation of the VWAP Equilibrium.
"smoothed_difference3" involves additional manipulation of "smoothed_difference" and "vwap_delta3."
"smoothed_difference4" incorporates the previous results, adjusted by the value of the VWAP.
Visual Customization:
The user has the option to enable or disable the display on the chart.
The line is colored in a shade of green.
It provides a smoothed representation of the Imbalance Anchor VWAP.
The line is colored in a shade of blue, and the calculation involves the summation of moving averages (20, 50, 200). Afterward, there is division by 3. Additionally, there is the summation of moving averages (766, 866, 966), divided by 3. The final step is to add these results together and divide by 2. media name is Imbalance Value2
Show VWAP Equilibrium (Max Variation) Calculated as the difference between two VWAPs derived from the highest and lowest price changes
Show Equilibrium VWAP Calculated as the sum of VWAP and (sma200 - sma20)
calculate the difference between the media of 200 to 20
Show Equilibrium VWAP Calculated as the sum of VWAP and (766+866+966)/3 - (sma200 - sma20)
Show Equilibrium VWAP Standard Deviation Calculated as the Exponential Moving Average (EMA) of the Standard Deviation of SMA (sma200 + sma20 + sma8)/3
Show Equilibrium VWAP Delta Calculated as the ratio of the smoothed VWAP Delta Result componentes
Show Standard Deviation Equilibrium VWAP Delta: Calculated as the Standard Deviation between the Average of VWAP Delta Result Components and Their Smoothed Versions
This average attempts to calculate the equilibrium."
vwap_equilibrium:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price (hl2) multiplied by volume, focusing on periods of volume equilibrium.
Calculation: Utilizes the simple moving average weighted (sma) of the product of the volume-weighted average price and volume only when there is no volume imbalance.
Interpretation: This indicator provides a view of the volume-weighted price trend during moments when the market is in equilibrium, meaning there is no noticeable imbalance in volume conditions. The calculation of VWAP is adjusted to reflect market characteristics during periods of stability.
vwap_percent_condition:
Definition: Represents the Volume Weighted Average Price (VWAP) adjusted by the volume-weighted average of the price multiplied by volume, with a focus on conditions where the percentage volume variation surpasses a predefined threshold.
Calculation: Utilizes the simple moving average weighted of the product of the volume-weighted average price and volume only when the percentage volume variation exceeds a specific threshold.
Interpretation: Provides insight into the volume-weighted price trend during conditions where the percentage volume variation exceeds a predefined limit.
The objective of these two VWAPs is to calculate possible equilibrium points between buyers and sellers.
The indicator works for all timeframes This indicator can be adjusted according to the preferences and characteristics of the specific asset or market. It provides clear visual information and can be used as a complementary tool for technical analysis in trading strategies.
Interesting
Interesting
lookback period 7 , 12, 20,70,200, 500,766,866,966
imbalance threshold 2.4, 3.3 ,4.2
The objective of this indicator is to identify and highlight various points of imbalance and equilibrium.
Price & Volume Profile (Expo)█ Overview
The Price & Volume Profile provides a holistic perspective on market dynamics by simultaneously tracking price action and trading volume across a range of price levels. So it is not only a volume-based indicator but also a price-based one. In addition to illustrating volume distribution, it quantifies how frequently the price has fallen within a particular range, thus offering a holistic perspective on market dynamics.
This unique and comprehensive approach to market analysis by considering both price action and trading volume, two crucial dimensions of market activity. Its distinctive methodology offers several advantages:
Holistic Market View: By simultaneously tracking the frequency of specific price ranges (Price Profile) and the volume traded at those ranges (Volume Profile), this indicator provides a more complete picture of market behavior. It shows not only where the market is trading but also how much it's trading, reflecting both price acceptance levels and market participation intensity.
Point of Control (POC): The POC, as highlighted by this indicator, serves as a significant reference point for traders. It identifies the price level with the highest trading activity, thus indicating a strong consensus among market participants about the asset's fair value. Observing how price interacts with the POC can offer valuable insights into market sentiment and potential trend reversals.
Support and Resistance Levels: Price levels with high trading activity often act as support or resistance in future price movements. The indicator visually represents these levels, enabling traders to anticipate potential price reactions.
Price Profile
Price and Volume Profile
█ Calculations
The algorithm analyzes both trade frequency and volume across different price levels. It identifies these levels within the visible chart range, then examines each bar to determine if the selected price falls within these levels. If so, it increases a counter and adds the trading volume. This process repeats across the visible range and is visualized as a horizontal histogram, each bar representing a price level and the bar length reflecting trade frequency and volume. Additionally, it calculates the Point of Control (POC), signifying the price level with the highest activity.
In summary: The histogram presents a dual perspective - not only the traded volume at each price level but also the frequency of the price hitting each range. The longer the bar, the more times the price has frequented that specific range, revealing key insights into price behavior and acceptance levels. These frequently visited areas often emerge as strong support or resistance zones, helping traders navigate market movements.
Please note that the indicator adjusts to the visible price range, making it adaptable to changing market conditions. This dynamic analysis can provide more relevant and timely information than static indicators.
█ How to use
This indicator is beneficial for traders as it offers insights into the distribution of trading activity across different price levels. It helps identify key areas of support and resistance and gives a visual representation of market sentiment and liquidity.
The point of control (POC) , which is the price level with the highest traded volume or frequency count, becomes even more crucial in this context. It marks the price at which the most trading activity occurred, signaling a strong consensus among market participants about the asset's fair value. If the market price deviates significantly from the POC, it could suggest an overbought or oversold condition, potentially leading to a price reversion.
Fair Price Areas/gaps are specific price levels or zones where an asset has spent limited time in the past. These areas are considered interesting or significant because they may have an impact on future price action.
Similar to the concept of fair value gaps, which refers to discrepancies between an asset's market price and its estimated intrinsic value, Fair Price Areas/gaps focus on price levels that have been relatively underutilized in terms of trading activity. When an asset's price reaches a Fair Price Area/gap, traders and investors pay attention because they expect the price to react in some way. The rationale behind this concept is that price tends to gravitate towards areas where it has spent less time in the past, as the market perceives them as significant levels.
█ Settings
The indicator is customizable, allowing users to define the number of price levels (rows), the offset, the data source, and whether to display volume or frequency count. It also adjusts dynamically to the visible price range on the chart, ensuring that the analysis remains relevant and timely with changing market conditions.
Source: The price to use for the calculation. Typically, this is the closing price. By considering the user-selected Source (typically the closing price), the indicator determines the frequency with which the price lands within each designated price level (row) over the selected period. In essence, the indicator provides a count of bars where the Source price falls within each range, essentially creating a "Price Profile."
Row Size: The number of price levels (rows) to divide the visible price range into.
Display: Choose whether to display the number of bars ("Counter") or the total volume ("Volume") for each price level.
Offset: The distance of the histogram from the price chart.
Point of Control (POC): If enabled, the indicator will highlight the price level with the most activity.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Powertrend - Volume Range Filter Strategy [wbburgin]The Powertrend is a range filter that is based off of volume, instead of price. This helps the range filter capture trends more accurately than a price-based range filter, because the range filter will update itself from changes in volume instead of changes in price. In certain scenarios this means that the Powertrend will be more profitable than a normal range filter.
Essentials of the Strategy
This is a breakout strategy which works best on trending assets with high volume and liquidity. It should be used on middle to higher timeframes and can be used on all assets that have volume provided by the data source (stocks, crypto, forex). It is long-only as of now. It can work on lower timeframes if you optimize the strategy filters to make less trades or if your exchange/broker is low/no fees, provided that your exchange/broker has high liquidity and volume.
The strategy enters a long position if the range filter is trending upwards and the price crosses over the upper range band, which signifies a price-volume breakout. The strategy closes the long position if the range filter is trending downwards and the price crosses under the lower range band, which signifies a breakdown. Both these conditions can be altered by the three filter options in the settings. The default trend filter is not alterable because it helps prevent false entries and exits that are against the trend.
Settings
The Length setting is the lookback period for the range smoothing.
The ADX Filter setting enables you to turn on an ADX filter, which will halt entries and exits unless the ADX of your customizable length is above a ADX VWMA of that length.
The Range Supertrend setting creates a supertrend from the top and bottom ranges, which can be used to filter entries and exits. The length is customizable. The filter can show you whether the range is making higher highs and lower lows. Below is an example of the Range Supertrend being used as a filter and plotted on-chart:
The VWMA setting halts entries if they are below a customizable length VWMA.
Both the Range Supertrend and the VWMA can also be plotted separately without actually filtering the strategy, so that you can use them independently if you wish. You can turn off the bar color, the highlighting, and the labels if you wish in the settings. A note about the bar color: if the color changes but the strategy does not signal an exit or entry this means that the crossover was against the trend. In these circumstances it may be indicative of a pullback to enter or exit or to add onto your position.
About the Strategy Results Below
A range filter is normally composed of two components - the range filter itself and a smoothing function. In the development of this script I tested both normal and volume-based varieties of the range filter and the smoothing function:
Tests Performed
Volume-based Range x VWMA smoothing
Price-based Range x VWMA smoothing
Price-based Range x EMA smoothing
Volume-based Range x EMA smoothing (final result)
The highest-performing was a volume-based range filter and a normal EMA-based smoothing function, but that does not mean that this strategy will be profitable - exits are based off of signal reversion so I strongly encourage you to develop your own take profits/stop losses for the strategy if you think it may be a good fit for you. The results below are with a commission value of 0.05% (because I built the strategy first for equities), slippage of 3, so if your exchange/broker has a higher fee schedule, I recommend adding filters and/or moving to higher timeframes for the strategy. Additionally, I used 10% of equity in each trade, while using the Range Supertrend filter (the previous upload was unrealistic because it used 100% of equity - missed a 0, apologies, and added in slippage).
OverNightSession @joshuuuThis indicator highlights the Overnightsession (ONS), taught by TheCurrenyMerchant.
The Overnightsession is from 4-8 am UTC-5. This session can be used to form trades, e.g. after one side has been taken out.
It has the options to display Projection and the equilibrium level. Equilibrium level (50%) can be used to identify if price is currently in premium/discount of the range and the projections (standard deviations of the range) can be used to identify possible targets.
A classic setup he teaches is:
Price trades agressively out of the range taking liquidity. As soon as we trade above the high of the candle that took liquidity, that candle can be considered an orderblock, where the 50% level can be used for long setups.
⚠️ Open Source ⚠️
Coders and TV users are authorized to copy this code base, but a paid distribution is prohibited. A mention to the original author is expected, and appreciated.
⚠️ Terms and Conditions ⚠️
This financial tool is for educational purposes only and not financial advice. Users assume responsibility for decisions made based on the tool's information. Past performance doesn't guarantee future results. By using this tool, users agree to these terms.
Volume composition / quantifytools— Overview
While net volume is useful information, it can be a blunt data point. Volume composition breaks down the content of volume, allowing a more detailed look inside each volume node. Volume composition consists of the following information:
Total volume (buy and sell). By default gray node.
Dominating volume (buy or sell). By default dark green/dark red node.
Dominating active volume (buy or sell). By default light green/light red node.
Dominating volume as percentage of total volume.
Dominating active volume as percentage of total active volume.
Buy and sell volume is defined by volume associated with lower timeframe up/down moves. This classification is further broken down to passive/active, standing for decreasing/increasing volume, e.g. a move up with volume higher than previous bar volume = active buy volume, a move up with volume lower than previous bar volume = passive buy volume.
Volume data is fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied:
Charts <= 30 min: 1 minute timeframe
Charts > 30 min & <= 3 hours : 5 minute timeframe
Charts > 3 hours & <= 8 hours : 15 minute timeframe
Charts > 8 hours & <= 1D: 1 hour timeframe
Charts > 1D & <= 3D : 2 hour timeframe
Charts > 3D: 4 hour timeframe
Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining buy/sell volume, e.g. using close as source, a close that is higher than previous close would be considered as buy volume. This could be replaced with OHLC4 for example, resulting in a volume direction based on OHLC average.
Volume composition of current chart can also be replaced with any other chart volume composition:
— Visuals
Breakdown of visual elements:
1. Symbol and timeframe used for volume composition calculations. By default the chart that is viewed and automatically selected lower timeframe.
2. Dominating volume threshold exceeded. Can be defined via input menu, 70% of total volume by default.
3. Dominating volume as percentage of total volume. Plotted below volume nodes, without % symbol.
4. Dominating active volume, + or - symbol, standing for buy and sell. Plotted below dominating volume percentage. When dominating volume and dominating active volume sides are in a disagreement (e.g. dominating volume is on buy side while dominating active volume is on sell side) this symbol will appear inside brackets, (+) or (-).
5. Dominating active volume as percentage of total active volume. Plotted below +/- symbol.
6. Dominating active volume threshold exceeded. Can be defined via input menu, 70% by default.
Dominating volume & active volume percentages can be rounded to single numbers to avoid clutter caused by overlapping values. The percentage values will be rounded to closest single number value, e.g. dominating volume percentage at 54% = 5, dominating volume percentage at 55% = 6.
Volume anomalies can be highlighted on the chart with a color for studying the events and their past implications in greater detail. Available anomalies for highlights are the following:
Buy volume threshold exceeded
Sell volume threshold exceeded
Active buy volume threshold exceeded
Active sell volume threshold exceeded
Volume & active volume divergence
— Practical guide
Volume is arguably one of the most important data points as it directly relates to liquidity. High volume can be an indication of strength (price likely to continue moving) or absorption (price likely to halt/turn). Same applies to active volume, but with an element of aggression. High active volume serves as an indication of exuberance or otherwise forceful transacting, like stop losses triggering. With these principles in mind, the composition of volume allows distinguishing potentially important events.
Example #1 : Identifying areas of trapped market participants
Often when volume spikes distinctively, we can make the case that price has found sufficient liquidity to halt/turn. Since we know which side was absorbed, in what quantity and type (passive/active), we can identify areas of trapped market participants. In such scenarios, the higher the dominant active volume and volume spike itself, the better.
Example #2 : Identifying a healthy trend
A healthy trend is one that has an active and consistent bid driving it. When this is the case, it can be seen in consistently supportive active volume.
Example #3 : Identifying inflection points
When dominant side of volume and dominant side of active volume diverge, something is up. A divergence often marks an area of indecision, hinting an imminent move one way or the other.
Vol in FiatThis indicator is modified from veryevilone's BTC Volume in Fiat. Modified color and style, and bumped Pine language Version.
It shows volume in fiat, AKA dollar volume . If a trade pair is not traded in fiat, e.g. AAA-BBB , then it shows how much volume the BBB is involved.
Good for comparing liquidity between different pairs. Also good for pairs with big price fluctuation to determine actual liquidity.
Futures Exchange SessionsIn the 24-hour trading of the futures market, this indicator provides the user with full customization concerning the most important factor: time. This indicator is centered around three main visualizations: labels, backgrounds, and lines that minimalistically allows the user to keep track of the many time intervals that occur during a futures market 24-hour trading cycle. It also artfully displays the previous days highs and lows. And everything can be individually toggled and configured so the user can get exactly what they want.
Labels
There are three main futures market sessions in a 24-hour period: the London, New York, and Asian Sessions. Each session is given an independent label for the open and close times. The six labels (LO, LC, NYO, NYC, AO, AC) can be individually toggled on or off, the label background color changed, the text switched between black or white, and the height can be lowered or raised. These customizations are intended to give the user full control of the session they are interested in at the moment.
Backgrounds
Backgrounds are the heart of this indicator. There are different colored transparent backgrounds for each of the futures sessions. So the user can clearly see the session they want to highlight without cluttering their chart and getting in the way of analyzing the candles.
If you are familiar with the London and New York killzones, these backgrounds are each individually configured.
If you are familiar with the Inner Circle Trader’s (ICT) NY Morning and Afternoon sessions, these are available. Also, most times weird price action occurs during the lunch hour of these sessions. The London and New York have a background for their respective lunch hours so the user is never caught of guard during these periods.
Lines
The markets are constantly looking for liquidity. To help the user see runs on liquidity, this indicator projects the previous days highs and lows on to the current day with a line and a price label. The line make it very easy to see where price may be headed. See the image below for the perfect example of this phenomenon. Each of the lines can be independently controlled by color, style, and width. And even the labels can be toggled on or off if the user would prefer just to see the lines. Lastly, there is a line that marks the midnight open price in EST.
Special Notes
This indicator is specifically designed for futures tickers.
All of the backgrounds are not designed to be turned on a once (there are many that overlap). They are designed to give the user ultimate control over exactly what timeframe backgrounds to display on their charts.
The labels only appear when timeframe is 1 hour or less.
USDT/USD PremiumKraken + FTX USDT premium indicator.
Inspired by John J Brown, forked from IAmSatoshi (Migrated to V5 and few changes + more markets coming).
John J Brown: "
USDt premium/discount exist because of conversion fees.
It is a good market indicator:
If USDt>USD, then market is growing and in need of liquidity;
If USDt
40+ Coin Screener (workaround to 40 Security Limit Per Script) This is a far inferior method for a screener/scanner (compared to my first publication) but after looking at that script from a noobs eyes again, I could see how this form would be a lot easier to take in/understand so wanted to publish it. Everything that I could think of to mention about this is in my 1st pub so ill leave it to you to check it out...though I did include some comments in the script. It is pretty straight forward but if you have any questions don't hold them in. I'll answer them if I can. The only thing that is not in this one is setting up the alert feature so that you only have to create 1 alert per iteration of the script and it takes care of all of the coins for that iteration/set that is chosen in the settings (so please see previous script if would like to do this for your screener/scanner).
To be PERFECTLY CLEAR, the workaround is to the issue of not being able to scan but only 40 coins per script. You can scan more than 40 per script but only if you create "batches" or "sets" that the user can select within the settings which set to use for each iteration of the script on the chart. That being, you have to the script multiple times to the chart and merge them into 1 window and merge the scales (instructions in first publications). Here in this script I am scanning 72 different coins that are the Margin Coins on KUCOIN. I have split them up into 3 sets (24 coins per set). I could have made 2 sets but the script will be slower to load and to respond (like, when it comes to receiving alerts), thus I split them up the way I did. If you want to change any of this there are slightly more details in the previous script.
One great use-case that I LOVE about this particular version (and the way I use it) is right at the end of when I see a whole market dump/pump coming to an end and want to know which horse to bet on. Used to think whichever coin come out the fastest from the dump was the one to bet on but quickly learned that 1-2 (or even a few) hrs needs to go by first bc the ones that look the strongest in the beginning are NOT the ones to have performed the best when viewing the results 12 hrs later. IN FACT, many instances of using this exact script for reasons as such has taught me that the manipulators (I believe this to be the case as least) WANT everyone to bet on these that come out the gate the hardest and thus they make them move REALLY hard in the beginning then they QUICKLY become stagnant (moreso, they become WORSE than stagnant, they actually quickly retrace to put you into the negative so that you get out to get into the others now moving (to provide the market with more liquidity. They WANT you to get into a coin thats moving crazy hard so that they can then cease that movement once many fall for the trick just to then make that once strong looking coin now stagnant and make others move crazy hard. They wait for you to get out of the 1st and into the next set of movers just to do this time and time again bc hey, what are we sheep good for other than to provide the big guns with liquidity, am I right? Thats rhetorical, which you would know if you've ever had this happen to you (without a doubt MANY of you have). Let this script (above all other things) provide good evidence to back up this cynical way of viewing the markets to anyone that is questioning it.
This prolonged time between when the dump is over and when the ACTUAL movers REALLY start moving can actually be of great benefit to us sheep if used correctly, Firstly, it gives us some time to determine if when we thought was the bottom, ACTUALLY was the bottom. That bottom is easily determined if there are no (or very few) coins that went any lower than the point in time that the script began calculating on. Secondly, it allows us time to wait for the REAL movers and shakers to start moving and shaking.
One new feature that I LOVE that TV has implemented is the ability (once the script is added to the chart) to be able to click a point in time on the chart where you want the script to begin its calculations. If this point needs to be changed at any point in time then you can either go into the setting and input the time you wish or simply remove the script and add it again so that you are prompted to select another point in time. Ok, I think that everything I wanted to say. The next version that I will add will be probably my favorite and most used by yours truly...not to mention unique in a way that I have yet to see an implementation anything like it in all of TV's public library. Not to say its not there, but I have yet to come across it and I have DEFINITELY done my fair share of searching for it when I couldn't figure out how to code it for the longest time (though, I was and still am a noob so might get some great feedback on better ways to approach it, but we'll save that jabbering for the next of the publications.
I hope each and every one of ya'll (yes, Im from the South) have the GREATEST of Thanksgivings (if in the US that is...I graced my parents with the best gift anyone could have given them 35 years ago on Thanksgiving....MEEEE ;) So I will sure as hell be having a great holiday. Thanks for checking out my script...you can "like" and leave a comment if you so feel the urge to...or not. Im not doing this for me, but rather to stretch my arms out as far as possible to benefit the most people as possible and more people would see the script if it has more likes/comments/traffic pointing towards it...not to mention as other publishers have...it IS gratifying to see a few likes in my side window, which btw, I have MANY more variations and completely diff types of scanners/screeners Ill be publishing in the future and to know that they've become of use....I"VE become of use to the community is very....pleasing to me and does (as I've also seen many publishers mention as well) drive me to want to publish ones that I originally thought I would keep for myself. Peace out people.
Smarter Money Concepts - Wyckoff Springs & Upthrusts [PhenLabs]📊Smarter Money Concepts - Wyckoff Springs & Upthrusts
Version: PineScript™v6
📌Description
Discover institutional manipulation in real-time with this advanced Wyckoff indicator that detects Springs (accumulation phases) and Upthrusts (distribution phases). It identifies when price tests support or resistance on high volume, followed by a strong recovery, signaling potential reversals where smart money accumulates or distributes positions. This tool solves the common problem of missing these subtle phase transitions, helping traders anticipate trend changes and avoid traps in volatile markets.
By combining volume spike detection, ATR-normalized recovery strength, and a sigmoid probability model, it filters out weak signals and highlights only high-confidence setups. Whether you’re swing trading or day trading, this indicator provides clear visual cues to align with institutional flows, improving entry timing and risk management.
🚀Points of Innovation
Sigmoid-based probability threshold for signal filtering, ensuring only statistically significant Wyckoff patterns trigger alerts
ATR-normalized recovery measurement that adapts to market volatility, unlike static recovery checks in traditional indicators
Customizable volume spike multiplier to distinguish institutional volume from retail noise
Integrated dashboard legend with position and size options for personalized chart visualization
Hidden probability plots for advanced users to analyze underlying math without chart clutter
🔧Core Components
Support/Resistance Calculator: Scans a user-defined lookback period to establish dynamic levels for Spring and Upthrust detection
Volume Spike Detector: Compares current volume to a 10-period SMA, multiplied by a configurable factor to identify significant surges
Recovery Strength Analyzer: Uses ATR to measure price recovery after breaks, normalizing for different market conditions
Probability Model: Applies sigmoid function to combine volume and recovery data, generating a confidence score for each potential signal
🔥Key Features
Spring Detection: Spots accumulation when price dips below support but recovers strongly, helping traders enter longs at potential bottoms
Upthrust Detection: Identifies distribution when price spikes above resistance but falls back, alerting to possible short opportunities at tops
Customizable Inputs: Adjust lookback, volume multiplier, ATR period, and probability threshold to match your trading style and market
Visual Signals: Clear + (green) and - (red) labels on charts for instant recognition of accumulation and distribution phases
Alert System: Triggers notifications for signals and probability thresholds, keeping you informed without constant monitoring
🎨Visualization
Spring Signal: Green upward label (+) below the bar, indicating strong recovery after support break for accumulation
Upthrust Signal: Red downward label (-) above the bar, showing failed breakout above resistance for distribution
Dashboard Legend: Customizable table explaining signals, positioned anywhere on the chart for quick reference
📖Usage Guidelines
Core Settings
Support/Resistance Lookback
Default: 20
Range: 5-50
Description: Sets bars back for S/R levels; lower for recent sensitivity, higher for stable long-term zones – ideal for spotting Wyckoff phases
Volume Spike Multiplier
Default: 1.5
Range: 1.0-3.0
Description: Multiplies 10-period volume SMA; higher values filter to significant spikes, confirming institutional involvement in patterns
ATR for Recovery Measurement
Default: 5
Range: 2-20
Description: ATR period for recovery strength; shorter for volatile markets, longer for smoother analysis of post-break recoveries
Phase Transition Probability Threshold
Default: 0.9
Range: 0.5-0.99
Description: Minimum sigmoid probability for signals; higher for strict filtering, ensuring only high-confidence Wyckoff setups
Display Settings
Dashboard Position
Default: Top Right
Range: Various positions
Description: Places legend table on chart; choose based on layout to avoid overlapping price action
Dashboard Text Size
Default: Normal
Range: Auto to Huge
Description: Adjusts legend text; larger for visibility, smaller for minimal space use
✅Best Use Cases
Swing Trading: Identify Springs for long entries in downtrends turning to accumulation
Day Trading: Catch Upthrusts for short scalps during intraday distribution at resistance
Trend Reversal Confirmation: Use in conjunction with other indicators to validate phase shifts in ranging markets
Volatility Plays: Spot signals in high-volume environments like news events for quick reversals
⚠️Limitations
May produce false signals in low-volume or sideways markets where volume spikes are unreliable
Depends on historical data, so performance varies in unprecedented market conditions or gaps
Probability model is statistical, not predictive, and cannot account for external factors like news
💡What Makes This Unique
Probability-Driven Filtering: Sigmoid model combines multiple factors for superior signal quality over basic Wyckoff detectors
Adaptive Recovery: ATR normalization ensures reliability across assets and timeframes, unlike fixed-threshold tools
User-Centric Design: Tooltips, customizable dashboard, and alerts make it accessible yet powerful for all trader levels
🔬How It Works
Calculate S/R Levels:
Uses the highest high and the lowest low over the lookback period to set dynamic zones
Establishes baseline for detecting breaks in Wyckoff patterns
Detect Breaks and Recovery:
Checks for price breaking support/resistance, then recovering on volume
Measures recovery strength via ATR for volatility adjustment
Apply Probability Model:
Combines volume spike and recovery into a sigmoid function for confidence score
Triggers signal only if above threshold, plotting visuals and alerts
💡Note:
For optimal results, combine with price action analysis and test settings on historical charts. Remember, Wyckoff patterns are most effective in trending markets – use lower probability thresholds for practice, then increase for live trading to focus on high-quality setups.
Turtle Soup Model [PhenLabs]📊 Turtle Soup Model
Version: PineScript™ v6
Description
The Turtle Soup Model is an innovative technical analysis tool that combines market structure analysis with inter-market comparison and gap detection. Unlike traditional structure indicators, it validates market movements against a comparison symbol (default: ES1!) to identify high-probability trading opportunities. The indicator features a unique “soup pattern” detection system, comprehensive gap analysis, and real-time structure breaks visualization.
Innovation Points:
First indicator to combine structure analysis with gap detection and inter-market validation
Advanced memory management system for efficient long-term analysis
Sophisticated pattern recognition with multi-market confirmation
Real-time structure break detection with comparative validation
🔧 Core Components
Structure Analysis: Advanced pivot detection with inter-market validation
Gap Detection: Sophisticated gap identification and classification system
Inversion Patterns: “Soup pattern” recognition for reversal opportunities
Visual System: Dynamic rendering of structure levels and gaps
Alert Framework: Multi-condition notification system
🚨 Key Features 🚨
The indicator provides comprehensive analysis through:
Structure Levels: Validated support and resistance zones
Gap Patterns: Identification of significant market gaps
Inversion Signals: Detection of potential reversal points
Real-time Comparison: Continuous inter-market analysis
Visual Alerts: Dynamic structure break notifications
📈 Visualization
Structure Lines: Color-coded for highs and lows
Gap Boxes: Visual representation of gap zones
Inversion Patterns: Clear marking of potential reversal points
Comparison Overlay: Inter-market divergence visualization
Alert Indicators: Visual signals for structure breaks
💡Example
📌 Usage Guidelines
The indicator offers multiple customization options:
Structure Settings:
Pivot Period: Adjustable for different market conditions
Comparison Symbol: Customizable reference market
Visual Style: Configurable colors and line widths
Gap Analysis:
Signal Mode: Choice between close and wick-based signals
Box Rendering: Automatic gap zone visualization
Middle Line: Reference point for gap measurements
✅ Best Practices:
🚨Use comparison symbol from related market🚨
Monitor both structure breaks and gap inversions
Combine signals for higher probability trades
Pay attention to inter-market divergences
⚠️ Limitations
Requires comparison symbol data
Performance depends on market correlation
Best suited for liquid markets
What Makes This Unique
Inter-market Validation: Uses comparison symbol for signal confirmation
Gap Integration: Combines structure and gap analysis
Soup Pattern Detection: Identifies specific reversal patterns
Dynamic Structure Management: Automatically updates and removes invalid levels
Memory-Efficient Design: Optimized for long-term chart analysis
🔧 How It Works
The indicator processes market data through three main components:
1. Structure Analysis:
Detects pivot points with comparison validation
Tracks structure levels with array management
Identifies and processes structure breaks
2. Gap Analysis:
Identifies significant market gaps
Processes gap inversions
Manages gap zones visualization
3. Pattern Recognition:
Detects “soup” patterns
Validates with comparison market
Generates structure break signals
💡 Note: The indicator performs best when used with correlated comparison symbols and appropriate timeframe selection. Its unique inter-market validation system provides additional confirmation for traditional structure-based trading strategies.
Volume Order Block Scanner [BOSWaves]Volume Order Block Scanner - Dynamic Detection of High-Volume Supply and Demand Zones
Overview
The Volume Order Block Scanner introduces a refined approach to institutional zone mapping, combining volume-weighted order flow, structural displacement, and ATR-based proportionality to identify regions of aggressive participation from large entities.
Unlike static zone mapping or simplistic body-size filters, this framework dynamically evaluates each candle through a multi-layer model of relative volume, candle structure, and volatility context to isolate genuine order block formations while filtering out market noise.
Each identified zone represents a potential institutional footprint, defined by significant volume surges and efficient body-to-ATR relationships that indicate purposeful positioning. Once mapped, each order block is dynamically adjusted for volatility and tracked throughout its lifecycle - from creation to mitigation to potential invalidation - producing an evolving liquidity map that adapts with price.
This adaptive behavior allows traders to visualize where liquidity was absorbed and where it remains unfilled, revealing the structural foundation of institutional intent across timeframes.
Theoretical Foundation
At its core, the Volume Order Block Scanner is built on the interaction between volume displacement and structural imbalance. Traditional order block systems often rely on fixed candle formations or simple engulfing logic, neglecting the fundamental driver of institutional activity: volume concentration relative to volatility.
This framework redefines that approach. Each candle is filtered through two comparative ratios:
Relative Volume Ratio (RVR) - the candle’s volume compared to its rolling average, confirming genuine transactional surges.
Body-ATR Ratio (BAR) - a measure of displacement efficiency relative to recent volatility, ensuring structural strength.
Only when both conditions align is an order block validated, marking a displacement event significant enough to create a lasting imbalance.
By embedding this logic within a volatility-adjusted environment, the system maintains scalability across asset classes and volatility regimes - equally effective in crypto, forex, or index markets.
How It Works
The Volume Order Block Scanner operates through a structured multi-stage process:
Displacement Detection - Identifies candles whose body and volume exceed dynamic thresholds derived from ATR and rolling volume averages. These represent the origin points of institutional aggression.
Zone Construction - Each qualified candle generates an order block with ATR-proportional dimensions to ensure consistency across instruments and timeframes. The zone includes two regions: Body Zone (the precise initiation point of displacement) and Wick Imbalance (the residual inefficiency representing unfilled liquidity).
Lifecycle Tracking - Each zone is continuously monitored for market interaction. Reactions within a defined window are classified as respected, mitigated, or invalidated, giving traders a data-driven sense of ongoing institutional relevance.
Volume Confirmation Layer - Reinforces signal integrity by ensuring that all detected blocks correspond with meaningful increases in transactional activity.
Temporal Decay Control - Zones that remain untested beyond a set period gradually lose visual and analytical weight, maintaining chart clarity and contextual precision.
Interpretation
The Volume Order Block Scanner visualizes how institutional participants interact with the market through zones of accumulation and distribution.
Bullish order blocks denote demand imbalances where price displaced upward under high volume; bearish order blocks signify supply regions formed by concentrated selling pressure.
Price revisiting these areas often reflects institutional re-entry or liquidity rebalancing, offering actionable insights for both continuation and reversal scenarios.
By continuously monitoring interaction and expiry, the framework enables traders to distinguish between active institutional footprints and historical liquidity artifacts.
Strategy Integration
The Volume Order Block Scanner integrates naturally into advanced structural and order-flow methodologies:
Liquidity Mapping : Identify high-volume regions that are likely to influence future price reactions.
Break-of-Structure Confirmation : Validate BOS and CHOCH signals through aligned order block behavior.
Volume Confluence : Combine with BOSWaves volume or momentum indicators to confirm real institutional intent.
Smart-Money Frameworks : Utilize order block retests as precision entry zones within SMC-based setups.
Trend Continuation : Filter zones in line with higher-timeframe bias to maintain directional integrity.
Technical Implementation Details
Core Engine : Dual-filter mechanism using Relative Volume Ratio (RVR) and Body-ATR Ratio (BAR).
Volatility Framework : ATR-based scaling for cross-asset proportionality.
Zone Composition : Body and wick regions plotted independently for visual clarity of imbalance.
Lifecycle Logic : Real-time monitoring of reaction, mitigation, and invalidation states.
Directional Coloring : Distinct bullish and bearish shading with adjustable transparency.
Computation Efficiency : Lightweight structure suitable for multi-timeframe or multi-asset environments.
Optimal Application Parameters
Timeframe Guidance:
5m - 15m : Reactive intraday zones for short-term liquidity engagement.
1H - 4H : Medium-term structures for swing or intraday trend mapping.
Daily - Weekly : Macro accumulation and distribution footprints.
Suggested Configuration:
Relative Volume Threshold : 1.5× - 2.0× average volume.
Body-ATR Threshold : 0.8× - 1.2× for valid displacement.
Zone Expiry : 5 - 10 bars for intraday use, 15 - 30 for swing/macro contexts.
Parameter optimization should be asset-specific, tuned to volatility conditions and liquidity depth.
Performance Characteristics
High Effectiveness:
Markets exhibiting clear displacement and directional flow.
Environments with consistent volume expansion and liquidity inefficiencies.
Reduced Effectiveness:
Range-bound markets with frequent false impulses.
Low-volume sessions lacking institutional participation.
Integration Guidelines
Confluence Framework : Pair with structure-based BOS or liquidity tools for validation.
Risk Management : Treat active order blocks as contextual areas of interest, not guaranteed reversal points.
Multi-Timeframe Logic : Derive bias from higher-timeframe blocks and execute from refined lower-timeframe structures.
Volume Verification : Confirm each reaction with concurrent volume acceleration to avoid false liquidity cues.
Disclaimer
The Volume Order Block Scanner is a quantitative mapping framework designed for professional traders and analysts. It is not a predictive or guaranteed system of profit.
Performance depends on correct configuration, market conditions, and disciplined risk management. BOSWaves recommends using this indicator as part of a comprehensive analytical process - integrating structural, volume, and liquidity context for accurate interpretation.
Institutional Activity DetectorInstitutional Activity Detector - Complete Tutorial
Table of Contents
Installation
Understanding the Indicator
Signal Interpretation
Settings Configuration
Trading Strategies
Best Practices
Common Mistakes to Avoid
1. Installation {#installation}
Step-by-Step Setup:
Step 1: Access TradingView
Go to TradingView.com
Log in to your account (free account works fine)
Step 2: Open Pine Editor
Click on "Pine Editor" at the bottom of the chart
If you don't see it, go to the top menu and select "Pine Editor"
Step 3: Add the Script
Click "New" to create a new indicator
Delete any default code
Copy the entire Institutional Activity Detector code
Paste it into the editor
Step 4: Save and Apply
Click "Save" (give it a name like "Inst Detector")
Click "Add to Chart"
The indicator will now appear on your chart
2. Understanding the Indicator {#understanding}
What It Detects:
This indicator identifies institutional traders (banks, hedge funds, market makers) by analyzing:
Volume Analysis
Detects unusual volume spikes that indicate large players entering
Compares current volume to 20-period average
Institutional trades create volume 2-5x normal levels
Order Flow
Delta: Difference between buying and selling volume
Positive delta = More buying pressure
Negative delta = More selling pressure
Institutions leave "footprints" in order flow
Price Action Patterns
Bullish Rejection Wicks:
| <- Small upper wick
|
███ <- Small body
███
|
|
| <- Large lower wick (rejection)
Indicates institutions bought aggressively at lower prices
Bearish Rejection Wicks:
|
|
| <- Large upper wick (rejection)
|
███ <- Small body
███
| <- Small lower wick
Indicates institutions sold aggressively at higher prices
Liquidity Grabs
Institutions often:
Push price above resistance or below support
Trigger stop losses (grab liquidity)
Reverse direction and trade the other way
Dark Pool Activity
Large block trades executed off-exchange:
High volume with minimal price movement
Indicates institutional accumulation/distribution without moving price
3. Signal Interpretation {#signals}
Signal Types:
🟢 INSTITUTIONAL BUY Signal
Appears as green triangle below candle with strength number (2-5)
What it means:
Institutions are actively accumulating (buying)
Higher strength = More confirmation factors
Strength Levels:
2-3: Moderate confidence - Wait for confirmation
4: High confidence - Strong institutional interest
5: Maximum confidence - Multiple factors aligned
🔴 INSTITUTIONAL SELL Signal
Appears as red triangle above candle with strength number (2-5)
What it means:
Institutions are actively distributing (selling)
Higher strength = More confirmation factors
🟠 Dark Pool (DP) Marker
Small orange diamond
What it means:
Large block trade executed
Accumulation/distribution happening quietly
Often precedes significant moves
Liquidity Zones
Red boxes above price = Resistance/sell liquidity
Green boxes below price = Support/buy liquidity
Institutions target these zones to trigger stops
4. Settings Configuration {#settings}
Recommended Settings by Asset Type:
For Stocks (SPY, AAPL, TSLA):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 1H
For Forex (EUR/USD, GBP/USD):
Volume Spike Multiplier: 1.5
Volume Average Period: 30
Delta Threshold: 65%
Minimum Signal Strength: 3
Timeframe: 15m, 1H, 4H
For Crypto (BTC, ETH):
Volume Spike Multiplier: 2.5
Volume Average Period: 20
Delta Threshold: 70%
Minimum Signal Strength: 4
Timeframe: 15m, 1H, 4H
For Futures (ES, NQ):
Volume Spike Multiplier: 2.0
Volume Average Period: 20
Delta Threshold: 75%
Minimum Signal Strength: 3
Timeframe: 5m, 15m, 30m
Parameter Explanations:
Volume Spike Multiplier (1.0 - 10.0)
Lower = More sensitive (more signals, some false)
Higher = Less sensitive (fewer signals, more reliable)
Start with 2.0 and adjust based on your asset's volatility
Delta Threshold % (50 - 100)
Measures buying vs selling pressure
70% = Strong institutional bias required
Lower for ranging markets, higher for trending
Minimum Signal Strength (2 - 5)
Number of factors that must align for a signal
2 = Very sensitive (many signals)
5 = Very conservative (rare signals)
Recommended: 3-4 for balance
5. Trading Strategies {#strategies}
Strategy 1: Liquidity Grab Reversal
Setup:
Price approaches a liquidity zone (green/red box)
Price penetrates the zone briefly
Institutional BUY/SELL signal appears
Price reverses away from the zone
Entry:
Enter on the signal candle close
Or wait for next candle confirmation
Stop Loss:
Below the liquidity grab low (for buys)
Above the liquidity grab high (for sells)
Take Profit:
2:1 or 3:1 risk/reward ratio
Or next opposing liquidity zone
Example:
Price drops below support → Triggers stops →
Institutional BUY signal (4-5 strength) →
Enter LONG → Price rallies
Strategy 2: Trend Continuation
Setup:
Identify the trend (higher highs/higher lows for uptrend)
Wait for pullback to support in uptrend
Institutional BUY signal appears during pullback
Confirms institutions are adding to positions
Entry:
Enter on signal with strength ≥ 4
Or next candle after signal
Stop Loss:
Below the pullback low + small buffer
Take Profit:
Previous swing high
Or trailing stop using ATR
Strategy 3: Dark Pool Accumulation
Setup:
Dark Pool (DP) markers appear multiple times
Price consolidates in tight range
Institutional BUY signal with high strength appears
Breakout occurs
Entry:
Enter on breakout candle after signal
Or on retest of breakout level
Stop Loss:
Below consolidation range
Take Profit:
Measured move (height of consolidation projected)
Strategy 4: Divergence Play
Setup:
Price makes lower low
MFI/RSI makes higher low (bullish divergence)
Institutional BUY signal appears
Volume confirms with spike
Entry:
Enter on signal candle or next
Stop Loss:
Below the divergence low
Take Profit:
Previous swing high or resistance
6. Best Practices {#best-practices}
✅ DO's:
1. Use Multiple Timeframes
Check higher timeframe for trend direction
Trade signals that align with higher timeframe
Example: 15m signals in direction of 1H trend
2. Combine with Key Levels
Support/resistance
Supply/demand zones
Previous day high/low
Round numbers (psychological levels)
3. Wait for Confirmation
Don't rush into trades
Let the signal candle close
Watch next candle for follow-through
4. Check the Metrics Table
Look at Relative Volume (should be >2.0)
Check Delta % (should be strong positive/negative)
Verify Order Flow aligns with signal
5. Consider Market Context
News events can override signals
Low liquidity times (lunch, overnight) less reliable
Major economic releases need caution
6. Paper Trade First
Test the indicator for 2-4 weeks
Learn how it behaves on your chosen assets
Develop confidence before using real money
Best Times to Trade:
Stock Market Hours:
9:30-11:30 AM EST (high volume, strong moves)
2:00-4:00 PM EST (institutional positioning)
Avoid: 11:30 AM-2:00 PM (lunch, low volume)
Forex:
London Open: 3:00-6:00 AM EST
New York Open: 8:00-11:00 AM EST
London/NY Overlap: 8:00 AM-12:00 PM EST
Crypto:
24/7 market, but highest volume during US/European hours
Watch for weekend low liquidity
7. Common Mistakes to Avoid {#mistakes}
❌ DON'T:
1. Trade Every Signal
Not all signals are equal
Focus on strength 4-5 signals
Wait for optimal setups
2. Ignore Market Structure
Don't buy into strong downtrends (catch falling knife)
Don't sell into strong uptrends (fight the tape)
Respect major support/resistance
3. Use Too Small Timeframes
1m and 2m charts are too noisy
Minimum recommended: 5m for scalping
Better: 15m, 30m, 1H for reliability
4. Overtrade
Quality over quantity
2-5 good trades per day is excellent
Forcing trades leads to losses
5. Ignore Risk Management
Always use stop losses
Risk only 1-2% per trade
Don't revenge trade after losses
6. Trade During Low Volume
Signals less reliable with low volume
Check Relative Volume metric (should be >1.5)
Avoid pre-market/after-hours for stocks
7. Misread Liquidity Grabs
Not every wick is a liquidity grab
Need volume confirmation
Must have institutional signal
Advanced Tips:
Filtering False Signals:
Use Signal Strength Filter:
Minimum strength 3 = Balanced
Minimum strength 4 = Conservative (recommended)
Minimum strength 5 = Ultra conservative
Confluence Checklist:
Signal strength ≥ 4
Relative volume > 2.0
At key support/resistance
Aligns with higher timeframe trend
Delta % strongly positive/negative
Clean price action setup
If 4+ boxes checked = High probability trade
Setting Up Alerts:
Click the three dots on the indicator
Select "Create Alert"
Choose condition:
"Institutional Buy Signal"
"Institutional Sell Signal"
"Dark Pool Activity"
Set up notification (email, SMS, app)
Save alert
Alert Strategy:
Set minimum strength to 4 for fewer, better alerts
Use for assets you can't watch constantly
Don't rely solely on alerts - check chart context
Practice Exercise:
Week 1-2: Observation
Add indicator to your favorite assets
Watch how signals develop
Note which ones lead to profitable moves
Don't trade yet - just observe
Week 3-4: Paper Trading
Use TradingView's paper trading
Trade only strength 4-5 signals
Record results in a journal
Note: entry, exit, profit/loss, what worked/didn't
Week 5+: Small Live Positions
Start with smallest position size
Trade only your best setups
Gradually increase size as you gain confidence
Keep detailed journal
Quick Reference Card:
Signal Quality Ranking:
🔥 Best Setups (Take These):
Strength 5 + Liquidity grab + Key level
Strength 4-5 + Volume >3.0 + Trend alignment
Dark Pool markers + Strength 4+ signal
✅ Good Setups:
Strength 4 at support/resistance
Strength 3-4 with strong delta
Liquidity grab + Strength 3+
⚠️ Caution (Wait for More):
Strength 2-3 in middle of nowhere
Against higher timeframe trend
Low volume (Rel Vol <1.5)
❌ Avoid:
Strength 2 only
During major news
Low liquidity hours
Against strong trend
Troubleshooting:
"Too many signals"
→ Increase Minimum Signal Strength to 4
→ Increase Volume Spike Multiplier to 2.5-3.0
"Too few signals"
→ Decrease Minimum Signal Strength to 2-3
→ Decrease Volume Spike Multiplier to 1.5
"Signals not working"
→ Check if you're trading during low volume hours
→ Verify you're using recommended timeframes
→ Make sure signals align with market structure
"Can't see liquidity zones"
→ Enable "Show Liquidity Zones" in settings
→ Adjust Swing Detection Length (try 7-15)
Resources for Further Learning:
Concepts to Study:
Order Flow Trading
Market Profile / Volume Profile
Smart Money Concepts (SMC)
Liquidity Sweeps and Stop Hunts
Institutional Order Flow
Wyckoff Method
Volume Spread Analysis (VSA)
Recommended Practice:
Study past signals on chart
Replay market using TradingView's bar replay feature
Join trading communities to share setups
Keep a detailed trading journal
Final Thoughts:
This indicator is a tool, not a crystal ball. It identifies high-probability setups where institutions are active, but still requires:
Proper risk management
Market context understanding
Patience and discipline
Continuous learning
Success Formula:
Right Tool + Proper Training + Risk Management + Discipline = Consistent Profits
Start slow, master the basics, and gradually increase complexity as you gain experience.
Good luck and trade smart! 📊📈
Smart Money Concept v1Smart Money Concept Indicator – Visual Interpretation Guide
What Happens When Liquidity Lines Are Broken
🟩 Green Line Broken (Buy-Side Liquidity Pool Swept)
- Indicates price has dipped below a previous swing low where sell stops are likely placed.
- Market Makers may be triggering these stops to accumulate long positions.
- Often followed by a bullish reversal.
- Trader Actions:
• Look for a bullish candle close after the sweep.
• Confirm with nearby Bullish Order Block or Fair Value Gap.
• Consider entering a Buy trade (SLH entry).
- If price continues falling: Indicates trend continuation and invalidation of the buy-side liquidity zone.
🟥 Red Line Broken (Sell-Side Liquidity Pool Swept)
- Indicates price has moved above a previous swing high where buy stops are likely placed.
- Market Makers may be triggering these stops to accumulate short positions.
- Often followed by a bearish reversal.
- Trader Actions:
• Look for a bearish candle close after the sweep.
• Confirm with nearby Bearish Order Block or Fair Value Gap.
• Consider entering a Sell trade (SLH entry).
- If price continues rising: Indicates trend continuation and invalidation of the sell-side liquidity zone.
Chart-Based Interpretation of Green Line Breaks
In the provided DOGE/USD 15-minute chart image:
- Green lines represent buy-side liquidity zones.
- If these lines are broken:
• It may be a stop hunt before a bullish continuation.
• Or a false Break of Structure (BOS) leading to deeper retracement.
- Confirmation is needed from candle structure and nearby OB/FVG zones.
Is the Pink Zone a Valid Bullish Order Block?
To validate the pink zone as a Bullish OB:
- It should be formed by a strong down-close candle followed by a bullish move.
- Price should have rallied from this zone previously.
- If price is now retesting it and showing bullish reaction, it confirms validity.
- If formed during low volume or price never rallied from it, it may not be valid.
Smart Money Concept - Liquidity Line Breaks Explained
This document explains how traders should interpret the breaking of green (buy-side) and red (sell-side) liquidity lines when using the Smart Money Concept indicator. These lines represent key liquidity pools where stop orders are likely placed.
🟩 Green Line Broken (Buy-Side Liquidity Pool Swept)
When the green line is broken, it indicates:
• - Price has dipped below a previous swing low where sell stops were likely placed.
• - Market Makers have triggered those stops to accumulate long positions.
• - This is often followed by a bullish reversal.
Trader Actions:
• - Look for a bullish candle close after the sweep.
• - Confirm with a nearby Bullish Order Block or Fair Value Gap.
• - Consider entering a Buy trade (SLH entry).
🟥 Red Line Broken (Sell-Side Liquidity Pool Swept)
When the red line is broken, it indicates:
• - Price has moved above a previous swing high where buy stops were likely placed.
• - Market Makers have triggered those stops to accumulate short positions.
• - This is often followed by a bearish reversal.
Trader Actions:
• - Look for a bearish candle close after the sweep.
• - Confirm with a nearby Bearish Order Block or Fair Value Gap.
• - Consider entering a Sell trade (SLH entry).
📌 Additional Notes
• - If price continues beyond the liquidity line without reversal, it may indicate a trend continuation rather than a stop hunt.
• - Always confirm with Higher Time Frame bias, Institutional Order Flow, and price reaction at the zone.
Game Theory Trading StrategyGame Theory Trading Strategy: Explanation and Working Logic
This Pine Script (version 5) code implements a trading strategy named "Game Theory Trading Strategy" in TradingView. Unlike the previous indicator, this is a full-fledged strategy with automated entry/exit rules, risk management, and backtesting capabilities. It uses Game Theory principles to analyze market behavior, focusing on herd behavior, institutional flows, liquidity traps, and Nash equilibrium to generate buy (long) and sell (short) signals. Below, I'll explain the strategy's purpose, working logic, key components, and usage tips in detail.
1. General Description
Purpose: The strategy identifies high-probability trading opportunities by combining Game Theory concepts (herd behavior, contrarian signals, Nash equilibrium) with technical analysis (RSI, volume, momentum). It aims to exploit market inefficiencies caused by retail herd behavior, institutional flows, and liquidity traps. The strategy is designed for automated trading with defined risk management (stop-loss/take-profit) and position sizing based on market conditions.
Key Features:
Herd Behavior Detection: Identifies retail panic buying/selling using RSI and volume spikes.
Liquidity Traps: Detects stop-loss hunting zones where price breaks recent highs/lows but reverses.
Institutional Flow Analysis: Tracks high-volume institutional activity via Accumulation/Distribution and volume spikes.
Nash Equilibrium: Uses statistical price bands to assess whether the market is in equilibrium or deviated (overbought/oversold).
Risk Management: Configurable stop-loss (SL) and take-profit (TP) percentages, dynamic position sizing based on Game Theory (minimax principle).
Visualization: Displays Nash bands, signals, background colors, and two tables (Game Theory status and backtest results).
Backtesting: Tracks performance metrics like win rate, profit factor, max drawdown, and Sharpe ratio.
Strategy Settings:
Initial capital: $10,000.
Pyramiding: Up to 3 positions.
Position size: 10% of equity (default_qty_value=10).
Configurable inputs for RSI, volume, liquidity, institutional flow, Nash equilibrium, and risk management.
Warning: This is a strategy, not just an indicator. It executes trades automatically in TradingView's Strategy Tester. Always backtest thoroughly and use proper risk management before live trading.
2. Working Logic (Step by Step)
The strategy processes each bar (candle) to generate signals, manage positions, and update performance metrics. Here's how it works:
a. Input Parameters
The inputs are grouped for clarity:
Herd Behavior (🐑):
RSI Period (14): For overbought/oversold detection.
Volume MA Period (20): To calculate average volume for spike detection.
Herd Threshold (2.0): Volume multiplier for detecting herd activity.
Liquidity Analysis (💧):
Liquidity Lookback (50): Bars to check for recent highs/lows.
Liquidity Sensitivity (1.5): Volume multiplier for trap detection.
Institutional Flow (🏦):
Institutional Volume Multiplier (2.5): For detecting large volume spikes.
Institutional MA Period (21): For Accumulation/Distribution smoothing.
Nash Equilibrium (⚖️):
Nash Period (100): For calculating price mean and standard deviation.
Nash Deviation (0.02): Multiplier for equilibrium bands.
Risk Management (🛡️):
Use Stop-Loss (true): Enables SL at 2% below/above entry price.
Use Take-Profit (true): Enables TP at 5% above/below entry price.
b. Herd Behavior Detection
RSI (14): Checks for extreme conditions:
Overbought: RSI > 70 (potential herd buying).
Oversold: RSI < 30 (potential herd selling).
Volume Spike: Volume > SMA(20) x 2.0 (herd_threshold).
Momentum: Price change over 10 bars (close - close ) compared to its SMA(20).
Herd Signals:
Herd Buying: RSI > 70 + volume spike + positive momentum = Retail buying frenzy (red background).
Herd Selling: RSI < 30 + volume spike + negative momentum = Retail selling panic (green background).
c. Liquidity Trap Detection
Recent Highs/Lows: Calculated over 50 bars (liquidity_lookback).
Psychological Levels: Nearest round numbers (e.g., $100, $110) as potential stop-loss zones.
Trap Conditions:
Up Trap: Price breaks recent high, closes below it, with a volume spike (volume > SMA x 1.5).
Down Trap: Price breaks recent low, closes above it, with a volume spike.
Visualization: Traps are marked with small red/green crosses above/below bars.
d. Institutional Flow Analysis
Volume Check: Volume > SMA(20) x 2.5 (inst_volume_mult) = Institutional activity.
Accumulation/Distribution (AD):
Formula: ((close - low) - (high - close)) / (high - low) * volume, cumulated over time.
Smoothed with SMA(21) (inst_ma_length).
Accumulation: AD > MA + high volume = Institutions buying.
Distribution: AD < MA + high volume = Institutions selling.
Smart Money Index: (close - open) / (high - low) * volume, smoothed with SMA(20). Positive = Smart money buying.
e. Nash Equilibrium
Calculation:
Price mean: SMA(100) (nash_period).
Standard deviation: stdev(100).
Upper Nash: Mean + StdDev x 0.02 (nash_deviation).
Lower Nash: Mean - StdDev x 0.02.
Conditions:
Near Equilibrium: Price between upper and lower Nash bands (stable market).
Above Nash: Price > upper band (overbought, sell potential).
Below Nash: Price < lower band (oversold, buy potential).
Visualization: Orange line (mean), red/green lines (upper/lower bands).
f. Game Theory Signals
The strategy generates three types of signals, combined into long/short triggers:
Contrarian Signals:
Buy: Herd selling + (accumulation or down trap) = Go against retail panic.
Sell: Herd buying + (distribution or up trap).
Momentum Signals:
Buy: Below Nash + positive smart money + no herd buying.
Sell: Above Nash + negative smart money + no herd selling.
Nash Reversion Signals:
Buy: Below Nash + rising close (close > close ) + volume > MA.
Sell: Above Nash + falling close + volume > MA.
Final Signals:
Long Signal: Contrarian buy OR momentum buy OR Nash reversion buy.
Short Signal: Contrarian sell OR momentum sell OR Nash reversion sell.
g. Position Management
Position Sizing (Minimax Principle):
Default: 1.0 (10% of equity).
In Nash equilibrium: Reduced to 0.5 (conservative).
During institutional volume: Increased to 1.5 (aggressive).
Entries:
Long: If long_signal is true and no existing long position (strategy.position_size <= 0).
Short: If short_signal is true and no existing short position (strategy.position_size >= 0).
Exits:
Stop-Loss: If use_sl=true, set at 2% below/above entry price.
Take-Profit: If use_tp=true, set at 5% above/below entry price.
Pyramiding: Up to 3 concurrent positions allowed.
h. Visualization
Nash Bands: Orange (mean), red (upper), green (lower).
Background Colors:
Herd buying: Red (90% transparency).
Herd selling: Green.
Institutional volume: Blue.
Signals:
Contrarian buy/sell: Green/red triangles below/above bars.
Liquidity traps: Red/green crosses above/below bars.
Tables:
Game Theory Table (Top-Right):
Herd Behavior: Buying frenzy, selling panic, or normal.
Institutional Flow: Accumulation, distribution, or neutral.
Nash Equilibrium: In equilibrium, above, or below.
Liquidity Status: Trap detected or safe.
Position Suggestion: Long (green), Short (red), or Wait (gray).
Backtest Table (Bottom-Right):
Total Trades: Number of closed trades.
Win Rate: Percentage of winning trades.
Net Profit/Loss: In USD, colored green/red.
Profit Factor: Gross profit / gross loss.
Max Drawdown: Peak-to-trough equity drop (%).
Win/Loss Trades: Number of winning/losing trades.
Risk/Reward Ratio: Simplified Sharpe ratio (returns / drawdown).
Avg Win/Loss Ratio: Average win per trade / average loss per trade.
Last Update: Current time.
i. Backtesting Metrics
Tracks:
Total trades, winning/losing trades.
Win rate (%).
Net profit ($).
Profit factor (gross profit / gross loss).
Max drawdown (%).
Simplified Sharpe ratio (returns / drawdown).
Average win/loss ratio.
Updates metrics on each closed trade.
Displays a label on the last bar with backtest period, total trades, win rate, and net profit.
j. Alerts
No explicit alertconditions defined, but you can add them for long_signal and short_signal (e.g., alertcondition(long_signal, "GT Long Entry", "Long Signal Detected!")).
Use TradingView's alert system with Strategy Tester outputs.
3. Usage Tips
Timeframe: Best for H1-D1 timeframes. Shorter frames (M1-M15) may produce noisy signals.
Settings:
Risk Management: Adjust sl_percent (e.g., 1% for volatile markets) and tp_percent (e.g., 3% for scalping).
Herd Threshold: Increase to 2.5 for stricter herd detection in choppy markets.
Liquidity Lookback: Reduce to 20 for faster markets (e.g., crypto).
Nash Period: Increase to 200 for longer-term analysis.
Backtesting:
Use TradingView's Strategy Tester to evaluate performance.
Check win rate (>50%), profit factor (>1.5), and max drawdown (<20%) for viability.
Test on different assets/timeframes to ensure robustness.
Live Trading:
Start with a demo account.
Combine with other indicators (e.g., EMAs, support/resistance) for confirmation.
Monitor liquidity traps and institutional flow for context.
Risk Management:
Always use SL/TP to limit losses.
Adjust position_size for risk tolerance (e.g., 5% of equity for conservative trading).
Avoid over-leveraging (pyramiding=3 can amplify risk).
Troubleshooting:
If no trades are executed, check signal conditions (e.g., lower herd_threshold or liquidity_sensitivity).
Ensure sufficient historical data for Nash and liquidity calculations.
If tables overlap, adjust position.top_right/bottom_right coordinates.
4. Key Differences from the Previous Indicator
Indicator vs. Strategy: The previous code was an indicator (VP + Game Theory Integrated Strategy) focused on visualization and alerts. This is a strategy with automated entries/exits and backtesting.
Volume Profile: Absent in this strategy, making it lighter but less focused on high-volume zones.
Wick Analysis: Not included here, unlike the previous indicator's heavy reliance on wick patterns.
Backtesting: This strategy includes detailed performance metrics and a backtest table, absent in the indicator.
Simpler Signals: Focuses on Game Theory signals (contrarian, momentum, Nash reversion) without the "Power/Ultra Power" hierarchy.
Risk Management: Explicit SL/TP and dynamic position sizing, not present in the indicator.
5. Conclusion
The "Game Theory Trading Strategy" is a sophisticated system leveraging herd behavior, institutional flows, liquidity traps, and Nash equilibrium to trade market inefficiencies. It’s designed for traders who understand Game Theory principles and want automated execution with robust risk management. However, it requires thorough backtesting and parameter optimization for specific markets (e.g., forex, crypto, stocks). The backtest table and visual aids make it easy to monitor performance, but always combine with other analysis tools and proper capital management.
If you need help with backtesting, adding alerts, or optimizing parameters, let me know!
ICT Macro Zone Boxes w/ Individual H/L Tracking v3.1ICT Macro Zones (Grey Box Version
This indicator dynamically highlights key intraday time-based macro sessions using a clean, minimalistic grey box overlay, helping traders align with institutional trading cycles. Inspired by ICT (Inner Circle Trader) concepts, it tracks real-time highs and lows for each session and optionally extends the zone box after the session ends — making it a precision tool for intraday setups, order flow analysis, and macro-level liquidity sweeps.
### 🔍 **What It Does**
- Plots **six predefined macro sessions** used in Smart Money Concepts:
- AM Macro (09:50–10:10)
- London Close (10:50–11:10)
- Lunch Macro (11:30–13:30)
- PM Macro (14:50–15:10)
- London SB (03:00–04:00)
- PM SB (15:00–16:00)
- Each zone:
- **Tracks high and low dynamically** throughout the session.
- **Draws a consistent grey shaded box** to visualize price boundaries.
- **Displays a label** at the first bar of the session (optional).
- **Optionally extends** the box to the right after the session closes.
### 🧠 **How It Works**
- Uses Pine Script arrays to define each session’s time window, label, and color.
- Detects session entry using `time()` within a New York timezone context.
- High/Low values are updated per bar inside the session window.
- Once a session ends, the box is optionally closed and fixed in place.
- All visual zones use a standardized grey tone for clarity and consistency across charts.
### 🛠️ **Settings**
- **Shade Zone High→Low:** Enable/disable the grey macro box.
- **Extend Box After Session:** Keep the zone visible after it ends.
- **Show Entry Label:** Display a label at the start of each session.
### 🎯 **Why This Script is Unique**
Unlike basic session markers or colored backgrounds, this tool:
- Focuses on **macro moments of liquidity and reversal**, not just open/close times.
- Uses **per-session logic** to individually track price behavior inside key time windows.
- Supports **real-time high/low tracking and clean zone drawing**, ideal for Smart Money and ICT-style strategies.
Perfect — based on your list, here's a **bundle-style description** that not only explains the function of each script but also shows how they **work together** in a Smart Money/ICT workflow. This kind of cross-script explanation is exactly what TradingView wants to see to justify closed-source mashups or interdependent tools.
---
📚 ICT SMC Toolkit — Script Integration Guide
This set of advanced Smart Money Concept (SMC) tools is designed for traders who follow ICT-based methodologies, combining liquidity theory, time-based precision, and engineered confluences for high-probability trades. Each indicator is optimized to work both independently and synergistically, forming a comprehensive trading framework.
---
First FVG Custom Time Range
**Purpose:**
Plots the **first Fair Value Gap (FVG)** that appears within a defined session (e.g., NY Kill Zone, Custom range). Includes optional retest alerts.
**Best Used With:**
- Use with **ICT Macro Zones (Grey Box Version)** to isolate FVGs during high-probability times like AM Macro or PM SB.
- Combine with **Liquidity Levels** to assess whether FVGs form near swing points or liquidity voids.
---
ICT SMC Liquidity Grabs and OB s
**Purpose:**
Detects **liquidity grabs** (stop hunts above/below swing highs/lows) and **bullish/bearish order blocks**. Includes optional Fibonacci OTE levels for sniper entries.
**Best Used With:**
- Use with **ICT Turtle Soup (Reversal)** for confirmation after a liquidity grab.
- Combine with **Macro Zones** to catch order blocks forming inside timed macro windows.
- Match with **Smart Swing Levels** to confirm structure breaks before entry.
ICT SMC Liquidity Levels (Smart Swing Lows)
**Purpose:**
Automatically marks swing highs/lows based on user-defined lookbacks. Tracks whether those levels have been breached or respected.
**Best Used With:**
- Combine with **Turtle Soup** to detect if a swing level was swept, then reversed.
- Use with **Liquidity Grabs** to confirm a grab occurred at a meaningful structural point.
- Align with **Macro Zones** to understand when liquidity events occur within macro session timing.
ICT Turtle Soup (Liquidity Reversal)
**Purpose:**
Implements the classic ICT Turtle Soup model. Looks for swing failure and quick reversals after a liquidity sweep — ideal for catching traps.
Best Used With:
- Confirm with **Liquidity Grabs + OBs** to identify institutional activity at the reversal point.
- Use **Liquidity Levels** to ensure the reversal is happening at valid previous swing highs/lows.
- Amplify probability when pattern appears during **Macro Zones** or near the **First FVG**.
ICT Turtle Soup Ultimate V2
**Purpose:**
An enhanced, multi-layer version of the Turtle Soup setup that includes built-in liquidity checks, OTE levels, structure validation, and customizable visual output.
**Best Used With:**
- Use as an **entry signal generator** when other indicators (e.g., OBs, liquidity grabs) are aligned.
- Pair with **Macro Zones** for high-precision timing.
- Combine with **First FVG** to anticipate price rebalancing before explosive moves.
---
## 🧠 Workflow Example:
1. **Start with Macro Zones** to focus only on institutional trading windows.
2. Look for **Liquidity Grabs or Swing Sweeps** around key highs/lows.
3. Check for a **Turtle Soup Reversal** or **Order Block Reaction** near that level.
4. Confirm confluence with a **Fair Value Gap**.
5. Execute using the **OTE level** from the Liquidity Grabs + OB script.
---
Let me know which script you want to publish first — I’ll tailor its **individual TradingView description** and flag its ideal **“Best Used With” partners** to help users see the value in your ecosystem.
CISD [TakingProphets]🧠 Indicator Purpose:
The "CISD - Change in State of Delivery" is a precision tool designed for traders utilizing ICT (Inner Circle Trader) conecpets. It detects critical shifts in delivery conditions after liquidity sweeps — helping you spot true smart money activity and optimal trade opportunities. This script is especially valuable for traders applying liquidity concepts, displacement recognition, and market structure shifts at both intraday and swing levels.
🌟 What Makes This Indicator Unique:
Unlike basic trend-following or scalping tools, CISD operates through a two-phase smart money logic:
Liquidity Sweep Detection (sweeping Buyside or Sellside Liquidity).
State of Delivery Change Identification (through bearish or bullish displacement after the sweep).
It intelligently tracks candle sequences and only signals a CISD event after true displacement — offering a much deeper context than ordinary indicators.
⚙️ How the Indicator Works:
Swing Point Detection: Identifies recent pivot highs/lows to map Buyside Liquidity (BSL) and Sellside Liquidity (SSL) zones.
Liquidity Sweeps: Watches for price breaches of these liquidity points to detect institutional stop hunts.
Sequence Recognition: Finds series of same-direction candles before sweeps to mark institutional accumulation/distribution.
Change of Delivery Confirmation: Confirms CISD only after significant displacement moves price against the initial candle sequence.
Visual Markings: Automatically plots CISD lines and optional labels, customizable in color, style, and size.
🎯 How to Use It:
Identify Liquidity Sweeps: Watch for CISD levels plotted after a liquidity sweep event.
Plan Entries: Look for retracements into CISD lines for high-probability entries.
Manage Risk: Use CISD levels to refine your stop-loss and profit-taking zones.
Best Application:
After stop hunts during Killzones (London Open, New York AM).
As part of the Flow State Model: identify higher timeframe PD Arrays ➔ wait for lower timeframe CISD confirmation.
🔎 Underlying Concepts:
Liquidity Pools: Highs and lows cluster stop orders, attracting institutional sweeps.
Displacement: Powerful price moves post-sweep confirm smart money involvement.
Market Structure: CISD frequently precedes major Change of Character (CHoCH) or Break of Structure (BOS) shifts.
🎨 Customization Options:
Adjustable line color, width, and style (solid, dashed, dotted).
Optional label display with customizable color and sizing.
Line extension settings to keep CISD zones visible for future reference.
✅ Recommended for:
Traders studying ICT Smart Money Concepts.
Intraday scalpers and higher timeframe swing traders.
Traders who want to improve entries around liquidity sweeps and institutional displacement moves.
🚀 Bonus Tip:
For maximum confluence, pair this with the HTF POI, ICT Liquidity Levels, and HTF Market Structure indicators available at TakingProphets.com! 🔥
SMT SwiftEdge PowerhouseSMT SwiftEdge Powerhouse: Precision Trading with Divergence, Liquidity Grabs, and OTE Zones
The SMT SwiftEdge Powerhouse is a powerful trading tool designed to help traders identify high-probability entry points during the most active market sessions—London and New York. By combining Smart Money Technique (SMT) Divergence, Liquidity Grabs, and Optimal Trade Entry (OTE) Zones, this script provides a unique and cohesive strategy for capturing market reversals with precision. Whether you're a scalper or a swing trader, this indicator offers clear visual signals to enhance your trading decisions on any timeframe.
What Does This Script Do?
This script integrates three key concepts to identify potential trading opportunities:
SMT Divergence:
SMT Divergence compares the price action of two correlated assets (e.g., Nasdaq and S&P 500 futures) to detect hidden market reversals. When one asset makes a higher high while the other makes a lower high (bearish divergence), or one makes a lower low while the other makes a higher low (bullish divergence), it signals a potential reversal. This technique leverages institutional "smart money" behavior to anticipate market shifts.
Liquidity Grabs:
Liquidity Grabs occur when price breaks above recent highs or below recent lows on higher timeframes (5m and 15m), often triggering stop-loss orders from retail traders. These breakouts are identified using pivot points and confirm institutional activity, setting the stage for a reversal. The script focuses on liquidity grabs during the London and New York sessions for maximum market activity.
Optimal Trade Entry (OTE) Zones:
OTE Zones are Fibonacci-based retracement areas (e.g., 61.8%) calculated after a liquidity grab. These zones highlight where price is likely to retrace before continuing in the direction of the reversal, offering a high-probability entry point. The script adjusts the width of these zones using the Average True Range (ATR) to adapt to market volatility.
By combining these components, the script identifies when institutional activity (liquidity grabs) aligns with market reversals (SMT divergence) and pinpoints precise entry points (OTE zones) during high-liquidity sessions.
Why Combine These Components?
The integration of SMT Divergence, Liquidity Grabs, and OTE Zones creates a robust trading system for several reasons:
Synergy of Institutional Signals: SMT Divergence and Liquidity Grabs both reflect "smart money" behavior—divergence shows hidden reversals, while liquidity grabs confirm institutional intent to trap retail traders. Together, they provide a strong foundation for identifying high-probability setups.
Session-Based Precision: Focusing on the London and New York sessions ensures signals occur during periods of high volatility and liquidity, increasing their reliability.
Precision Entries with OTE: After confirming a setup with divergence and liquidity grabs, OTE zones provide a clear entry area, reducing guesswork and improving trade accuracy.
Adaptability: The script works on any timeframe, with adjustable settings for signal sensitivity, session times, and Fibonacci levels, making it versatile for different trading styles.
This combination makes the script unique by aligning institutional insights with actionable entry points, tailored to the most active market hours.
How to Use the Script
Setup:
Add the script to your chart (works on any timeframe, e.g., 1m, 5m, 15m).
Configure the settings in the indicator's inputs:
Session Settings: Adjust the start/end times for London and New York sessions (default: London 8-11 UTC, New York 13-16 UTC). You can disable session restrictions if desired.
Asset Settings: Set the primary and secondary assets for SMT Divergence (default: NQ1! and ES1!). Ensure the assets are correlated.
Signal Settings: Adjust the lookback period, ATR period, and signal sensitivity (Low/Medium/High) to control the frequency of signals.
OTE Settings: Choose the Fibonacci level for OTE zones (default: 61.8%).
Visual Settings: Enable/disable OTE zones, SMT labels, and debug labels for troubleshooting.
Interpreting Signals:
Blue Circles: Indicate a liquidity grab (price breaking a 5m or 15m pivot high/low), marking the start of a potential setup.
Blue OTE Zones: Appear after a liquidity grab, showing the retracement area (e.g., 61.8% Fibonacci level) where price is likely to enter for a reversal trade. The label "OTE Trigger 5m/15m" confirms the direction (Short/Long) and session.
Green/Red Entry Boxes: Mark precise entry points when price enters the OTE zone and confirms the SMT Divergence. Green boxes indicate a long entry, red boxes a short entry.
Trading Example:
On a 1m chart, a blue circle appears when price breaks a 5m pivot high during the London session.
A blue OTE zone forms, showing a retracement area (e.g., 61.8% Fibonacci level) with the label "OTE Trigger 5m/15m (Short, London)".
Price retraces into the OTE zone, and a red "Short Entry" box appears, confirming a bearish SMT Divergence.
Enter a short trade at the red box, with a stop-loss above the OTE zone and a take-profit at the next support level.
Originality and Utility
The SMT SwiftEdge Powerhouse stands out by merging SMT Divergence, Liquidity Grabs, and OTE Zones into a single, session-focused indicator. Unlike traditional indicators that focus on one aspect of price action, this script combines institutional reversal signals with precise entry zones, tailored to the most active market hours. Its adaptability across timeframes, customizable settings, and clear visual cues make it a versatile tool for traders seeking to capitalize on smart money movements with confidence.
Tips for Best Results
Use on correlated assets like NQ1! (Nasdaq futures) and ES1! (S&P 500 futures) for accurate SMT Divergence.
Test on lower timeframes (1m, 5m) for scalping or higher timeframes (15m, 1H) for swing trading.
Adjust the "Signal Sensitivity" to "High" for more signals or "Low" for fewer, high-quality setups.
Enable "Show Debug Labels" if signals are not appearing as expected, to troubleshoot pivot points and liquidity grabs.
Indiq 2.0The functionality of the indicator includes the following features:
Moving Averages (MA):
The ability to adjust periods for short (short_ma_length) and long (long_ma_length) moving averages.
Display of moving averages on the chart:
Short MA (blue line).
Long MA (red line).
Generation of buy and sell signals:
Buy (BUY): When the short MA crosses the long MA from below.
Sell (SELL): When the short MA crosses the long MA from above.
Visualization of signals on the chart:
Buy is displayed as a green BUY marker below the candle.
Sell is displayed as a red SELL marker above the candle.
Liquidity Heatmap:
Liquidity levels:
Levels are calculated based on the closing price and a step (liquidity_step).
Levels are grouped by the nearest price values.
Volumes at levels:
Volume (volume) is accumulated for each liquidity level.
Levels with a volume less than min_volume_filter are not displayed.
Time filtering:
Levels that have not been updated within the last time_filter bars are not displayed.
Volatility filtering:
Levels are filtered by volatility (ATR) to exclude those outside the volatility range.
Color gradient:
The color of levels depends on volume (gradient from gradient_start_color to gradient_end_color).
Visualization:
Liquidity levels are displayed as horizontal lines.
Volumes at levels are shown as text labels.
RSI Filtering:
The ability to enable/disable RSI filtering (rsi_filter).
Liquidity levels are filtered based on overbought (rsi_overbought) and oversold (rsi_oversold) conditions.
Levels that do not meet RSI conditions are not displayed.
MACD Filtering:
The ability to enable/disable MACD filtering (macd_filter).
Liquidity levels are filtered based on the MACD histogram condition (e.g., only if the histogram is above zero).
Levels that do not meet MACD conditions are not displayed.
Display of Market Maker Buys:
Condition for market maker buys:
Volume exceeds the average volume over the last 20 bars by 2 times.
Closing price is above the opening price.
Market maker buys are displayed on the chart as orange MM Buy markers below the candle.
Indicator Settings:
Moving average parameters:
short_ma_length: Period for the short MA.
long_ma_length: Period for the long MA.
Liquidity heatmap parameters:
liquidity_step: Step between liquidity levels.
max_levels: Maximum number of levels to display.
time_filter: Time filter (last N bars).
min_volume_filter: Minimum volume for displaying a level.
volatility_filter: Volatility filter (ATR multiplier).
RSI parameters:
rsi_filter: Enable/disable RSI filtering.
rsi_overbought: Overbought RSI level.
rsi_oversold: Oversold RSI level.
MACD parameters:
macd_filter: Enable/disable MACD filtering.
Color settings:
gradient_start_color: Starting color of the gradient.
gradient_end_color: Ending color of the gradient.
Visualization:
Moving averages:
Short MA: Blue line.
Long MA: Red line.
Signals:
Buy: Green BUY marker.
Sell: Red SELL marker.
Liquidity heatmap:
Liquidity levels: Horizontal lines with a color gradient.
Volumes: Text labels at levels.
Market maker buys:
Orange MM Buy markers.
Alerts:
The ability to set alerts for signals:
Buy (BUY).
Sell (SELL).
Additional Features:
Flexible filter settings:
Filtering by time, volume, volatility, RSI, and MACD.
Extensibility:
The ability to add new filters (e.g., Stochastic, Volume Profile, etc.).
Visual customization:
Adjustment of colors, sizes, and display styles.
Summary:
The indicator provides a comprehensive tool for analyzing liquidity, generating trading signals, and tracking market maker activity. It combines:
A liquidity heatmap.
Signals based on moving averages.
Filtering by RSI and MACD.
Display of market maker buys.
Flexible settings and visualization.
This indicator is suitable for traders who want to analyze liquidity levels, identify entry and exit points, and monitor the actions of large market players.
