High-Probability IndicatorExplanation of the Code
Trend Filter (EMA):
A 50-period Exponential Moving Average (EMA) is used to determine the overall trend.
trendUp is true when the price is above the EMA.
trendDown is true when the price is below the EMA.
Momentum Filter (RSI):
A 14-period RSI is used to identify overbought and oversold conditions.
oversold is true when RSI ≤ 30.
overbought is true when RSI ≥ 70.
Volatility Filter (ATR):
A 14-period Average True Range (ATR) is used to measure volatility.
ATR is multiplied by a user-defined multiplier (default: 2.0) to set a volatility threshold.
Ensures trades are only taken during periods of sufficient volatility.
Entry Conditions:
Long Entry: Price is above the EMA (uptrend), RSI is oversold, and the candle range exceeds the ATR threshold.
Short Entry: Price is below the EMA (downtrend), RSI is overbought, and the candle range exceeds the ATR threshold.
Exit Conditions:
Take Profit: A fixed percentage above/below the entry price.
Stop Loss: A fixed percentage below/above the entry price.
Visualization:
The EMA is plotted on the chart.
Background colors highlight uptrends and downtrends.
Buy and sell signals are displayed as labels on the chart.
Alerts:
Alerts are triggered for buy and sell signals.
How to Use the Indicator
Trend Filter:
Only take trades in the direction of the trend (e.g., long in an uptrend, short in a downtrend).
Momentum Filter:
Look for oversold conditions in an uptrend for long entries.
Look for overbought conditions in a downtrend for short entries.
Volatility Filter:
Ensure the candle range exceeds the ATR threshold to avoid low-volatility trades.
Risk Management:
Use the built-in take profit and stop loss levels to manage risk.
Optimization Tips
Backtesting:
Test the indicator on multiple timeframes and assets to evaluate its performance.
Adjust the input parameters (e.g., EMA length, RSI length, ATR multiplier) to optimize for specific markets.
Combination with Other Strategies:
Add additional filters, such as volume analysis or support/resistance levels, to improve accuracy.
Risk Management:
Use proper position sizing and risk-reward ratios to maximize profitability.
Disclaimer
No indicator can guarantee an 85% win ratio due to the inherent unpredictability of financial markets. This script is provided for educational purposes only. Always conduct thorough backtesting and paper trading before using any strategy in live trading.
Let me know if you need further assistance or enhancements!
在脚本中搜索"entry"
BBSS+This Pine Script implements a custom indicator overlaying Bollinger Bands with additional features for trend analysis using Exponential Moving Averages (EMAs). Here's a breakdown of its functionality:
Bollinger Bands:
The script calculates the Bollinger Bands using a 20-period Simple Moving Average (SMA) as the basis and a multiplier of 2 for the standard deviation.
It plots the Upper Band and Lower Band in red.
EMA Calculations:
Three EMAs are calculated for the close price with periods of 5, 10, and 40.
The EMAs are plotted in green (5-period), cyan (10-period), and orange (40-period) to distinguish between them.
Trend Detection:
The script determines bullish or bearish EMA alignments:
Bullish Order: EMA 5 > EMA 10 > EMA 40.
Bearish Order: EMA 5 < EMA 10 < EMA 40.
Entry Signals:
Long Entry: Triggered when:
The close price crosses above the Upper Bollinger Band.
The Upper Band is above its 5-period SMA (indicating momentum).
The EMAs are in a bullish order.
Short Entry: Triggered when:
The close price crosses below the Lower Bollinger Band.
The Lower Band is below its 5-period SMA.
The EMAs are in a bearish order.
Trend State Tracking:
A variable tracks whether the market is in a Long or Short trend based on conditions:
A Long trend continues unless conditions for a Short Entry are met or the Upper Band dips below its average.
A Short trend continues unless conditions for a Long Entry are met or the Lower Band rises above its average.
Visual Aids:
Signal Shapes:
Triangle-up shapes indicate Long Entry points below the bar.
Triangle-down shapes indicate Short Entry points above the bar.
Bar Colors:
Green bars indicate a Long trend.
Red bars indicate a Short trend.
This script combines Bollinger Bands with EMA crossovers to generate entry signals and visualize market trends, making it a versatile tool for identifying momentum and trend reversals.
Smart Wick Concept (SWC)Smart Wick Concept (SWC)
The Smart Wick Concept (SWC) is a unique trend-following strategy designed to capture precise entry points in trending markets. This indicator identifies trade opportunities based on higher timeframe trends and wick behavior on lower timeframes, making it an effective tool for intraday and swing traders.
Key Features:
Trend Identification:
SWC uses the H1 timeframe to define the primary market trend (bullish or bearish), ensuring alignment with the overall market direction.
Precise Entry Signals:
Entry opportunities are generated on the M15 timeframe when a candle's wick interacts with the prior candle's range. This approach minimizes false signals and enhances accuracy.
Stop Loss and Take Profit Levels:
The indicator automatically calculates suggested stop loss and take profit levels based on market dynamics, providing traders with a clear risk-reward framework.
Customizable Parameters:
SWC allows traders to adjust key settings, such as the higher timeframe and minimum trend range, to align with their trading preferences and market conditions.
How It Works:
Bullish Entry:
Higher timeframe trend must be bullish.
A M15 candle must dip below the previous candle’s low and close back above it, signaling a potential buy opportunity.
Bearish Entry:
Higher timeframe trend must be bearish.
A M15 candle must exceed the previous candle’s high and close back below it, signaling a potential sell opportunity.
Risk Management:
Stop loss is placed at the low (for buys) or high (for sells) of the current M15 candle.
Take profit targets are calculated at twice the risk, ensuring a favorable risk-reward ratio.
Benefits:
Aligns trades with market momentum.
Reduces noise by filtering out weak or sideways trends.
Provides a structured approach to trading XAUUSD and other volatile instruments.
Use Cases:
The Smart Wick Concept is ideal for traders looking for a disciplined and data-driven approach to trading. While it is optimized for XAUUSD, it can also be applied to other trending markets such as major currency pairs or indices with some parameter adjustments.
Disclaimer:
This indicator is a trading tool and should not be used as a standalone strategy. Always backtest the indicator thoroughly and use proper risk management to protect your capital. Past performance does not guarantee future results.
Turtle Trade Channels Indicator with EMATurtle Trade Channels Indicator with EMA (TuTCI + EMA)
This custom indicator combines the classic Turtle Trading Channel strategy with an Exponential Moving Average (EMA) filter to provide clear entry and exit signals, as well as trend direction guidance.
Features:
Turtle Channels: The indicator calculates the upper and lower Turtle Trading Channels based on the highest and lowest values over a user-defined period ( Entry Length for the channel).
Entry/Exit Signals: Alerts you to potential buy and sell opportunities with visual signals on the chart.
Long Entry: When the price crosses above the upper channel.
Short Entry: When the price crosses below the lower channel.
Long Exit: When the price breaks below the exit line.
Short Exit: When the price breaks above the exit line.
EMA Filter: A 50-period Exponential Moving Average (EMA) is included to identify the overall trend. The background color turns green when the price is above the EMA (bullish trend) and red when the price is below the EMA (bearish trend).
Highlighter: Optional background highlighting for the most relevant signals, such as when the price crosses the upper or lower Turtle Channel. This feature helps to easily identify key market movements.
Visual Customization: Customize the EMA length, Entry/Exit lengths, and toggle signals and highlighting to suit your preferences.
How It Works:
The Turtle Trade Channels are designed to capture breakouts by identifying key price levels (highest high and lowest low) over a specified period. By combining this strategy with an EMA, the indicator ensures trades are aligned with the broader trend, increasing the probability of successful trades.
Uptrend: When the price is above the EMA, the indicator considers the trend to be bullish, and it highlights long entry signals.
Downtrend: When the price is below the EMA, the trend is considered bearish, and short entries are emphasized.
Customization:
Entry Length: Adjusts the period for calculating the Turtle Channel's entry levels.
Exit Length: Defines the period for calculating the exit levels.
EMA Length: The period for the Exponential Moving Average (default is set to 50).
Show Entry/Exit Signals: Toggle the visibility of entry/exit signals on the chart.
Highlighter On/Off: Toggle background highlighting for key signals.
This indicator is suitable for traders who follow trend-following strategies, particularly those influenced by the Turtle Trading methodology, and wish to use an EMA filter for better trend confirmation.
Use Cases:
Trend-following traders looking for clear entry/exit signals.
Breakout traders using the Turtle Trading concept to identify price breakouts.
Swing traders who want to incorporate trend analysis with price levels.
MERCURY by DrAbhiramSivprasad"MERCURY by DrAbhiramSivprasad"
Developed from over 10 years of personal trading experience, the Mercury Indicator is a strategic tool designed to enhance accuracy in trading decisions. Think of it as a guiding light—a supportive tool that helps traders refine and build more robust strategies by integrating multiple powerful elements into a single indicator. I’ll be sharing some examples to illustrate how I use this indicator in my own trading journey, highlighting its potential to improve strategy accuracy.
Reason behind the combination of emas , cpr and vwap is it provides very good support and resistance in my trading carrier so now i brought them together in one plate
How It Works:
Mercury combines three essential elements—EMA, VWAP, and CPR—each of which plays a vital role in detecting support and resistance:
Exponential Moving Averages (EMAs): Known for their strength in providing dynamic support and resistance levels, EMAs help in identifying trends and shifts in momentum. This indicator includes a dashboard with up to nine customizable EMAs, showing whether each is acting as support or resistance based on real-time price movement.
Volume Weighted Average Price (VWAP): VWAP also provides valuable support and resistance, often regarded as a fair price level by institutional traders. Paired with EMAs, it forms a dual-layered support/resistance system, adding an additional level of confirmation.
Central Pivot Range (CPR): By combining CPR with EMAs and VWAP, Mercury highlights “traffic blocks” in your target journey. This means it identifies zones where price is likely to stall or reverse, providing additional guidance for navigating entries and exits.
Why This Combination Matters:
Using these three tools together gives you a more complete view of the market. VWAP and EMAs offer dynamic trend direction and support/resistance, while CPR pinpoints critical price zones. This combination helps you find high-probability trades, adding clarity to complex market situations and enabling stronger confirmation on trend or reversal decisions.
How to Use:
Trend Confirmation: Check if all EMAs are aligned (green for uptrend, red for downtrend), which is visible in the EMA dashboard. An alignment across VWAP, CPR, and EMAs signifies high confidence in trend direction.
Breakouts & Breakdowns: Mercury has an alert system to signal when a price breakout or breakdown occurs across VWAP, EMA1, and EMA2. This can help in spotting strong directional moves.
Example Application: In my trading, I use Mercury to identify support/resistance zones, confirming trends with EMA/VWAP alignment and using CPR as a checkpoint. I find this especially useful for day trading and swing setups.
Recommended Timeframes:
Day Trading: 5 to 15-minute charts for swift, actionable insights.
Swing Trading: 1-hour or 4-hour charts for broader trend analysis.
Note:
The Mercury Indicator should be used as a supportive tool rather than a standalone strategy, guiding you toward informed decisions in line with your trading style and goals.
EXAMPLE OF TRADE
you can see the cart of XAUUSD on 11th nov 2024
1.SHORT POSITION - TIME FRAME 15 MIN
So here for a short position you need to wait for a breakdown candle which will print in orange post the candle you need to check ema dashboard is completly red that indicates no traffic blocks in your journey to destiny target from ema's and you can take the target from nearest cpr support line
TAKEN IN XAUUSD you can see in chart of XAUUSD on 7th nov
2.LONG POSITION - TIME FRAME 15 MIN -
So here for long position you need to wait for a breakout candle from indicator thats here is blue and check all ema boxes are green and candle body should close above all the 3 lines here it is the both ema 1 and 2 and the vwap line then you can take and entry and your target will be the nearest resistance from the daily cpr
3. STOP LOSS CRITERIA
After the entry any candle close below any of the last line from entry for example we have 3 lines vwap and ema 1 and 2 lines and u have made an entry and the last line before the entry is vwap then if any candle closes below vwap can be considered as stoploss like wise in any lines
The MERCURY indicator is a comprehensive trading tool designed to enhance traders' ability to identify trends, breakouts, and reversals effectively. Created by Dr. Abhiram Sivprasad, this indicator integrates several technical elements, including Central Pivot Range (CPR), EMA crossovers, VWAP levels, and a table-based EMA dashboard, to offer a holistic trading view.
Core Components and Functionality:
Central Pivot Range (CPR):
The CPR in MERCURY provides a central pivot level along with Below Central (BC) and Top Central (TC) pivots. These levels act as potential support and resistance, useful for identifying reversal points and zones where price may consolidate.
Exponential Moving Averages (EMAs):
MERCURY includes up to nine EMAs, with a customizable EMA crossover alert system. This feature enables traders to see shifts in trend direction, especially when shorter EMAs cross longer ones.
VWAP (Volume-Weighted Average Price):
VWAP is incorporated as a dynamic support/resistance level and, combined with EMA crossovers, helps refine entry and exit points for higher probability trades.
Breakout and Breakdown Alerts:
MERCURY monitors conditions for upside and downside breakouts. For an upside breakout, all EMAs turn green and a candle closes above VWAP, EMA1, and EMA2. Similarly, all EMAs turning red, combined with a close below VWAP and EMA1/EMA2, signals a downside breakdown. Continuous alerts are available until the trend shifts.
Real-Time EMA Dashboard:
A table displays each EMA’s relative position (Above or Below), helping traders quickly gauge trend direction. Colors in the table adjust to long/short conditions based on EMA alignment.
Usage Recommendations:
Trend Confirmation:
Use the CPR, EMA alignments, and VWAP to confirm uptrends and downtrends. The table highlights trends, making it easy to spot long or short setups at a glance.
Breakout and Breakdown Alerts:
The alert system is customizable for continuous notifications on critical price levels. When all EMAs align in one direction (green for long, red for short) and the close is above or below VWAP and key EMAs, the indicator confirms a breakout/breakdown.
Adaptable for Different Styles:
Day Trading: Traders can set shorter EMAs for quick insights.
Swing Trading: Longer EMAs combined with CPR offer insights into sustained trends.
Recommended Settings:
Timeframes: MERCURY is suitable for timeframes as low as 5 minutes for intraday traders, up to daily charts for trend analysis.
Symbols: Works across forex, stocks, and crypto. Adjust EMA lengths for asset volatility.
Example Strategy:
Long Entry: When the price crosses above CPR and closes above both EMA1 and EMA2.
Short Entry: When the price falls below CPR with a close below both EMA1 and EMA2.
Composite Oscillation Indicator Based on MACD and OthersThis indicator combines various technical analysis tools to create a composite oscillator that aims to capture multiple aspects of market behavior. Here's a breakdown of its components:
* Individual RSIs (xxoo1-xxoo15): The code calculates the RSI (Relative Strength Index) of numerous indicators, including volume-based indicators (NVI, PVI, OBV, etc.), price-based indicators (CCI, CMO, etc.), and moving averages (WMA, ALMA, etc.). It also includes the RSI of the MACD histogram (xxoo14).
* Composite RSI (xxoojht): The individual RSIs are then averaged to create a composite RSI, aiming to provide a more comprehensive view of market momentum and potential turning points.
* MACD Line RSI (xxoo14): The RSI of the MACD histogram incorporates the momentum aspect of the MACD indicator into the composite measure.
* Double EMA (co, coo): The code employs two Exponential Moving Averages (EMAs) of the composite RSI, with different lengths (9 and 18 periods).
* Difference (jo): The difference between the two EMAs (co and coo) is calculated, aiming to capture the rate of change in the composite RSI.
* Smoothed Difference (xxp): The difference (jo) is further smoothed using another EMA (9 periods) to reduce noise and enhance the signal.
* RSI of Smoothed Difference (cco): Finally, the RSI is applied to the smoothed difference (xxp) to create the core output of the indicator.
Market Applications and Trading Strategies:
* Overbought/Oversold: The indicator's central line (plotted at 50) acts as a reference for overbought/oversold conditions. Values above 50 suggest potential overbought zones, while values below 50 indicate oversold zones.
* Crossovers and Divergences: Crossovers of the cco line above or below its previous bar's value can signal potential trend changes. Divergences between the cco line and price action can also provide insights into potential trend reversals.
* Emoji Markers: The code adds emoji markers ("" for bullish and "" for bearish) based on the crossover direction of the cco line. These can provide a quick visual indication of potential trend shifts.
* Colored Fill: The area between the composite RSI line (xxoojht) and the central line (50) is filled with color to visually represent the prevailing market sentiment (green for above 50, red for below 50).
Trading Strategies (Examples):
* Long Entry: Consider a long entry (buying) signal when the cco line crosses above its previous bar's value and the composite RSI (xxoojht) is below 50, suggesting a potential reversal from oversold conditions.
* Short Entry: Conversely, consider a short entry (selling) signal when the cco line crosses below its previous bar's value and the composite RSI (xxoojht) is above 50, suggesting a potential reversal from overbought conditions.
* Confirmation: Always combine the indicator's signals with other technical analysis tools and price action confirmation for better trade validation.
Additional Notes:
* The indicator offers a complex combination of multiple indicators. Consider testing and optimizing the parameters (EMAs, RSI periods) to suit your trading style and market conditions.
* Backtesting with historical data can help assess the indicator's effectiveness and identify potential strengths and weaknesses in different market environments.
* Remember that no single indicator is perfect, and the cco indicator should be used in conjunction with other forms of analysis to make informed trading decisions.
By understanding the logic behind this composite oscillator and its potential applications, you can incorporate it into your trading strategy to potentially identify trends, gauge market sentiment, and generate trading signals.
TrendWave VWAP Indicator with ATR-based SignalsThe TrendWave VWAP Indicator with ATR-Based Signals is a robust TradingView tool for traders who prioritize precision and adaptability. This indicator combines the Volume-Weighted Average Price (VWAP) with the Average True Range (ATR) to provide actionable entry and exit signals while dynamically filtering out sideways market conditions. Designed with flexibility in mind, the indicator offers extensive customization options to tailor signals and filtering to individual trading styles.
Key Features and Customizable Settings
VWAP Integration
VWAP offers a volume-weighted benchmark, ideal for tracking price trends in relation to average trading levels. Customization: Traders can enable or disable VWAP functionality via a toggle, allowing easy adjustments based on market conditions or strategy preferences.
ATR-Based Signal Levels
ATR provides volatility-based levels for precise entry and exit points by measuring average price range. Customization: Traders can set the ATR length (default: 14) and the multiplier (default: 1.5) for adjusting sensitivity. A sideways threshold can be set to control the ATR value at which the indicator pauses signals, helping to avoid low-volatility markets.
Signal Cooldown
To reduce noise in choppy conditions, a signal cooldown enforces a minimum number of bars between signals. Customization: The cooldown period (default: 10 bars) can be adjusted to match preferred trading frequency and discipline requirements.
Signal Logic
Long Entry: Activated when price crosses above the VWAP in a trending market. Cooldown applies to avoid consecutive signals.
Long Exit: Triggered when price crosses below the VWAP.
Short Entry: Initiated when price crosses below the VWAP, in non-sideways conditions.
Short Exit: Occurs when price crosses back above the VWAP following a short position.
Visual Indicators
The VWAP is displayed as a line on the chart for easy trend reference. Entry and exit signals are clearly marked with color-coded shapes, enhancing readability without clutter.
Practical Application
The TrendWave VWAP Indicator with ATR-Based Signals provides tailored entries and exits for trending markets. Its customization options make it suitable for traders who require flexibility and precision in varying market conditions. By adjusting VWAP, ATR, and cooldown parameters, users can fine-tune the indicator to suit different trading styles, making it an essential tool for disciplined trading in dynamic markets.
HBK Price Action Strategy HBKPrice Action Strategy for XAUUSD with a Favorable Risk-Reward Ratio
Understanding the Strategy:
This strategy leverages price action principles to identify potential entry and exit points for XAUUSD on a 5-minute timeframe. The core idea is to identify price action patterns that suggest a high probability of a particular direction, and then to set stop-loss and take-profit levels to manage risk and reward.
Key Price Action Patterns to Watch:
Pin Bar: A pin bar is a candlestick with a long wick in one direction and a small body in the opposite direction. It often signals a reversal in the current trend.
Inside Bar: An inside bar forms when the current candle's high is lower than the previous candle's high, and the current candle's low is higher than the previous candle's low. It often indicates indecision or a potential breakout.
Engulfing Pattern: An engulfing pattern occurs when the current candle completely engulfs the previous candle. A bullish engulfing pattern signals a potential uptrend, while a bearish engulfing pattern signals a potential downtrend.
Risk-Reward Ratio:
A favorable risk-reward ratio is crucial for long-term trading success. Aim for a minimum risk-reward ratio of 1:2, meaning you risk $1 to potentially gain $2.
Entry and Exit Signals:
Long Entry:
Identify a bullish pin bar or engulfing pattern.
Wait for a confirmation candle to close above the pin bar's high or the engulfing pattern's high.
Place a stop-loss below the recent swing low.
Set a take-profit target at a key resistance level or a multiple of the stop-loss distance.
Short Entry:
Identify a bearish pin bar or engulfing pattern.
Wait for a confirmation candle to close below the pin bar's low or the engulfing pattern's low.
Place a stop-loss above the recent swing high.
Set a take-profit target at a key support level or a multiple of the stop-loss distance.
Additional Tips:
Use Support and Resistance Levels: Identify key support and resistance levels to set your stop-loss and take-profit targets.
Consider Market Sentiment: Pay attention to market sentiment and news events that may impact gold prices.
Manage Risk: Always use stop-loss orders to limit potential losses.
Be Patient: Don't force trades. Wait for high-probability setups.
Practice Discipline: Stick to your trading plan and avoid impulsive decisions.
Remember:
Price action trading requires practice and patience.
Backtest your strategy on historical data to refine your approach.
Always adapt to changing market conditions.
By following these guidelines and practicing disciplined risk management, you can increase your chances of success in trading XAUUSD on a 5-minute timeframe.
Austin's Apex AcceleratorIndicator Name: Austin’s Apex Accelerator
Overview
The Austin’s Apex Accelerator is a highly aggressive trading indicator designed specifically for high-frequency Forex trading. It combines several technical analysis tools to identify rapid entry and exit points, making it well-suited for intraday or even lower timeframe trades. The indicator leverages a combination of exponential moving averages (EMAs), Bollinger Bands, volume filters, and volatility-adjusted ranges to detect breakout opportunities and manage risk with precision.
Core Components
Fast and Slow EMAs: The two EMAs act as trend and momentum indicators. When the shorter EMA crosses the longer EMA, it signals a change in momentum. The crossover of these EMAs often indicates a potential entry point, especially when combined with volume and volatility filters.
ATR-Based Range Filter: Using the Average True Range (ATR) for dynamic range calculation, the indicator adapts to market volatility. Higher ATR values widen the range, helping the indicator adjust for volatile conditions.
Volume Filter: A volume condition ensures that buy and sell signals only trigger when there’s significant market interest, reducing the likelihood of false signals in low-liquidity environments.
Bollinger Bands: The Bollinger Bands provide additional context for potential overbought or oversold conditions, highlighting opportunities for price reversals or trend continuations.
Key Features
Aggressive Buy and Sell Signals:
Buy Signal: A buy signal is generated when the fast EMA crosses above the slow EMA, confirming bullish momentum, and the volume condition is met. If the price is also near the lower Bollinger Band, it adds further confirmation of an oversold condition.
Sell Signal: A sell signal is generated when the fast EMA crosses below the slow EMA, confirming bearish momentum, with sufficient trading volume. If the price is near the upper Bollinger Band, it signals a potential overbought condition, which supports the sell signal.
Dynamic Range with ATR:
The indicator uses a volatility-based range, derived from the ATR, to adjust the signal sensitivity based on recent price fluctuations. This dynamic range ensures that signals are responsive in both high and low volatility conditions.
The range’s upper and lower bands act as thresholds, with trades often occurring when the price breaches these levels, signaling momentum shifts or trend reversals.
Trend Background Color:
A green background highlights bullish trends when the fast EMA is above the slow EMA.
A red background signifies bearish trends when the fast EMA is below the slow EMA, providing a visual indication of the overall market trend direction.
Trend Line:
The indicator plots a dynamic trend line that changes color based on the price's relationship to the EMAs, helping traders quickly assess the current trend’s strength and direction.
Alerts:
The indicator includes configurable alerts for buy and sell signals, allowing traders to be notified of entry opportunities without needing to monitor the chart continuously.
How to Use Austin’s Apex Accelerator
Identify Entry Points:
Buy Entry: When the fast EMA crosses above the slow EMA, a buy signal is triggered. Confirm this signal by checking if the price is near or below the lower Bollinger Band (indicating an oversold condition) and if trading volume meets the set threshold.
Sell Entry: When the fast EMA crosses below the slow EMA, a sell signal is triggered. Confirm the signal by ensuring the price is near or above the upper Bollinger Band (suggesting an overbought condition) and that volume is sufficient.
Exit Strategy:
Take Profit: The take profit level is calculated as 1.5 times the ATR from the entry point. This ensures that each trade aims to achieve a positive risk/reward ratio.
Stop Loss: The stop loss is set at 1 ATR from the entry, providing a tight risk control mechanism that limits potential losses on each trade.
Trend Identification and Background Colors:
Use the background colors to assess the trend direction. A green background indicates a bullish trend, while a red background suggests a bearish trend. These colors can help you filter signals that go against the trend, increasing the chances of a successful trade.
Volume Confirmation:
This indicator has an inbuilt volume filter to prevent trading in low-volume conditions. Look for signals only when volume exceeds the average volume threshold, which is set by the multiplier. This helps avoid trading during quieter times when false signals are more likely.
Alerts:
Set up alerts for buy and sell signals to be notified in real-time whenever a new trading opportunity arises, so you can act on high-quality signals promptly.
Practical Tips for Using Austin’s Apex Accelerator
Timeframe: Best suited for short timeframes such as 5-minute or 15-minute charts for high-frequency trading.
RSI ProfitGuard [CHE]The RSI ProfitGuard Indicator is a comprehensive tool designed to assist traders in making informed decisions by integrating the Relative Strength Index (RSI) with automated Take Profit (TP) and Stop Loss (SL) levels. This indicator enhances trading strategies by providing clear entry signals and risk management parameters.
Key Features
RSIBased Signals: Utilizes RSI crossovers and crossunders to generate trade signals.
Automated TP and SL: Automatically calculates and plots Take Profit and Stop Loss levels based on userdefined methods.
Customizable Trade Types: Supports Long trades, Short trades, or both simultaneously.
Flexible Calculation Methods: Choose between Percentagebased or ATRbased methods for determining TP and SL levels.
Visual Enhancements: Highlights overbought and oversold RSI regions with background colors and marks trade entries with arrows.
Alerts: Provides realtime alerts when TP or SL levels are reached, ensuring timely trade management.
How It Works
1. RSI Calculation: The indicator calculates the RSI value based on the specified length.
2. Trade Signals:
Long Entry: Triggered when RSI crosses above the defined crossover threshold.
Short Entry: Triggered when RSI crosses below the defined crossunder threshold.
3. TP/SL Level Determination:
Percentage Method: Sets TP and SL as a percentage above and below the entry price.
ATR Method: Sets TP and SL based on the Average True Range (ATR), allowing for dynamic adjustments based on market volatility.
4. Visualization: Draws lines and labels on the chart to indicate TP, SL, and entry points.
5. Trade Management: Monitors price movements to determine if TP or SL levels are hit, automatically managing the trade state.
Customization Options
Trade Type Selection: Choose to execute Long trades, Short trades, or both.
RSI Settings:
RSI Length: Defines the period for RSI calculation (default is 14).
Crossover Threshold: RSI level above which a Long entry is signaled (default is 65).
Crossunder Threshold: RSI level below which a Short entry is signaled (default is 35).
Delay Settings: Sets the minimum number of bars between consecutive trade signals to avoid overtrading.
TP/SL Settings:
Method Selection: Choose between Percentage or ATRbased calculations.
Percentage Values: Define the percentage for TP and SL levels.
ATR Settings: Define ATR length and multipliers for TP and SL when using the ATR method.
Visual Settings:
Line Colors and Styles: Customize the appearance of TP, SL, crossover, and crossunder lines.
Transparency: Adjust the transparency of lines for better chart visibility.
Label Offset: Position labels at a specified number of bars to the right for clarity.
Using the Indicator
1. Add to Chart: Apply the RSI ProfitGuard Indicator to your TradingView chart.
2. Configure Settings: Adjust the parameters according to your trading strategy and risk tolerance.
3. Interpret Signals:
Long Entries: Look for green upward arrows indicating potential buy opportunities.
Short Entries: Look for red downward arrows indicating potential sell opportunities.
4. Monitor TP and SL Levels: Observe the plotted lines and labels to manage your trades effectively.
5. Set Up Alerts: Enable alerts to receive notifications when TP or SL levels are reached, ensuring you can act promptly.
Benefits
Enhanced DecisionMaking: Combines RSI signals with clear risk management levels.
Time Efficiency: Automates the calculation and plotting of TP and SL, saving time and reducing manual errors.
Flexibility: Adapts to various trading styles and market conditions through customizable settings.
Risk Management: Helps in defining and adhering to risk parameters, essential for longterm trading success.
Conclusion
The RSI ProfitGuard Indicator is an invaluable tool for traders seeking to integrate technical analysis with automated risk management. Its customizable features and realtime alerts provide a robust framework for executing and managing trades with confidence.
Disclaimer
The content provided with our RSI ProfitGuard Indicator, including all code, scripts, lessons, and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell, or an offer of any financial product or service.
Key Points:
Educational Purpose:
All strategies, tools, and examples included within the RSI ProfitGuard Indicator are provided solely for illustrative purposes. They are designed to demonstrate coding techniques and the functionality of Pine Script within a trading context.
No Financial Advice:
The RSI ProfitGuard Indicator does not constitute financial advice. Users should not rely on it as a basis for making investment or trading decisions.
Hypothetical Results:
Any results or performance metrics derived from using the RSI ProfitGuard Indicator are purely hypothetical. Past performance is not indicative of future results, and there is no guarantee of profitability.
Risk Disclosure:
Trading and investing involve significant risks, including the potential loss of principal. The RSI ProfitGuard Indicator is not suitable for all persons, and users should be aware of the inherent risks involved in trading.
Professional Consultation:
Before making any trading decisions, it is strongly recommended to consult with a qualified financial professional to fully understand the risks and ensure that such decisions align with your financial situation and goals.
User Responsibility:
By using the RSI ProfitGuard Indicator, you acknowledge and agree that all trading decisions are made solely at your own discretion and risk. The developers and providers of the RSI ProfitGuard Indicator assume no responsibility or liability for any losses or damages resulting from its use.
Additional Notes:
No Guarantees:
There are no guarantees regarding the accuracy, reliability, or completeness of the RSI ProfitGuard Indicator. Users utilize the tool at their own risk.
No Endorsement:
Any mention of third-party products, services, or strategies within the RSI ProfitGuard Indicator does not constitute an endorsement or recommendation.
Updates and Modifications:
The RSI ProfitGuard Indicator may be updated or modified over time. Users are responsible for staying informed about any changes and understanding how they may impact the use of the tool.
Summary
This disclaimer clearly states that the RSI ProfitGuard Indicator is intended for educational purposes and should not be used as financial advice. It highlights the risks associated with trading, the hypothetical nature of any results, and the importance of consulting with a financial professional. Additionally, it emphasizes that users are solely responsible for their trading decisions and any outcomes that result from using the indicator.
Tips for Implementation:
Visibility:
Ensure that this disclaimer is prominently displayed wherever the RSI ProfitGuard Indicator is offered, such as on your website, within the TradingView description, or in any accompanying documentation.
Clarity:
Use clear and concise language to make sure that all users understand the limitations and responsibilities associated with using the indicator.
Legal Review:
Consider having the disclaimer reviewed by a legal professional to ensure that it meets all necessary legal requirements and adequately protects your interests.
Regular Updates:
Periodically review and update the disclaimer to reflect any changes in the indicator's functionality or in relevant laws and regulations.
Uptrick: RSI Histogram
1. **Introduction to the RSI and Moving Averages**
2. **Detailed Breakdown of the Uptrick: RSI Histogram**
3. **Calculation and Formula**
4. **Visual Representation**
5. **Customization and User Settings**
6. **Trading Strategies and Applications**
7. **Risk Management**
8. **Case Studies and Examples**
9. **Comparison with Other Indicators**
10. **Advanced Usage and Tips**
---
## 1. Introduction to the RSI and Moving Averages
### **1.1 Relative Strength Index (RSI)**
The Relative Strength Index (RSI) is a momentum oscillator developed by J. Welles Wilder and introduced in his 1978 book "New Concepts in Technical Trading Systems." It is widely used in technical analysis to measure the speed and change of price movements.
**Purpose of RSI:**
- **Identify Overbought/Oversold Conditions:** RSI values range from 0 to 100. Traditionally, values above 70 are considered overbought, while values below 30 are considered oversold. These thresholds help traders identify potential reversal points in the market.
- **Trend Strength Measurement:** RSI also indicates the strength of a trend. High RSI values suggest strong bullish momentum, while low values indicate bearish momentum.
**Calculation of RSI:**
1. **Calculate the Average Gain and Loss:** Over a specified period (e.g., 14 days), calculate the average gain and loss.
2. **Compute the Relative Strength (RS):** RS is the ratio of average gain to average loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS))
### **1.2 Moving Averages (MA)**
Moving Averages are used to smooth out price data and identify trends by filtering out short-term fluctuations. Two common types are:
**Simple Moving Average (SMA):** The average of prices over a specified number of periods.
**Exponential Moving Average (EMA):** A type of moving average that gives more weight to recent prices, making it more responsive to recent price changes.
**Smoothed Moving Average (SMA):** Used to reduce the impact of volatility and provide a clearer view of the underlying trend. The RMA, or Running Moving Average, used in the USH script is similar to an EMA but based on the average of RSI values.
## 2. Detailed Breakdown of the Uptrick: RSI Histogram
### **2.1 Indicator Overview**
The Uptrick: RSI Histogram (USH) is a technical analysis tool that combines the RSI with a moving average to create a histogram that reflects momentum and trend strength.
**Key Components:**
- **RSI Calculation:** Determines the relative strength of price movements.
- **Moving Average Application:** Smooths the RSI values to provide a clearer trend indication.
- **Histogram Plotting:** Visualizes the deviation of the smoothed RSI from a neutral level.
### **2.2 Indicator Purpose**
The primary purpose of the USH is to provide a clear visual representation of the market's momentum and trend strength. It helps traders identify:
- **Bullish and Bearish Trends:** By showing how far the smoothed RSI is from the neutral 50 level.
- **Potential Reversal Points:** By highlighting changes in momentum.
### **2.3 Indicator Design**
**RSI Moving Average (RSI MA):** The RSI MA is a smoothed version of the RSI, calculated using a running moving average. This smooths out short-term fluctuations and provides a clearer indication of the underlying trend.
**Histogram Calculation:**
- **Neutral Level:** The histogram is plotted relative to the neutral level of 50. This level represents a balanced market where neither bulls nor bears have dominance.
- **Histogram Values:** The histogram bars show the difference between the RSI MA and the neutral level. Positive values indicate bullish momentum, while negative values indicate bearish momentum.
## 3. Calculation and Formula
### **3.1 RSI Calculation**
The RSI calculation involves:
1. **Average Gain and Loss:** Calculated over the specified length (e.g., 14 periods).
2. **Relative Strength (RS):** RS = Average Gain / Average Loss.
3. **RSI Formula:** RSI = 100 - (100 / (1 + RS)).
### **3.2 Moving Average Calculation**
For the USH indicator, the RSI is smoothed using a running moving average (RMA). The RMA formula is similar to that of the EMA but is based on averaging RSI values over the specified length.
### **3.3 Histogram Calculation**
The histogram value is calculated as:
- **Histogram Value = RSI MA - 50**
**Plotting the Histogram:**
- **Positive Histogram Values:** Indicate that the RSI MA is above the neutral level, suggesting bullish momentum.
- **Negative Histogram Values:** Indicate that the RSI MA is below the neutral level, suggesting bearish momentum.
## 4. Visual Representation
### **4.1 Histogram Bars**
The histogram is plotted as bars on the chart:
- **Bullish Bars:** Colored green when the RSI MA is above 50.
- **Bearish Bars:** Colored red when the RSI MA is below 50.
### **4.2 Customization Options**
Traders can customize:
- **RSI Length:** Adjust the length of the RSI calculation to match their trading style.
- **Bull and Bear Colors:** Choose colors for histogram bars to enhance visual clarity.
### **4.3 Interpretation**
**Bullish Signal:** A histogram bar that moves from red to green indicates a potential shift to a bullish trend.
**Bearish Signal:** A histogram bar that moves from green to red indicates a potential shift to a bearish trend.
## 5. Customization and User Settings
### **5.1 Adjusting RSI Length**
The length parameter determines the number of periods over which the RSI is calculated and smoothed. Shorter lengths make the RSI more sensitive to price changes, while longer lengths provide a smoother view of trends.
### **5.2 Color Settings**
Traders can adjust:
- **Bull Color:** Color of histogram bars indicating bullish momentum.
- **Bear Color:** Color of histogram bars indicating bearish momentum.
**Customization Benefits:**
- **Visual Clarity:** Traders can choose colors that stand out against their chart’s background.
- **Personal Preference:** Adjust settings to match individual trading styles and preferences.
## 6. Trading Strategies and Applications
### **6.1 Trend Following**
**Identifying Entry Points:**
- **Bullish Entry:** When the histogram changes from red to green, it signals a potential entry point for long positions.
- **Bearish Entry:** When the histogram changes from green to red, it signals a potential entry point for short positions.
**Trend Confirmation:** The histogram helps confirm the strength of a trend. Strong, consistent green bars indicate robust bullish momentum, while strong, consistent red bars indicate robust bearish momentum.
### **6.2 Swing Trading**
**Momentum Analysis:**
- **Entry Signals:** Look for significant shifts in the histogram to time entries. A shift from bearish to bullish (red to green) indicates potential for upward movement.
- **Exit Signals:** A shift from bullish to bearish (green to red) suggests a potential weakening of the trend, signaling an exit or reversal point.
### **6.3 Range Trading**
**Market Conditions:**
- **Consolidation:** The histogram close to zero suggests a range-bound market. Traders can use this information to identify support and resistance levels.
- **Breakout Potential:** A significant move away from the neutral level may indicate a potential breakout from the range.
### **6.4 Risk Management**
**Stop-Loss Placement:**
- **Bullish Positions:** Place stop-loss orders below recent support levels when the histogram is green.
- **Bearish Positions:** Place stop-loss orders above recent resistance levels when the histogram is red.
**Position Sizing:** Adjust position sizes based on the strength of the histogram signals. Strong trends (indicated by larger histogram bars) may warrant larger positions, while weaker signals suggest smaller positions.
## 7. Risk Management
### **7.1 Importance of Risk Management**
Effective risk management is crucial for long-term trading success. It involves protecting capital, managing losses, and optimizing trade setups.
### **7.2 Using USH for Risk Management**
**Stop-Loss and Take-Profit Levels:**
- **Stop-Loss Orders:** Use the histogram to set stop-loss levels based on trend strength. For instance, place stops below support levels in bullish trends and above resistance levels in bearish trends.
- **Take-Profit Targets:** Adjust take-profit levels based on histogram changes. For example, lock in profits as the histogram starts to shift from green to red.
**Position Sizing:**
- **Trend Strength:** Scale position sizes based on the strength of histogram signals. Larger histogram bars indicate stronger trends, which may justify larger positions.
- **Volatility:** Consider market volatility and adjust position sizes to mitigate risk.
## 8. Case Studies and Examples
### **8.1 Example 1: Bullish Trend**
**Scenario:** A trader notices a transition from red to green histogram bars.
**Analysis:**
- **Entry Point:** The transition indicates a potential bullish trend. The trader decides to enter a long position.
- **Stop-Loss:** Set stop-loss below recent support levels.
- **Take-Profit:** Consider taking profits as the histogram moves back towards zero or turns red.
**Outcome:** The bullish trend continues, and the histogram remains green, providing a profitable trade setup.
### **8.2 Example 2: Bearish Trend**
**Scenario:** A trader observes a transition from green to red histogram bars.
**Analysis:**
- **Entry Point:** The transition suggests a potential
bearish trend. The trader decides to enter a short position.
- **Stop-Loss:** Set stop-loss above recent resistance levels.
- **Take-Profit:** Consider taking profits as the histogram approaches zero or shifts to green.
**Outcome:** The bearish trend continues, and the histogram remains red, resulting in a successful trade.
## 9. Comparison with Other Indicators
### **9.1 RSI vs. USH**
**RSI:** Measures momentum and identifies overbought/oversold conditions.
**USH:** Builds on RSI by incorporating a moving average and histogram to provide a clearer view of trend strength and momentum.
### **9.2 RSI vs. MACD**
**MACD (Moving Average Convergence Divergence):** A trend-following momentum indicator that uses moving averages to identify changes in trend direction.
**Comparison:**
- **USH:** Provides a smoothed RSI perspective and visual histogram for trend strength.
- **MACD:** Offers signals based on the convergence and divergence of moving averages.
### **9.3 RSI vs. Stochastic Oscillator**
**Stochastic Oscillator:** Measures the level of the closing price relative to the high-low range over a specified period.
**Comparison:**
- **USH:** Focuses on smoothed RSI values and histogram representation.
- **Stochastic Oscillator:** Provides overbought/oversold signals and potential reversals based on price levels.
## 10. Advanced Usage and Tips
### **10.1 Combining Indicators**
**Multi-Indicator Strategies:** Combine the USH with other technical indicators (e.g., Moving Averages, Bollinger Bands) for a comprehensive trading strategy.
**Confirmation Signals:** Use the USH to confirm signals from other indicators. For instance, a bullish histogram combined with a moving average crossover may provide a stronger buy signal.
### **10.2 Customization Tips**
**Adjust RSI Length:** Experiment with different RSI lengths to match various market conditions and trading styles.
**Color Preferences:** Choose histogram colors that enhance visibility and align with personal preferences.
### **10.3 Continuous Learning**
**Backtesting:** Regularly backtest the USH with historical data to refine strategies and improve accuracy.
**Education:** Stay updated with trading education and adapt strategies based on market changes and personal experiences.
Fibo Level DailyOverview
The "Fibo Level Daily" strategy is designed for trading Bitcoin (BTC) using the 1-hour timeframe. This strategy relies on Fibonacci levels calculated from the previous day's range and determines entry and exit points based on whether the previous daily candle was bullish or bearish.
How It Works
Fibonacci Levels Calculation:
The indicator calculates Fibonacci levels (0.8, 0.5, and 0.2) based on the high and low of the previous day.
The levels are calculated as follows:
0.8: This level is calculated by multiplying the difference between the previous day's high and low by 0.8 and adding the result to the previous day's low.
0.5: This is the midpoint of the previous day's range.
0.2: This level is calculated by multiplying the difference between the previous day's high and low by 0.2 and adding the result to the previous day's low.
Identifying the Previous Day's Trend:
The indicator checks if the previous daily candle closed bullish (close greater than open) or bearish (close less than open).
Setting Entry and Take Profit Levels:
If the previous daily candle was bearish:
Sell Entry: Wait for the price to rise to the 0.5 level (midpoint of the previous day's range) to enter a sell position.
Take Profit: The profit target is set at the 0.2 level.
If the previous daily candle was bullish:
Buy Entry: Wait for the price to drop to the 0.5 level (midpoint of the previous day's range) to enter a buy position.
Take Profit: The profit target is set at the 0.8 level.
Visual Representation on the Chart:
The indicator draws horizontal lines on the chart representing the Fibonacci levels (0.8, 0.5, and 0.2) from the previous day. These lines help visualize entry and exit points clearly.
Additionally, the last 15 minutes of the daily session are highlighted with a light red background to indicate the session's end.
Conditions of Use:
Timeframe: This indicator is specifically designed for use on the 1-hour timeframe.
Assets: While it can be used on any asset, it is optimized for trading Bitcoin (BTC).
Steps to Use the Indicator
Add the Indicator:
Insert the "Fibo Level Daily" indicator script into your trading platform (such as TradingView).
Select Timeframe:
Change the chart timeframe to 1 hour.
Interpret the Levels:
Observe the horizontal lines drawn on the chart representing the Fibonacci levels.
Identify whether the previous daily candle was bullish or bearish.
Wait for the Entry Price:
For a bearish previous daily candle: Wait for the price to rise to the 0.5 level to enter a sell position.
For a bullish previous daily candle: Wait for the price to drop to the 0.5 level to enter a buy position.
Set the Profit Target:
For a sell: Set your profit target at the 0.2 level.
For a buy: Set your profit target at the 0.8 level.
Execute the Trade:
Initiate the trade once the price reaches the entry level and set your take profit according to the identified trend from the previous day.
Conclusion
The "Fibo Level Daily" strategy provides a clear and precise methodology for identifying entry and exit points in Bitcoin using Fibonacci levels. By following this step-by-step guide, any trader can take advantage of market movements based on the previous day's price action, optimizing their trading opportunities on the 1-hour timeframe.
Prometheus Polarized Fractal Efficiency (PFE)This indicator uses market data to calculate Polarized Fractal Efficiency (PFE) on an asset, so traders can have a better idea of which direction it may go.
Users can control the lookback length for the fractal calculation, the lookback length for the Exponential Moving Average (EMA), and whether or not to display lines at the -50 and 50 level, or -25 and 25 level.
Polarized Fractal Efficiency:
The Polarized Fractal Efficiency (PFE) indicator is a value between -100 and 100 with 0 as a midpoint.
A PFE above 0 indicates the asset may trend higher, a PFE below 0 indicates the asset may trend lower.
There are many ways to trade with PFE, the intuitive trend riding as described above, or reversals.
Even when the PFE is above 0, if it gets high enough, it may also be an indication of a reversal. A PFE of 90 - 100, or -100 - -90, may indicate price is ready to revert the other direction. Furthermore, traders already in a position may look to breaks of other levels to be their take profit or stop out spot.
Calculation:
Pi = 100 x (Price - Price )2 + N2 / Summation, j= 0, to N-2 (Price - Price )2 + 1
If Close < Close Pi = -Pi
PFEi = EMA(Pi, M)
Where:
N = period of indicator
M = smoothing period
Citation: www.investopedia.com
Scenarios:
Inputs are (9, 5) and every display option is on.
Trend example
Step 1: A short trade appears as PFE crosses below -25. We reach a safe take profit as PFE crosses below -50. Traders can use these levels to exit as well as enter.
Step 2: On the cross above 25 there is a safe long. As the PFE value breaks 0 a safe, early take profit could be appropriate for this trade. No guarantee we would see 50.
Step 3: Long scenario at break of 25, straight to 50. Simple, straightforward setup.
Step 4: This long results in a stop loss. Once again entry as PFE crosses 25, but as we cross the 0 line it is for a loss.
Step 5: The last trade in this example is reminiscent of step 3. This is a short trade entry at break of 25 and exit at break of 50.
Traders have liberty to use the PFE value to determine spots to enter and exit trades, long or short. 25 and 50 were chosen arbitrarily, values like 10 and 60 may work as well, we encourage traders to use their own discretion along with tools.
Reversal example
Step 1: PFE is around -100, crossing below it at one point! Strong zone for a potential reversal.
Step 2: PFE crosses above 25 adding conviction.
Step 3: Option to exit at 70.
Step 4: Option to exit at 90.
There is no “one size fits all method”, this approach may be more intuitive for some users and is just as feasible as the first.
Longer trend example
Step 1: Using -50 and 50 this time instead of -25 and 25 to be safer on our entries we see a short here. Was a good entry and as the value gets closer to -70 we can safely close.
Step 2: On this candle we see a long for the break of 50. On the next candle we break the 0 line, but because of our safe entry at 50, we could hold this and only stop out at a break of -25. We get close but stay in it and close at 70.
Step 3: Break of 50 for a long once again. This time the break of 0 line occurs as we are in profit, not letting a green trade go red is a golden rule of trading, so an early exit here.
Step 4: Same at step 2, break of 50 to long and stay in it, not stopping out at break of 0 line. The PFE value eventually reaches 70 and there is a good exit.
Quicker Reversal example
Step 1: Notice a close with PFE below -90, enter long for the reversal. Then close for profit when the PFE crosses above 70.
Step 2: When the PFE breaks above 90 we have a short entry. Like the long closing it when it crosses below -70.
Step 3: This step is the same setup as step 2. As PFE breaks above 90 we have a short entry. Closing it when it crosses below -70.
Recap:
Described above are 4 different examples with many different trades. Both trend and reversal trades. The PFE value is an indicator that can be used by traders in many different ways and Prometheus encourages traders to use their own discretion along with tools and not follow indicators blindly.
Options:
Users can control the input for the lookback of the indicator. The default is 9.
The smoothing factor for the EMA is also changeable, default is 5.
Users have options to display lines at -50, -25, 25, and 50.
VWAP Suite, Session Cloud RevOverview
The VWAP Suite with Standard Deviation Strategy is a comprehensive indicator designed to help traders make informed trading decisions based on the Volume Weighted Average Price (VWAP) and its associated standard deviation bands. This indicator provides multiple VWAP calculations for different timeframes (Session, Day, Week, Month) and incorporates standard deviation bands to identify potential trade entry and exit points.
Components
VWAP Calculation:
Session VWAP: VWAP calculated based on the current trading session.
Day VWAP: VWAP calculated for the daily timeframe.
Week VWAP: VWAP calculated for the weekly timeframe.
Month VWAP: VWAP calculated for the monthly timeframe.
Standard Deviation Bands:
The indicator includes three standard deviation bands (StDev 1, StDev 2, and StDev 3) around the VWAP. These bands help identify the dispersion of price from the VWAP, providing insight into potential overbought or oversold conditions.
Additional VWAP Lines:
VWAP 2: An additional VWAP line with a customizable timeframe (Day, Week, Month).
VWAP 3: Another VWAP line for further analysis with a customizable timeframe (Day, Week, Month).
Strategy Description
The primary strategy implemented in this indicator revolves around the second standard deviation band (StDev 2). The key aspects of this strategy include:
Entry Points:
Long Entry: Consider entering a long position when the price moves below the lower StDev 2 band and then starts to revert back towards the VWAP. This indicates a potential oversold condition.
Short Entry: Consider entering a short position when the price moves above the upper StDev 2 band and then starts to revert back towards the VWAP. This indicates a potential overbought condition.
Exit Points:
Long Exit: Exit the long position when the price moves back up to the VWAP or the upper StDev 1 band, indicating a normalization of the price.
Short Exit: Exit the short position when the price moves back down to the VWAP or the lower StDev 1 band, indicating a normalization of the price.
Risk Management:
Set stop-loss levels slightly beyond the StDev 3 bands to protect against significant adverse price movements.
Use trailing stops to lock in profits as the price moves favorably.
Customization
The VWAP Suite allows for extensive customization, enabling traders to adjust the following settings:
VWAP Mode: Select the timeframe for the primary VWAP calculation (Session, Day, Week, Month).
Line Widths and Colors: Customize the line widths and colors for VWAP and standard deviation bands.
Fill Opacity: Adjust the opacity of the fill between standard deviation bands for better visual clarity.
Additional VWAPs: Enable and customize additional VWAP lines (VWAP 2 and VWAP 3) for further analysis.
Three Candle Rolling Pivot Range**Strategy Description: Three Previous Candle Rolling Pivot Range**
**Introduction:**
This trading strategy is based on the concept of the rolling pivot range calculated from the high, low, and close prices of the three previous candles. The rolling pivot range serves as a dynamic support and resistance level, and this strategy aims to capture potential trading opportunities based on the price relationship with this range.
**Strategy Components:**
**1. Rolling Pivot Range Calculation:**
- **Rolling Pivot:** Calculate the rolling pivot by averaging the high, low, and close prices of the three previous candles.
- **Second Number:** Find the midpoint between the high and low of the three previous candles.
- **Pivot Differential:** Measure the difference between the rolling pivot and the second number.
- **Rolling Pivot Range High:** Set as rolling pivot + pivot differential.
- **Rolling Pivot Range Low:** Set as rolling pivot - pivot differential.
**2. Entry Rules:**
- **Long Entry:**
- Initiate a long entry when the current close is above both the rolling pivot range high and the rolling pivot.
- Continue the long entry as long as both the rolling pivot range high and low are higher than the corresponding values of the previous candle.
- **Short Entry:**
- Start a short entry when the current close is below both the rolling pivot range high and the rolling pivot.
- Continue the short entry as long as both the rolling pivot range high and low are lower than the corresponding values of the previous candle.
**Visualization:**
- **Plotting:**
- The rolling pivot range high, rolling pivot, and rolling pivot range low are plotted on the chart for visual reference.
- Long entry points are marked with a green triangle below the corresponding candle.
- Short entry points are marked with a red triangle above the corresponding candle.
**Conclusion:**
This strategy leverages the rolling pivot range to identify potential reversal points in the market. By considering the relative position of the current price compared to the dynamic support and resistance levels, the strategy aims to capture favorable trading opportunities. However, like all trading strategies, it should be used cautiously and backtested thoroughly on historical data to ensure its effectiveness before implementation in a live trading environment. Additionally, risk management techniques should always be applied to safeguard trading capital.
Scalping EMA ADX RSI with Buy/Sell AlertsThis is a study indicator that shows the entries in the strategy seen in one of the youtube channel so it does not belong to me. I can't tell who it is because it's against the House Rules to advertise but you can find out if you look for it on youtube. Default values of oscilators and ema adjusted as suggested. He says he got the best results in 5 min timeframe but i tried to make things as modifiable as possible so you can mess around with the settings and create your own strategy for different timeframes if you'd like. Suggested to use with normal candlestick charts. The blue line below indicates the ADX is above the selected threshold set in the settings named "Trend Ready Limit". You can set alerts for Buy, Sell or Buy/Sell signal together.
The entry strategy itself is pretty straight forward.
The rules for entry are as follows, the script will check all of this on auto and will give you buy or sell signal :
Recommended time frame: 5 min
For Long Entry:
- Check if price above the set EMA (Can disable this rule if you'd like in the settings)
- RSI is in Oversold
- ADX is above set "Trend Ready" threshold (Meaning there is a trend going on)
- Price must approve the trend of previous candles. This is bullish for buy entries and bearish for sell entries.
- Enter with stop loss below last swing low with 1:1 or 1.5:1 take profit ratio.
For Short Entry:
- Check if price below the set EMA (Can disable this rule if you'd like in the settings)
- RSI is in Overbought
- ADX is above set "Trend Ready" threshold (Meaning there is a trend going on)
- Price must approve the trend of previous candles. This is bullish for buy entries and bearish for sell entries.
- Enter with stop loss above last swing high with 1:1 or 1.5:1 take profit ratio.
This is my first indicator. Let me know if you want any updates. I am not sure if i can add everything but i'll try nonetheless.
Changed: Signals will check up to 2 candles before if the RSI is below or above the set value to show signal. This is because sometimes the entry signal is right but the response might be a bit late.
RSI 30 CROSSScript will give the RSI 30 40 and 70 level for present price of the stock , when the price cross the green line RSI value will be 70 , blue line RSI value will be 40 and red line RSI value will be 30 . Helps to put entry and exit based on RSI strategy.
RED line give price for RSI 30
BLUE line give price for RSI 40
GREEN line give price for RSI 70
BLACK line give SMA 200
Strategy
Stock price should above 200 MA
price should touch RSI 30 RED line and bounce back.
Entry will be the high of candle lies on RSI 40 BLUE line.
Stop loss will be the RSI 30 price(RED line ) during entry.
Target will be the RSI 70 price ( GREEEN line) during entry.
You can take half profit at RSI 70 and trail stop loss on RSI 70 till it cross.
This will help you to find the Price for stock, when it cross RSI value 30 , 40 and 70 to place entry exit and target based on the trade strategy will follow RSI.
If you want to entry, when stock cross RSI 30 or 40 from below . You can place a stop loss limit buy order at price range .
If you want to exit, When stock cross RSI 70 . you place stock loss at green line price.
Momentum by Trading BiZonesSqueeze Momentum Indicator with EMA
Overview
The Squeeze Momentum Indicator with EMA is a powerful technical analysis tool that combines the original Squeeze Momentum concept with an Exponential Moving Average (EMA) overlay. This enhanced version helps traders identify market momentum, volatility contractions (squeezes), and potential trend reversals with greater precision.
Core Concept
The indicator operates on the principle of volatility contraction and expansion:
Squeeze Phase: When Bollinger Bands move inside the Keltner Channel, indicating low volatility and potential energy buildup
Expansion Phase: When momentum breaks out of the squeeze, signaling potential directional moves
Key Components
1. Squeeze Momentum Calculation
Formula: Momentum = Linear Regression(Close - Average Price)
Where Average Price = (Highest High + Lowest Low + SMA(Close)) / 3
Visualization: Histogram bars showing positive (green) and negative (red) momentum
Zero Line: Represents equilibrium point between buyers and sellers
2. EMA Overlay
Purpose: Smooths momentum values to identify underlying trends
Customization:
Adjustable period (default: 20)
Toggle on/off display
Customizable color and line thickness
Cross Signals: Buy/sell signals when momentum crosses above/below EMA
3. Volatility Bands
Bollinger Bands (20-period, 2 standard deviations)
Keltner Channels (20-period, 1.5 ATR multiplier)
Squeeze Detection: Visual background shading when BB are inside KC
Trading Signals
Buy Signals (Green Upward Triangle)
Momentum histogram crosses ABOVE EMA line
Occurs during or after squeeze release
Confirmed by expanding histogram bars
Sell Signals (Red Downward Triangle)
Momentum histogram crosses BELOW EMA line
Often precedes market downturns
Watch for increasing negative momentum
Squeeze Warnings (Gray Background)
Market in low volatility state
Prepare for potential breakout
Direction indicated by momentum bias
Indicator Settings
Main Parameters
Length: Period for calculations (default: 20)
Show EMA: Toggle EMA visibility
EMA Period: Smoothing period for EMA
Visual Settings
Histogram color-coding based on momentum direction
EMA line color and thickness
Signal marker size and visibility
Squeeze zone background display
Practical Applications
Trend Identification
Uptrend: Consistently positive momentum with EMA support
Downtrend: Consistently negative momentum with EMA resistance
Range-bound: Oscillating around zero line
Entry/Exit Points
Conservative Entry: Wait for squeeze release + EMA crossover
Aggressive Entry: Anticipate breakout during squeeze
Exit: Opposite crossover or momentum divergence
Risk Management
Use squeeze zones as warning periods
EMA crossovers as confirmation signals
Combine with support/resistance levels
Advanced Interpretation
Momentum Strength
Strong Bullish: Tall green bars above EMA
Weak Bullish: Short green bars near EMA
Strong Bearish: Tall red bars below EMA
Weak Bearish: Short red bars near EMA
Divergence Detection
Price makes higher high, momentum makes lower high → Bearish divergence
Price makes lower low, momentum makes higher low → Bullish divergence
Squeeze Characteristics
Long squeezes: More potential energy
Frequent squeezes: Choppy market conditions
No squeezes: High volatility, trending markets
Recommended Timeframes
Scalping: 1-15 minute charts
Day Trading: 15-minute to 4-hour charts
Swing Trading: 4-hour to daily charts
Position Trading: Daily to weekly charts
Best Practices
Confirmation
Use with volume indicators
Check higher timeframe direction
Wait for candle close confirmation
Filtering Signals
Ignore signals during extreme volatility
Require minimum bar size for crossovers
Consider market context (news, sessions)
Combination Suggestions
With RSI: Confirm overbought/oversold conditions
With Volume Profile: Identify high-volume nodes
With Support/Resistance: Key level reactions
With Trend Lines: Breakout confirmations
Limitations
Lagging indicator (based on past data)
Works best in trending markets
May give false signals in ranging markets
Requires proper risk management
Conclusion
The Squeeze Momentum Indicator with EMA provides a comprehensive view of market dynamics by combining volatility analysis, momentum measurement, and trend smoothing. Its visual clarity and customizable parameters make it suitable for traders of all experience levels seeking to identify high-probability trading opportunities during volatility contractions and expansions.
Adaptive Genesis Engine [AGE]ADAPTIVE GENESIS ENGINE (AGE)
Pure Signal Evolution Through Genetic Algorithms
Where Darwin Meets Technical Analysis
🧬 WHAT YOU'RE GETTING - THE PURE INDICATOR
This is a technical analysis indicator - it generates signals, visualizes probability, and shows you the evolutionary process in real-time. This is NOT a strategy with automatic execution - it's a sophisticated signal generation system that you control .
What This Indicator Does:
Generates Long/Short entry signals with probability scores (35-88% range)
Evolves a population of up to 12 competing strategies using genetic algorithms
Validates strategies through walk-forward optimization (train/test cycles)
Visualizes signal quality through premium gradient clouds and confidence halos
Displays comprehensive metrics via enhanced dashboard
Provides alerts for entries and exits
Works on any timeframe, any instrument, any broker
What This Indicator Does NOT Do:
Execute trades automatically
Manage positions or calculate position sizes
Place orders on your behalf
Make trading decisions for you
This is pure signal intelligence. AGE tells you when and how confident it is. You decide whether and how much to trade.
🔬 THE SCIENCE: GENETIC ALGORITHMS MEET TECHNICAL ANALYSIS
What Makes This Different - The Evolutionary Foundation
Most indicators are static - they use the same parameters forever, regardless of market conditions. AGE is alive . It maintains a population of competing strategies that evolve, adapt, and improve through natural selection principles:
Birth: New strategies spawn through crossover breeding (combining DNA from fit parents) plus random mutation for exploration
Life: Each strategy trades virtually via shadow portfolios, accumulating wins/losses, tracking drawdown, and building performance history
Selection: Strategies are ranked by comprehensive fitness scoring (win rate, expectancy, drawdown control, signal efficiency)
Death: Weak strategies are culled periodically, with elite performers (top 2 by default) protected from removal
Evolution: The gene pool continuously improves as successful traits propagate and unsuccessful ones die out
This is not curve-fitting. Each new strategy must prove itself on out-of-sample data through walk-forward validation before being trusted for live signals.
🧪 THE DNA: WHAT EVOLVES
Every strategy carries a 10-gene chromosome controlling how it interprets market data:
Signal Sensitivity Genes
Entropy Sensitivity (0.5-2.0): Weight given to market order/disorder calculations. Low values = conservative, require strong directional clarity. High values = aggressive, act on weaker order signals.
Momentum Sensitivity (0.5-2.0): Weight given to RSI/ROC/MACD composite. Controls responsiveness to momentum shifts vs. mean-reversion setups.
Structure Sensitivity (0.5-2.0): Weight given to support/resistance positioning. Determines how much price location within swing range matters.
Probability Adjustment Genes
Probability Boost (-0.10 to +0.10): Inherent bias toward aggressive (+) or conservative (-) entries. Acts as personality trait - some strategies naturally optimistic, others pessimistic.
Trend Strength Requirement (0.3-0.8): Minimum trend conviction needed before signaling. Higher values = only trades strong trends, lower values = acts in weak/sideways markets.
Volume Filter (0.5-1.5): Strictness of volume confirmation. Higher values = requires strong volume, lower values = volume less important.
Risk Management Genes
ATR Multiplier (1.5-4.0): Base volatility scaling for all price levels. Controls whether strategy uses tight or wide stops/targets relative to ATR.
Stop Multiplier (1.0-2.5): Stop loss tightness. Lower values = aggressive profit protection, higher values = more breathing room.
Target Multiplier (1.5-4.0): Profit target ambition. Lower values = quick scalping exits, higher values = swing trading holds.
Adaptation Gene
Regime Adaptation (0.0-1.0): How much strategy adjusts behavior based on detected market regime (trending/volatile/choppy). Higher values = more reactive to regime changes.
The Magic: AGE doesn't just try random combinations. Through tournament selection and fitness-weighted crossover, successful gene combinations spread through the population while unsuccessful ones fade away. Over 50-100 bars, you'll see the population converge toward genes that work for YOUR instrument and timeframe.
📊 THE SIGNAL ENGINE: THREE-LAYER SYNTHESIS
Before any strategy generates a signal, AGE calculates probability through multi-indicator confluence:
Layer 1 - Market Entropy (Information Theory)
Measures whether price movements exhibit directional order or random walk characteristics:
The Math:
Shannon Entropy = -Σ(p × log(p))
Market Order = 1 - (Entropy / 0.693)
What It Means:
High entropy = choppy, random market → low confidence signals
Low entropy = directional market → high confidence signals
Direction determined by up-move vs down-move dominance over lookback period (default: 20 bars)
Signal Output: -1.0 to +1.0 (bearish order to bullish order)
Layer 2 - Momentum Synthesis
Combines three momentum indicators into single composite score:
Components:
RSI (40% weight): Normalized to -1/+1 scale using (RSI-50)/50
Rate of Change (30% weight): Percentage change over lookback (default: 14 bars), clamped to ±1
MACD Histogram (30% weight): Fast(12) - Slow(26), normalized by ATR
Why This Matters: RSI catches mean-reversion opportunities, ROC catches raw momentum, MACD catches momentum divergence. Weighting favors RSI for reliability while keeping other perspectives.
Signal Output: -1.0 to +1.0 (strong bearish to strong bullish)
Layer 3 - Structure Analysis
Evaluates price position within swing range (default: 50-bar lookback):
Position Classification:
Bottom 20% of range = Support Zone → bullish bounce potential
Top 20% of range = Resistance Zone → bearish rejection potential
Middle 60% = Neutral Zone → breakout/breakdown monitoring
Signal Logic:
At support + bullish candle = +0.7 (strong buy setup)
At resistance + bearish candle = -0.7 (strong sell setup)
Breaking above range highs = +0.5 (breakout confirmation)
Breaking below range lows = -0.5 (breakdown confirmation)
Consolidation within range = ±0.3 (weak directional bias)
Signal Output: -1.0 to +1.0 (bearish structure to bullish structure)
Confluence Voting System
Each layer casts a vote (Long/Short/Neutral). The system requires minimum 2-of-3 agreement (configurable 1-3) before generating a signal:
Examples:
Entropy: Bullish, Momentum: Bullish, Structure: Neutral → Signal generated (2 long votes)
Entropy: Bearish, Momentum: Neutral, Structure: Neutral → No signal (only 1 short vote)
All three bullish → Signal generated with +5% probability bonus
This is the key to quality. Single indicators give too many false signals. Triple confirmation dramatically improves accuracy.
📈 PROBABILITY CALCULATION: HOW CONFIDENCE IS MEASURED
Base Probability:
Raw_Prob = 50% + (Average_Signal_Strength × 25%)
Then AGE applies strategic adjustments:
Trend Alignment:
Signal with trend: +4%
Signal against strong trend: -8%
Weak/no trend: no adjustment
Regime Adaptation:
Trending market (efficiency >50%, moderate vol): +3%
Volatile market (vol ratio >1.5x): -5%
Choppy market (low efficiency): -2%
Volume Confirmation:
Volume > 70% of 20-bar SMA: no change
Volume below threshold: -3%
Volatility State (DVS Ratio):
High vol (>1.8x baseline): -4% (reduce confidence in chaos)
Low vol (<0.7x baseline): -2% (markets can whipsaw in compression)
Moderate elevated vol (1.0-1.3x): +2% (trending conditions emerging)
Confluence Bonus:
All 3 indicators agree: +5%
2 of 3 agree: +2%
Strategy Gene Adjustment:
Probability Boost gene: -10% to +10%
Regime Adaptation gene: scales regime adjustments by 0-100%
Final Probability: Clamped between 35% (minimum) and 88% (maximum)
Why These Ranges?
Below 35% = too uncertain, better not to signal
Above 88% = unrealistic, creates overconfidence
Sweet spot: 65-80% for quality entries
🔄 THE SHADOW PORTFOLIO SYSTEM: HOW STRATEGIES COMPETE
Each active strategy maintains a virtual trading account that executes in parallel with real-time data:
Shadow Trading Mechanics
Entry Logic:
Calculate signal direction, probability, and confluence using strategy's unique DNA
Check if signal meets quality gate:
Probability ≥ configured minimum threshold (default: 65%)
Confluence ≥ configured minimum (default: 2 of 3)
Direction is not zero (must be long or short, not neutral)
Verify signal persistence:
Base requirement: 2 bars (configurable 1-5)
Adapts based on probability: high-prob signals (75%+) enter 1 bar faster, low-prob signals need 1 bar more
Adjusts for regime: trending markets reduce persistence by 1, volatile markets add 1
Apply additional filters:
Trend strength must exceed strategy's requirement gene
Regime filter: if volatile market detected, probability must be 72%+ to override
Volume confirmation required (volume > 70% of average)
If all conditions met for required persistence bars, enter shadow position at current close price
Position Management:
Entry Price: Recorded at close of entry bar
Stop Loss: ATR-based distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit: ATR-based distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Position: +1 (long) or -1 (short), only one at a time per strategy
Exit Logic:
Check if price hit stop (on low) or target (on high) on current bar
Record trade outcome in R-multiples (profit/loss normalized by ATR)
Update performance metrics:
Total trades counter incremented
Wins counter (if profit > 0)
Cumulative P&L updated
Peak equity tracked (for drawdown calculation)
Maximum drawdown from peak recorded
Enter cooldown period (default: 8 bars, configurable 3-20) before next entry allowed
Reset signal age counter to zero
Walk-Forward Tracking:
During position lifecycle, trades are categorized:
Training Phase (first 250 bars): Trade counted toward training metrics
Testing Phase (next 75 bars): Trade counted toward testing metrics (out-of-sample)
Live Phase (after WFO period): Trade counted toward overall metrics
Why Shadow Portfolios?
No lookahead bias (uses only data available at the bar)
Realistic execution simulation (entry on close, stop/target checks on high/low)
Independent performance tracking for true fitness comparison
Allows safe experimentation without risking capital
Each strategy learns from its own experience
🏆 FITNESS SCORING: HOW STRATEGIES ARE RANKED
Fitness is not just win rate. AGE uses a comprehensive multi-factor scoring system:
Core Metrics (Minimum 3 trades required)
Win Rate (30% of fitness):
WinRate = Wins / TotalTrades
Normalized directly (0.0-1.0 scale)
Total P&L (30% of fitness):
Normalized_PnL = (PnL + 300) / 600
Clamped 0.0-1.0. Assumes P&L range of -300R to +300R for normalization scale.
Expectancy (25% of fitness):
Expectancy = Total_PnL / Total_Trades
Normalized_Expectancy = (Expectancy + 30) / 60
Clamped 0.0-1.0. Rewards consistency of profit per trade.
Drawdown Control (15% of fitness):
Normalized_DD = 1 - (Max_Drawdown / 15)
Clamped 0.0-1.0. Penalizes strategies that suffer large equity retracements from peak.
Sample Size Adjustment
Quality Factor:
<50 trades: 1.0 (full weight, small sample)
50-100 trades: 0.95 (slight penalty for medium sample)
100 trades: 0.85 (larger penalty for large sample)
Why penalize more trades? Prevents strategies from gaming the system by taking hundreds of tiny trades to inflate statistics. Favors quality over quantity.
Bonus Adjustments
Walk-Forward Validation Bonus:
if (WFO_Validated):
Fitness += (WFO_Efficiency - 0.5) × 0.1
Strategies proven on out-of-sample data receive up to +10% fitness boost based on test/train efficiency ratio.
Signal Efficiency Bonus (if diagnostics enabled):
if (Signals_Evaluated > 10):
Pass_Rate = Signals_Passed / Signals_Evaluated
Fitness += (Pass_Rate - 0.1) × 0.05
Rewards strategies that generate high-quality signals passing the quality gate, not just profitable trades.
Final Fitness: Clamped at 0.0 minimum (prevents negative fitness values)
Result: Elite strategies typically achieve 0.50-0.75 fitness. Anything above 0.60 is excellent. Below 0.30 is prime candidate for culling.
🔬 WALK-FORWARD OPTIMIZATION: ANTI-OVERFITTING PROTECTION
This is what separates AGE from curve-fitted garbage indicators.
The Three-Phase Process
Every new strategy undergoes a rigorous validation lifecycle:
Phase 1 - Training Window (First 250 bars, configurable 100-500):
Strategy trades normally via shadow portfolio
All trades count toward training performance metrics
System learns which gene combinations produce profitable patterns
Tracks independently: Training_Trades, Training_Wins, Training_PnL
Phase 2 - Testing Window (Next 75 bars, configurable 30-200):
Strategy continues trading without any parameter changes
Trades now count toward testing performance metrics (separate tracking)
This is out-of-sample data - strategy has never seen these bars during "optimization"
Tracks independently: Testing_Trades, Testing_Wins, Testing_PnL
Phase 3 - Validation Check:
Minimum_Trades = 5 (configurable 3-15)
IF (Train_Trades >= Minimum AND Test_Trades >= Minimum):
WR_Efficiency = Test_WinRate / Train_WinRate
Expectancy_Efficiency = Test_Expectancy / Train_Expectancy
WFO_Efficiency = (WR_Efficiency + Expectancy_Efficiency) / 2
IF (WFO_Efficiency >= 0.55): // configurable 0.3-0.9
Strategy.Validated = TRUE
Strategy receives fitness bonus
ELSE:
Strategy receives 30% fitness penalty
ELSE:
Validation deferred (insufficient trades in one or both periods)
What Validation Means
Validated Strategy (Green "✓ VAL" in dashboard):
Performed at least 55% as well on unseen data compared to training data
Gets fitness bonus: +(efficiency - 0.5) × 0.1
Receives priority during tournament selection for breeding
More likely to be chosen as active trading strategy
Unvalidated Strategy (Orange "○ TRAIN" in dashboard):
Failed to maintain performance on test data (likely curve-fitted to training period)
Receives 30% fitness penalty (0.7x multiplier)
Makes strategy prime candidate for culling
Can still trade but with lower selection probability
Insufficient Data (continues collecting):
Hasn't completed both training and testing periods yet
OR hasn't achieved minimum trade count in both periods
Validation check deferred until requirements met
Why 55% Efficiency Threshold?
If a strategy earned 10R during training but only 5.5R during testing, it still proved an edge exists beyond random luck. Requiring 100% efficiency would be unrealistic - market conditions change between periods. But requiring >50% ensures the strategy didn't completely degrade on fresh data.
The Protection: Strategies that work great on historical data but fail on new data are automatically identified and penalized. This prevents the population from being polluted by overfitted strategies that would fail in live trading.
🌊 DYNAMIC VOLATILITY SCALING (DVS): ADAPTIVE STOP/TARGET PLACEMENT
AGE doesn't use fixed stop distances. It adapts to current volatility conditions in real-time.
Four Volatility Measurement Methods
1. ATR Ratio (Simple Method):
Current_Vol = ATR(14) / Close
Baseline_Vol = SMA(Current_Vol, 100)
Ratio = Current_Vol / Baseline_Vol
Basic comparison of current ATR to 100-bar moving average baseline.
2. Parkinson (High-Low Range Based):
For each bar: HL = log(High / Low)
Parkinson_Vol = sqrt(Σ(HL²) / (4 × Period × log(2)))
More stable than close-to-close volatility. Captures intraday range expansion without overnight gap noise.
3. Garman-Klass (OHLC Based):
HL_Term = 0.5 × ²
CO_Term = (2×log(2) - 1) × ²
GK_Vol = sqrt(Σ(HL_Term - CO_Term) / Period)
Most sophisticated estimator. Incorporates all four price points (open, high, low, close) plus gap information.
4. Ensemble Method (Default - Median of All Three):
Ratio_1 = ATR_Current / ATR_Baseline
Ratio_2 = Parkinson_Current / Parkinson_Baseline
Ratio_3 = GK_Current / GK_Baseline
DVS_Ratio = Median(Ratio_1, Ratio_2, Ratio_3)
Why Ensemble?
Takes median to avoid outliers and false spikes
If ATR jumps but range-based methods stay calm, median prevents overreaction
If one method fails, other two compensate
Most robust approach across different market conditions
Sensitivity Scaling
Scaled_Ratio = (Raw_Ratio) ^ Sensitivity
Sensitivity 0.3: Cube root - heavily dampens volatility impact
Sensitivity 0.5: Square root - moderate dampening
Sensitivity 0.7 (Default): Balanced response to volatility changes
Sensitivity 1.0: Linear - full 1:1 volatility impact
Sensitivity 1.5: Exponential - amplified response to volatility spikes
Safety Clamps: Final DVS Ratio always clamped between 0.5x and 2.5x baseline to prevent extreme position sizing or stop placement errors.
How DVS Affects Shadow Trading
Every strategy's stop and target distances are multiplied by the current DVS ratio:
Stop Loss Distance:
Stop_Distance = ATR × ATR_Mult (gene) × Stop_Mult (gene) × DVS_Ratio
Take Profit Distance:
Target_Distance = ATR × ATR_Mult (gene) × Target_Mult (gene) × DVS_Ratio
Example Scenario:
ATR = 10 points
Strategy's ATR_Mult gene = 2.5
Strategy's Stop_Mult gene = 1.5
Strategy's Target_Mult gene = 2.5
DVS_Ratio = 1.4 (40% above baseline volatility - market heating up)
Stop = 10 × 2.5 × 1.5 × 1.4 = 52.5 points (vs. 37.5 in normal vol)
Target = 10 × 2.5 × 2.5 × 1.4 = 87.5 points (vs. 62.5 in normal vol)
Result:
During volatility spikes: Stops automatically widen to avoid noise-based exits, targets extend for bigger moves
During calm periods: Stops tighten for better risk/reward, targets compress for realistic profit-taking
Strategies adapt risk management to match current market behavior
🧬 THE EVOLUTIONARY CYCLE: SPAWN, COMPETE, CULL
Initialization (Bar 1)
AGE begins with 4 seed strategies (if evolution enabled):
Seed Strategy #0 (Balanced):
All sensitivities at 1.0 (neutral)
Zero probability boost
Moderate trend requirement (0.4)
Standard ATR/stop/target multiples (2.5/1.5/2.5)
Mid-level regime adaptation (0.5)
Seed Strategy #1 (Momentum-Focused):
Lower entropy sensitivity (0.7), higher momentum (1.5)
Slight probability boost (+0.03)
Higher trend requirement (0.5)
Tighter stops (1.3), wider targets (3.0)
Seed Strategy #2 (Entropy-Driven):
Higher entropy sensitivity (1.5), lower momentum (0.8)
Slight probability penalty (-0.02)
More trend tolerant (0.6)
Wider stops (1.8), standard targets (2.5)
Seed Strategy #3 (Structure-Based):
Balanced entropy/momentum (0.8/0.9), high structure (1.4)
Slight probability boost (+0.02)
Lower trend requirement (0.35)
Moderate risk parameters (1.6/2.8)
All seeds start with WFO validation bypassed if WFO is disabled, or must validate if enabled.
Spawning New Strategies
Timing (Adaptive):
Historical phase: Every 30 bars (configurable 10-100)
Live phase: Every 200 bars (configurable 100-500)
Automatically switches to live timing when barstate.isrealtime triggers
Conditions:
Current population < max population limit (default: 8, configurable 4-12)
At least 2 active strategies exist (need parents)
Available slot in population array
Selection Process:
Run tournament selection 3 times with different seeds
Each tournament: randomly sample active strategies, pick highest fitness
Best from 3 tournaments becomes Parent 1
Repeat independently for Parent 2
Ensures fit parents but maintains diversity
Crossover Breeding:
For each of 10 genes:
Parent1_Fitness = fitness
Parent2_Fitness = fitness
Weight1 = Parent1_Fitness / (Parent1_Fitness + Parent2_Fitness)
Gene1 = parent1's value
Gene2 = parent2's value
Child_Gene = Weight1 × Gene1 + (1 - Weight1) × Gene2
Fitness-weighted crossover ensures fitter parent contributes more genetic material.
Mutation:
For each gene in child:
IF (random < mutation_rate):
Gene_Range = GENE_MAX - GENE_MIN
Noise = (random - 0.5) × 2 × mutation_strength × Gene_Range
Mutated_Gene = Clamp(Child_Gene + Noise, GENE_MIN, GENE_MAX)
Historical mutation rate: 20% (aggressive exploration)
Live mutation rate: 8% (conservative stability)
Mutation strength: 12% of gene range (configurable 5-25%)
Initialization of New Strategy:
Unique ID assigned (total_spawned counter)
Parent ID recorded
Generation = max(parent generations) + 1
Birth bar recorded (for age tracking)
All performance metrics zeroed
Shadow portfolio reset
WFO validation flag set to false (must prove itself)
Result: New strategy with hybrid DNA enters population, begins trading in next bar.
Competition (Every Bar)
All active strategies:
Calculate their signal based on unique DNA
Check quality gate with their thresholds
Manage shadow positions (entries/exits)
Update performance metrics
Recalculate fitness score
Track WFO validation progress
Strategies compete indirectly through fitness ranking - no direct interaction.
Culling Weak Strategies
Timing (Adaptive):
Historical phase: Every 60 bars (configurable 20-200, should be 2x spawn interval)
Live phase: Every 400 bars (configurable 200-1000, should be 2x spawn interval)
Minimum Adaptation Score (MAS):
Initial MAS = 0.10
MAS decays: MAS × 0.995 every cull cycle
Minimum MAS = 0.03 (floor)
MAS represents the "survival threshold" - strategies below this fitness level are vulnerable.
Culling Conditions (ALL must be true):
Population > minimum population (default: 3, configurable 2-4)
At least one strategy has fitness < MAS
Strategy's age > culling interval (prevents premature culling of new strategies)
Strategy is not in top N elite (default: 2, configurable 1-3)
Culling Process:
Find worst strategy:
For each active strategy:
IF (age > cull_interval):
Fitness = base_fitness
IF (not WFO_validated AND WFO_enabled):
Fitness × 0.7 // 30% penalty for unvalidated
IF (Fitness < MAS AND Fitness < worst_fitness_found):
worst_strategy = this_strategy
worst_fitness = Fitness
IF (worst_strategy found):
Count elite strategies with fitness > worst_fitness
IF (elite_count >= elite_preservation_count):
Deactivate worst_strategy (set active flag = false)
Increment total_culled counter
Elite Protection:
Even if a strategy's fitness falls below MAS, it survives if fewer than N strategies are better. This prevents culling when population is generally weak.
Result: Weak strategies removed from population, freeing slots for new spawns. Gene pool improves over time.
Selection for Display (Every Bar)
AGE chooses one strategy to display signals:
Best fitness = -1
Selected = none
For each active strategy:
Fitness = base_fitness
IF (WFO_validated):
Fitness × 1.3 // 30% bonus for validated strategies
IF (Fitness > best_fitness):
best_fitness = Fitness
selected_strategy = this_strategy
Display selected strategy's signals on chart
Result: Only the highest-fitness (optionally validated-boosted) strategy's signals appear as chart markers. Other strategies trade invisibly in shadow portfolios.
🎨 PREMIUM VISUALIZATION SYSTEM
AGE includes sophisticated visual feedback that standard indicators lack:
1. Gradient Probability Cloud (Optional, Default: ON)
Multi-layer gradient showing signal buildup 2-3 bars before entry:
Activation Conditions:
Signal persistence > 0 (same directional signal held for multiple bars)
Signal probability ≥ minimum threshold (65% by default)
Signal hasn't yet executed (still in "forming" state)
Visual Construction:
7 gradient layers by default (configurable 3-15)
Each layer is a line-fill pair (top line, bottom line, filled between)
Layer spacing: 0.3 to 1.0 × ATR above/below price
Outer layers = faint, inner layers = bright
Color transitions from base to intense based on layer position
Transparency scales with probability (high prob = more opaque)
Color Selection:
Long signals: Gradient from theme.gradient_bull_mid to theme.gradient_bull_strong
Short signals: Gradient from theme.gradient_bear_mid to theme.gradient_bear_strong
Base transparency: 92%, reduces by up to 8% for high-probability setups
Dynamic Behavior:
Cloud grows/shrinks as signal persistence increases/decreases
Redraws every bar while signal is forming
Disappears when signal executes or invalidates
Performance Note: Computationally expensive due to linefill objects. Disable or reduce layers if chart performance degrades.
2. Population Fitness Ribbon (Optional, Default: ON)
Histogram showing fitness distribution across active strategies:
Activation: Only draws on last bar (barstate.islast) to avoid historical clutter
Visual Construction:
10 histogram layers by default (configurable 5-20)
Plots 50 bars back from current bar
Positioned below price at: lowest_low(100) - 1.5×ATR (doesn't interfere with price action)
Each layer represents a fitness threshold (evenly spaced min to max fitness)
Layer Logic:
For layer_num from 0 to ribbon_layers:
Fitness_threshold = min_fitness + (max_fitness - min_fitness) × (layer / layers)
Count strategies with fitness ≥ threshold
Height = ATR × 0.15 × (count / total_active)
Y_position = base_level + ATR × 0.2 × layer
Color = Gradient from weak to strong based on layer position
Line_width = Scaled by height (taller = thicker)
Visual Feedback:
Tall, bright ribbon = healthy population, many fit strategies at high fitness levels
Short, dim ribbon = weak population, few strategies achieving good fitness
Ribbon compression (layers close together) = population converging to similar fitness
Ribbon spread = diverse fitness range, active selection pressure
Use Case: Quick visual health check without opening dashboard. Ribbon growing upward over time = population improving.
3. Confidence Halo (Optional, Default: ON)
Circular polyline around entry signals showing probability strength:
Activation: Draws when new position opens (shadow_position changes from 0 to ±1)
Visual Construction:
20-segment polyline forming approximate circle
Center: Low - 0.5×ATR (long) or High + 0.5×ATR (short)
Radius: 0.3×ATR (low confidence) to 1.0×ATR (elite confidence)
Scales with: (probability - min_probability) / (1.0 - min_probability)
Color Coding:
Elite (85%+): Cyan (theme.conf_elite), large radius, minimal transparency (40%)
Strong (75-85%): Strong green (theme.conf_strong), medium radius, moderate transparency (50%)
Good (65-75%): Good green (theme.conf_good), smaller radius, more transparent (60%)
Moderate (<65%): Moderate green (theme.conf_moderate), tiny radius, very transparent (70%)
Technical Detail:
Uses chart.point array with index-based positioning
5-bar horizontal spread for circular appearance (±5 bars from entry)
Curved=false (Pine Script polyline limitation)
Fill color matches line color but more transparent (88% vs line's transparency)
Purpose: Instant visual probability assessment. No need to check dashboard - halo size/brightness tells the story.
4. Evolution Event Markers (Optional, Default: ON)
Visual indicators of genetic algorithm activity:
Spawn Markers (Diamond, Cyan):
Plots when total_spawned increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.spawn_marker (cyan/bright blue)
Size: tiny
Indicates new strategy just entered population
Cull Markers (X-Cross, Red):
Plots when total_culled increases on current bar
Location: bottom of chart (location.bottom)
Color: theme.cull_marker (red/pink)
Size: tiny
Indicates weak strategy just removed from population
What It Tells You:
Frequent spawning early = population building, active exploration
Frequent culling early = high selection pressure, weak strategies dying fast
Balanced spawn/cull = healthy evolutionary churn
No markers for long periods = stable population (evolution plateaued or optimal genes found)
5. Entry/Exit Markers
Clear visual signals for selected strategy's trades:
Long Entry (Triangle Up, Green):
Plots when selected strategy opens long position (position changes 0 → +1)
Location: below bar (location.belowbar)
Color: theme.long_primary (green/cyan depending on theme)
Transparency: Scales with probability:
Elite (85%+): 0% (fully opaque)
Strong (75-85%): 10%
Good (65-75%): 20%
Acceptable (55-65%): 35%
Size: small
Short Entry (Triangle Down, Red):
Plots when selected strategy opens short position (position changes 0 → -1)
Location: above bar (location.abovebar)
Color: theme.short_primary (red/pink depending on theme)
Transparency: Same scaling as long entries
Size: small
Exit (X-Cross, Orange):
Plots when selected strategy closes position (position changes ±1 → 0)
Location: absolute (at actual exit price if stop/target lines enabled)
Color: theme.exit_color (orange/yellow depending on theme)
Transparency: 0% (fully opaque)
Size: tiny
Result: Clean, probability-scaled markers that don't clutter chart but convey essential information.
6. Stop Loss & Take Profit Lines (Optional, Default: ON)
Visual representation of shadow portfolio risk levels:
Stop Loss Line:
Plots when selected strategy has active position
Level: shadow_stop value from selected strategy
Color: theme.short_primary with 60% transparency (red/pink, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Take Profit Line:
Plots when selected strategy has active position
Level: shadow_target value from selected strategy
Color: theme.long_primary with 60% transparency (green, subtle)
Width: 2
Style: plot.style_linebr (breaks when no position)
Purpose:
Shows where shadow portfolio would exit for stop/target
Helps visualize strategy's risk/reward ratio
Useful for manual traders to set similar levels
Disable for cleaner chart (recommended for presentations)
7. Dynamic Trend EMA
Gradient-colored trend line that visualizes trend strength:
Calculation:
EMA(close, trend_length) - default 50 period (configurable 20-100)
Slope calculated over 10 bars: (current_ema - ema ) / ema × 100
Color Logic:
Trend_direction:
Slope > 0.1% = Bullish (1)
Slope < -0.1% = Bearish (-1)
Otherwise = Neutral (0)
Trend_strength = abs(slope)
Color = Gradient between:
- Neutral color (gray/purple)
- Strong bullish (bright green) if direction = 1
- Strong bearish (bright red) if direction = -1
Gradient factor = trend_strength (0 to 1+ scale)
Visual Behavior:
Faint gray/purple = weak/no trend (choppy conditions)
Light green/red = emerging trend (low strength)
Bright green/red = strong trend (high conviction)
Color intensity = trend strength magnitude
Transparency: 50% (subtle, doesn't overpower price action)
Purpose: Subconscious awareness of trend state without checking dashboard or indicators.
8. Regime Background Tinting (Subtle)
Ultra-low opacity background color indicating detected market regime:
Regime Detection:
Efficiency = directional_movement / total_range (over trend_length bars)
Vol_ratio = current_volatility / average_volatility
IF (efficiency > 0.5 AND vol_ratio < 1.3):
Regime = Trending (1)
ELSE IF (vol_ratio > 1.5):
Regime = Volatile (2)
ELSE:
Regime = Choppy (0)
Background Colors:
Trending: theme.regime_trending (dark green, 92-93% transparency)
Volatile: theme.regime_volatile (dark red, 93% transparency)
Choppy: No tint (normal background)
Purpose:
Subliminal regime awareness
Helps explain why signals are/aren't generating
Trending = ideal conditions for AGE
Volatile = fewer signals, higher thresholds applied
Choppy = mixed signals, lower confidence
Important: Extremely subtle by design. Not meant to be obvious, just subconscious context.
📊 ENHANCED DASHBOARD
Comprehensive real-time metrics in single organized panel (top-right position):
Dashboard Structure (5 columns × 14 rows)
Header Row:
Column 0: "🧬 AGE PRO" + phase indicator (🔴 LIVE or ⏪ HIST)
Column 1: "POPULATION"
Column 2: "PERFORMANCE"
Column 3: "CURRENT SIGNAL"
Column 4: "ACTIVE STRATEGY"
Column 0: Market State
Regime (📈 TREND / 🌊 CHAOS / ➖ CHOP)
DVS Ratio (current volatility scaling factor, format: #.##)
Trend Direction (▲ BULL / ▼ BEAR / ➖ FLAT with color coding)
Trend Strength (0-100 scale, format: #.##)
Column 1: Population Metrics
Active strategies (count / max_population)
Validated strategies (WFO passed / active total)
Current generation number
Total spawned (all-time strategy births)
Total culled (all-time strategy deaths)
Column 2: Aggregate Performance
Total trades across all active strategies
Aggregate win rate (%) - color-coded:
Green (>55%)
Orange (45-55%)
Red (<45%)
Total P&L in R-multiples - color-coded by positive/negative
Best fitness score in population (format: #.###)
MAS - Minimum Adaptation Score (cull threshold, format: #.###)
Column 3: Current Signal Status
Status indicator:
"▲ LONG" (green) if selected strategy in long position
"▼ SHORT" (red) if selected strategy in short position
"⏳ FORMING" (orange) if signal persisting but not yet executed
"○ WAITING" (gray) if no active signal
Confidence percentage (0-100%, format: #.#%)
Quality assessment:
"🔥 ELITE" (cyan) for 85%+ probability
"✓ STRONG" (bright green) for 75-85%
"○ GOOD" (green) for 65-75%
"- LOW" (dim) for <65%
Confluence score (X/3 format)
Signal age:
"X bars" if signal forming
"IN TRADE" if position active
"---" if no signal
Column 4: Selected Strategy Details
Strategy ID number (#X format)
Validation status:
"✓ VAL" (green) if WFO validated
"○ TRAIN" (orange) if still in training/testing phase
Generation number (GX format)
Personal fitness score (format: #.### with color coding)
Trade count
P&L and win rate (format: #.#R (##%) with color coding)
Color Scheme:
Panel background: theme.panel_bg (dark, low opacity)
Panel headers: theme.panel_header (slightly lighter)
Primary text: theme.text_primary (bright, high contrast)
Secondary text: theme.text_secondary (dim, lower contrast)
Positive metrics: theme.metric_positive (green)
Warning metrics: theme.metric_warning (orange)
Negative metrics: theme.metric_negative (red)
Special markers: theme.validated_marker, theme.spawn_marker
Update Frequency: Only on barstate.islast (current bar) to minimize CPU usage
Purpose:
Quick overview of entire system state
No need to check multiple indicators
Trading decisions informed by population health, regime state, and signal quality
Transparency into what AGE is thinking
🔍 DIAGNOSTICS PANEL (Optional, Default: OFF)
Detailed signal quality tracking for optimization and debugging:
Panel Structure (3 columns × 8 rows)
Position: Bottom-right corner (doesn't interfere with main dashboard)
Header Row:
Column 0: "🔍 DIAGNOSTICS"
Column 1: "COUNT"
Column 2: "%"
Metrics Tracked (for selected strategy only):
Total Evaluated:
Every signal that passed initial calculation (direction ≠ 0)
Represents total opportunities considered
✓ Passed:
Signals that passed quality gate and executed
Green color coding
Percentage of evaluated signals
Rejection Breakdown:
⨯ Probability:
Rejected because probability < minimum threshold
Most common rejection reason typically
⨯ Confluence:
Rejected because confluence < minimum required (e.g., only 1 of 3 indicators agreed)
⨯ Trend:
Rejected because signal opposed strong trend
Indicates counter-trend protection working
⨯ Regime:
Rejected because volatile regime detected and probability wasn't high enough to override
Shows regime filter in action
⨯ Volume:
Rejected because volume < 70% of 20-bar average
Indicates volume confirmation requirement
Color Coding:
Passed count: Green (success metric)
Rejection counts: Red (failure metrics)
Percentages: Gray (neutral, informational)
Performance Cost: Slight CPU overhead for tracking counters. Disable when not actively optimizing settings.
How to Use Diagnostics
Scenario 1: Too Few Signals
Evaluated: 200
Passed: 10 (5%)
⨯ Probability: 120 (60%)
⨯ Confluence: 40 (20%)
⨯ Others: 30 (15%)
Diagnosis: Probability threshold too high for this strategy's DNA.
Solution: Lower min probability from 65% to 60%, or allow strategy more time to evolve better DNA.
Scenario 2: Too Many False Signals
Evaluated: 200
Passed: 80 (40%)
Strategy win rate: 45%
Diagnosis: Quality gate too loose, letting low-quality signals through.
Solution: Raise min probability to 70%, or increase min confluence to 3 (all indicators must agree).
Scenario 3: Regime-Specific Issues
⨯ Regime: 90 (45% of rejections)
Diagnosis: Frequent volatile regime detection blocking otherwise good signals.
Solution: Either accept fewer trades during chaos (recommended), or disable regime filter if you want signals regardless of market state.
Optimization Workflow:
Enable diagnostics
Run 200+ bars
Analyze rejection patterns
Adjust settings based on data
Re-run and compare pass rate
Disable diagnostics when satisfied
⚙️ CONFIGURATION GUIDE
🧬 Evolution Engine Settings
Enable AGE Evolution (Default: ON):
ON: Full genetic algorithm (recommended for best results)
OFF: Uses only 4 seed strategies, no spawning/culling (static population for comparison testing)
Max Population (4-12, Default: 8):
Higher = more diversity, more exploration, slower performance
Lower = faster computation, less exploration, risk of premature convergence
Sweet spot: 6-8 for most use cases
4 = minimum for meaningful evolution
12 = maximum before diminishing returns
Min Population (2-4, Default: 3):
Safety floor - system never culls below this count
Prevents population extinction during harsh selection
Should be at least half of max population
Elite Preservation (1-3, Default: 2):
Top N performers completely immune to culling
Ensures best genes always survive
1 = minimal protection, aggressive selection
2 = balanced (recommended)
3 = conservative, slower gene pool turnover
Historical: Spawn Interval (10-100, Default: 30):
Bars between spawning new strategies during historical data
Lower = faster evolution, more exploration
Higher = slower evolution, more evaluation time per strategy
30 bars = ~1-2 hours on 15min chart
Historical: Cull Interval (20-200, Default: 60):
Bars between culling weak strategies during historical data
Should be 2x spawn interval for balanced churn
Lower = aggressive selection pressure
Higher = patient evaluation
Live: Spawn Interval (100-500, Default: 200):
Bars between spawning during live trading
Much slower than historical for stability
Prevents population chaos during live trading
200 bars = ~1.5 trading days on 15min chart
Live: Cull Interval (200-1000, Default: 400):
Bars between culling during live trading
Should be 2x live spawn interval
Conservative removal during live trading
Historical: Mutation Rate (0.05-0.40, Default: 0.20):
Probability each gene mutates during breeding (20% = 2 out of 10 genes on average)
Higher = more exploration, slower convergence
Lower = more exploitation, faster convergence but risk of local optima
20% balances exploration vs exploitation
Live: Mutation Rate (0.02-0.20, Default: 0.08):
Mutation rate during live trading
Much lower for stability (don't want population to suddenly degrade)
8% = mostly inherits parent genes with small tweaks
Mutation Strength (0.05-0.25, Default: 0.12):
How much genes change when mutated (% of gene's total range)
0.05 = tiny nudges (fine-tuning)
0.12 = moderate jumps (recommended)
0.25 = large leaps (aggressive exploration)
Example: If gene range is 0.5-2.0, 12% strength = ±0.18 possible change
📈 Signal Quality Settings
Min Signal Probability (0.55-0.80, Default: 0.65):
Quality gate threshold - signals below this never generate
0.55-0.60 = More signals, accept lower confidence (higher risk)
0.65 = Institutional-grade balance (recommended)
0.70-0.75 = Fewer but higher-quality signals (conservative)
0.80+ = Very selective, very few signals (ultra-conservative)
Min Confluence Score (1-3, Default: 2):
Required indicator agreement before signal generates
1 = Any single indicator can trigger (not recommended - too many false signals)
2 = Requires 2 of 3 indicators agree (RECOMMENDED for balance)
3 = All 3 must agree (very selective, few signals, high quality)
Base Persistence Bars (1-5, Default: 2):
Base bars signal must persist before entry
System adapts automatically:
High probability signals (75%+) enter 1 bar faster
Low probability signals (<68%) need 1 bar more
Trending regime: -1 bar (faster entries)
Volatile regime: +1 bar (more confirmation)
1 = Immediate entry after quality gate (responsive but prone to whipsaw)
2 = Balanced confirmation (recommended)
3-5 = Patient confirmation (slower but more reliable)
Cooldown After Trade (3-20, Default: 8):
Bars to wait after exit before next entry allowed
Prevents overtrading and revenge trading
3 = Minimal cooldown (active trading)
8 = Balanced (recommended)
15-20 = Conservative (position trading)
Entropy Length (10-50, Default: 20):
Lookback period for market order/disorder calculation
Lower = more responsive to regime changes (noisy)
Higher = more stable regime detection (laggy)
20 = works across most timeframes
Momentum Length (5-30, Default: 14):
Period for RSI/ROC calculations
14 = standard (RSI default)
Lower = more signals, less reliable
Higher = fewer signals, more reliable
Structure Length (20-100, Default: 50):
Lookback for support/resistance swing range
20 = short-term swings (day trading)
50 = medium-term structure (recommended)
100 = major structure (position trading)
Trend EMA Length (20-100, Default: 50):
EMA period for trend detection and direction bias
20 = short-term trend (responsive)
50 = medium-term trend (recommended)
100 = long-term trend (position trading)
ATR Period (5-30, Default: 14):
Period for volatility measurement
14 = standard ATR
Lower = more responsive to vol changes
Higher = smoother vol calculation
📊 Volatility Scaling (DVS) Settings
Enable DVS (Default: ON):
Dynamic volatility scaling for adaptive stop/target placement
Highly recommended to leave ON
OFF only for testing fixed-distance stops
DVS Method (Default: Ensemble):
ATR Ratio: Simple, fast, single-method (good for beginners)
Parkinson: High-low range based (good for intraday)
Garman-Klass: OHLC based (sophisticated, considers gaps)
Ensemble: Median of all three (RECOMMENDED - most robust)
DVS Memory (20-200, Default: 100):
Lookback for baseline volatility comparison
20 = very responsive to vol changes (can overreact)
100 = balanced adaptation (recommended)
200 = slow, stable baseline (minimizes false vol signals)
DVS Sensitivity (0.3-1.5, Default: 0.7):
How much volatility affects scaling (power-law exponent)
0.3 = Conservative, heavily dampens vol impact (cube root)
0.5 = Moderate dampening (square root)
0.7 = Balanced response (recommended)
1.0 = Linear, full 1:1 vol response
1.5 = Aggressive, amplified response (exponential)
🔬 Walk-Forward Optimization Settings
Enable WFO (Default: ON):
Out-of-sample validation to prevent overfitting
Highly recommended to leave ON
OFF only for testing or if you want unvalidated strategies
Training Window (100-500, Default: 250):
Bars for in-sample optimization
100 = fast validation, less data (risky)
250 = balanced (recommended) - about 1-2 months on daily, 1-2 weeks on 15min
500 = patient validation, more data (conservative)
Testing Window (30-200, Default: 75):
Bars for out-of-sample validation
Should be ~30% of training window
30 = minimal test (fast validation)
75 = balanced (recommended)
200 = extensive test (very conservative)
Min Trades for Validation (3-15, Default: 5):
Required trades in BOTH training AND testing periods
3 = minimal sample (risky, fast validation)
5 = balanced (recommended)
10+ = conservative (slow validation, high confidence)
WFO Efficiency Threshold (0.3-0.9, Default: 0.55):
Minimum test/train performance ratio required
0.30 = Very loose (test must be 30% as good as training)
0.55 = Balanced (recommended) - test must be 55% as good
0.70+ = Strict (test must closely match training)
Higher = fewer validated strategies, lower risk of overfitting
🎨 Premium Visuals Settings
Visual Theme:
Neon Genesis: Cyberpunk aesthetic (cyan/magenta/purple)
Carbon Fiber: Industrial look (blue/red/gray)
Quantum Blue: Quantum computing (blue/purple/pink)
Aurora: Northern lights (teal/orange/purple)
⚡ Gradient Probability Cloud (Default: ON):
Multi-layer gradient showing signal buildup
Turn OFF if chart lags or for cleaner look
Cloud Gradient Layers (3-15, Default: 7):
More layers = smoother gradient, more CPU intensive
Fewer layers = faster, blockier appearance
🎗️ Population Fitness Ribbon (Default: ON):
Histogram showing fitness distribution
Turn OFF for cleaner chart
Ribbon Layers (5-20, Default: 10):
More layers = finer fitness detail
Fewer layers = simpler histogram
⭕ Signal Confidence Halo (Default: ON):
Circular indicator around entry signals
Size/brightness scales with probability
Minimal performance cost
🔬 Evolution Event Markers (Default: ON):
Diamond (spawn) and X (cull) markers
Shows genetic algorithm activity
Minimal performance cost
🎯 Stop/Target Lines (Default: ON):
Shows shadow portfolio stop/target levels
Turn OFF for cleaner chart (recommended for screenshots/presentations)
📊 Enhanced Dashboard (Default: ON):
Comprehensive metrics panel
Should stay ON unless you want zero overlays
🔍 Diagnostics Panel (Default: OFF):
Detailed signal rejection tracking
Turn ON when optimizing settings
Turn OFF during normal use (slight performance cost)
📈 USAGE WORKFLOW - HOW TO USE THIS INDICATOR
Phase 1: Initial Setup & Learning
Add AGE to your chart
Recommended timeframes: 15min, 30min, 1H (best signal-to-noise ratio)
Works on: 5min (day trading), 4H (swing trading), Daily (position trading)
Load 1000+ bars for sufficient evolution history
Let the population evolve (100+ bars minimum)
First 50 bars: Random exploration, poor results expected
Bars 50-150: Population converging, fitness improving
Bars 150+: Stable performance, validated strategies emerging
Watch the dashboard metrics
Population should grow toward max capacity
Generation number should advance regularly
Validated strategies counter should increase
Best fitness should trend upward toward 0.50-0.70 range
Observe evolution markers
Diamond markers (cyan) = new strategies spawning
X markers (red) = weak strategies being culled
Frequent early activity = healthy evolution
Activity slowing = population stabilizing
Be patient. Evolution takes time. Don't judge performance before 150+ bars.
Phase 2: Signal Observation
Watch signals form
Gradient cloud builds up 2-3 bars before entry
Cloud brightness = probability strength
Cloud thickness = signal persistence
Check signal quality
Look at confidence halo size when entry marker appears
Large bright halo = elite setup (85%+)
Medium halo = strong setup (75-85%)
Small halo = good setup (65-75%)
Verify market conditions
Check trend EMA color (green = uptrend, red = downtrend, gray = choppy)
Check background tint (green = trending, red = volatile, clear = choppy)
Trending background + aligned signal = ideal conditions
Review dashboard signal status
Current Signal column shows:
Status (Long/Short/Forming/Waiting)
Confidence % (actual probability value)
Quality assessment (Elite/Strong/Good)
Confluence score (2/3 or 3/3 preferred)
Only signals meeting ALL quality gates appear on chart. If you're not seeing signals, population is either still learning or market conditions aren't suitable.
Phase 3: Manual Trading Execution
When Long Signal Fires:
Verify confidence level (dashboard or halo size)
Confirm trend alignment (EMA sloping up, green color)
Check regime (preferably trending or choppy, avoid volatile)
Enter long manually on your broker platform
Set stop loss at displayed stop line level (if lines enabled), or use your own risk management
Set take profit at displayed target line level, or trail manually
Monitor position - exit if X marker appears (signal reversal)
When Short Signal Fires:
Same verification process
Confirm downtrend (EMA sloping down, red color)
Enter short manually
Use displayed stop/target levels or your own
AGE tells you WHEN and HOW CONFIDENT. You decide WHETHER and HOW MUCH.
Phase 4: Set Up Alerts (Never Miss a Signal)
Right-click on indicator name in legend
Select "Add Alert"
Choose condition:
"AGE Long" = Long entry signal fired
"AGE Short" = Short entry signal fired
"AGE Exit" = Position reversal/exit signal
Set notification method:
Sound alert (popup on chart)
Email notification
Webhook to phone/trading platform
Mobile app push notification
Name the alert (e.g., "AGE BTCUSD 15min Long")
Save alert
Recommended: Set alerts for both long and short, enable mobile push notifications. You'll get alerted in real-time even if not watching charts.
Phase 5: Monitor Population Health
Weekly Review:
Check dashboard Population column:
Active count should be near max (6-8 of 8)
Validated count should be >50% of active
Generation should be advancing (1-2 per week typical)
Check dashboard Performance column:
Aggregate win rate should be >50% (target: 55-65%)
Total P&L should be positive (may fluctuate)
Best fitness should be >0.50 (target: 0.55-0.70)
MAS should be declining slowly (normal adaptation)
Check Active Strategy column:
Selected strategy should be validated (✓ VAL)
Personal fitness should match best fitness
Trade count should be accumulating
Win rate should be >50%
Warning Signs:
Zero validated strategies after 300+ bars = settings too strict or market unsuitable
Best fitness stuck <0.30 = population struggling, consider parameter adjustment
No spawning/culling for 200+ bars = evolution stalled (may be optimal or need reset)
Aggregate win rate <45% sustained = system not working on this instrument/timeframe
Health Check Pass:
50%+ strategies validated
Best fitness >0.50
Aggregate win rate >52%
Regular spawn/cull activity
Selected strategy validated
Phase 6: Optimization (If Needed)
Enable Diagnostics Panel (bottom-right) for data-driven tuning:
Problem: Too Few Signals
Evaluated: 200
Passed: 8 (4%)
⨯ Probability: 140 (70%)
Solutions:
Lower min probability: 65% → 60% or 55%
Reduce min confluence: 2 → 1
Lower base persistence: 2 → 1
Increase mutation rate temporarily to explore new genes
Check if regime filter is blocking signals (⨯ Regime high?)
Problem: Too Many False Signals
Evaluated: 200
Passed: 90 (45%)
Win rate: 42%
Solutions:
Raise min probability: 65% → 70% or 75%
Increase min confluence: 2 → 3
Raise base persistence: 2 → 3
Enable WFO if disabled (validates strategies before use)
Check if volume filter is being ignored (⨯ Volume low?)
Problem: Counter-Trend Losses
⨯ Trend: 5 (only 5% rejected)
Losses often occur against trend
Solutions:
System should already filter trend opposition
May need stronger trend requirement
Consider only taking signals aligned with higher timeframe trend
Use longer trend EMA (50 → 100)
Problem: Volatile Market Whipsaws
⨯ Regime: 100 (50% rejected by volatile regime)
Still getting stopped out frequently
Solutions:
System is correctly blocking volatile signals
Losses happening because vol filter isn't strict enough
Consider not trading during volatile periods (respect the regime)
Or disable regime filter and accept higher risk
Optimization Workflow:
Enable diagnostics
Run 200+ bars with current settings
Analyze rejection patterns and win rate
Make ONE change at a time (scientific method)
Re-run 200+ bars and compare results
Keep change if improvement, revert if worse
Disable diagnostics when satisfied
Never change multiple parameters at once - you won't know what worked.
Phase 7: Multi-Instrument Deployment
AGE learns independently on each chart:
Recommended Strategy:
Deploy AGE on 3-5 different instruments
Different asset classes ideal (e.g., ES futures, EURUSD, BTCUSD, SPY, Gold)
Each learns optimal strategies for that instrument's personality
Take signals from all 5 charts
Natural diversification reduces overall risk
Why This Works:
When one market is choppy, others may be trending
Different instruments respond to different news/catalysts
Portfolio-level win rate more stable than single-instrument
Evolution explores different parameter spaces on each chart
Setup:
Same settings across all charts (or customize if preferred)
Set alerts for all
Take every validated signal across all instruments
Position size based on total account (don't overleverage any single signal)
⚠️ REALISTIC EXPECTATIONS - CRITICAL READING
What AGE Can Do
✅ Generate probability-weighted signals using genetic algorithms
✅ Evolve strategies in real-time through natural selection
✅ Validate strategies on out-of-sample data (walk-forward optimization)
✅ Adapt to changing market conditions automatically over time
✅ Provide comprehensive metrics on population health and signal quality
✅ Work on any instrument, any timeframe, any broker
✅ Improve over time as weak strategies are culled and fit strategies breed
What AGE Cannot Do
❌ Win every trade (typical win rate: 55-65% at best)
❌ Predict the future with certainty (markets are probabilistic, not deterministic)
❌ Work perfectly from bar 1 (needs 100-150 bars to learn and stabilize)
❌ Guarantee profits under all market conditions
❌ Replace your trading discipline and risk management
❌ Execute trades automatically (this is an indicator, not a strategy)
❌ Prevent all losses (drawdowns are normal and expected)
❌ Adapt instantly to regime changes (re-learning takes 50-100 bars)
Performance Realities
Typical Performance After Evolution Stabilizes (150+ bars):
Win Rate: 55-65% (excellent for trend-following systems)
Profit Factor: 1.5-2.5 (realistic for validated strategies)
Signal Frequency: 5-15 signals per 100 bars (quality over quantity)
Drawdown Periods: 20-40% of time in equity retracement (normal trading reality)
Max Consecutive Losses: 5-8 losses possible even with 60% win rate (probability says this is normal)
Evolution Timeline:
Bars 0-50: Random exploration, learning phase - poor results expected, don't judge yet
Bars 50-150: Population converging, fitness climbing - results improving
Bars 150-300: Stable performance, most strategies validated - consistent results
Bars 300+: Mature population, optimal genes dominant - best results
Market Condition Dependency:
Trending Markets: AGE excels - clear directional moves, high-probability setups
Choppy Markets: AGE struggles - fewer signals generated, lower win rate
Volatile Markets: AGE cautious - higher rejection rate, wider stops, fewer trades
Market Regime Changes:
When market shifts from trending to choppy overnight
Validated strategies can become temporarily invalidated
AGE will adapt through evolution, but not instantly
Expect 50-100 bar re-learning period after major regime shifts
Fitness may temporarily drop then recover
This is NOT a holy grail. It's a sophisticated signal generator that learns and adapts using genetic algorithms. Your success depends on:
Patience during learning periods (don't abandon after 3 losses)
Proper position sizing (risk 0.5-2% per trade, not 10%)
Following signals consistently (cherry-picking defeats statistical edge)
Not abandoning system prematurely (give it 200+ bars minimum)
Understanding probability (60% win rate means 40% of trades WILL lose)
Respecting market conditions (trending = trade more, choppy = trade less)
Managing emotions (AGE is emotionless, you need to be too)
Expected Drawdowns:
Single-strategy max DD: 10-20% of equity (normal)
Portfolio across multiple instruments: 5-15% (diversification helps)
Losing streaks: 3-5 consecutive losses expected periodically
No indicator eliminates risk. AGE manages risk through:
Quality gates (rejecting low-probability signals)
Confluence requirements (multi-indicator confirmation)
Persistence requirements (no knee-jerk reactions)
Regime awareness (reduced trading in chaos)
Walk-forward validation (preventing overfitting)
But it cannot prevent all losses. That's inherent to trading.
🔧 TECHNICAL SPECIFICATIONS
Platform: TradingView Pine Script v5
Indicator Type: Overlay indicator (plots on price chart)
Execution Type: Signals only - no automatic order placement
Computational Load:
Moderate to High (genetic algorithms + shadow portfolios)
8 strategies × shadow portfolio simulation = significant computation
Premium visuals add additional load (gradient cloud, fitness ribbon)
TradingView Resource Limits (Built-in Caps):
Max Bars Back: 500 (sufficient for WFO and evolution)
Max Labels: 100 (plenty for entry/exit markers)
Max Lines: 150 (adequate for stop/target lines)
Max Boxes: 50 (not heavily used)
Max Polylines: 100 (confidence halos)
Recommended Chart Settings:
Timeframe: 15min to 1H (optimal signal/noise balance)
5min: Works but noisier, more signals
4H/Daily: Works but fewer signals
Bars Loaded: 1000+ (ensures sufficient evolution history)
Replay Mode: Excellent for testing without risk
Performance Optimization Tips:
Disable gradient cloud if chart lags (most CPU intensive visual)
Disable fitness ribbon if still laggy
Reduce cloud layers from 7 to 3
Reduce ribbon layers from 10 to 5
Turn off diagnostics panel unless actively tuning
Close other heavy indicators to free resources
Browser/Platform Compatibility:
Works on all modern browsers (Chrome, Firefox, Safari, Edge)
Mobile app supported (full functionality on phone/tablet)
Desktop app supported (best performance)
Web version supported (may be slower on older computers)
Data Requirements:
Real-time or delayed data both work
No special data feeds required
Works with TradingView's standard data
Historical + live data seamlessly integrated
🎓 THEORETICAL FOUNDATIONS
AGE synthesizes advanced concepts from multiple disciplines:
Evolutionary Computation
Genetic Algorithms (Holland, 1975): Population-based optimization through natural selection metaphor
Tournament Selection: Fitness-based parent selection with diversity preservation
Crossover Operators: Fitness-weighted gene recombination from two parents
Mutation Operators: Random gene perturbation for exploration of new parameter space
Elitism: Preservation of top N performers to prevent loss of best solutions
Adaptive Parameters: Different mutation rates for historical vs. live phases
Technical Analysis
Support/Resistance: Price structure within swing ranges
Trend Following: EMA-based directional bias
Momentum Analysis: RSI, ROC, MACD composite indicators
Volatility Analysis: ATR-based risk scaling
Volume Confirmation: Trade activity validation
Information Theory
Shannon Entropy (1948): Quantification of market order vs. disorder
Signal-to-Noise Ratio: Directional information vs. random walk
Information Content: How much "information" a price move contains
Statistics & Probability
Walk-Forward Analysis: Rolling in-sample/out-of-sample optimization
Out-of-Sample Validation: Testing on unseen data to prevent overfitting
Monte Carlo Principles: Shadow portfolio simulation with realistic execution
Expectancy Theory: Win rate × avg win - loss rate × avg loss
Probability Distributions: Signal confidence quantification
Risk Management
ATR-Based Stops: Volatility-normalized risk per trade
Volatility Regime Detection: Market state classification (trending/choppy/volatile)
Drawdown Control: Peak-to-trough equity measurement
R-Multiple Normalization: Performance measurement in risk units
Machine Learning Concepts
Online Learning: Continuous adaptation as new data arrives
Fitness Functions: Multi-objective optimization (win rate + expectancy + drawdown)
Exploration vs. Exploitation: Balance between trying new strategies and using proven ones
Overfitting Prevention: Walk-forward validation as regularization
Novel Contribution:
AGE is the first TradingView indicator to apply genetic algorithms to real-time indicator parameter optimization while maintaining strict anti-overfitting controls through walk-forward validation.
Most "adaptive" indicators simply recalibrate lookback periods or thresholds. AGE evolves entirely new strategies through competitive selection - it's not parameter tuning, it's Darwinian evolution of trading logic itself.
The combination of:
Genetic algorithm population management
Shadow portfolio simulation for realistic fitness evaluation
Walk-forward validation to prevent overfitting
Multi-indicator confluence for signal quality
Dynamic volatility scaling for adaptive risk
...creates a system that genuinely learns and improves over time while avoiding the curse of curve-fitting that plagues most optimization approaches.
🏗️ DEVELOPMENT NOTES
This project represents months of intensive development, facing significant technical challenges:
Challenge 1: Making Genetics Actually Work
Early versions spawned garbage strategies that polluted the gene pool:
Random gene combinations produced nonsensical parameter sets
Weak strategies survived too long, dragging down population
No clear convergence toward optimal solutions
Solution:
Comprehensive fitness scoring (4 factors: win rate, P&L, expectancy, drawdown)
Elite preservation (top 2 always protected)
Walk-forward validation (unproven strategies penalized 30%)
Tournament selection (fitness-weighted breeding)
Adaptive culling (MAS decay creates increasing selection pressure)
Challenge 2: Balancing Evolution Speed vs. Stability
Too fast = population chaos, no convergence. Too slow = can't adapt to regime changes.
Solution:
Dual-phase timing: Fast evolution during historical (30/60 bar intervals), slow during live (200/400 bar intervals)
Adaptive mutation rates: 20% historical, 8% live
Spawn/cull ratio: Always 2:1 to prevent population collapse
Challenge 3: Shadow Portfolio Accuracy
Needed realistic trade simulation without lookahead bias:
Can't peek at future bars for exits
Must track multiple portfolios simultaneously
Stop/target checks must use bar's high/low correctly
Solution:
Entry on close (realistic)
Exit checks on current bar's high/low (realistic)
Independent position tracking per strategy
Cooldown periods to prevent unrealistic rapid re-entry
ATR-normalized P&L (R-multiples) for fair comparison across volatility regimes
Challenge 4: Pine Script Compilation Limits
Hit TradingView's execution limits multiple times:
Too many array operations
Too many variables
Too complex conditional logic
Solution:
Optimized data structures (single DNA array instead of 8 separate arrays)
Minimal visual overlays (only essential plots)
Efficient fitness calculations (vectorized where possible)
Strategic use of barstate.islast to minimize dashboard updates
Challenge 5: Walk-Forward Implementation
Standard WFO is difficult in Pine Script:
Can't easily "roll forward" through historical data
Can't re-optimize strategies mid-stream
Must work in real-time streaming environment
Solution:
Age-based phase detection (first 250 bars = training, next 75 = testing)
Separate metric tracking for train vs. test
Efficiency calculation at fixed interval (after test period completes)
Validation flag persists for strategy lifetime
Challenge 6: Signal Quality Control
Early versions generated too many signals with poor win rates:
Single indicators produced excessive noise
No trend alignment
No regime awareness
Instant entries on single-bar spikes
Solution:
Three-layer confluence system (entropy + momentum + structure)
Minimum 2-of-3 agreement requirement
Trend alignment checks (penalty for counter-trend)
Regime-based probability adjustments
Persistence requirements (signals must hold multiple bars)
Volume confirmation
Quality gate (probability + confluence thresholds)
The Result
A system that:
Truly evolves (not just parameter sweeps)
Truly validates (out-of-sample testing)
Truly adapts (ongoing competition and breeding)
Stays within TradingView's platform constraints
Provides institutional-quality signals
Maintains transparency (full metrics dashboard)
Development time: 3+ months of iterative refinement
Lines of code: ~1500 (highly optimized)
Test instruments: ES, NQ, EURUSD, BTCUSD, SPY, AAPL
Test timeframes: 5min, 15min, 1H, Daily
🎯 FINAL WORDS
The Adaptive Genesis Engine is not just another indicator - it's a living system that learns, adapts, and improves through the same principles that drive biological evolution. Every bar it observes adds to its experience. Every strategy it spawns explores new parameter combinations. Every strategy it culls removes weakness from the gene pool.
This is evolution in action on your charts.
You're not getting a static formula locked in time. You're getting a system that thinks , that competes , that survives through natural selection. The strongest strategies rise to the top. The weakest die. The gene pool improves generation after generation.
AGE doesn't claim to predict the future - it adapts to whatever the future brings. When markets shift from trending to choppy, from calm to volatile, from bullish to bearish - AGE evolves new strategies suited to the new regime.
Use it on any instrument. Any timeframe. Any market condition. AGE will adapt.
This indicator gives you the pure signal intelligence. How you choose to act on it - position sizing, risk management, execution discipline - that's your responsibility. AGE tells you when and how confident . You decide whether and how much .
Trust the process. Respect the evolution. Let Darwin work.
"In markets, as in nature, it is not the strongest strategies that survive, nor the most intelligent - but those most responsive to change."
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
— Happy Holiday's
ICT Fair Value Gap Detector [Eˣ]⚡ Fair Value Gap Detector
Overview
The Fair Value Gap Detector automatically identifies price imbalances on your charts - the inefficiencies left behind when price moves too quickly. This indicator reveals where price is likely to return for "rebalancing", based on ICT (Inner Circle Trader) concepts of market efficiency.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎯 What This Indicator Does
Detects Fair Value Gaps:
• 🟢 Bullish FVG - Gap left below during aggressive upward move
• 🔴 Bearish FVG - Gap left above during aggressive downward move
• Automatically identifies 3-candle price inefficiencies
• Works on all timeframes and instruments
Smart Fill Tracking:
• Full Fill - Price completely fills the gap
• 50% Fill - Price fills half the gap (critical level)
• Partial Fill - Price touches gap edge
• Real-time fill percentage tracking
• Auto-removes filled gaps (optional)
Professional Features:
• Active Gap Highlighting - Shows nearest unfilled gap
• Distance Calculator - Displays how far price is from gaps
• Market Bias - Analysis based on gap balance
• Size Filtering - Minimum gap size to avoid noise
• Visual Clarity - Clean boxes with color-coding
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📚 Understanding Fair Value Gaps
What Are Fair Value Gaps?
Fair Value Gaps (FVGs), also known as imbalances or inefficiencies, are zones where price moved so quickly that normal trading didn't occur. They represent:
• Price Imbalance - One-sided aggressive buying or selling
• Unfair Pricing - Some participants didn't get to trade at these levels
• Market Inefficiency - Supply/demand equilibrium was disrupted
• Rebalancing Zones - Price often returns to "fill" these gaps
The ICT Concept:
Markets constantly seek equilibrium (fair value). When price moves too fast:
1. It leaves gaps where normal trading didn't happen
2. These gaps represent unfair/inefficient pricing
3. Market has a tendency to return and "rebalance"
4. Smart money knows this and trades the fills
Why FVGs Work:
• Unfilled Orders - Traders who missed the move have pending orders in the gap
• Algorithmic Trading - Algos programmed to exploit inefficiencies
• Market Psychology - Traders notice gaps and place orders there
• Institutional Behavior - Smart money uses gaps for entries/exits
FVG vs Regular Gaps:
• Regular Gaps - Occur at market open, between daily closes
• Fair Value Gaps - Occur intraday, between 3 consecutive candles
• FVGs happen more frequently and on all timeframes
• FVGs are more tradeable for intraday/swing traders
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🟢 Bullish Fair Value Gaps Explained
How They Form:
Bullish FVG requires 3 candles:
1. Candle 1 - Any candle (sets the high reference)
2. Candle 2 - Strong bullish candle (aggressive buying)
3. Candle 3 - Continuation candle
The Gap: Candle 3's LOW is above Candle 1's HIGH = Gap left unfilled
Visual Example:
```
Candle 3: Low at $105 ──────────┐
│ ← GAP (Bullish FVG)
Candle 2: Strong bullish │
│
Candle 1: High at $100 ──────────┘
```
What It Means:
• Price jumped from $100 to $105+ so fast, no trading occurred in between
• This $100-$105 zone is "unfair" - buyers/sellers didn't get to trade there
• Market may return to this zone to "rebalance"
• When price returns, it often acts as support
Trading Bullish FVGs:
Strategy:
• Wait for price to retrace down into the bullish FVG (green box)
• Look for rejection/bounce from the gap zone
• Enter long when price respects the FVG as support
• Stop loss: Below the FVG
• Target: Previous high or opposite FVG
Best Entry Points:
• 50% Fill: Price enters middle of gap (highest probability)
• Full Fill: Price touches bottom of gap (aggressive entry)
• Tap & Reject: Price quickly enters and exits gap (strong signal)
Example Trade:
• Bullish FVG forms: $50,000 - $50,500 (500 point gap)
• Price rallies to $52,000 then retraces
• Price drops to $50,250 (50% of gap filled)
• Bullish reversal candle appears
• Enter long at $50,500, stop at $49,800
• Target: $52,000+
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🔴 Bearish Fair Value Gaps Explained
How They Form:
Bearish FVG requires 3 candles:
1. Candle 1 - Any candle (sets the low reference)
2. Candle 2 - Strong bearish candle (aggressive selling)
3. Candle 3 - Continuation candle
The Gap: Candle 3's HIGH is below Candle 1's LOW = Gap left unfilled
Visual Example:
```
Candle 1: Low at $100 ───────────┐
│ ← GAP (Bearish FVG)
Candle 2: Strong bearish │
│
Candle 3: High at $95 ───────────┘
```
What It Means:
• Price dropped from $100 to $95 so fast, no trading occurred in between
• This $95-$100 zone is "unfair" - buyers/sellers didn't get to trade there
• Market may return to this zone to "rebalance"
• When price returns, it often acts as resistance
Trading Bearish FVGs:
Strategy:
• Wait for price to retrace up into the bearish FVG (red box)
• Look for rejection/reversal from the gap zone
• Enter short when price respects the FVG as resistance
• Stop loss: Above the FVG
• Target: Previous low or opposite FVG
Best Entry Points:
• 50% Fill: Price enters middle of gap (highest probability)
• Full Fill: Price touches top of gap (aggressive entry)
• Tap & Reject: Price quickly enters and exits gap (strong signal)
Example Trade:
• Bearish FVG forms: $48,000 - $48,500 (500 point gap)
• Price drops to $46,000 then retraces
• Price rallies to $48,250 (50% of gap filled)
• Bearish reversal candle appears
• Enter short at $48,000, stop at $48,700
• Target: $46,000-
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 How To Use This Indicator
Strategy 1: FVG Rebalancing (Classic)
Best For: Swing trading, reversal trading
Timeframes: 15min, 1H, 4H
Win Rate: 65-75%
Entry Rules:
1. Identify unfilled FVG (bright color, not gray)
2. Wait for price to return to the gap
3. Best entry: 50% fill of the gap
4. Look for reversal confirmation:
• Bullish FVG: Pin bar, engulfing, hammer
• Bearish FVG: Shooting star, bearish engulfing
5. Enter when price bounces/rejects from FVG
6. Stop: Beyond opposite side of FVG
7. Target: 2-3R or previous high/low
Why It Works: 70%+ of FVGs get filled, and 60%+ show reaction
Strategy 2: FVG + Order Block Confluence
Best For: High-probability setups
Timeframes: 1H, 4H
Win Rate: 75-85%
Entry Rules:
1. Find FVG that overlaps with Order Block
2. This creates a "super zone" of confluence
3. Wait for price to return to this zone
4. Enter on first touch of confluence zone
5. Stop: Beyond the confluence zone
6. Target: 3-4R
Why It Works: Double institutional concepts = highest probability
Strategy 3: Multi-Timeframe FVG
Best For: Position trading, major moves
Timeframes: Combine Daily + 4H or 4H + 1H
Win Rate: 70-80%
Entry Rules:
1. Identify large FVG on higher timeframe (Daily/4H)
2. Wait for price to enter this HTF FVG
3. Switch to lower timeframe (4H/1H)
4. Look for LTF FVG within HTF FVG in same direction
5. Trade the LTF FVG fill
6. Stop: Below LTF FVG
7. Target: Exit HTF FVG or beyond
Why It Works: Timeframe alignment = institutional consensus
Strategy 4: FVG Rejection Trade
Best For: Quick scalps, day trading
Timeframes: 5min, 15min
Win Rate: 60-70%
Entry Rules:
1. Price enters FVG zone
2. Immediate rejection (strong reversal candle)
3. Enter on close of rejection candle
4. Tight stop beyond FVG
5. Quick target: 1-2R
Why It Works: Strong rejection = institutional defense of level
Strategy 5: FVG-to-FVG Trading
Best For: Momentum trading
Timeframes: 15min, 1H
Win Rate: 55-65%
Entry Rules:
1. Identify bullish FVG below and bearish FVG above
2. Enter long at bullish FVG, target bearish FVG
3. Or enter short at bearish FVG, target bullish FVG
4. Price often moves from one imbalance to another
5. Stop: Beyond trading FVG
6. Target: Opposite FVG
Why It Works: Price rebalances from one inefficiency to another
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
⚙️ Settings Explained
Display Settings
Show Bullish/Bearish FVG
• Toggle each type on/off independently
• Customize colors for each FVG type
• Default: Green (bullish), Red (bearish)
• Tip: Use colors that contrast with your chart
Max FVG to Display (Default: 20)
• Limits how many gaps are shown at once
• Lower (10-15): Cleaner chart, recent gaps only
• Higher (30-50): More historical context
• Recommended: 15-25 for most trading
Show FVG Labels (Default: ON)
• Displays "FVG+" and "FVG-" text on gaps
• Shows 🎯 on active (nearest) gap
• Shows fill percentage (e.g., "FVG+ 35%")
• Turn OFF for minimal appearance
• Recommended: Keep ON for clarity
Extend Gaps (bars) (Default: 50)
• How far to extend gap boxes to the right
• Lower (20-30): Shorter boxes
• Higher (100+): Longer boxes, easier to see
• Gaps auto-extend until filled or limit reached
• Recommended: 40-60 bars
Filters
Min Gap Size % (Default: 0.05)
• Minimum gap size as percentage of price
• Filters out tiny, insignificant gaps
• Crypto: 0.05-0.15% (high volatility)
• Forex: 0.03-0.10% (moderate volatility)
• Stocks: 0.05-0.20% (varies by stock)
• Indices: 0.05-0.15%
• Adjust based on instrument's average move
Show Filled Gaps (Default: OFF)
• When ON: Shows gray boxes for filled gaps
• When OFF: Gaps disappear after mitigation
• Use ON: For learning and backtesting
• Use OFF: For clean, active trading view
Advanced Settings
Auto-Detect Mitigation (Default: ON)
• Automatically tracks when gaps are filled
• Updates fill percentage in real-time
• Marks gaps as "mitigated" when filled
• Recommended: Keep ON
Mitigation Type (Default: Full)
• Full: Gap considered filled when price closes through entire gap
• 50%: Gap considered filled at 50% (critical level)
• Partial: Gap considered filled on first touch
• For learning: Use "Full"
• For aggressive trading: Use "50%"
• For conservative trading: Use "Partial"
Highlight Nearest Gap (Default: ON)
• Highlights the closest unfilled gap to current price
• Active gap shown with 🎯 emoji and brighter color
• Helps focus on most relevant opportunity
• Recommended: Keep ON
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📱 Info Panel Guide
Bullish FVG Count
• Number of active (unfilled) bullish fair value gaps
• Higher number = More potential support zones below
• Multiple bullish FVGs = Strong rebalancing demand
Bearish FVG Count
• Number of active (unfilled) bearish fair value gaps
• Higher number = More potential resistance zones above
• Multiple bearish FVGs = Strong rebalancing supply
Bias Indicator
• ⬆ Bullish: More bullish FVGs than bearish
• ⬇ Bearish: More bearish FVGs than bullish
• ↔ Neutral: Equal FVGs on both sides
• Market tends to fill nearby gaps first
Target Indicator
• Shows nearest unfilled gap and distance
• Example: "Bull FVG -1.25%" = Bullish gap is 1.25% below price
• Example: "Bear FVG +0.85%" = Bearish gap is 0.85% above price
• Watch for price to reach these targets
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📱 Alert Setup
This indicator includes 4 alert types:
1. Price Entering Bullish FVG
• Fires when price drops into a bullish gap
• Action: Watch for bounce/reversal
• High-probability long setup developing
2. Price Entering Bearish FVG
• Fires when price rallies into a bearish gap
• Action: Watch for rejection/reversal
• High-probability short setup developing
3. New Bullish FVG Detected
• Fires when a new bullish gap forms
• Action: Mark zone for future fill
• New rebalancing target below identified
4. New Bearish FVG Detected
• Fires when a new bearish gap forms
• Action: Mark zone for future fill
• New rebalancing target above identified
To Set Up Alerts:
1. Click "Alert" button (clock icon)
2. Select "Fair Value Gap Detector"
3. Choose your alert condition
4. Configure notification method
5. Click "Create"
Pro Tip: Set "Price Entering" alerts to catch fills in real-time
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
💎 Pro Tips & Best Practices
✅ DO:
• Wait for 50% fill - Middle of gap has highest win rate (65-70%)
• Use confirmation - Don't trade just because price touched gap
• Combine with structure - FVG + support/resistance = high probability
• Trade first fill - Unfilled gaps have better success rate than refilled
• Respect full fills - Once fully filled, gap is less reliable
• Use multiple timeframes - HTF FVGs are stronger than LTF
• Check session timing - FVGs work best during London/NY sessions
• Follow the bias - More bullish FVGs = favor longs
⚠️ DON'T:
• Don't blindly fade gaps - Wait for price action confirmation
• Don't ignore momentum - Strong trends can blow through FVGs
• Don't trade every gap - Quality over quantity
• Don't assume all gaps fill - About 70-80% fill, 20-30% don't
• Don't use tight stops - Allow room for wick into gap
• Don't overtrade - Wait for confluence and confirmation
• Don't fight trends - Best FVG trades are with higher TF trend
• Don't ignore fill percentage - 50% is often the sweet spot
🎯 Best Timeframes:
• Scalpers: 1min, 5min (many gaps, quick fills)
• Day Traders: 5min, 15min, 1H (balanced)
• Swing Traders: 1H, 4H, Daily (larger, more reliable gaps)
• Position Traders: 4H, Daily, Weekly (major imbalances)
🔥 Best Instruments:
• Excellent: BTC, ETH, ES, NQ, Forex majors (clean price action)
• Good: Gold, Oil, Major indices, Large-cap stocks
• Moderate: Altcoins, small-cap stocks (more noise)
• Best Markets: Trending markets with clear swings
⏰ Best Times for FVG Trading:
• London Session: High volume = reliable gap fills
• NY Session: Strong moves create quality gaps
• London-NY Overlap: Best time for gap creation and fills
• Asian Session: Lower probability, wait for London
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🎓 Advanced FVG Concepts
FVG Mitigation Levels
Understanding fill percentages:
• 0-25% Fill: Gap barely touched, often continues without fill
• 25-50% Fill: Partial rebalancing, may reverse here
• 50% Fill: CRITICAL LEVEL - Highest probability reversal zone
• 50-75% Fill: Deep rebalancing, strong reversal likely
• 75-100% Fill: Full rebalancing, gap's purpose fulfilled
Why 50% Matters: Market seeks equilibrium, and 50% represents perfect balance
FVG Inversions
When price breaks through a gap completely:
• Bullish FVG that's broken becomes bearish (support → resistance)
• Bearish FVG that's broken becomes bullish (resistance → support)
• Inverted gaps are weaker than fresh gaps
• Trading: Can fade the inverted gap but with caution
FVG Confluence Zones
Multiple FVGs at similar level:
• Creates "super gap" or confluence zone
• Much higher probability of reaction
• Wider zone for entries (more room for stops)
• Often aligns with other institutional concepts
FVG + Order Block Combo
When FVG overlaps with Order Block:
• Double institutional concept
• Extremely high probability setup (75-85% win rate)
• Price drawn to fill gap AND test order block
• Use tight stops, generous targets (3-5R possible)
Nested FVGs (Multi-Timeframe)
Small FVG inside larger FVG:
• Daily FVG contains 4H FVG contains 1H FVG
• Trade the smallest FVG in direction of larger ones
• Highest probability when all aligned
• Progressive targets: Fill small → medium → large gaps
FVG Exhaustion
When price creates multiple FVGs in same direction:
• Indicates strong momentum/impulsive move
• Each gap represents acceleration
• Last gap often signals exhaustion
• Watch for reversal after filling final gap
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 Common FVG Patterns
Pattern 1: The Perfect Rebalance
• FVG forms during strong move
• Price continues 100+ pips
• Clean return to 50% of gap
• Immediate reversal
• Textbook setup, 70%+ win rate
Pattern 2: The Double Fill
• Price partially fills gap (25%)
• Weak reaction, continues
• Returns again for deeper fill (75%)
• Strong reversal on second fill
• Second fill often better entry
Pattern 3: The Blow-Through
• Price approaches gap
• Completely ignores it, no reaction
• Keeps going in same direction
• Sign of very strong momentum
Pattern 4: The Magnet Effect
• Price slowly grinds toward gap
• Accelerates as it gets close
• Quickly fills and reverses
• Common in ranging markets
Pattern 5: The False Fill
• Price wicks into gap briefly
• Immediately reverses without filling
• "Stop hunt" or liquidity grab
• Gap remains unfilled
• Often precedes strong move
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🚀 What Makes This Different?
Unlike basic gap indicators, Fair Value Gap Detector:
• ICT Methodology - Based on proven institutional concepts
• Real-Time Fill Tracking - Shows percentage filled as it happens
• 3 Mitigation Types - Full, 50%, Partial for different strategies
• Active Gap Highlighting - Shows most relevant opportunity
• Smart Filtering - Minimum size to avoid noise
• Visual Clarity - Clean, professional appearance
• Auto-Management - Removes filled gaps automatically
• Distance Tracking - Know exactly where price needs to go
Based On Professional Concepts:
• ICT Fair Value Gap theory
• Market efficiency principles
• Price rebalancing dynamics
• Institutional order flow analysis
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📈 FVG Statistics & Probabilities
Based on ICT concepts and trader observations:
Gap Fill Rates:
• 70-80% of FVGs get filled eventually
• 60-70% show some reaction when filled
• 50% fill level has ~65% reversal rate
• Full fills have ~55% reversal rate
Timeframe Reliability:
• Daily FVGs: ~75-85% fill rate, strongest reactions
• 4H FVGs: ~70-80% fill rate, strong reactions
• 1H FVGs: ~65-75% fill rate, good reactions
• 15min FVGs: ~60-70% fill rate, moderate reactions
• 5min FVGs: ~55-65% fill rate, weaker reactions
Best Practices:
• First touch of gap = 65-70% win rate
• 50% fill = 65% win rate
• FVG + Order Block = 75-85% win rate
• Multi-timeframe aligned FVG = 70-80% win rate
• FVG in trending market = 60-70% win rate
Common Failures:
• Strong momentum blows through gaps (20-30% of time)
• Gaps in low-volume periods less reliable
• Very small gaps (<0.05%) often ignored
• Counter-trend gaps have lower success rate
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
🙏 If You Find This Helpful
• ⭐ Leave your feedback
• 💬 Share your experience in the comments
• 🔔 Follow for updates and new tools
Questions about Fair Value Gaps? Feel free to ask in the comments.
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Version History
• v1.0 - Initial release with 3-candle FVG detection and real-time fill tracking
DCA Ladder CalculatorThis script is a DCA (Dollar-Cost Averaging) Ladder Calculator with Risk & Leverage Management baked in.
It’s designed for both LONG and SHORT positions, and helps you:
🎯 Strategically scale into positions across multiple entry points
🔐 Control risk exposure via defined capital allocation
⚖️ Utilize leverage responsibly — for efficiency, not destruction
🧮 Visualize risk, stop loss level, and entry distribution
🔁 Adapt to trend reversals or key zones, especially when combined with reversal indicators or higher timeframe signals
🧠 How It Works
This tool takes a capital allocation approach to building a ladder of positions:
1. You define:
- Portfolio value
- Risk per trade (as %)
- Leverage
- Number of DCA levels
- Entry multiplier (e.g. 1x, 2x, 4x...)
2. The script then:
- Calculates total margin to risk = Portfolio × Risk %
- Calculates total leveraged position size = Margin × Leverage
- Distributes entries according to exponential weights (1x, 2x, 4x...), totaling 7 for 3 levels
- Calculates per-entry:
- Entry price (based on price zone spacing)
- Multiplier
- Exact margin per entry
- Leverage per entry (margin × leverage)
- Computes:
- Average entry price (margin-weighted)
- Approximate stop loss level based on recent ATR and price structure
- % drawdown to SL
- Total margin and position size
3. Displays all this in a clean on-chart table.
📈 How to Use It
1. Apply the indicator to a chart (default: 1D — ideal for clean zones).
2. Configure your:
- Portfolio Value (total trading capital)
- Risk per Trade (%) (your acceptable loss)
- Leverage (exchange or strategy-based)
- DCA Levels (e.g. 3 = anchor + 2 entries)
- Multiplier (typically 2.0 for doubling)
3. Choose LONG or SHORT mode depending on direction.
4. The table will show:
- Entry price ladder
- Margin used per entry
- Total position size
- Approx. stop loss (where your full risk is defined)
Use in conjunction with price action, S/R zones, trendline breaks, volume divergence, or reversal indicators.
✅ Best Practices for Using This Tool
- Leverage is a tool, not a weapon. Use it to scale smartly — not recklessly.
- Use fewer, higher-conviction entries. Don’t blindly ladder; combine with price structure and signals.
- Stick to your risk percent. Never risk more than you can afford to lose. Let this calculator enforce discipline.
- Combine with other confirmation tools, like RSI divergence, momentum shifts, OB zones, etc.
- Avoid martingale-style over-exposure. This is not a gambling tool — it’s for capital efficiency.
🛡️ What This Tool Does NOT Do
- This is not a trade signal indicator.
- It does not place trades or auto-manage positions.
- It does not replace personal responsibility or strategy — it's a tool to help apply structure.
⚠️ Disclaimer
This script is for educational and informational purposes only.
It does not constitute financial advice, nor is it a recommendation to buy or sell any financial instrument.
Always consult a licensed financial advisor before making investment decisions.
Use of leverage involves high risk and can lead to substantial losses.
The author and publisher assume no liability for any trading losses resulting from use of this script.
Quantum Ribbon Lite📊 WHAT IS IT?
Quantum Ribbon Lite is a trend trading indicator built on a 5-layer exponential moving average ribbon system. It analyzes price momentum, volume, and ribbon alignment to generate entry signals with pre-calculated stop loss and take profit levels.
The indicator is designed for traders who want a straightforward approach to trend trading without managing complex configurations.
🔧 HOW IT WORKS
The Ribbon System
The indicator uses 5 pairs of EMAs (10 moving averages total) that create colored "clouds" on your chart:
Blue/Teal ribbons indicate bullish alignment
Red/Pink ribbons indicate bearish alignment
Mixed colors indicate neutral or transitional periods
The ribbon spacing automatically adjusts from a fast EMA (21) to a slow EMA (60), creating layers that show trend strength and direction.
Signal Generation
Signals appear when multiple conditions align:
For LONG signals:
Fast EMAs are above slow EMAs
Price momentum is positive and strong (> 0.5 ATR)
Volume is above average (> 1.1x average)
Ribbon confirms bullish state
Minimum confidence threshold met (filters weak setups)
For SHORT signals:
Fast EMAs are below slow EMAs
Price momentum is negative and strong
Volume is above average
Ribbon confirms bearish state
Minimum confidence threshold met
📈 VISUAL COMPONENTS
Entry Signals
Green "BUY" label = Long entry signal at candle close
Red "SELL" label = Short entry signal at candle close
Signals only trigger on confirmed candle closes (no repainting).
Risk Management Lines
Three lines appear when you have an active position:
White dotted line = Entry price
Red dotted line = Stop loss level
Green dotted line = Take profit target
Performance Dashboard
The stats table shows:
Current position status (In Long/Short or Waiting for signal)
Entry, stop, and target prices when in a trade
Win/loss record
Win rate percentage with color coding
⚙️ SETTINGS
1. Signal Sensitivity (1-10)
Controls the minimum time between signals (cooldown period):
1 = 2 bars between signals (most frequent)
5 = 10 bars between signals (balanced)
10 = 20 bars between signals (most selective)
Lower values generate more signals, higher values filter for better setups.
2. Stop Loss Distance
Determines how stops are calculated using ATR (Average True Range):
Tight = 1.5x ATR from entry
Normal = 2.0x ATR from entry
Wide = 2.5x ATR from entry
ATR adapts to market volatility, so stops are tighter in calm markets and wider in volatile markets.
3. Take Profit Target
Sets your risk-to-reward ratio:
1.5R = Target is 1.5 times your risk
2R = Target is 2 times your risk
3R = Target is 3 times your risk
Example: With a $100 stop distance and 2R setting, your take profit will be $200 away from entry.
4. Show Stats Table
Toggle to show/hide the performance dashboard in the top-right corner.
5. Show Risk Lines
Toggle to show/hide the entry/stop/target lines on the chart.
📋 HOW TO USE
Step 1: Apply to Chart
Add the indicator to your preferred instrument and timeframe (daily recommended).
Step 2: Wait for Signal
A BUY or SELL label will appear on the chart when conditions align.
Step 3: Enter Position
Enter at the close of the signal candle in the indicated direction.
Step 4: Set Risk Parameters Use the displayed lines:
Red line = Your stop loss
Green line = Your take profit
Step 5: Hold Position
Wait for the position to hit either the stop or target. No new signals will appear while you're in a position.
Step 6: Review Results
Check the stats table to track your win rate and adjust settings if needed.
🎯 RISK MANAGEMENT
Stop Loss Calculation
Stops are based on ATR (Average True Range) which measures recent price volatility:
In quiet markets: Stops are placed closer to entry
In volatile markets: Stops are placed further away
This adaptive approach helps prevent stop-hunting while maintaining appropriate risk levels.
Take Profit Calculation
Targets are calculated as a multiple of your stop distance:
If stop is 50 points away and you use 2R, target is 100 points away
Maintains consistent risk-reward ratios across all trades
Required Win Rates To break even after fees:
1.5R requires ~40% win rate
2R requires ~34% win rate
3R requires ~25% win rate
📊 RECOMMENDED USAGE
Timeframes:
Daily charts show strongest performance in testing
4H and 1H timeframes work but may have lower win rates
Lower timeframes generate more signals but reduced quality
Markets:
Works on all instruments: Stocks, Forex, Crypto, Futures, Indices
Best suited for trending markets
May generate false signals in tight ranges or choppy conditions
Gap-Up Momentum Screener (S.S)
ENGLISH-VERSION
1) TradingView Gap Screener (for US stocks)
➤ Conditions
Gap-Up ≥ +3% (large gaps indicate institutional pressure)
Pre-market volume ≥ 150% of the 20-day average
RS line > 50
Price > 50 SMA
Market cap ≥ 1 billion USD
No penny stocks
2) Minervini Gap-Entry Strategy (Swing Trading)
This is a variant specifically optimized for gaps + momentum.
A) Setup Criteria
The stock must meet the following conditions:
Gap-Up ≥ +3%
First retracement ≤ 30% of the gap
High relative strength (RS line rising)
Volume on the gap day > 2× average
Price above 20 EMA, 50 SMA, 150 SMA, 200 SMA
No immediate resistance within 2–5%
B) Entry Setups
Entry 1: First Pullback Entry (FPE)
Wait for the first 1–3 day consolidation.
Entry → Breakout of the small range.
Stop → Below the low of the pullback.
Rule: No entry on the gap day itself.
Entry 2: High Tight Flag above the Gap
Stock rises > 10% after the gap
Then forms a 3–8 day sideways phase
Entry → Break above the flag’s high
Stop → Below the flag base
Entry 3: ORB Entry (Opening Range Breakout, 30 minutes)
Very effective for strong gaps.
Wait 30 minutes after the market opens
Entry → Break above the high of these first 30 minutes
Stop → Below the 30-minute low
C) Stop Levels
For FPE: 4–8%
For ORB: 1–2 × ATR(14)
For flags: 3–5%
D) Add Rules
Only if the stock continues showing strong volume:
Add on every new 3–5 day high
Add only above half-range levels
Maximum 3 adds
3) Early-Warning Module (Setup forming but not ready for entry)
This module marks stocks that are forming a setup but are not yet buyable.
➤ Criteria
Gap-Up ≥ 3%
Strong volume
Stock pulls back and consolidates (1–5 bars)
BUT no breakout yet
4) Exact Entry Checklist (Minervini-style, optimized for gaps)
Checklist before entry:
Gap ≥ +3%
20 EMA rising
Volume > 2× average
RS line rising
Price > 50 SMA
Pullback not deeper than 30% of the gap
3+ green signals from the Early-Warning diamonds
If all 7 are fulfilled → green light.
5) How to apply the strategy in daily practice
Morning (08:00–09:00)
Check the screener
Build your watchlist
Identify gaps
US Market Open (15:30)
Monitor the Early-Warning module
Sort gap momentum opportunities
16:00–17:00
Enter: First Pullback / ORB / Flag
Set stops
Determine position size based on risk
After 20:00
Check volume strength
If momentum fades → no more adds
