AI Trading Alerts v6 — SL/TP + Confidence + Panel (Fixed)Overview
This Pine Script is designed to identify high-probability trading opportunities in Forex, commodities, and crypto markets. It combines EMA trend filters, RSI, and Stochastic RSI, with automatic stop-loss (SL) & take-profit (TP) suggestions, and provides a confidence panel to quickly assess the trade setup strength.
It also includes TradingView alert conditions so you can set up notifications for Long/Short setups and EMA crosses.
⚙️ Features
EMA Trend Filter
Uses EMA 50, 100, 200 for trend confirmation.
Bull trend = EMA50 > EMA100 > EMA200
Bear trend = EMA50 < EMA100 < EMA200
RSI Filter
Bullish trades require RSI > 50
Bearish trades require RSI < 50
Stochastic RSI Filter
Prevents entries during overbought/oversold extremes.
Bullish entry only if %K and %D < 80
Bearish entry only if %K and %D > 20
EMA Proximity Check
Price must be near EMA50 (within ATR × adjustable multiplier).
Signals
Continuation Signals:
Long if all bullish conditions align.
Short if all bearish conditions align.
Cross Events:
Long Cross when price crosses above EMA50 in bull trend.
Short Cross when price crosses below EMA50 in bear trend.
Automatic SL/TP Suggestions
SL size adjusts depending on asset:
Gold/Silver (XAU/XAG): 5 pts
Bitcoin/Ethereum: 100 pts
FX pairs (default): 20 pts
TP = SL × Risk:Reward ratio (default 1:2).
Confidence Score (0–4)
Based on conditions met (trend, RSI, Stoch, EMA proximity).
Labels:
Strongest (4/4)
Strong (3/4)
Medium (2/4)
Low (1/4)
Visual Panel on Chart
Shows ✅/❌ for each condition (trend, RSI, Stoch, EMA proximity, signal now).
Confidence row with color-coded strength.
Alerts
Long Setup
Short Setup
Long Cross
Short Cross
🖥️ How to Use
1. Add the Script
Open TradingView → Pine Editor.
Paste the full script.
Click Add to chart.
Save as "AI Trading Alerts v6 — SL/TP + Confidence + Panel".
2. Configure Inputs
EMA Lengths: Default 50/100/200 (works well for swing trading).
RSI Length: 14 (standard).
Stochastic Length/K/D: Default 14/3/3.
Risk:Reward Ratio: Default 2.0 (can change to 1.5, 3.0, etc.).
EMA Proximity Threshold: Default 0.20 × ATR (adjust to be stricter/looser).
3. Read the Panel
Top-right of chart, you’ll see ✅ or ❌ for:
Trend → Are EMAs aligned?
RSI → Above 50 (bull) or below 50 (bear)?
Stoch OK → Not extreme?
Near EMA50 → Close enough to EMA50?
Above/Below OK → Price position vs. EMA50 matches trend?
Signal Now → Entry triggered?
Confidence row:
🟢 Green = Strongest
🟩 Light green = Strong
🟧 Orange = Medium
🟨 Yellow = Low
⬜ Gray = None
4. Alerts Setup
Go to TradingView Alerts (⏰ icon).
Choose the script under “Condition”.
Select alert type:
Long Setup
Short Setup
Long Cross
Short Cross
Set notification method (popup, sound, email, mobile).
Click Create.
Now TradingView will notify you automatically when signals appear.
5. Example Workflow
Wait for Confidence = Strong/Strongest.
Check if market session supports volatility (e.g., XAU in London/NY).
Review SL/TP suggestions:
Long → Entry: current price, SL: close - risk_pts, TP: close + risk_pts × RR.
Short → Entry: current price, SL: close + risk_pts, TP: close - risk_pts × RR.
Adjust based on your own price action analysis.
📊 Best Practices
Use on H1 + D1 combo → align higher timeframe bias with intraday entries.
Risk only 1–2% of account per trade (position sizing required).
Filter with market sessions (Asia, Europe, US).
Strongest signals work best with trending pairs (e.g., XAUUSD, USDJPY, BTCUSD).
חפש סקריפטים עבור "swing trading"
Volume Profile AnalysisThe Volume Profile Dashboard is a professional-grade analysis tool built for TradingView. It focuses on displaying a comprehensive volume profile breakdown within a dashboard format directly on the chart. The purpose of this tool is to help traders quickly assess buy versus sell volume dynamics, momentum, and sentiment in order to support informed trading decisions.
Instead of plotting simple bars, this indicator uses a detailed table and visual progress bar to summarize live and historical market activity. By condensing key metrics into a structured format, traders can analyse market behaviour without manually calculating or switching between multiple indicators.
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How the Script Works
1. Data Gathering
The script uses lower-timeframe price and volume data to calculate buy volume, sell volume, and total traded volume for the current and previous candles.
2. Volume Allocation
Buy and sell volumes are estimated by looking at the candle’s range (high to low) and how the closing price aligns within that range. The closer the close is to the high, the stronger the buying pressure. The closer the close is to the low, the stronger the selling pressure.
3. Delta and Momentum
o Delta measures the difference between buy and sell volume.
o Volume momentum compares the current candle’s activity to the previous one, showing if interest is rising or fading.
4. Point of Control (POC)
An average of high, low, and close is calculated to give an approximate “point of control” level—an area of balance where buyers and sellers previously agreed on price.
5. Dashboard Visualization
All these calculations are displayed inside a clean dashboard table with separate rows for the current candle, previous candle, and a summary row. Icons, colors, and progress bars make it visually intuitive.
6. On-Chart Progress Indicator
A dynamic horizontal progress bar is plotted on the chart above price, showing the balance between buy and sell volume for the latest activity.
7. Alerts
Built-in alerts trigger when strong buying or selling pressure is detected or when there is a significant spike in total traded volume.
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How This Tool Can Be Used
• Intraday Trading: Quickly gauge whether buyers or sellers are in control of the market at any moment.
• Swing Trading: Compare momentum shifts between candles to identify early trend reversals.
• Risk Management: Use delta and sentiment signals to confirm whether to hold or reduce exposure.
• Confirmation: Align the volume profile dashboard with other indicators (such as RSI, MACD, or trendlines) for stronger trading conviction.
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Using Mixed Indicators for Decisions
This dashboard alone provides volume insights, but better decisions come when it is combined with other tools:
• Pairing it with an RSI can show whether heavy buying is happening in overbought conditions.
• Combining with a SuperTrend or moving averages can confirm if volume momentum aligns with the price trend.
• Overlaying support/resistance levels can identify whether strong buy/sell signals occur at critical levels.
Mixed indicators prevent relying on one signal alone, reducing false trades.
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Importance of This Tool
• Clarity: Condenses complex volume data into a simple, visual format.
• Speed: Traders can react faster with pre-calculated buy/sell percentages.
• Precision: Highlights hidden imbalances that are not obvious from candles alone.
• Professional-grade dashboard: Offers an institutional-style view of market behavior directly within TradingView.
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Parameters in the Dashboard Table
• Period: Shows whether the row is for the current or previous candle, along with trend arrows.
• Price Range: The high–low range of the candle.
• Total Volume: The sum of buy and sell activity.
• Buy Volume / Sell Volume: Separated distribution of transactions leaning bullish or bearish.
• Delta: The net difference between buy and sell volumes, highlighting pressure imbalance.
• Buy % / Sell %: The percentage contribution of each side to total volume.
• POC: An average reference level where market consensus was strongest.
• Progress: A graphical bar showing buy vs sell dominance.
• Signal: Simplified output like Strong Buy, Buy, Strong Sell, Sell, Neutral.
• Summary Row: Compares changes between the current and previous candles and gives overall market sentiment.
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Stock Market Disclaimer
This tool is for educational and informational purposes only. It does not constitute financial advice, investment advice, or trading recommendations. The stock market and cryptocurrency markets involve high risk. Traders and investors should do their own research and consult licensed financial advisors before making investment decisions. Past performance is not indicative of future results.
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Misuse Disclaimer
This script has been developed as per TradingView’s rules and is intended for responsible trading analysis only. Any misuse, redistribution, or modification outside of TradingView’s policies is discouraged. The author and platform are not responsible for financial losses, misinterpretation of signals, or misuse of the code.
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Disclaimer
Training & Educational Only — This material and the indicator are provided for educational purposes only. Nothing here is investment advice or a solicitation to buy or sell financial instruments. Past simulated or historical performance does not predict future results. Always perform full back testing and risk management, and consider seeking advice from a qualified financial professional before trading with real capital.
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Market Outlook Score (MOS)Overview
The "Market Outlook Score (MOS)" is a custom technical indicator designed for TradingView, written in Pine Script version 6. It provides a quantitative assessment of market conditions by aggregating multiple factors, including trend strength across different timeframes, directional movement (via ADX), momentum (via RSI changes), volume dynamics, and volatility stability (via ATR). The MOS is calculated as a weighted score that ranges typically between -1 and +1 (though it can exceed these bounds in extreme conditions), where positive values suggest bullish (long) opportunities, negative values indicate bearish (short) setups, and values near zero imply neutral or indecisive markets.
This indicator is particularly useful for traders seeking a holistic "outlook" score to gauge potential entry points or market bias. It overlays on a separate pane (non-overlay mode) and visualizes the score through horizontal threshold lines and dynamic labels showing the numeric MOS value along with a simple trading decision ("Long", "Short", or "Neutral"). The script avoids using the plot function for compatibility reasons (e.g., potential TradingView bugs) and instead relies on hline for static lines and label.new for per-bar annotations.
Key features:
Multi-Timeframe Analysis: Incorporates slope data from 5-minute, 15-minute, and 30-minute charts to capture short-term trends.
Trend and Strength Integration: Uses ADX to weight trend bias, ensuring stronger signals in trending markets.
Momentum and Volume: Includes RSI momentum impulses and volume deviations for added confirmation.
Volatility Adjustment: Factors in ATR changes to assess market stability.
Customizable Inputs: Allows users to tweak periods for lookback, ADX, and ATR.
Decision Labels: Automatically classifies the MOS into actionable categories with visual labels.
This indicator is best suited for intraday or swing trading on volatile assets like stocks, forex, or cryptocurrencies. It does not generate buy/sell signals directly but can be combined with other tools (e.g., moving averages or oscillators) for comprehensive strategies.
Inputs
The script provides three user-configurable inputs via TradingView's input panel:
Lookback Period (lookback):
Type: Integer
Default: 20
Range: Minimum 10, Maximum 50
Purpose: Defines the number of bars used in slope calculations for trend analysis. A shorter lookback makes the indicator more sensitive to recent price action, while a longer one smooths out noise for longer-term trends.
ADX Period (adxPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Sets the smoothing period for the Average Directional Index (ADX) and its components (DI+ and DI-). Standard value is 14, but shorter periods increase responsiveness, and longer ones reduce false signals.
ATR Period (atrPeriod):
Type: Integer
Default: 14
Range: Minimum 5, Maximum 30
Purpose: Determines the period for the Average True Range (ATR) calculation, which measures volatility. Adjust this to match your trading timeframe—shorter for scalping, longer for positional trading.
These inputs allow customization without editing the code, making the indicator adaptable to different market conditions or user preferences.
Core Calculations
The MOS is computed through a series of steps, blending trend, momentum, volume, and volatility metrics. Here's a breakdown:
Multi-Timeframe Slopes:
The script fetches data from higher timeframes (5m, 15m, 30m) using request.security.
Slope calculation: For each timeframe, it computes the linear regression slope of price over the lookback period using the formula:
textslope = correlation(close, bar_index, lookback) * stdev(close, lookback) / stdev(bar_index, lookback)
This measures the rate of price change, where positive slopes indicate uptrends and negative slopes indicate downtrends.
Variables: slope5m, slope15m, slope30m.
ATR (Average True Range):
Calculated using ta.atr(atrPeriod).
Represents average volatility over the specified period. Used later to derive volatility stability.
ADX (Average Directional Index):
A detailed, manual implementation (not using built-in ta.adx for customization):
Computes upward movement (upMove = high - high ) and downward movement (downMove = low - low).
Derives +DM (Plus Directional Movement) and -DM (Minus Directional Movement) by filtering non-relevant moves.
Smooths true range (trur = ta.rma(ta.tr(true), adxPeriod)).
Calculates +DI and -DI: plusDI = 100 * ta.rma(plusDM, adxPeriod) / trur, similarly for minusDI.
DX: dx = 100 * abs(plusDI - minusDI) / max(plusDI + minusDI, 0.0001).
ADX: adx = ta.rma(dx, adxPeriod).
ADX values above 25 typically indicate strong trends; here, it's normalized (divided by 50) to influence the trend bias.
Volume Delta (5m Timeframe):
Fetches 5m volume: volume_5m = request.security(syminfo.tickerid, "5", volume, lookahead=barmerge.lookahead_on).
Computes a 12-period SMA of volume: avgVolume = ta.sma(volume_5m, 12).
Delta: (volume_5m - avgVolume) / avgVolume (or 0 if avgVolume is zero).
This measures relative volume spikes, where positive deltas suggest increased interest (bullish) and negative suggest waning activity (bearish).
MOS Components and Final Calculation:
Trend Bias: Average of the three slopes, normalized by close price and scaled by 100, then weighted by ADX influence: (slope5m + slope15m + slope30m) / 3 / close * 100 * (adx / 50).
Emphasizes trends in strong ADX conditions.
Momentum Impulse: Change in 5m RSI(14) over 1 bar, divided by 50: ta.change(request.security(syminfo.tickerid, "5", ta.rsi(close, 14), lookahead=barmerge.lookahead_on), 1) / 50.
Captures short-term momentum shifts.
Volatility Clarity: 1 - ta.change(atr, 1) / max(atr, 0.0001).
Measures ATR stability; values near 1 indicate low volatility changes (clearer trends), while lower values suggest erratic markets.
MOS Formula: Weighted average:
textmos = (0.35 * trendBias + 0.25 * momentumImpulse + 0.2 * volumeDelta + 0.2 * volatilityClarity)
Weights prioritize trend (35%) and momentum (25%), with volume and volatility at 20% each. These can be adjusted in code for experimentation.
Trading Decision:
A variable mosDecision starts as "Neutral".
If mos > 0.15, set to "Long".
If mos < -0.15, set to "Short".
Thresholds (0.15 and -0.15) are hardcoded but can be modified.
Visualization and Outputs
Threshold Lines (using hline):
Long Threshold: Horizontal dashed green line at +0.15.
Short Threshold: Horizontal dashed red line at -0.15.
Neutral Line: Horizontal dashed gray line at 0.
These provide visual reference points for MOS interpretation.
Dynamic Labels (using label.new):
Placed at each bar's index and MOS value.
Text: Formatted MOS value (e.g., "0.2345") followed by a newline and the decision (e.g., "Long").
Style: Downward-pointing label with gray background and white text for readability.
This replaces a traditional plot line, showing exact values and decisions per bar without cluttering the chart.
The indicator appears in a separate pane below the main price chart, making it easy to monitor alongside price action.
Usage Instructions
Adding to TradingView:
Copy the script into TradingView's Pine Script editor.
Save and add to your chart via the "Indicators" menu.
Select a symbol and timeframe (e.g., 1-minute for intraday).
Interpretation:
Long Signal: MOS > 0.15 – Consider bullish positions if supported by other indicators.
Short Signal: MOS < -0.15 – Potential bearish setups.
Neutral: Between -0.15 and 0.15 – Avoid trades or wait for confirmation.
Watch for MOS crossings of thresholds for momentum shifts.
Combine with price patterns, support/resistance, or volume for better accuracy.
Limitations and Considerations:
Lookahead Bias: Uses barmerge.lookahead_on for multi-timeframe data, which may introduce minor forward-looking bias in backtesting (use with caution).
No Alerts Built-In: Add custom alerts via TradingView's alert system based on MOS conditions.
Performance: Tested for compatibility; may require adjustments for illiquid assets or extreme volatility.
Backtesting: Use TradingView's strategy tester to evaluate historical performance, but remember past results don't guarantee future outcomes.
Customization: Edit weights in the MOS formula or thresholds to fit your strategy.
This indicator distills complex market data into a single score, aiding decision-making while encouraging users to verify signals with additional analysis. If you need modifications, such as restoring plot functionality or adding features, provide details for further refinement.
Kelly Position Size CalculatorThis position sizing calculator implements the Kelly Criterion, developed by John L. Kelly Jr. at Bell Laboratories in 1956, to determine mathematically optimal position sizes for maximizing long-term wealth growth. Unlike arbitrary position sizing methods, this tool provides a scientifically solution based on your strategy's actual performance statistics and incorporates modern refinements from over six decades of academic research.
The Kelly Criterion addresses a fundamental question in capital allocation: "What fraction of capital should be allocated to each opportunity to maximize growth while avoiding ruin?" This question has profound implications for financial markets, where traders and investors constantly face decisions about optimal capital allocation (Van Tharp, 2007).
Theoretical Foundation
The Kelly Criterion for binary outcomes is expressed as f* = (bp - q) / b, where f* represents the optimal fraction of capital to allocate, b denotes the risk-reward ratio, p indicates the probability of success, and q represents the probability of loss (Kelly, 1956). This formula maximizes the expected logarithm of wealth, ensuring maximum long-term growth rate while avoiding the risk of ruin.
The mathematical elegance of Kelly's approach lies in its derivation from information theory. Kelly's original work was motivated by Claude Shannon's information theory (Shannon, 1948), recognizing that maximizing the logarithm of wealth is equivalent to maximizing the rate of information transmission. This connection between information theory and wealth accumulation provides a deep theoretical foundation for optimal position sizing.
The logarithmic utility function underlying the Kelly Criterion naturally embodies several desirable properties for capital management. It exhibits decreasing marginal utility, penalizes large losses more severely than it rewards equivalent gains, and focuses on geometric rather than arithmetic mean returns, which is appropriate for compounding scenarios (Thorp, 2006).
Scientific Implementation
This calculator extends beyond basic Kelly implementation by incorporating state of the art refinements from academic research:
Parameter Uncertainty Adjustment: Following Michaud (1989), the implementation applies Bayesian shrinkage to account for parameter estimation error inherent in small sample sizes. The adjustment formula f_adjusted = f_kelly × confidence_factor + f_conservative × (1 - confidence_factor) addresses the overconfidence bias documented by Baker and McHale (2012), where the confidence factor increases with sample size and the conservative estimate equals 0.25 (quarter Kelly).
Sample Size Confidence: The reliability of Kelly calculations depends critically on sample size. Research by Browne and Whitt (1996) provides theoretical guidance on minimum sample requirements, suggesting that at least 30 independent observations are necessary for meaningful parameter estimates, with 100 or more trades providing reliable estimates for most trading strategies.
Universal Asset Compatibility: The calculator employs intelligent asset detection using TradingView's built-in symbol information, automatically adapting calculations for different asset classes without manual configuration.
ASSET SPECIFIC IMPLEMENTATION
Equity Markets: For stocks and ETFs, position sizing follows the calculation Shares = floor(Kelly Fraction × Account Size / Share Price). This straightforward approach reflects whole share constraints while accommodating fractional share trading capabilities.
Foreign Exchange Markets: Forex markets require lot-based calculations following Lot Size = Kelly Fraction × Account Size / (100,000 × Base Currency Value). The calculator automatically handles major currency pairs with appropriate pip value calculations, following industry standards described by Archer (2010).
Futures Markets: Futures position sizing accounts for leverage and margin requirements through Contracts = floor(Kelly Fraction × Account Size / Margin Requirement). The calculator estimates margin requirements as a percentage of contract notional value, with specific adjustments for micro-futures contracts that have smaller sizes and reduced margin requirements (Kaufman, 2013).
Index and Commodity Markets: These markets combine characteristics of both equity and futures markets. The calculator automatically detects whether instruments are cash-settled or futures-based, applying appropriate sizing methodologies with correct point value calculations.
Risk Management Integration
The calculator integrates sophisticated risk assessment through two primary modes:
Stop Loss Integration: When fixed stop-loss levels are defined, risk calculation follows Risk per Trade = Position Size × Stop Loss Distance. This ensures that the Kelly fraction accounts for actual risk exposure rather than theoretical maximum loss, with stop-loss distance measured in appropriate units for each asset class.
Strategy Drawdown Assessment: For discretionary exit strategies, risk estimation uses maximum historical drawdown through Risk per Trade = Position Value × (Maximum Drawdown / 100). This approach assumes that individual trade losses will not exceed the strategy's historical maximum drawdown, providing a reasonable estimate for strategies with well-defined risk characteristics.
Fractional Kelly Approaches
Pure Kelly sizing can produce substantial volatility, leading many practitioners to adopt fractional Kelly approaches. MacLean, Sanegre, Zhao, and Ziemba (2004) analyze the trade-offs between growth rate and volatility, demonstrating that half-Kelly typically reduces volatility by approximately 75% while sacrificing only 25% of the growth rate.
The calculator provides three primary Kelly modes to accommodate different risk preferences and experience levels. Full Kelly maximizes growth rate while accepting higher volatility, making it suitable for experienced practitioners with strong risk tolerance and robust capital bases. Half Kelly offers a balanced approach popular among professional traders, providing optimal risk-return balance by reducing volatility significantly while maintaining substantial growth potential. Quarter Kelly implements a conservative approach with low volatility, recommended for risk-averse traders or those new to Kelly methodology who prefer gradual introduction to optimal position sizing principles.
Empirical Validation and Performance
Extensive academic research supports the theoretical advantages of Kelly sizing. Hakansson and Ziemba (1995) provide a comprehensive review of Kelly applications in finance, documenting superior long-term performance across various market conditions and asset classes. Estrada (2008) analyzes Kelly performance in international equity markets, finding that Kelly-based strategies consistently outperform fixed position sizing approaches over extended periods across 19 developed markets over a 30-year period.
Several prominent investment firms have successfully implemented Kelly-based position sizing. Pabrai (2007) documents the application of Kelly principles at Berkshire Hathaway, noting Warren Buffett's concentrated portfolio approach aligns closely with Kelly optimal sizing for high-conviction investments. Quantitative hedge funds, including Renaissance Technologies and AQR, have incorporated Kelly-based risk management into their systematic trading strategies.
Practical Implementation Guidelines
Successful Kelly implementation requires systematic application with attention to several critical factors:
Parameter Estimation: Accurate parameter estimation represents the greatest challenge in practical Kelly implementation. Brown (1976) notes that small errors in probability estimates can lead to significant deviations from optimal performance. The calculator addresses this through Bayesian adjustments and confidence measures.
Sample Size Requirements: Users should begin with conservative fractional Kelly approaches until achieving sufficient historical data. Strategies with fewer than 30 trades may produce unreliable Kelly estimates, regardless of adjustments. Full confidence typically requires 100 or more independent trade observations.
Market Regime Considerations: Parameters that accurately describe historical performance may not reflect future market conditions. Ziemba (2003) recommends regular parameter updates and conservative adjustments when market conditions change significantly.
Professional Features and Customization
The calculator provides comprehensive customization options for professional applications:
Multiple Color Schemes: Eight professional color themes (Gold, EdgeTools, Behavioral, Quant, Ocean, Fire, Matrix, Arctic) with dark and light theme compatibility ensure optimal visibility across different trading environments.
Flexible Display Options: Adjustable table size and position accommodate various chart layouts and user preferences, while maintaining analytical depth and clarity.
Comprehensive Results: The results table presents essential information including asset specifications, strategy statistics, Kelly calculations, sample confidence measures, position values, risk assessments, and final position sizes in appropriate units for each asset class.
Limitations and Considerations
Like any analytical tool, the Kelly Criterion has important limitations that users must understand:
Stationarity Assumption: The Kelly Criterion assumes that historical strategy statistics represent future performance characteristics. Non-stationary market conditions may invalidate this assumption, as noted by Lo and MacKinlay (1999).
Independence Requirement: Each trade should be independent to avoid correlation effects. Many trading strategies exhibit serial correlation in returns, which can affect optimal position sizing and may require adjustments for portfolio applications.
Parameter Sensitivity: Kelly calculations are sensitive to parameter accuracy. Regular calibration and conservative approaches are essential when parameter uncertainty is high.
Transaction Costs: The implementation incorporates user-defined transaction costs but assumes these remain constant across different position sizes and market conditions, following Ziemba (2003).
Advanced Applications and Extensions
Multi-Asset Portfolio Considerations: While this calculator optimizes individual position sizes, portfolio-level applications require additional considerations for correlation effects and aggregate risk management. Simplified portfolio approaches include treating positions independently with correlation adjustments.
Behavioral Factors: Behavioral finance research reveals systematic biases that can interfere with Kelly implementation. Kahneman and Tversky (1979) document loss aversion, overconfidence, and other cognitive biases that lead traders to deviate from optimal strategies. Successful implementation requires disciplined adherence to calculated recommendations.
Time-Varying Parameters: Advanced implementations may incorporate time-varying parameter models that adjust Kelly recommendations based on changing market conditions, though these require sophisticated econometric techniques and substantial computational resources.
Comprehensive Usage Instructions and Practical Examples
Implementation begins with loading the calculator on your desired trading instrument's chart. The system automatically detects asset type across stocks, forex, futures, and cryptocurrency markets while extracting current price information. Navigation to the indicator settings allows input of your specific strategy parameters.
Strategy statistics configuration requires careful attention to several key metrics. The win rate should be calculated from your backtest results using the formula of winning trades divided by total trades multiplied by 100. Average win represents the sum of all profitable trades divided by the number of winning trades, while average loss calculates the sum of all losing trades divided by the number of losing trades, entered as a positive number. The total historical trades parameter requires the complete number of trades in your backtest, with a minimum of 30 trades recommended for basic functionality and 100 or more trades optimal for statistical reliability. Account size should reflect your available trading capital, specifically the risk capital allocated for trading rather than total net worth.
Risk management configuration adapts to your specific trading approach. The stop loss setting should be enabled if you employ fixed stop-loss exits, with the stop loss distance specified in appropriate units depending on the asset class. For stocks, this distance is measured in dollars, for forex in pips, and for futures in ticks. When stop losses are not used, the maximum strategy drawdown percentage from your backtest provides the risk assessment baseline. Kelly mode selection offers three primary approaches: Full Kelly for aggressive growth with higher volatility suitable for experienced practitioners, Half Kelly for balanced risk-return optimization popular among professional traders, and Quarter Kelly for conservative approaches with reduced volatility.
Display customization ensures optimal integration with your trading environment. Eight professional color themes provide optimization for different chart backgrounds and personal preferences. Table position selection allows optimal placement within your chart layout, while table size adjustment ensures readability across different screen resolutions and viewing preferences.
Detailed Practical Examples
Example 1: SPY Swing Trading Strategy
Consider a professionally developed swing trading strategy for SPY (S&P 500 ETF) with backtesting results spanning 166 total trades. The strategy achieved 110 winning trades, representing a 66.3% win rate, with an average winning trade of $2,200 and average losing trade of $862. The maximum drawdown reached 31.4% during the testing period, and the available trading capital amounts to $25,000. This strategy employs discretionary exits without fixed stop losses.
Implementation requires loading the calculator on the SPY daily chart and configuring the parameters accordingly. The win rate input receives 66.3, while average win and loss inputs receive 2200 and 862 respectively. Total historical trades input requires 166, with account size set to 25000. The stop loss function remains disabled due to the discretionary exit approach, with maximum strategy drawdown set to 31.4%. Half Kelly mode provides the optimal balance between growth and risk management for this application.
The calculator generates several key outputs for this scenario. The risk-reward ratio calculates automatically to 2.55, while the Kelly fraction reaches approximately 53% before scientific adjustments. Sample confidence achieves 100% given the 166 trades providing high statistical confidence. The recommended position settles at approximately 27% after Half Kelly and Bayesian adjustment factors. Position value reaches approximately $6,750, translating to 16 shares at a $420 SPY price. Risk per trade amounts to approximately $2,110, representing 31.4% of position value, with expected value per trade reaching approximately $1,466. This recommendation represents the mathematically optimal balance between growth potential and risk management for this specific strategy profile.
Example 2: EURUSD Day Trading with Stop Losses
A high-frequency EURUSD day trading strategy demonstrates different parameter requirements compared to swing trading approaches. This strategy encompasses 89 total trades with a 58% win rate, generating an average winning trade of $180 and average losing trade of $95. The maximum drawdown reached 12% during testing, with available capital of $10,000. The strategy employs fixed stop losses at 25 pips and take profit targets at 45 pips, providing clear risk-reward parameters.
Implementation begins with loading the calculator on the EURUSD 1-hour chart for appropriate timeframe alignment. Parameter configuration includes win rate at 58, average win at 180, and average loss at 95. Total historical trades input receives 89, with account size set to 10000. The stop loss function is enabled with distance set to 25 pips, reflecting the fixed exit strategy. Quarter Kelly mode provides conservative positioning due to the smaller sample size compared to the previous example.
Results demonstrate the impact of smaller sample sizes on Kelly calculations. The risk-reward ratio calculates to 1.89, while the Kelly fraction reaches approximately 32% before adjustments. Sample confidence achieves 89%, providing moderate statistical confidence given the 89 trades. The recommended position settles at approximately 7% after Quarter Kelly application and Bayesian shrinkage adjustment for the smaller sample. Position value amounts to approximately $700, translating to 0.07 standard lots. Risk per trade reaches approximately $175, calculated as 25 pips multiplied by lot size and pip value, with expected value per trade at approximately $49. This conservative position sizing reflects the smaller sample size, with position sizes expected to increase as trade count surpasses 100 and statistical confidence improves.
Example 3: ES1! Futures Systematic Strategy
Systematic futures trading presents unique considerations for Kelly criterion application, as demonstrated by an E-mini S&P 500 futures strategy encompassing 234 total trades. This systematic approach achieved a 45% win rate with an average winning trade of $1,850 and average losing trade of $720. The maximum drawdown reached 18% during the testing period, with available capital of $50,000. The strategy employs 15-tick stop losses with contract specifications of $50 per tick, providing precise risk control mechanisms.
Implementation involves loading the calculator on the ES1! 15-minute chart to align with the systematic trading timeframe. Parameter configuration includes win rate at 45, average win at 1850, and average loss at 720. Total historical trades receives 234, providing robust statistical foundation, with account size set to 50000. The stop loss function is enabled with distance set to 15 ticks, reflecting the systematic exit methodology. Half Kelly mode balances growth potential with appropriate risk management for futures trading.
Results illustrate how favorable risk-reward ratios can support meaningful position sizing despite lower win rates. The risk-reward ratio calculates to 2.57, while the Kelly fraction reaches approximately 16%, lower than previous examples due to the sub-50% win rate. Sample confidence achieves 100% given the 234 trades providing high statistical confidence. The recommended position settles at approximately 8% after Half Kelly adjustment. Estimated margin per contract amounts to approximately $2,500, resulting in a single contract allocation. Position value reaches approximately $2,500, with risk per trade at $750, calculated as 15 ticks multiplied by $50 per tick. Expected value per trade amounts to approximately $508. Despite the lower win rate, the favorable risk-reward ratio supports meaningful position sizing, with single contract allocation reflecting appropriate leverage management for futures trading.
Example 4: MES1! Micro-Futures for Smaller Accounts
Micro-futures contracts provide enhanced accessibility for smaller trading accounts while maintaining identical strategy characteristics. Using the same systematic strategy statistics from the previous example but with available capital of $15,000 and micro-futures specifications of $5 per tick with reduced margin requirements, the implementation demonstrates improved position sizing granularity.
Kelly calculations remain identical to the full-sized contract example, maintaining the same risk-reward dynamics and statistical foundations. However, estimated margin per contract reduces to approximately $250 for micro-contracts, enabling allocation of 4-5 micro-contracts. Position value reaches approximately $1,200, while risk per trade calculates to $75, derived from 15 ticks multiplied by $5 per tick. This granularity advantage provides better position size precision for smaller accounts, enabling more accurate Kelly implementation without requiring large capital commitments.
Example 5: Bitcoin Swing Trading
Cryptocurrency markets present unique challenges requiring modified Kelly application approaches. A Bitcoin swing trading strategy on BTCUSD encompasses 67 total trades with a 71% win rate, generating average winning trades of $3,200 and average losing trades of $1,400. Maximum drawdown reached 28% during testing, with available capital of $30,000. The strategy employs technical analysis for exits without fixed stop losses, relying on price action and momentum indicators.
Implementation requires conservative approaches due to cryptocurrency volatility characteristics. Quarter Kelly mode is recommended despite the high win rate to account for crypto market unpredictability. Expected position sizing remains reduced due to the limited sample size of 67 trades, requiring additional caution until statistical confidence improves. Regular parameter updates are strongly recommended due to cryptocurrency market evolution and changing volatility patterns that can significantly impact strategy performance characteristics.
Advanced Usage Scenarios
Portfolio position sizing requires sophisticated consideration when running multiple strategies simultaneously. Each strategy should have its Kelly fraction calculated independently to maintain mathematical integrity. However, correlation adjustments become necessary when strategies exhibit related performance patterns. Moderately correlated strategies should receive individual position size reductions of 10-20% to account for overlapping risk exposure. Aggregate portfolio risk monitoring ensures total exposure remains within acceptable limits across all active strategies. Professional practitioners often consider using lower fractional Kelly approaches, such as Quarter Kelly, when running multiple strategies simultaneously to provide additional safety margins.
Parameter sensitivity analysis forms a critical component of professional Kelly implementation. Regular validation procedures should include monthly parameter updates using rolling 100-trade windows to capture evolving market conditions while maintaining statistical relevance. Sensitivity testing involves varying win rates by ±5% and average win/loss ratios by ±10% to assess recommendation stability under different parameter assumptions. Out-of-sample validation reserves 20% of historical data for parameter verification, ensuring that optimization doesn't create curve-fitted results. Regime change detection monitors actual performance against expected metrics, triggering parameter reassessment when significant deviations occur.
Risk management integration requires professional overlay considerations beyond pure Kelly calculations. Daily loss limits should cease trading when daily losses exceed twice the calculated risk per trade, preventing emotional decision-making during adverse periods. Maximum position limits should never exceed 25% of account value in any single position regardless of Kelly recommendations, maintaining diversification principles. Correlation monitoring reduces position sizes when holding multiple correlated positions that move together during market stress. Volatility adjustments consider reducing position sizes during periods of elevated VIX above 25 for equity strategies, adapting to changing market conditions.
Troubleshooting and Optimization
Professional implementation often encounters specific challenges requiring systematic troubleshooting approaches. Zero position size displays typically result from insufficient capital for minimum position sizes, negative expected values, or extremely conservative Kelly calculations. Solutions include increasing account size, verifying strategy statistics for accuracy, considering Quarter Kelly mode for conservative approaches, or reassessing overall strategy viability when fundamental issues exist.
Extremely high Kelly fractions exceeding 50% usually indicate underlying problems with parameter estimation. Common causes include unrealistic win rates, inflated risk-reward ratios, or curve-fitted backtest results that don't reflect genuine trading conditions. Solutions require verifying backtest methodology, including all transaction costs in calculations, testing strategies on out-of-sample data, and using conservative fractional Kelly approaches until parameter reliability improves.
Low sample confidence below 50% reflects insufficient historical trades for reliable parameter estimation. This situation demands gathering additional trading data, using Quarter Kelly approaches until reaching 100 or more trades, applying extra conservatism in position sizing, and considering paper trading to build statistical foundations without capital risk.
Inconsistent results across similar strategies often stem from parameter estimation differences, market regime changes, or strategy degradation over time. Professional solutions include standardizing backtest methodology across all strategies, updating parameters regularly to reflect current conditions, and monitoring live performance against expectations to identify deteriorating strategies.
Position sizes that appear inappropriately large or small require careful validation against traditional risk management principles. Professional standards recommend never risking more than 2-3% per trade regardless of Kelly calculations. Calibration should begin with Quarter Kelly approaches, gradually increasing as comfort and confidence develop. Most institutional traders utilize 25-50% of full Kelly recommendations to balance growth with prudent risk management.
Market condition adjustments require dynamic approaches to Kelly implementation. Trending markets may support full Kelly recommendations when directional momentum provides favorable conditions. Ranging or volatile markets typically warrant reducing to Half or Quarter Kelly to account for increased uncertainty. High correlation periods demand reducing individual position sizes when multiple positions move together, concentrating risk exposure. News and event periods often justify temporary position size reductions during high-impact releases that can create unpredictable market movements.
Performance monitoring requires systematic protocols to ensure Kelly implementation remains effective over time. Weekly reviews should compare actual versus expected win rates and average win/loss ratios to identify parameter drift or strategy degradation. Position size efficiency and execution quality monitoring ensures that calculated recommendations translate effectively into actual trading results. Tracking correlation between calculated and realized risk helps identify discrepancies between theoretical and practical risk exposure.
Monthly calibration provides more comprehensive parameter assessment using the most recent 100 trades to maintain statistical relevance while capturing current market conditions. Kelly mode appropriateness requires reassessment based on recent market volatility and performance characteristics, potentially shifting between Full, Half, and Quarter Kelly approaches as conditions change. Transaction cost evaluation ensures that commission structures, spreads, and slippage estimates remain accurate and current.
Quarterly strategic reviews encompass comprehensive strategy performance analysis comparing long-term results against expectations and identifying trends in effectiveness. Market regime assessment evaluates parameter stability across different market conditions, determining whether strategy characteristics remain consistent or require fundamental adjustments. Strategic modifications to position sizing methodology may become necessary as markets evolve or trading approaches mature, ensuring that Kelly implementation continues supporting optimal capital allocation objectives.
Professional Applications
This calculator serves diverse professional applications across the financial industry. Quantitative hedge funds utilize the implementation for systematic position sizing within algorithmic trading frameworks, where mathematical precision and consistent application prove essential for institutional capital management. Professional discretionary traders benefit from optimized position management that removes emotional bias while maintaining flexibility for market-specific adjustments. Portfolio managers employ the calculator for developing risk-adjusted allocation strategies that enhance returns while maintaining prudent risk controls across diverse asset classes and investment strategies.
Individual traders seeking mathematical optimization of capital allocation find the calculator provides institutional-grade methodology previously available only to professional money managers. The Kelly Criterion establishes theoretical foundation for optimal capital allocation across both single strategies and multiple trading systems, offering significant advantages over arbitrary position sizing methods that rely on intuition or fixed percentage approaches. Professional implementation ensures consistent application of mathematically sound principles while adapting to changing market conditions and strategy performance characteristics.
Conclusion
The Kelly Criterion represents one of the few mathematically optimal solutions to fundamental investment problems. When properly understood and carefully implemented, it provides significant competitive advantage in financial markets. This calculator implements modern refinements to Kelly's original formula while maintaining accessibility for practical trading applications.
Success with Kelly requires ongoing learning, systematic application, and continuous refinement based on market feedback and evolving research. Users who master Kelly principles and implement them systematically can expect superior risk-adjusted returns and more consistent capital growth over extended periods.
The extensive academic literature provides rich resources for deeper study, while practical experience builds the intuition necessary for effective implementation. Regular parameter updates, conservative approaches with limited data, and disciplined adherence to calculated recommendations are essential for optimal results.
References
Archer, M. D. (2010). Getting Started in Currency Trading: Winning in Today's Forex Market (3rd ed.). John Wiley & Sons.
Baker, R. D., & McHale, I. G. (2012). An empirical Bayes approach to optimising betting strategies. Journal of the Royal Statistical Society: Series D (The Statistician), 61(1), 75-92.
Breiman, L. (1961). Optimal gambling systems for favorable games. In J. Neyman (Ed.), Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability (pp. 65-78). University of California Press.
Brown, D. B. (1976). Optimal portfolio growth: Logarithmic utility and the Kelly criterion. In W. T. Ziemba & R. G. Vickson (Eds.), Stochastic Optimization Models in Finance (pp. 1-23). Academic Press.
Browne, S., & Whitt, W. (1996). Portfolio choice and the Bayesian Kelly criterion. Advances in Applied Probability, 28(4), 1145-1176.
Estrada, J. (2008). Geometric mean maximization: An overlooked portfolio approach? The Journal of Investing, 17(4), 134-147.
Hakansson, N. H., & Ziemba, W. T. (1995). Capital growth theory. In R. A. Jarrow, V. Maksimovic, & W. T. Ziemba (Eds.), Handbooks in Operations Research and Management Science (Vol. 9, pp. 65-86). Elsevier.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Kaufman, P. J. (2013). Trading Systems and Methods (5th ed.). John Wiley & Sons.
Kelly Jr, J. L. (1956). A new interpretation of information rate. Bell System Technical Journal, 35(4), 917-926.
Lo, A. W., & MacKinlay, A. C. (1999). A Non-Random Walk Down Wall Street. Princeton University Press.
MacLean, L. C., Sanegre, E. O., Zhao, Y., & Ziemba, W. T. (2004). Capital growth with security. Journal of Economic Dynamics and Control, 28(4), 937-954.
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Michaud, R. O. (1989). The Markowitz optimization enigma: Is 'optimized' optimal? Financial Analysts Journal, 45(1), 31-42.
Pabrai, M. (2007). The Dhandho Investor: The Low-Risk Value Method to High Returns. John Wiley & Sons.
Shannon, C. E. (1948). A mathematical theory of communication. Bell System Technical Journal, 27(3), 379-423.
Tharp, V. K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill.
Thorp, E. O. (2006). The Kelly criterion in blackjack sports betting, and the stock market. In L. C. MacLean, E. O. Thorp, & W. T. Ziemba (Eds.), The Kelly Capital Growth Investment Criterion: Theory and Practice (pp. 789-832). World Scientific.
Van Tharp, K. (2007). Trade Your Way to Financial Freedom (2nd ed.). McGraw-Hill Education.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Vince, R., & Zhu, H. (2015). Optimal betting under parameter uncertainty. Journal of Statistical Planning and Inference, 161, 19-31.
Ziemba, W. T. (2003). The Stochastic Programming Approach to Asset, Liability, and Wealth Management. The Research Foundation of AIMR.
Further Reading
For comprehensive understanding of Kelly Criterion applications and advanced implementations:
MacLean, L. C., Thorp, E. O., & Ziemba, W. T. (2011). The Kelly Capital Growth Investment Criterion: Theory and Practice. World Scientific.
Vince, R. (1992). The Mathematics of Money Management: Risk Analysis Techniques for Traders. John Wiley & Sons.
Thorp, E. O. (2017). A Man for All Markets: From Las Vegas to Wall Street. Random House.
Cover, T. M., & Thomas, J. A. (2006). Elements of Information Theory (2nd ed.). John Wiley & Sons.
Ziemba, W. T., & Vickson, R. G. (Eds.). (2006). Stochastic Optimization Models in Finance. World Scientific.
RSI, CCI, ADX Panel (Custom TF for Each)RSI, CCI, and ADX Combined – Multi-Timeframe, Fully Customizable Panel Indicator for TradingView
Overview
This Pine Script indicator integrates the Relative Strength Index (RSI), Commodity Channel Index (CCI), and Average Directional Index (ADX) into a single, clean panel for effortless technical analysis. Each indicator operates independently, with customizable length, smoothing, and time frame for maximum flexibility. Traders can now monitor momentum, trend strength, and overbought/oversold conditions across different time frames—all in one place.
Key Features
Independent Controls: Set length, smoothing (ADX), and time frame individually for each indicator via the settings panel.
Multi-Timeframe Support: Each oscillator (RSI, CCI, ADX) can be calculated on its own time frame, enabling nuanced inter-timeframe analysis.
Customizable Visualization: Adjust line color and thickness for each indicator to match your chart style.
Clean, Non-Overlay Display: All three indicators are plotted in a dedicated panel beneath the price chart, reducing clutter.
Reference Levels: Includes standard reference lines for oversold/overbought (RSI, CCI) and trend threshold (ADX) for quick visual cues.
Usage Ideas
Swing Trading: Compare short- and long-term momentum using different time frames for RSI, CCI, and ADX.
Trend Confirmation: Use ADX to filter RSI and CCI signals—only trade overbought/oversold conditions during strong trends.
Divergence Hunting: Spot divergences between time frames for early reversal signals.
Scalping: Set RSI and CCI to lower time frames for entry, while monitoring higher timeframe ADX for trend context.
How to Install
Paste the script into the Pine Editor on TradingView.
Add to chart. Adjust settings as desired.
Save as a template for quick reuse on any chart—all your custom settings will be preserved.
Customization
Edit lengths and time frames in the indicator’s settings dialog.
Toggle reference lines on/off as needed.
Fine-tune line appearance (color, thickness) for clarity.
Note:
This indicator does not provide automated buy/sell signals. It is a customizable analytical tool for manual or semi-automated trading. Use in combination with other technical or fundamental analysis for best results.
Combine Momentum, Trend, and Volatility—Seamlessly and Visually—With One Indicator.
Drunken Bird Inspiration for the support and resistance plateau lines came from AnotherDAPTrader.
The TSL Drunken Bird is an enhanced technical analysis tool for swing traders on TradingView, based on the original Accurate Swing Trading System by ceyhun. It generates buy and sell signals when price crosses a dynamic Trailing Stop Loss (TSL) level derived from recent highs and lows. This version introduces plateau detection for support and resistance lines, dynamic label expiration to reduce clutter, customizable line styles and decay, and improved HTF confluence for trend-aligned trading. Visual elements include signal labels, horizontal lines, a colored TSL plot, and optional bar/background coloring. Alerts are available for buy/sell crossovers, making it suitable for assets like NASDAQ E-mini futures, stocks, forex, and more.
This script adapts and expands upon ceyhun's original codetradingview.com, adding significant features such as tolerance-based plateau identification for support/resistance, label management with timeframe-aware expiration (~7 days), cross-count decay for lines, and expanded customization options. Inspiration for the support and resistance plateau lines came from AnotherDAPTrader. Released under the Mozilla Public License 2.0.Key
Features
Swing Signals: "BUY" and "SELL" labels on price crossovers/crossunders of the TSL, with a user-defined lookback (default 3).
HTF Confluence: Filters signals based on higher timeframe trend (e.g., "EXIT LONG" instead of "SELL" if HTF is bullish); toggleable.
HTF Options: Select from 5m, 15m, 30m, 1h, 4h, Daily, Weekly, or Monthly.
Plateau Detection: Identifies flat highs/lows (with tolerance) for resistance/support lines, plotted as dotted/solid/dashed with customizable colors, thickness, and decay after crosses (default 2).
Horizontal Lines: Green (buy) and red (sell) lines at signal closes, extending right until crossed; toggle between short (no extension limit) or long visualization.
TSL Visualization: Colored line (green if close >= TSL, red otherwise) for dynamic levels.
Bar/Background Coloring: Optional green/red coloring based on price vs. TSL.
Label Expiration: All labels (signals and plateaus) auto-delete after ~7 days (timeframe-adjusted, default 1008 bars).
Alerts: Triggers for "Buy Signal" and "Sell Signal" on crossovers.
How to Use
Add to Chart: Paste the Pine Script into TradingView's editor and add to your chart.
Configure Settings:
Swing: Lookback for highs/lows (min 1).
Plateau Tolerance: Flatness allowance (default 0.0).
Use HTF Confluence: Enable for trend filtering.
Higher Time Frame: Choose timeframe string.
Barcolor/Bgcolor: Toggle coloring.
Show Plateau Lines: Enable support/resistance.
Line Styles/Colors/Thickness: Customize buy/sell and plateau visuals.
Plateau Line Decay: Crosses before stopping extension.
Label Expiration: Bars for auto-deletion (~7 days).
Interpret Elements:
Labels: "BUY"/"SELL" (green/red), "EXIT SHORT"/"EXIT LONG" (orange) on signals; "Res"/"Sup" on plateaus.
Lines: Extend right until conditions met (cross for buy/sell, decay threshold for plateaus).
TSL Plot: Monitors trend shifts.
Set Alerts: Use "Buy Signal" or "Sell Signal" conditions for notifications.
Testing: Apply to volatile assets; adjust Swing for signal frequency, tolerance for plateau sensitivity.
Ideal Use Cases
Swing trading on 1m–1h charts for entries/exits aligned with HTF trends.
Identifying support/resistance in ranging markets via plateaus.
Scalping with short lookbacks or longer swings with HTF enabled.
Manual or alert-based trading on futures, stocks, or forex.
Why It's Valuable
This indicator builds on ceyhun's core TSL logic with practical enhancements for modern trading: clutter reduction via expiration/decay, visual customization, and plateau-based S/R for better context. It promotes disciplined, trend-aware decisions while maintaining simplicity.
Note: Optimized for any timeframe/asset; test in demo. Not financial advice—use with risk management.
Support Resistance with Order BlocksIndicator Description
Professional Price Level Detection for Smart Trading. Master the Markets with Precision Support/Resistance and Order Block Analysis . It provides traders with clear visual cues for potential reversal and breakout areas, combining both retail and institutional trading concepts into one powerful tool.
The Support & Resistance with Order Blocks indicator is a versatile Pine Script tool designed to empower traders with clear, actionable insights into key market levels. By combining advanced pivot-based support and resistance (S/R) detection with order block (OB) filtering, this indicator delivers clean, high-probability zones for entries, exits, and reversals. With customizable display options (boxes or lines) and intuitive settings, it’s perfect for traders of all styles—whether you’re scalping, swing trading, or investing long-term. Overlay it on your TradingView chart and elevate your trading strategy today!
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Key Features
✅ Dynamic Support/Resistance - Auto-adjusting levels based on price action
✅ Smart Order Block Detection - Identifies institutional buying/selling zones
✅ Dual Display Modes - Choose between Boxes or Clean Lines for different chart styles
✅ Customizable Sensitivity - Adjust detection parameters for different markets
✅ Broken Level Markers - Clearly shows when key levels are breached
✅ Timeframe-Adaptive - Automatically adjusts for daily/weekly charts
1. Dynamic Support & Resistance Detection
Identifies critical S/R zones using pivot high/low calculations with adjustable look back periods.
Visualizes active S/R zones with distinct colors and labels ("Support" or "Resistance" for boxes, lines for cleaner charts).
Marks broken S/R levels as "Br S" (broken support) or "Br R" (broken resistance) when historical display is enabled, aiding in breakout and reversal analysis.
2. Smart Order Block Identification
Detects bullish and bearish order blocks based on significant price movements (default: ±0.3% over 5 candles).
Highlights institutional buying/selling zones with customizable colors, displayed as boxes or lines.
Filters out overlapping OB zones to keep your chart clutter-free.
3. Dual Display Options
Boxes or Lines: Choose to display S/R and OB as boxes for detailed zones or lines for a minimalist view.
Line Width Customization: Adjust line widths for S/R and OB (1–5 pixels) for optimal visibility.
Color Customization: Tailor colors for active/broken S/R and bullish/bearish OB zones.
4. Advanced Overlap Filtering
Ensures S/R zones don’t overlap with OB zones or other S/R levels, providing only the most relevant levels.
Limits the number of active zones (default: 10) to maintain chart clarity.
5. Historical S/R Visualization
Optionally display broken S/R levels with distinct colors and labels ("Br S" or "Br R") to track historical price reactions.
Broken levels are dynamically updated and removed (or retained) based on user settings.
6. Timeframe Adaptability
Automatically adjusts pivot detection for daily/weekly timeframes (40-candle look back) versus shorter timeframes (20-candle look back).
Works seamlessly across all asset classes (stocks, forex, crypto, etc.) and timeframes.
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How It Works
• Support & Resistance:
Uses ta.pivothigh and ta.pivotlow to detect significant price pivots, with a user-defined look back (default: 5 candles post-pivot).
Plots S/R as boxes (with labels "Support" or "Resistance") or lines, extending to the current bar for real-time relevance.
Broken S/R levels are marked with adjusted colors and labels ("S" or "R" for boxes, "Br S" or "Br R" for lines when historical display is enabled).
• Order Blocks:
Identifies OB based on strong price movements over 4 candles, plotted as boxes or lines at the candle’s midpoint.
Validates OB to prevent overlap, ensuring only significant zones are displayed.
Removes OB zones when price breaks through, keeping the chart focused on active levels.
• Customization:
Toggle S/R and OB visibility, adjust detection sensitivity, and set maximum active zones (4–50).
Fine-tune line widths and colors for a personalized chart experience.
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Why Use This Indicator?
• Precision Trading: Pinpoint high-probability entry/exit zones with filtered S/R and OB levels.
• Clean Charts: Overlap filtering and zone limits reduce clutter, focusing on key levels.
• Versatile Display: Switch between boxes for detailed zones or lines for simplicity, with adjustable line widths.
• Institutional Edge: Leverage OB detection to align with institutional activity for smarter trades.
• User-Friendly: Intuitive settings and clear visuals make it accessible for beginners and pros alike.
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Settings Overview________________________________________
⚙ Input Parameters
Settings Overview
Display Options:
Display Type: Choose "Boxes" or "Lines" for S/R and OB visualization.
S/R Line Width: Set line thickness for S/R lines (1–5 pixels, default: 2).
OB Line Width: Set line thickness for OB lines (1–5 pixels, default: 2).
Order Block Options:
Show Order Block: Enable/disable OB display.
Bull/Bear OB Colors: Customise border and fill colors for bullish and bearish OB zones.
Support/Resistance Options:
Show S/R: Toggle active S/R zones.
Show Historical S/R: Display broken S/R levels, marked as "Br S" or "Br R" for lines.
Detection Period: Set candle lookback for pivot detection (4–50, default: 5).
Max Active Zones: Limit active S/R and OB zones (4–50, default: 10).
Colors: Customise active and broken S/R colors for clear differentiation.
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How to Use
1. Add to Chart: Apply the indicator to your TradingView chart.
2. Customize Settings:
o Select "Boxes" or "Lines" for your preferred display style.
o Adjust line widths, colors, and detection parameters to suit your trading style.
o Enable "Show Historical S/R" to track broken levels with "Br S" and "Br R" labels.
3. Analyze Levels:
o Use support zones (green) for buy entries and resistance zones (red) for sell entries.
o Monitor OB zones for institutional activity, signaling potential reversals or continuations.
o Watch for "Br S" or "Br R" labels to identify breakout opportunities.
4. Combine with Other Tools: Pair with trend indicators, volume analysis, or price action for a robust strategy.
5. Monitor Breakouts: Trade breakouts when price breaches S/R or OB zones, with historical labels providing context.
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Example Use Cases
• Swing Trading: Use S/R and OB zones to identify entry/exit points, with historical broken levels for context.
• Breakout Trading: Trade price breaks through S/R or OB, using "Br S" and "Br R" labels to confirm reversals.
• Scalping: Adjust detection period for faster S/R and OB identification on lower timeframes.
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• Performance: Optimized for all timeframes, with best results on 5M, 15M, 30M, 1H, 4H, or daily charts for swing trading.
• Compatibility: Works with any asset class and TradingView chart.
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Get Started
Transform your trading with Support & Resistance with Order Blocks! Add it to your chart, customize it to your style, and trade with confidence. For questions or feedback, drop a comment on TradingView or message the author. Happy trading! 🚀
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Disclaimer: This indicator is for educational and informational purposes only. Always conduct your own analysis and practice proper risk management before trading.
Ticker Pulse Meter BasicPairs nicely with the Contrarian 100 MA located here:
and the Enhanced Stock Ticker with 50MA vs 200MA located here:
Description
The Ticker Pulse Meter Basic is a dynamic Pine Script v6 indicator designed to provide traders with a visual representation of a stock’s price position relative to its short-term and long-term ranges, enabling clear entry and exit signals for long-only trading strategies. By calculating three normalized metrics—Percent Above Long & Above Short, Percent Above Long & Below Short, and Percent Below Long & Below Short—this indicator offers a unique "pulse" of market sentiment, plotted as stacked area charts in a separate pane. With customizable lookback periods, thresholds, and signal plotting options, it empowers traders to identify optimal entry points and profit-taking levels. The indicator leverages Pine Script’s force_overlay feature to plot signals on either the main price chart or the indicator pane, making it versatile for various trading styles.
Key Features
Pulse Meter Metrics:
Computes three percentages based on short-term (default: 50 bars) and long-term (default: 200 bars) lookback periods:
Percent Above Long & Above Short: Measures price strength when above both short and long ranges (green area).
Percent Above Long & Below Short: Indicates mixed momentum (orange area).
Percent Below Long & Below Short: Signals weakness when below both ranges (red area).
Flexible Signal Plotting:
Toggle between plotting entry (blue dots) and exit (white dots) signals on the main price chart (location.abovebar/belowbar) or in the indicator pane (location.top/bottom) using the Plot Signals on Main Chart option.
Entry/Exit Logic:
Long Entry: Triggered when Percent Above Long & Above Short crosses above the high threshold (default: 20%) and Percent Below Long & Below Short is below the low threshold (default: 40%).
Long Exit: Triggered when Percent Above Long & Above Short crosses above the profit-taking level (default: 95%).
Visual Enhancements:
Plots stacked area charts with semi-transparent colors (green, orange, red) for intuitive trend analysis.
Displays threshold lines for entry (high/low) and profit-taking levels.
Includes a ticker and timeframe table in the top-right corner for quick reference.
Alert Conditions: Supports alerts for long entry and exit signals, integrable with TradingView’s alert system for automated trading.
Technical Innovation: Combines normalized price metrics with Pine Script v6’s force_overlay for seamless signal integration on the price chart or indicator pane.
Technical Details
Calculation Logic:
Uses confirmed bars (barstate.isconfirmed) to calculate metrics, ensuring reliability.
Short-term percentage: (close - lowest(low, lookback_short)) / (highest(high, lookback_short) - lowest(low, lookback_short)).
Long-term percentage: (close - lowest(low, lookback_long)) / (highest(high, lookback_long) - lowest(low, lookback_long)).
Derived metrics:
pct_above_long_above_short = (pct_above_long * pct_above_short) * 100.
pct_above_long_below_short = (pct_above_long * (1 - pct_above_short)) * 100.
pct_below_long_below_short = ((1 - pct_above_long) * (1 - pct_above_short)) * 100.
Signal Plotting:
Entry signals (long_entry) use ta.crossover to detect when pct_above_long_above_short crosses above entryThresholdhigh and pct_below_long_below_short is below entryThresholdlow.
Exit signals (long_exit) use ta.crossover for pct_above_long_above_short crossing above profitTake.
Signals are plotted as tiny circles with force_overlay=true for main chart or standard plotting for the indicator pane.
Performance Considerations: Optimized for efficiency by calculating metrics only on confirmed bars and using lightweight plotting functions.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
Short Lookback Period: Adjust the short-term lookback (default: 50 bars) for sensitivity.
Long Lookback Period: Set the long-term lookback (default: 200 bars) for broader context.
Entry Thresholds: Modify high (default: 20%) and low (default: 40%) thresholds for entry conditions.
Profit Take Level: Set the exit threshold (default: 95%) for profit-taking.
Plot Signals on Main Chart: Check to display signals on the price chart; uncheck for the indicator pane.
Interpret Signals:
Long Entry: Blue dots indicate a strong bullish setup when price is high relative to both lookback ranges and weakness is low.
Long Exit: White dots signal profit-taking when strength reaches overbought levels.
Use the stacked area charts to assess trend strength and momentum.
Set Alerts:
Create alerts for Long Entry and Long Exit conditions using TradingView’s alert system.
Customize Visuals:
Adjust colors and thresholds via TradingView’s settings for better visibility.
The ticker table displays the symbol and timeframe in the top-right corner.
Example Use Cases
Swing Trading: Use entry signals to capture short-term bullish moves within a broader uptrend, exiting at profit-taking levels.
Trend Confirmation: Monitor the green area (Percent Above Long & Above Short) for sustained bullish momentum.
Market Sentiment Analysis: Use the stacked areas to gauge bullish vs. bearish sentiment across timeframes.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate its effectiveness.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 20, 2025.
Limitations: Signals are long-only; adapt the script for short strategies if needed.
Enhancements: Consider adding a histogram for the difference between metrics or additional thresholds for nuanced trading.
Acknowledgments
Inspired by public Pine Script examples and designed to simplify complex market dynamics into a clear, actionable tool. For licensing or support, contact Chuck Schultz (@chuckaschultz) on TradingView. Share feedback in the comments, and happy trading!
Contrarian 100 MAPairs nicely with Enhanced-Stock-Ticker-with-50MA-vs-200MA located here:
Description
The Contrarian 100 MA is a sophisticated Pine Script v6 indicator designed for traders seeking to identify key market structure shifts and trend reversals using a combination of a 100-period Simple Moving Average (SMA) envelope and Inner Circle Trader (ICT) Break of Structure (BoS) and Market Structure Shift (MSS) logic. By overlaying a semi-transparent SMA-based shadow on the price chart and plotting bullish and bearish structure signals, this indicator helps traders visualize critical price levels and potential trend changes. It leverages higher timeframe (HTF) pivot points and dynamic logic to adapt to various chart timeframes, making it ideal for swing and contrarian trading strategies. Customizable colors, timeframes, and alert conditions enhance its versatility for manual and automated trading setups.
Key Features
SMA Envelope: Plots a 100-period SMA for high and low prices, creating a semi-transparent (50% opacity) purple shadow to highlight the price range and provide context for price movements.
ICT BoS/MSS Logic: Identifies Break of Structure (BoS) and Market Structure Shift (MSS) signals for both bullish and bearish conditions, based on HTF pivot points.
Dynamic Timeframe Support: Adjusts pivot detection based on user-selected HTF (default: 1D) and chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D), ensuring adaptability across markets.
Visual Signals: Draws dotted lines for BoS (bullish/bearish) and MSS (bullish/bearish) signals at pivot levels, with customizable colors for easy identification.
Contrarian Approach: Signals potential reversals by combining SMA context with ICT structure breaks, ideal for traders looking to capitalize on trend shifts.
Alert Conditions: Supports alerts for bullish/bearish BoS and MSS signals, enabling integration with TradingView’s alert system for automated trading.
Performance Optimization: Uses efficient pivot detection and line management to minimize resource usage while maintaining accuracy.
Technical Details
SMA Calculation:
Computes 100-period SMAs for high (smaHigh) and low (smaLow) prices.
Plots invisible SMAs (fully transparent) and fills the area between them with 50% transparent purple for visual context.
Pivot Detection:
Uses ta.pivothigh and ta.pivotlow to identify HTF swing points, with dynamic lookback periods (rlBars: 5 for daily, 2 for intraday).
Tracks pivot highs (pH, nPh) and lows (pL, nPl) using a custom piv type for price and time.
BoS/MSS Logic:
Bullish BoS: Triggered when price breaks above a pivot high in a bullish trend, drawing a line at the pivot level.
Bearish BoS: Triggered when price breaks below a pivot low in a bearish trend.
Bullish MSS: Occurs when price breaks a pivot high in a bearish trend, signaling a potential trend reversal.
Bearish MSS: Occurs when price breaks a pivot low in a bullish trend.
Lines are drawn using line.new with xloc.bar_time for precise alignment, styled as dotted with customizable colors.
HTF Integration: Fetches HTF close prices and pivot data using request.security with lookahead_on for accurate signal timing.
Line Management: Maintains an array of lines (lin), removing outdated lines when new MSS signals occur to keep the chart clean.
Pivot Reset: Clears broken pivots (e.g., when price exceeds a pivot high or falls below a pivot low) to ensure fresh signal generation.
How to Use
Add to Chart:
Copy the script into TradingView’s Pine Editor and apply it to your chart.
Configure Settings:
SMA Length: Adjust the SMA period (default: 100 bars) to suit your trading style.
Structure Timeframe: Set the HTF for pivot detection (default: 1D).
Chart Timeframe: Select the chart timeframe (1M, 5M, 15M, 30M, 1H, 4H, 1D) to adjust pivot sensitivity.
Colors: Customize bullish/bearish BoS and MSS line colors via input settings.
Interpret Signals:
Bullish BoS: White dotted line (default) at a broken pivot high in a bullish trend, indicating trend continuation.
Bearish BoS: White dotted line at a broken pivot low in a bearish trend.
Bullish MSS: White dotted line at a broken pivot high in a bearish trend, suggesting a reversal to bullish.
Bearish MSS: White dotted line at a broken pivot low in a bullish trend, suggesting a reversal to bearish.
Use the SMA shadow to gauge price position within the recent range.
Set Alerts:
Create alerts for bullish/bearish BoS and MSS signals using TradingView’s alert system.
Customize Visuals:
Adjust line colors or SMA fill transparency via TradingView’s settings for better visibility.
Example Use Cases
Swing Trading: Use MSS signals to enter trades at potential trend reversals, with the SMA envelope confirming price extremes.
Contrarian Trading: Capitalize on BoS and MSS signals to trade against prevailing trends, using the SMA shadow for context.
Automated Trading: Integrate BoS/MSS alerts with trading bots for systematic entries and exits.
Multi-Timeframe Analysis: Combine HTF signals (e.g., 1D) with lower timeframe charts (e.g., 1H) for precise entries.
Notes
Testing: Backtest the indicator on your chosen market and timeframe to validate performance.
Compatibility: Built for Pine Script v6 and tested on TradingView as of June 19, 2025.
Limitations: Signals rely on HTF pivot accuracy, which may lag in fast-moving markets. Adjust rlBars or timeframe for sensitivity.
Optional Enhancements: Consider uncommenting or adding a histogram for SMA divergence (e.g., smaHigh - smaLow) for additional insights.
Acknowledgments
This indicator combines ICT’s market structure concepts with a dynamic SMA envelope to provide a unique contrarian trading tool. Share your feedback or suggestions in the TradingView comments, and happy trading!
Trailing Stop Loss [TradingFinder] 4 Machine Learning Methods🔵 Introduction
The trailing stop indicator dynamically adjusts stop-loss (SL) levels to lock in profits as price moves favorably. It uses pivot levels and ATR to set optimal SL points, balancing risk and reward.
Trade confirmation filters, a key feature, ensure entries align with market conditions, reducing false signals. In 2023 a study showed filtered entries improve win rates by 15% in forex. This enhances trade precision.
SL settings, ranging from very tight to very wide, adapt to volatility via ATR calculations. These settings anchor SL to previous pivot levels, ensuring alignment with market structure. This caters to diverse trading styles, from scalping to swing trading.
The indicator colors the profit zone between the entry point (EP) and SL, using light green for buy trades and light red for sell trades. This visual cue highlights profit potential. It’s ideal for traders seeking dynamic risk management.
A table displays real-time trade details, including EP, SL, and profit/loss (PNL). Backtests show trailing stops cut losses by 20% in trending markets. This transparency aids decision-making.
🔵 How to Use
🟣 SL Levels
The trailing stop indicator sets SL based on pivot levels and ATR, offering four options: very tight, tight, wide, or very wide. Very tight SLs suit scalpers, while wide SLs fit swing traders. Select the base level to match your strategy.
If price hits the SL, the trade closes, and the indicator evaluates the next trade using the selected filter. This ensures disciplined trade management. The cycle restarts with a new confirmed entry.
Very tight SLs, set near recent pivots, trigger exits early to minimize risk but limit profits in volatile markets. Wide SLs, shown as farther lines, allow more price movement but increase exposure to losses. Adjust based on ATR and conditions, noting SL breaches open new positions.
🟣 Visualization
The indicator’s visual cues, like colored profit zones, simplify monitoring, with light green showing the profit area from EP to trailed SL. Dashed lines mark entry points, while solid lines track the trailed SL, triggering new positions when breached.
When price moves into profit, the area between EP and SL is colored—light green for longs, light red for shorts. This highlights the profit zone visually. The SL trails price, locking in gains as the trade progresses.
🟣 Filters
Upon trade entry, the indicator requires confirmation via filters like SMA 2x or ADX to validate momentum. Filters reduce false entries, though no guarantee exists for improved outcomes. Monitor price action post-entry for trade validity.
Filters like Momentum or ADX assess trend strength before entry. For example, ADX above 25 confirms strong trends. Choose “none” for unfiltered entries.
🟣 Bullish Alert
For a bullish trade, the indicator opens a long position with a green SL Line (after optional filters), trailing the SL below price. Set alerts to On in the settings for notifications, or Off to monitor manually.
🟣 Bearish Alert
In a bearish trade, the indicator opens a short position with a red SL Line post-confirmation, trailing the SL above price. With alerts On in the settings, it notifies the potential reversal.
🟣 Panel
A table displays all trades’ details, including Win Rates, PNL, and trade status. This real-time data aids in tracking performance. Check the table to assess trade outcomes instantly.
Review the table regularly to evaluate trade performance and adjust settings. Consistent monitoring ensures alignment with market dynamics. This maximizes the indicator’s effectiveness.
🔵 Settings
Length (Default: 10) : Sets the pivot period for calculating SL levels, balancing sensitivity and reliability.
Base Level : Options (“Very tight,” “Tight,” “Wide,” “Very wide”) adjust SL distance via ATR.
Show EP Checkbox : Toggles visibility of the entry point on the chart.
Show PNL : Displays profit/loss data for active and closed trades.
Filter : Options (“none,” “SMA 2x,” “Momentum,” “ADX”) validate trade entries.
🔵 Conclusion
The trailing stop indicator, a dynamic risk management tool, adjusts SLs using pivot levels and ATR. Its confirmation filters reduce false entries, boosting precision. Backtests show 20% loss reduction in trending markets.
Customizable SL settings and visual profit zones enhance usability across trading styles. The real-time table provides clear trade insights, streamlining analysis. It’s ideal for forex, stocks, or crypto.
While filters like ADX improve entry accuracy, no setup guarantees success in all conditions. Contextual analysis, like trend strength, is key. This indicator empowers disciplined, data-driven trading.
[blackcat] L3 Adaptive Trend SeekerOVERVIEW
The indicator is designed to help traders identify dynamic trends in various markets efficiently. It employs advanced calculations including Dynamic Moving Averages (DMAs) and multiple moving averages to filter out noise and provide clear buy/sell signals 📈✨. By utilizing innovative algorithms that adapt to changing market conditions, this tool enables users to make informed decisions across different timeframes and asset classes.
This versatile indicator serves both novice and experienced traders seeking reliable ways to navigate volatile environments. Its primary objective is to simplify complex trend analysis into actionable insights, making it an indispensable addition to any trader’s arsenal ⚙️🎯.
FEATURES
Customizable Dynamic Moving Average: Calculates an adaptive moving average tailored to specific needs using customizable coefficients.
Trend Identification: Utilizes multi-period moving averages (e.g., short-term, medium-term, long-term) to discern prevailing trends accurately.
Crossover Alerts: Provides visual cues via labels when significant crossover events occur between key indicators.
Adjusted MA Plots: Displays steplines colored according to the current trend direction (green for bullish, red for bearish).
Historical Price Analysis: Analyzes historical highs and lows over specified periods, ensuring robust trend identification.
Conditional Signals: Generates bullish/bearish conditions based on predefined rules enhancing decision-making efficiency.
HOW TO USE
Script Installation:
Copy the provided code and add it under Indicators > Add Custom Indicator within TradingView.
Choose an appropriate name and enable it on your desired charts.
Parameter Configuration:
Adjust the is_trend_seeker_active flag to activate/deactivate the core functionality as needed.
Modify other parameters such as smoothing factors if more customized behavior is required.
Interpreting Trends:
Observe the steppled lines representing the long-term/trend-adjusted moving averages:
Green indicates a bullish trend where prices are above the dynamically calculated threshold.
Red signifies a bearish environment with prices below respective levels.
Pay attention to labels marked "B" (for Bullish Crossover) and "S" (for Bearish Crossover).
Signal Integration:
Incorporate these generated signals within broader strategies involving support/resistance zones, volume data, and complementary indicators for stronger validity.
Use crossover alerts responsibly by validating them against recent market movements before execution.
Setting Up Alerts:
Configure alert notifications through TradingView’s interface corresponding to crucial crossover events ensuring timely responses.
Backtesting & Optimization:
Conduct extensive backtests applying diverse datasets spanning varied assets/types verifying robustness amidst differing conditions.
Refine parameters iteratively improving overall effectiveness and minimizing false positives/negatives.
EXAMPLE SCENARIOS
Swing Trading: Employ the stepline crossovers coupled with momentum oscillators like RSI to capitalize on intermediate trend reversals.
Day Trading: Leverage rapid adjustments offered by short-medium term MAs aligning entries/exits alongside intraday volatility metrics.
LIMITATIONS
The performance hinges upon accurate inputs; hence regular recalibration aligning shifting dynamics proves essential.
Excessive reliance solely on this indicator might lead to missed opportunities especially during sideways/choppy phases necessitating additional filters.
Always consider combining outputs with fundamental analyses ensuring holistic perspectives while managing risks effectively.
NOTES
Educational Resources: Delve deeper into principles behind dynamic moving averages and their significance in technical analysis bolstering comprehension.
Risk Management: Maintain stringent risk management protocols integrating stop-loss/profit targets safeguarding capital preservation.
Continuous Learning: Stay updated exploring evolving financial landscapes incorporating new methodologies enhancing script utility and relevance.
THANKS
Thanks to all contributors who have played vital roles refining and optimizing this script. Your valuable feedback drives continual enhancements paving way towards superior trading experiences!
Happy charting, and here's wishing you successful ventures ahead! 🌐💰!
Green*DiamondGreen*Diamond (GD1)
Unleash Dynamic Trading Signals with Volatility and Momentum
Overview
GreenDiamond is a versatile overlay indicator designed for traders seeking actionable buy and sell signals across various markets and timeframes. Combining Volatility Bands (VB) bands, Consolidation Detection, MACD, RSI, and a unique Ribbon Wave, it highlights high-probability setups while filtering out noise. With customizable signals like Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, plus vibrant candle and volume visuals, GreenDiamond adapts to your trading style—whether you’re scalping, day trading, or swing trading.
Key Features
Volatility Bands (VB): Plots dynamic upper and lower bands to identify breakouts or reversals, with toggleable buy/sell signals outside consolidation zones.
Consolidation Detection: Marks low-range periods to avoid choppy markets, ensuring signals fire during trending conditions.
MACD Signals: Offers flexible buy/sell conditions (e.g., cross above signal, above zero, histogram up) with RSI divergence integration for precision.
RSI Filter: Enhances signals with customizable levels (midline, oversold/overbought) and bullish divergence detection.
Ribbon Wave: Visualizes trend strength using three EMAs, colored by MACD and RSI for intuitive momentum cues.
Custom Signals: Includes Green-Yellow Buy, Pullback Sell, and Inverse Pullback Buy, with limits on consecutive signals to prevent overtrading.
Candle & Volume Styling: Blends MACD/RSI colors on candles and scales volume bars to highlight momentum spikes.
Alerts: Set up alerts for VB signals, MACD crosses, Green*Diamond signals, and custom conditions to stay on top of opportunities.
How It Works
Green*Diamond integrates multiple indicators to generate signals:
Volatility Bands: Calculates bands using a pivot SMA and standard deviation. Buy signals trigger on crossovers above the lower band, sell signals on crossunders below the upper band (if enabled).
Consolidation Filter: Suppresses signals when candle ranges are below a threshold, keeping you out of flat markets.
MACD & RSI: Combines MACD conditions (e.g., cross above signal) with RSI filters (e.g., above midline) and optional volume spikes for robust signals.
Custom Logic: Green-Yellow Buy uses MACD bullishness, Pullback Sell targets retracements, and Inverse Pullback Buy catches reversals after downmoves—all filtered to avoid consolidation.
Visuals: Ribbon Wave shows trend direction, candles blend momentum colors, and volume bars scale dynamically to confirm signals.
Settings
Volatility Bands Settings:
VB Lookback Period (20): Adjust to 10–15 for faster markets (e.g., 1-minute scalping) or 25–30 for daily charts.
Upper/Lower Band Multiplier (1.0): Increase to 1.5–2.0 for wider bands in volatile stocks like AEHL; decrease to 0.5 for calmer markets.
Show Volatility Bands: Toggle off to reduce chart clutter.
Use VB Signals: Enable for breakout-focused trades; disable to focus on Green*Diamond signals.
Consolidation Settings:
Consolidation Lookback (14): Set to 5–10 for small caps (e.g., AEHL) to catch quick consolidations; 20 for higher timeframes.
Range Threshold (0.5): Lower to 0.3 for stricter filtering in choppy markets; raise to 0.7 for looser signals.
MACD Settings:
Fast/Slow Length (12/26): Shorten to 8/21 for scalping; extend to 15/34 for swing trading.
Signal Smoothing (9): Reduce to 5 for faster signals; increase to 12 for smoother trends.
Buy/Sell Signal Options: Choose “Cross Above Signal” for classic MACD; “Histogram Up” for momentum plays.
Use RSI Div + MACD Cross: Enable for high-probability reversal signals.
RSI Settings:
RSI Period (14): Drop to 10 for 1-minute charts; raise to 20 for daily.
Filter Level (50): Set to 55 for stricter buys; 45 for sells.
Overbought/Oversold (70/30): Tighten to 65/35 for small caps; widen to 75/25 for indices.
RSI Buy/Sell Options: Select “Bullish Divergence” for reversals; “Cross Above Oversold” for momentum.
Color Settings:
Adjust bullish/bearish colors for visibility (e.g., brighter green/red for dark themes).
Border Thickness (1): Increase to 2–3 for clearer candle outlines.
Volume Settings:
Volume Average Length (20): Shorten to 10 for scalping; extend to 30 for swing trades.
Volume Multiplier (2.0): Raise to 3.0 for AEHL’s volume surges; lower to 1.5 for steady stocks.
Bar Height (10%): Increase to 15% for prominent bars; decrease to 5% to reduce clutter.
Ribbon Settings:
EMA Periods (10/20/30): Tighten to 5/10/15 for scalping; widen to 20/40/60 for trends.
Color by MACD/RSI: Disable for simpler visuals; enable for dynamic momentum cues.
Gradient Fill: Toggle on for trend clarity; off for minimalism.
Custom Signals:
Enable Green-Yellow Buy: Use for momentum confirmation; limit to 1–2 signals to avoid spam.
Pullback/Inverse Pullback % (50): Set to 30–40% for small caps; 60–70% for indices.
Max Buy Signals (1): Increase to 2–3 for active markets; keep at 1 for discipline.
Tips and Tricks
Scalping Small Caps (e.g., AEHL):
Use 1-minute charts with VB Lookback = 10, Consolidation Lookback = 5, and Volume Multiplier = 3.0 to catch $0.10–$0.20 moves.
Enable Green-Yellow Buy and Inverse Pullback Buy for quick entries; disable VB Signals to focus on Green*Diamond logic.
Pair with SMC+ green boxes (if you use them) for reversal confirmation.
Day Trading:
Try 5-minute charts with MACD Fast/Slow = 8/21 and RSI Period = 10.
Enable RSI Divergence + MACD Cross for high-probability setups; set Max Buy Signals = 2.
Watch for volume bars turning yellow to confirm entries.
Swing Trading:
Use daily charts with VB Lookback = 30, Ribbon EMAs = 20/40/60.
Enable Pullback Sell (60%) to exit after rallies; disable RSI Color for cleaner candles.
Check Ribbon Wave gradient for trend strength—bright green signals strong bulls.
Avoiding Noise:
Increase Consolidation Threshold to 0.7 on volatile days to skip false breakouts.
Disable Ribbon Wave or Volume Bars if the chart feels crowded.
Limit Max Buy Signals to 1 for disciplined trading.
Alert Setup:
In TradingView’s Alerts panel, select:
“GD Buy Signal” for standard entries.
“RSI Div + MACD Cross Buy” for reversals.
“VB Buy Signal” for breakout plays.
Set to “Once Per Bar Close” for confirmed signals; “Once Per Bar” for scalping.
Backtesting:
Replay on small caps ( Float < 5M, Price $0.50–$5) to test signals.
Focus on “GD Buy Signal” with yellow volume bars and green Ribbon Wave.
Avoid signals during gray consolidation squares unless paired with RSI Divergence.
Usage Notes
Markets: Works on stocks, forex, crypto, and indices. Best for volatile assets (e.g., small-cap stocks, BTCUSD).
Timeframes: Scalping (1–5 minutes), day trading (15–60 minutes), or swing trading (daily). Adjust settings per timeframe.
Risk Management: Combine with stop-losses (e.g., 1% risk, $0.05 below AEHL entry) and take-profits (3–5%).
Customization: Tweak inputs to match your strategy—experiment in replay to find your sweet spot.
Disclaimer
Green*Diamond is a technical tool to assist with trade identification, not a guarantee of profits. Trading involves risks, and past performance doesn’t predict future results. Always conduct your own analysis, manage risk, and test settings before live trading.
Feedback
Love Green*Diamond? Found a killer setup?
Trend Detection
#### *Description:*
This *Trend Detection* indicator is designed to help traders identify and confirm trends in the market using a combination of moving averages, volume analysis, and MACD filters. It provides clear visual signals for uptrends and downtrends, along with customizable settings to adapt to different trading styles and timeframes. The indicator is suitable for both beginners and advanced traders who want to improve their trend-following strategies.
---
#### *Key Features:*
1. *Trend Detection:*
- Uses *Moving Averages (MA)* to determine the overall trend direction.
- Supports multiple MA types: *SMA (Simple), **EMA (Exponential), **WMA (Weighted), and **HMA (Hull)*.
2. *Advanced Filters:*
- *MACD Filter:* Confirms trends using MACD crossovers.
- *Volume Filter:* Ensures trends are supported by above-average volume.
- *Multi-Timeframe Filter:* Validates trends using a higher timeframe (e.g., Daily or Weekly).
3. *Visual Signals:*
- Plots a *trend line* on the chart to indicate the current trend direction.
- Fills the background with *green* for uptrends and *red* for downtrends.
4. *Customizable Settings:*
- Adjust the *MA lengths, **MACD parameters, and **confirmation thresholds* to suit your trading strategy.
- Control the transparency of the background fill for better chart readability.
5. *Alerts:*
- Generates *buy/sell signals* when a trend is confirmed.
- Alerts can be set to trigger at the close of a candle for precise entry/exit points.
---
#### *How to Use:*
1. *Adding the Indicator:*
- Copy and paste the Pine Script code into the TradingView Pine Script editor.
- Add the indicator to your chart.
2. *Configuring the Settings:*
- *Trend Settings:*
- Choose the *MA type* (e.g., EMA for faster response, HMA for smoother trends).
- Set the *Trend MA Period* (e.g., 200 for long-term trends) and *Filter MA Period* (e.g., 100 for medium-term trends).
- *Advanced Filters:*
- Enable/disable the *MACD Filter* and adjust its parameters (Fast, Slow, Signal).
- Enable/disable the *Volume Filter* to ensure trends are supported by volume.
- *Multi-Timeframe Filter:*
- Enable this filter to validate trends using a higher timeframe (e.g., Daily or Weekly).
3. *Interpreting the Signals:*
- *Uptrend:* The trend line turns *green*, and the background is filled with a transparent green color.
- *Downtrend:* The trend line turns *red*, and the background is filled with a transparent red color.
- *Alerts:* Buy/sell signals are generated when the trend is confirmed.
4. *Using Alerts:*
- Set up alerts for *Buy Signal* (bullish reversal) and *Sell Signal* (bearish reversal).
- Alerts can be configured to trigger at the close of a candle for precise execution.
---
#### *Settings and Their Effects:*
1. *MA Type:*
- *SMA:* Smooth but lagging. Best for long-term trends.
- *EMA:* Faster response to price changes. Suitable for medium-term trends.
- *WMA:* Gives more weight to recent prices. Useful for short-term trends.
- *HMA:* Combines speed and smoothness. Ideal for all timeframes.
2. *Trend MA Period:*
- A longer period (e.g., 200) identifies long-term trends but may lag.
- A shorter period (e.g., 50) reacts faster but may produce false signals.
3. *Filter MA Period:*
- Acts as a secondary filter to confirm the trend.
- A shorter period (e.g., 50) provides tighter confirmation but may increase noise.
4. *MACD Filter:*
- Ensures trends are confirmed by MACD crossovers.
- Adjust the *Fast, **Slow, and **Signal* lengths to match your trading style.
5. *Volume Filter:*
- Ensures trends are supported by above-average volume.
- Reduces false signals during low-volume periods.
6. *Multi-Timeframe Filter:*
- Validates trends using a higher timeframe (e.g., Daily or Weekly).
- Increases reliability but may delay signals.
7. *Confirmation Value:*
- Sets the minimum percentage deviation from the trend MA required to confirm a trend.
- A higher value (e.g., 2.0%) reduces false signals but may delay trend detection.
8. *Confirmation Bars:*
- Sets the number of bars required to confirm a trend.
- A higher value (e.g., 5 bars) ensures sustained trends but may delay signals.
---
#### *Who Should Use This Indicator?*
1. *Trend Followers:*
- Traders who focus on identifying and riding long-term trends.
- Suitable for *swing traders* and *position traders*.
2. *Day Traders:*
- Can use shorter MA periods and faster filters (e.g., EMA, HMA) for intraday trends.
3. *Volume-Based Traders:*
- Traders who rely on volume confirmation to validate trends.
4. *Multi-Timeframe Traders:*
- Traders who use higher timeframes to confirm trends on lower timeframes.
5. *Beginners:*
- Easy-to-understand visual signals and alerts make it beginner-friendly.
6. *Advanced Traders:*
- Customizable settings allow for fine-tuning to match specific strategies.
---
#### *Example Use Cases:*
1. *Long-Term Investing:*
- Use a *200-period SMA* with a *Daily* higher timeframe filter to identify long-term trends.
- Enable the *Volume Filter* to ensure trends are supported by strong volume.
2. *Swing Trading:*
- Use a *50-period EMA* with a *4-hour* higher timeframe filter for medium-term trends.
- Enable the *MACD Filter* to confirm trend reversals.
3. *Day Trading:*
- Use a *20-period HMA* with a *1-hour* higher timeframe filter for short-term trends.
- Disable the *Volume Filter* for faster signals.
---
#### *Conclusion:*
The *Trend Detection* indicator is a versatile tool for traders of all levels. Its customizable settings and advanced filters make it suitable for various trading styles and timeframes. By combining moving averages, volume analysis, and MACD filters, it provides reliable trend signals with minimal lag. Whether you're a beginner or an advanced trader, this indicator can help you make better trading decisions by identifying and confirming trends in the market.
---
#### *Publishing on TradingView:*
- *Title:* Trend Detection with Advanced Filters
- *Description:* A powerful trend detection tool using moving averages, volume analysis, and MACD filters. Suitable for all trading styles and timeframes.
- *Tags:* Trend, Moving Averages, MACD, Volume, Multi-Timeframe
- *Category:* Trend-Following
- *Access:* Public or Private (depending on your preference).
---
Let me know if you need further assistance or additional features!
Multi-Timeframe Stochastic Alert [tradeviZion]# Multi-Timeframe Stochastic Alert : Complete User Guide
## 1. Introduction
### What is the Multi-Timeframe Stochastic Alert?
The Multi-Timeframe Stochastic Alert is an advanced technical analysis tool that helps traders identify potential trading opportunities by analyzing momentum across multiple timeframes. It combines the power of the stochastic oscillator with multi-timeframe analysis to provide more reliable trading signals.
### Key Features and Benefits
- Simultaneous analysis of 6 different timeframes
- Advanced alert system with customizable conditions
- Real-time visual feedback with color-coded signals
- Comprehensive data table with instant market insights
- Motivational trading messages for psychological support
- Flexible theme support for comfortable viewing
### How it Can Help Your Trading
- Identify stronger trends by confirming momentum across multiple timeframes
- Reduce false signals through multi-timeframe confirmation
- Stay informed of market changes with customizable alerts
- Make more informed decisions with comprehensive market data
- Maintain trading discipline with clear visual signals
## 2. Understanding the Display
### The Stochastic Chart
The main chart displays three key components:
1. ** K-Line (Fast) **: The primary stochastic line (default color: green)
2. ** D-Line (Slow) **: The signal line (default color: red)
3. ** Reference Lines **:
- Overbought Level (80): Upper dashed line
- Middle Line (50): Center dashed line
- Oversold Level (20): Lower dashed line
### The Information Table
The table provides a comprehensive view of stochastic readings across all timeframes. Here's what each column means:
#### Column Explanations:
1. ** Timeframe **
- Shows the time period for each row
- Example: "5" = 5 minutes, "15" = 15 minutes, etc.
2. ** K Value **
- The fast stochastic line value (0-100)
- Higher values indicate stronger upward momentum
- Lower values indicate stronger downward momentum
3. ** D Value **
- The slow stochastic line value (0-100)
- Helps confirm momentum direction
- Crossovers with K-line can signal potential trades
4. ** Status **
- Shows current momentum with symbols:
- ▲ = Increasing (bullish)
- ▼ = Decreasing (bearish)
- Color matches the trend direction
5. ** Trend **
- Shows the current market condition:
- "Overbought" (above 80)
- "Bullish" (above 50)
- "Bearish" (below 50)
- "Oversold" (below 20)
#### Row Explanations:
1. ** Title Row **
- Shows "🎯 Multi-Timeframe Stochastic"
- Indicates the indicator is active
2. ** Header Row **
- Contains column titles
- Dark blue background for easy reading
3. ** Timeframe Rows **
- Six rows showing different timeframe analyses
- Each row updates independently
- Color-coded for easy trend identification
4. **Message Row**
- Shows rotating motivational messages
- Updates every 5 bars
- Helps maintain trading discipline
### Visual Indicators and Colors
- ** Green Background **: Indicates bullish conditions
- ** Red Background **: Indicates bearish conditions
- ** Color Intensity **: Shows strength of the signal
- ** Background Highlights **: Appear when alert conditions are met
## 3. Core Settings Groups
### Stochastic Settings
These settings control the core calculation of the stochastic oscillator.
1. ** Length (Default: 14) **
- What it does: Determines the lookback period for calculations
- Higher values (e.g., 21): More stable, fewer signals
- Lower values (e.g., 8): More sensitive, more signals
- Recommended:
* Day Trading: 8-14
* Swing Trading: 14-21
* Position Trading: 21-30
2. ** Smooth K (Default: 3) **
- What it does: Smooths the main stochastic line
- Higher values: Smoother line, fewer false signals
- Lower values: More responsive, but more noise
- Recommended:
* Day Trading: 2-3
* Swing Trading: 3-5
* Position Trading: 5-7
3. ** Smooth D (Default: 3) **
- What it does: Smooths the signal line
- Works in conjunction with Smooth K
- Usually kept equal to or slightly higher than Smooth K
- Recommended: Keep same as Smooth K for consistency
4. ** Source (Default: Close) **
- What it does: Determines price data for calculations
- Options: Close, Open, High, Low, HL2, HLC3, OHLC4
- Recommended: Stick with Close for most reliable signals
### Timeframe Settings
Controls the multiple timeframes analyzed by the indicator.
1. ** Main Timeframes (TF1-TF6) **
- TF1 (Default: 10): Shortest timeframe for quick signals
- TF2 (Default: 15): Short-term trend confirmation
- TF3 (Default: 30): Medium-term trend analysis
- TF4 (Default: 30): Additional medium-term confirmation
- TF5 (Default: 60): Longer-term trend analysis
- TF6 (Default: 240): Major trend confirmation
Recommended Combinations:
* Scalping: 1, 3, 5, 15, 30, 60
* Day Trading: 5, 15, 30, 60, 240, D
* Swing Trading: 15, 60, 240, D, W, M
2. ** Wait for Bar Close (Default: true) **
- What it does: Controls when calculations update
- True: More reliable but slightly delayed signals
- False: Faster signals but may change before bar closes
- Recommended: Keep True for more reliable signals
### Alert Settings
#### Main Alert Settings
1. ** Enable Alerts (Default: true) **
- Master switch for all alert notifications
- Toggle this off when you don't want any alerts
- Useful during testing or when you want to focus on visual signals only
2. ** Alert Condition (Options) **
- "Above Middle": Bullish momentum alerts only
- "Below Middle": Bearish momentum alerts only
- "Both": Alerts for both directions
- Recommended:
* Trending Markets: Choose direction matching the trend
* Ranging Markets: Use "Both" to catch reversals
* New Traders: Start with "Both" until you develop a specific strategy
3. ** Alert Frequency **
- "Once Per Bar": Immediate alerts during the bar
- "Once Per Bar Close": Alerts only after bar closes
- Recommended:
* Day Trading: "Once Per Bar" for quick reactions
* Swing Trading: "Once Per Bar Close" for confirmed signals
* Beginners: "Once Per Bar Close" to reduce false signals
#### Timeframe Check Settings
1. ** First Check (TF1) **
- Purpose: Confirms basic trend direction
- Alert Triggers When:
* For Bullish: Stochastic is above middle line (50)
* For Bearish: Stochastic is below middle line (50)
* For Both: Triggers in either direction based on position relative to middle line
- Settings:
* Enable/Disable: Turn first check on/off
* Timeframe: Default 5 minutes
- Best Used For:
* Quick trend confirmation
* Entry timing
* Scalping setups
2. ** Second Check (TF2) **
- Purpose: Confirms both position and momentum
- Alert Triggers When:
* For Bullish: Stochastic is above middle line AND both K&D lines are increasing
* For Bearish: Stochastic is below middle line AND both K&D lines are decreasing
* For Both: Triggers based on position and direction matching current condition
- Settings:
* Enable/Disable: Turn second check on/off
* Timeframe: Default 15 minutes
- Best Used For:
* Trend strength confirmation
* Avoiding false breakouts
* Day trading setups
3. ** Third Check (TF3) **
- Purpose: Confirms overall momentum direction
- Alert Triggers When:
* For Bullish: Both K&D lines are increasing (momentum confirmation)
* For Bearish: Both K&D lines are decreasing (momentum confirmation)
* For Both: Triggers based on matching momentum direction
- Settings:
* Enable/Disable: Turn third check on/off
* Timeframe: Default 30 minutes
- Best Used For:
* Major trend confirmation
* Swing trading setups
* Avoiding trades against the main trend
Note: All three conditions must be met simultaneously for the alert to trigger. This multi-timeframe confirmation helps reduce false signals and provides stronger trade setups.
#### Alert Combinations Examples
1. ** Conservative Setup **
- Enable all three checks
- Use "Once Per Bar Close"
- Timeframe Selection Example:
* First Check: 15 minutes
* Second Check: 1 hour (60 minutes)
* Third Check: 4 hours (240 minutes)
- Wider gaps between timeframes reduce noise and false signals
- Best for: Swing trading, beginners
2. ** Aggressive Setup **
- Enable first two checks only
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
- Closer timeframes for quicker signals
- Best for: Day trading, experienced traders
3. ** Balanced Setup **
- Enable all checks
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
* Third Check: 1 hour (60 minutes)
- Balanced spacing between timeframes
- Best for: All-around trading
### Visual Settings
#### Alert Visual Settings
1. ** Show Background Color (Default: true) **
- What it does: Highlights chart background when alerts trigger
- Benefits:
* Makes signals more visible
* Helps spot opportunities quickly
* Provides visual confirmation of alerts
- When to disable:
* If using multiple indicators
* When preferring a cleaner chart
* During manual backtesting
2. ** Background Transparency (Default: 90) **
- Range: 0 (solid) to 100 (invisible)
- Recommended Settings:
* Clean Charts: 90-95
* Multiple Indicators: 85-90
* Single Indicator: 80-85
- Tip: Adjust based on your chart's overall visibility
3. ** Background Colors **
- Bullish Background:
* Default: Green
* Indicates upward momentum
* Customizable to match your theme
- Bearish Background:
* Default: Red
* Indicates downward momentum
* Customizable to match your theme
#### Level Settings
1. ** Oversold Level (Default: 20) **
- Traditional Setting: 20
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 10): More conservative
* Higher values (e.g., 30): More aggressive
- Trading Applications:
* Potential bullish reversal zone
* Support level in uptrends
* Entry point for long positions
2. ** Overbought Level (Default: 80) **
- Traditional Setting: 80
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 70): More aggressive
* Higher values (e.g., 90): More conservative
- Trading Applications:
* Potential bearish reversal zone
* Resistance level in downtrends
* Exit point for long positions
3. ** Middle Line (Default: 50) **
- Purpose: Trend direction separator
- Applications:
* Above 50: Bullish territory
* Below 50: Bearish territory
* Crossing 50: Potential trend change
- Trading Uses:
* Trend confirmation
* Entry/exit trigger
* Risk management level
#### Color Settings
1. ** Bullish Color (Default: Green) **
- Used for:
* K-Line (Main stochastic line)
* Status symbols when trending up
* Trend labels for bullish conditions
- Customization:
* Choose colors that stand out
* Match your trading platform theme
* Consider color blindness accessibility
2. ** Bearish Color (Default: Red) **
- Used for:
* D-Line (Signal line)
* Status symbols when trending down
* Trend labels for bearish conditions
- Customization:
* Choose contrasting colors
* Ensure visibility on your chart
* Consider monitor settings
3. ** Neutral Color (Default: Gray) **
- Used for:
* Middle line (50 level)
- Customization:
* Should be less prominent
* Easy on the eyes
* Good background contrast
### Theme Settings
1. **Color Theme Options**
- Dark Theme (Default):
* Dark background with white text
* Optimized for dark chart backgrounds
* Reduces eye strain in low light
- Light Theme:
* Light background with black text
* Better visibility in bright conditions
- Custom Theme:
* Use your own color preferences
2. ** Available Theme Colors **
- Table Background
- Table Text
- Table Headers
Note: The theme affects only the table display colors. The stochastic lines and alert backgrounds use their own color settings.
### Table Settings
#### Position and Size
1. ** Table Position **
- Options:
* Top Right (Default)
* Middle Right
* Bottom Right
* Top Left
* Middle Left
* Bottom Left
- Considerations:
* Chart space utilization
* Personal preference
* Multiple monitor setups
2. ** Text Sizes **
- Title Size Options:
* Tiny: Minimal space usage
* Small: Compact but readable
* Normal (Default): Standard visibility
* Large: Enhanced readability
* Huge: Maximum visibility
- Data Size Options:
* Recommended: One size smaller than title
* Adjust based on screen resolution
* Consider viewing distance
3. ** Empowering Messages **
- Purpose:
* Maintain trading discipline
* Provide psychological support
* Remind of best practices
- Rotation:
* Changes every 5 bars
* Categories include:
- Market Wisdom
- Strategy & Discipline
- Mindset & Growth
- Technical Mastery
- Market Philosophy
## 4. Setting Up for Different Trading Styles
### Day Trading Setup
1. **Timeframes**
- Primary: 5, 15, 30 minutes
- Secondary: 1H, 4H
- Alert Settings: "Once Per Bar"
2. ** Stochastic Settings **
- Length: 8-14
- Smooth K/D: 2-3
- Alert Condition: Match market trend
3. ** Visual Settings **
- Background: Enabled
- Transparency: 85-90
- Theme: Based on trading hours
### Swing Trading Setup
1. ** Timeframes **
- Primary: 1H, 4H, Daily
- Secondary: Weekly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 14-21
- Smooth K/D: 3-5
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Optional
- Transparency: 90-95
- Theme: Personal preference
### Position Trading Setup
1. ** Timeframes **
- Primary: Daily, Weekly
- Secondary: Monthly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 21-30
- Smooth K/D: 5-7
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Disabled
- Focus on table data
- Theme: High contrast
## 5. Troubleshooting Guide
### Common Issues and Solutions
1. ** Too Many Alerts **
- Cause: Settings too sensitive
- Solutions:
* Increase timeframe intervals
* Use "Once Per Bar Close"
* Enable fewer timeframe checks
* Adjust stochastic length higher
2. ** Missed Signals **
- Cause: Settings too conservative
- Solutions:
* Decrease timeframe intervals
* Use "Once Per Bar"
* Enable more timeframe checks
* Adjust stochastic length lower
3. ** False Signals **
- Cause: Insufficient confirmation
- Solutions:
* Enable all three timeframe checks
* Use larger timeframe gaps
* Wait for bar close
* Confirm with price action
4. ** Visual Clarity Issues **
- Cause: Poor contrast or overlap
- Solutions:
* Adjust transparency
* Change theme settings
* Reposition table
* Modify color scheme
### Best Practices
1. ** Getting Started **
- Start with default settings
- Use "Both" alert condition
- Enable all timeframe checks
- Wait for bar close
- Monitor for a few days
2. ** Fine-Tuning **
- Adjust one setting at a time
- Document changes and results
- Test in different market conditions
- Find your optimal timeframe combination
- Balance sensitivity with reliability
3. ** Risk Management **
- Don't trade against major trends
- Confirm signals with price action
- Use appropriate position sizing
- Set clear stop losses
- Follow your trading plan
4. ** Regular Maintenance **
- Review settings weekly
- Adjust for market conditions
- Update color scheme for visibility
- Clean up chart regularly
- Maintain trading journal
## 6. Tips for Success
1. ** Entry Strategies **
- Wait for all timeframes to align
- Confirm with price action
- Use proper position sizing
- Consider market conditions
2. ** Exit Strategies **
- Trail stops using indicator levels
- Take partial profits at targets
- Honor your stop losses
- Don't fight the trend
3. ** Psychology **
- Stay disciplined with settings
- Don't override system signals
- Keep emotions in check
- Learn from each trade
4. ** Continuous Improvement **
- Record your trades
- Review performance regularly
- Adjust settings gradually
- Stay educated on markets
Wick Length Display + Alert conditionsDescription of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels:
◦ To ensure clarity, a maximum number of labels is defined.
Usage
1. Customization:
◦ Open the script in the Pine Script Editor in TradingView.
◦ Use the input options to customize parameters such as color selection, label size, thresholds and other details according to your requirements.
2. Enable thresholds:
◦ Enable thresholds to show labels only for relevant wicks (default is 6).
◦ Define the minimum wick lengths for bullish (green) and bearish (red) candles.
3. Show in pips:
◦ Enable the “Show wick length in pips” option to show the results in pips (especially suitable for Forex).
4. Edit pressure labels:
◦ Turn the “Bull Pressure” and “Bear Pressure” features on or off depending on your analysis settings.
Concepts behind the calculations
• Technical market analysis: Wick lengths can indicate buying or selling pressure and provide important information on market psychology.
• Thresholds and filtering: The script uses thresholds to avoid visual overload and highlight only essential data.
• Label display: Dynamic labels improve chart readability and give the user instant feedback on market developments.
Usage
This script is great for:
• Intraday trading: Analyzing short-term movements using wick lengths.
• Forex trading: Tracking market momentum using the pip indicator.
• Swing trading: Identifying buying or selling pressure in key markets.
• Visual support: Ideal for traders who prefer a graphical display.
Description of the Wick Length Display (Advanced) script
Originality and purpose of the script
The Wick Length Display (Advanced) script is an innovative tool for traders who want to gain detailed insights into the length of candle wicks. It stands out for its versatility and user-friendly customization options. It combines precise technical calculations with visual representation to provide important information about market movements and dynamics right on the chart.
Functionality
The script calculates and displays the length of the upper and lower wicks of each candle on the chart. It also provides additional visual cues such as:
• “Bull pressure”: When green candles do not have upper wicks, this indicates strong buying pressure.
• “Bear pressure”: When red candles do not have lower wicks, this indicates strong selling pressure.
• Threshold conditions: Only displays wicks that exceed a certain threshold (optional).
• Display in pips: Allows you to display wick lengths in pips, which is useful for forex traders.
How it works
The script analyzes each candle using the following calculations:
1. Wick length calculation:
◦ Upper wick length = High - (top of the body)
◦ Lower wick length = (bottom of the body) - Low
2. Display conditions:
◦ It distinguishes between bullish and bearish candles.
◦ It checks if the calculated wicks exceed the defined thresholds before displaying them.
3. Dynamic labels:
◦ Labels are placed above or below the respective candles.
◦ Size, color and type of labels are fully customizable.
4. Limitation of labels
Alert conditions:
Alerts are triggered when the wick length of a bullish or bearish candle exceeds the defined thresholds.
Alert function:
alert() is used to issue messages with a frequency of once per candle when the conditions are met.
How to set up alerts
Save the script and add it to your chart.
Open the alert settings in TradingView.
Select the script's custom message as a trigger.
Adjust the frequency and notification type (popup, email, etc.).
Now you have a powerful tool with visual analysis and alert function!
Uptrick: MultiTrend Squeeze System**Uptrick: MultiTrend Squeeze System Indicator: The Ultimate Trading Tool for Precision and Versatility 📈🔥**
### Introduction
The MultiTrend Squeeze System is a powerful, multi-faceted trading indicator designed to provide traders with precise buy and sell signals by combining the strengths of multiple technical analysis tools. This script isn't just an indicator; it's a comprehensive trading system that merges the power of SuperTrend, RSI, Volume Filtering, and Squeeze Momentum to give you an unparalleled edge in the market. Whether you're a day trader looking for short-term opportunities or a swing trader aiming to catch longer-term trends, this indicator is tailored to meet your needs.
### Key Features and Unique Aspects
1. **SuperTrend with Dynamic Adjustments 📊**
- **Adaptive SuperTrend Calculation:** The SuperTrend is a popular trend-following indicator that adjusts dynamically based on market conditions. It uses the Average True Range (ATR) to calculate upper and lower bands, which shift according to market volatility. This script takes it further by combining it with the RSI and Volume filtering to provide more accurate signals.
- **Direction Sensitivity:** The SuperTrend here is not static. It adjusts based on the direction of the previous SuperTrend value, ensuring that the indicator remains relevant even in choppy markets.
2. **RSI Integration for Overbought/Oversold Conditions 💹**
- **RSI Calculation:** The Relative Strength Index (RSI) is incorporated to identify overbought and oversold conditions, adding an extra layer of precision. This helps in filtering out false signals and ensuring that trades are taken only in optimal conditions.
- **Customizable RSI Settings:** The RSI settings are fully customizable, allowing traders to adjust the RSI length and the overbought/oversold levels according to their trading style and market.
3. **Volume Filtering for Enhanced Signal Confirmation 📉**
- **Volume Multiplier:** This unique feature integrates volume analysis, ensuring that signals are only generated when there is sufficient market participation. The Volume Multiplier can be adjusted to filter out weak signals that occur during low-volume periods.
- **Optional Volume Filtering:** Traders have the flexibility to turn the volume filter on or off, depending on their preference or market conditions. This makes the indicator versatile, allowing it to be used across different asset classes and market conditions.
4. **Squeeze Momentum Indicator (SMI) for Market Pressure Analysis 💥**
- **Squeeze Detection:** The Squeeze Momentum Indicator detects periods of market compression and expansion. This script goes beyond the traditional Bollinger Bands and Keltner Channels by incorporating true range calculations, offering a more nuanced view of market momentum.
- **Customizable Squeeze Settings:** The lengths and multipliers for both Bollinger Bands and Keltner Channels are customizable, giving traders the flexibility to fine-tune the indicator based on their specific needs.
5. **Visual and Aesthetic Customization 🎨**
- **Color-Coding for Clarity:** The indicator is color-coded to make it easy to interpret signals. Bullish trends are marked with a vibrant green color, while bearish trends are highlighted in red. Neutral or unconfirmed signals are displayed in softer tones to reduce noise.
- **Histogram Visualization:** The primary trend direction and strength are displayed as a histogram, making it easy to visualize the market's momentum at a glance. The height and color of the bars provide immediate feedback on the strength and direction of the trend.
6. **Alerts for Real-Time Trading 🚨**
- **Custom Alerts:** The script is equipped with custom alerts that notify traders when a buy or sell signal is generated. These alerts can be configured to send notifications through various channels, including email, SMS, or directly to the trading platform.
- **Immediate Reaction:** The alerts are triggered based on the confluence of SuperTrend, RSI, and Volume signals, ensuring that traders are notified only when the most robust trading opportunities arise.
7. **Comprehensive Input Customization ⚙️**
- **SuperTrend Settings:** Adjust the ATR length and factor to control the sensitivity of the SuperTrend. This allows you to adapt the indicator to different market conditions, whether you're trading a volatile cryptocurrency or a more stable stock.
- **RSI Settings:** Customize the RSI length and thresholds for overbought and oversold conditions, enabling you to tailor the indicator to your specific trading strategy.
- **Volume Settings:** The Volume Multiplier and the option to toggle the volume filter provide an additional layer of customization, allowing you to fine-tune the indicator based on market liquidity and participation.
- **Squeeze Momentum Settings:** The lengths and multipliers for Bollinger Bands and Keltner Channels can be adjusted to detect different levels of market compression, providing flexibility for both short-term and long-term traders.
### How It Works: A Deep Dive Into the Mechanics 🛠️
1. **SuperTrend Calculation:**
- The SuperTrend is calculated using the ATR, which measures market volatility. The indicator creates upper and lower bands around the price, adjusting these bands based on the current level of market volatility. The direction of the trend is determined by the position of the price relative to these bands.
- The script enhances the standard SuperTrend by ensuring that the bands do not flip-flop too quickly, reducing the chances of false signals in a choppy market. The direction is confirmed by checking the position of the close relative to the previous band, making the trend detection more reliable.
2. **RSI Integration:**
- The RSI is calculated over a customizable length and compared to user-defined overbought and oversold levels. When the RSI crosses below the oversold level, and the SuperTrend indicates a bullish trend, a buy signal is generated. Conversely, when the RSI crosses above the overbought level, and the SuperTrend indicates a bearish trend, a sell signal is triggered.
- The combination of RSI with SuperTrend ensures that trades are only taken when there is a strong confluence of signals, reducing the chances of entering trades during weak or indecisive market phases.
3. **Volume Filtering:**
- The script calculates the average volume over a 20-period simple moving average. The volume filter ensures that buy and sell signals are only valid when the current volume exceeds a multiple of this average, which can be adjusted by the user. This feature helps filter out weak signals that might occur during low-volume periods, such as just before a major news event or during after-hours trading.
- The volume filter is particularly useful in markets where volume spikes are common, as it ensures that signals are only generated when there is significant market interest in the direction of the trend.
4. **Squeeze Momentum:**
- The Squeeze Momentum Indicator (SMI) adds a layer of market pressure analysis. The script calculates Bollinger Bands and Keltner Channels, detecting when the market is in a "squeeze" — a period of low volatility that typically precedes a significant price move.
- When the Bollinger Bands are inside the Keltner Channels, the market is in a squeeze (compression phase). This is often a precursor to a breakout or breakdown. The script colors the histogram bars black during this phase, indicating a potential for a strong move. Once the squeeze is released, the bars are colored according to the direction of the SuperTrend, signaling a potential entry point.
5. **Integration and Signal Generation:**
- The script brings together the SuperTrend, RSI, Volume, and Squeeze Momentum to generate highly accurate buy and sell signals. A buy signal is triggered when the SuperTrend is bullish, the RSI indicates oversold conditions, and the volume filter confirms strong market participation. Similarly, a sell signal is generated when the SuperTrend is bearish, the RSI indicates overbought conditions, and the volume filter is met.
- The combination of these elements ensures that the signals are robust, reducing the likelihood of entering trades during weak or indecisive market conditions.
### Practical Applications: How to Use the MultiTrend Squeeze System 📅
1. **Day Trading:**
- For day traders, this indicator provides quick and reliable signals that can be used to enter and exit trades multiple times within a day. The volume filter ensures that you are trading during the most liquid times of the day, increasing the chances of successful trades. The Squeeze Momentum aspect helps you catch breakouts or breakdowns, which are common in intraday trading.
2. **Swing Trading:**
- Swing traders can use the MultiTrend Squeeze System to identify longer-term trends. By adjusting the ATR length and factor, you can make the SuperTrend more sensitive to catch longer-term moves. The RSI and Squeeze Momentum aspects help you time your entries and exits, ensuring that you get in early on a trend and exit before it reverses.
3. **Scalping:**
- For scalpers, the quick signals provided by this system, especially in combination with the volume filter, make it easier to take small profits repeatedly. The histogram bars give you a clear visual cue of the market's momentum, making it easier to scalp effectively.
4. **Position Trading:**
- Even position traders can benefit from this indicator by using it to confirm long-term trends. By adjusting the settings to less sensitive parameters, you can ensure that you are only entering trades when a strong trend is confirmed. The Squeeze Momentum indicator will help you stay in the trade during periods of consolidation, waiting for the next big move.
### Conclusion: Why the MultiTrend Squeeze System is a Game-Changer 🚀
The MultiTrend Squeeze System is not just another trading indicator; it’s a comprehensive trading strategy encapsulated within a single script. By combining the power
of SuperTrend, RSI, Volume Filtering, and Squeeze Momentum, this indicator provides a robust and versatile tool that can be adapted to various trading styles and market conditions.
**Why is it Unique?**
- **Multi-Dimensional Analysis:** Unlike many other indicators that rely on a single data point or calculation, this script incorporates multiple layers of analysis, ensuring that signals are based on a confluence of factors, which increases their reliability.
- **Customizability:** The vast range of input settings allows traders to tailor the indicator to their specific needs, whether they are trading forex, stocks, cryptocurrencies, or commodities.
- **Visual Clarity:** The color-coded bars, labels, and signals make it easy to interpret the market conditions at a glance, reducing the time needed to make trading decisions.
Whether you are a novice trader or an experienced market participant, the MultiTrend Squeeze System offers a powerful toolset to enhance your trading strategy, reduce risk, and maximize your potential returns. With its combination of trend analysis, momentum detection, and volume filtering, this indicator is designed to help you trade with confidence and precision in any market condition.
Day Trading MA Crossover IndicatorDay Trading MA Crossover Indicator Overview The Day Trading MA Crossover Indicator is a simple yet effective tool designed for day traders to identify potential buy and sell opportunities based on moving average crossovers. It plots two customizable moving averages on your chart and generates clear visual signals when they cross, helping you spot trend reversals or continuations in fast-paced markets.This indicator is ideal for intraday trading on lower timeframes (e.g., 5-min, 15-min charts) but can be adapted for swing trading or higher timeframes. It's built with flexibility in mind, allowing you to tweak the MA lengths and types to suit your strategy.Key FeaturesMoving Average Crossovers: Generates "BUY" signals when the fast MA crosses above the slow MA (potential bullish entry) and "SELL" signals when it crosses below (potential bearish entry or exit).
Visual Signals: Green "BUY" labels below bars for long entries and red "SELL" labels above bars for short entries or exits. Optional subtle background coloring highlights signals for quick spotting.
Customizable Parameters:Fast MA Length (default: 9): Period for the shorter moving average.
Slow MA Length (default: 21): Period for the longer moving average.
MA Type (default: EMA): Choose between SMA (Simple), EMA (Exponential), or WMA (Weighted) for different smoothing behaviors.
Overlay Mode: Plots directly on your price chart without cluttering separate panes.
Lightweight and Efficient: Minimal computation for real-time performance on TradingView.
How It WorksMoving Averages Calculation: The indicator computes two MAs based on your selected type and lengths using closing prices.
Signal Detection: A buy signal triggers on an upward crossover (fast MA > slow MA), indicating potential momentum shift to the upside. A sell signal triggers on a downward crossunder (fast MA < slow MA), signaling possible downside momentum.
Visual Aids: Signals appear as labeled shapes with optional background tints to emphasize key bars.
Usage TipsFor Day Trading: Apply on volatile instruments like forex pairs, stocks, or crypto. Combine with support/resistance levels or other indicators (e.g., RSI for overbought/oversold confirmation) to filter false signals in ranging markets.
Backtesting: Test on historical data to optimize MA lengths for your asset—shorter periods for aggressive trading, longer for smoother trends.
Risk Management: Always use stop-losses and position sizing. Signals are not foolproof and work best in trending conditions.
Customization: Adjust inputs via the indicator settings panel after adding it to your chart.
Example SetupOn a 5-min EUR/USD chart: Use EMA (9/21) for quick crossovers. Look for buy signals above key support with increasing volume.
Avoid choppy markets where frequent false crossovers ("whipsaws") can occur.
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results. Trading involves risk; consult a professional advisor before using any strategy. If you have feedback or suggestions for improvements, feel free to comment!
INSTITUTIONAL VOLUME PROFILE + FIBONACCI + ENHANCED SIGNALS🎯 INSTITUTIONAL VOLUME PROFILE + FIBONACCI + ENHANCED SIGNALS
A professional-grade indicator combining Volume Profile analysis, Fibonacci retracements, Anchored VWAP, and intelligent signal filtering to identify high-probability institutional positioning and trade setups.
📊 CORE FEATURES
▸ Volume Profile with POC (Point of Control)
- Visualizes where institutional volume accumulated
- Identifies High Volume Nodes (HVN) as key support/resistance
- Shows Value Area (70% volume zone) for market equilibrium
▸ Dynamic Fibonacci Levels
- Auto-detects swing high/low for retracement levels
- Golden Pocket (0.618-0.65) highlight zone
- Bull/bear direction recognition
▸ Anchored VWAP
- Anchored to swing range start
- Institutional mean reversion baseline
- Real-time trend bias indicator
▸ Graded Signal System (A+/B/C)
- A+ Signals: High probability setups (VWAP cross + POC alignment)
- B Signals: Above-average quality (VWAP cross above POC)
- C Signals: Lower probability (counter-trend setups)
🎮 DISPLAY MODES
⚡ TRADING LIVE MODE
- Clean chart showing only A+ signals
- Minimal visual noise for active trading
- Perfect for intraday execution
📈 FULL OVERVIEW MODE
- Complete analysis with all zones visible
- Volume Profile + Fibonacci + Value Area
- All signal grades displayed
- Statistics dashboard
🔬 ADVANCED SIGNAL FILTERS
✓ Volume Confirmation
- Requires above-average volume on signals
- Filters out weak institutional participation
- Configurable volume multiple (default 1.2x)
✓ Momentum Filter
- Ensures price momentum aligns with signal direction
- Prevents counter-trend entries
- Configurable lookback period
✓ SR Proximity Upgrade ⭐ GAME CHANGER
- Automatically upgrades B/C signals to A+ when near key levels
- Detects proximity to POC and HVN zones
- Combines technical confluence for best setups
🔔 SMART ALERTS
▸ Configurable alerts for A+, B, or C signals
▸ Real-time notifications to your device
▸ No need to watch charts constantly
▸ "Once per bar close" prevents repainting
💡 HOW TO USE
FOR DAY TRADING:
1. Switch to "Trading Live" mode
2. Enable only A+ alerts
3. Set filters: Volume 1.5x, Momentum ON, Proximity 0.3%
4. Trade only A+ signals at key levels
FOR SWING TRADING:
1. Use "Full Overview" mode
2. Analyze Value Area and Fibonacci confluence
3. Set filters: Volume 1.2x, Momentum ON, Proximity 0.8%
4. Enter on A+ signals with multi-timeframe confirmation
FOR ANALYSIS:
1. Full Overview mode with all visuals enabled
2. Disable filters to see all raw signals
3. Study how institutions positioned at key zones
4. Plan trades around POC and Value Area
⚙️ RECOMMENDED SETTINGS
5-15 MIN CHARTS (Scalping):
- Lookback: 200-300 bars
- Volume: 1.5x, Momentum: 5 bars, Proximity: 0.3%
- Trading Live mode + A+ alerts only
1 HOUR CHARTS (Intraday):
- Lookback: 300 bars
- Volume: 1.3x, Momentum: 3 bars, Proximity: 0.5%
- Full Overview or Trading Live
4 HOUR CHARTS (Swing):
- Lookback: 300-500 bars
- Volume: 1.2x, Momentum: 3 bars, Proximity: 0.8%
- Full Overview mode
DAILY CHARTS (Position):
- Lookback: 300-500 bars
- Volume: 1.1x, Momentum: 2 bars, Proximity: 1.0%
- Full Overview mode
📈 KEY CONCEPTS
POC (Point of Control): Price level with highest volume - acts as magnet
Value Area: Zone containing 70% of volume - equilibrium range
HVN: High Volume Nodes - institutional accumulation zones
AVWAP: Anchored VWAP - institutional average entry price
Golden Pocket: 0.618-0.65 Fib zone - highest probability reversal area
🎯 TRADING STRATEGY TIPS
1. Wait for A+ signals - quality over quantity
2. Best setups occur at POC or Value Area boundaries
3. Use multiple timeframes for confirmation
4. Combine with your own risk management rules
5. Signals are high probability, not guaranteed - always use stops
Trendlines & SR ZonesIt's a comprehensive indicator (Pine Script v6) that represents two powerful technical analysis tools: automatic trendline detection based on pivot points and volume delta analysis with support/resistance zone identification. This overlay indicator helps traders identify potential trend directions and key price levels where significant buying or selling pressure has occurred.
Features: =
1. Price Trendlines
The indicator automatically identifies and draws trendlines based on pivot points, creating dynamic support and resistance levels.
Key Components:
Pivot Detection: Uses configurable left and right bars to identify significant pivot highs and lows
Trendline Filtering: Only draws downward-sloping resistance trendlines and upward-sloping support trendlines
Zone Creation: Creates filled zones around trendlines based on average price volatility
Automatic Management: Maintains only the 3 most recent significant trendlines to avoid chart clutter
Customization Options:
Left/Right Bars for Pivot: Adjust sensitivity of pivot detection (default: 10 bars each side)
Extension Length: Control how far trendlines extend past the second pivot (default: 50 bars)
Average Body Periods: Set the lookback period for volatility calculation (default: 100)
Tolerance Multiplier: Adjust the width of the trendline zones (default: 1.0)
Color Customization: Separate colors for high (resistance) and low (support) trendlines and their fills
2. Volume Delta % Bars
The indicator analyzes volume distribution across price levels to identify significant supply and demand zones.
Key Components:
Volume Profile Analysis: Divides the price range into rows and calculates volume delta at each level
Delta Visualization: Displays horizontal bars showing the percentage difference between buying and selling volume
Zone Identification: Automatically identifies the most significant supply and demand zones
Visual Integration: Connects volume delta bars with corresponding support/resistance zones on the price chart
Customization Options:
Lookback Period: Set the number of bars to analyze for volume (default: 200)
Price Rows: Control the granularity of the volume analysis (default: 50 rows)
Delta Sections: Adjust the number of horizontal delta bars displayed (default: 20)
Panel Appearance: Customize width, position, and direction of the delta panel
Zone Settings: Control the number of supply/demand zones and their extension (default: 3 zones)
How It Works-
Trendline Logic:
The script continuously scans for pivot highs and lows based on the specified left and right bars
When a pivot is detected, it creates a horizontal line at that price level
The script then looks for the previous pivot of the same type (high or low)
It connects these pivots with a trendline, extending it based on the user-specified setting
A parallel line is created to form a zone, with the distance based on average price volatility
The script filters out invalid trendlines (upward-sloping resistance and downward-sloping support). Only the 3 most recent trendlines are maintained to prevent chart clutter
Volume Delta Logic:
The script divides the price range over the lookback period into the specified number of rows
For each bar in the lookback period, it categorizes volume as bullish (close > open) or bearish (close < open). This volume is assigned to the appropriate price level based on the HLC3 price.
The price levels are grouped into sections, and the net delta (bullish - bearish volume) is calculated for each Horizontal bars are drawn to represent these delta percentages.
The most significant positive and negative deltas are identified and displayed as support and resistance zones. These zones are extended to the left on the price chart and connected to the delta panel with dotted lines.
Ideal Timeframes:
The indicator is versatile and can be used across multiple timeframes, but it performs optimally on specific timeframes depending on your trading style:
For Day Trading:
Optimal Timeframes: 15-minute to 1-hour charts
Why: These timeframes provide a good balance between noise reduction and sufficient volume data. The volume delta analysis is particularly effective on these timeframes as it captures intraday accumulation/distribution patterns while the trendlines remain reliable enough for intraday trading decisions.
For Swing Trading:
Optimal Timeframes: 1-hour to 4-hour charts
Why: These timeframes offer the best combination of reliable trendline formation and meaningful volume analysis. The trendlines on these timeframes are less prone to whipsaws, while the volume delta analysis captures multi-day trading sessions and institutional activity.
For Position Trading:
Optimal Timeframes: Daily and weekly charts
Why: On these higher timeframes, trendlines become extremely reliable as they represent significant market structure points. The volume delta analysis reveals longer-term accumulation and distribution patterns that can define major support and resistance zones for weeks or months.
Timeframe-Specific Adjustments:
Lower Timeframes (1-15 minutes):
Reduce left/right bars for pivots (5-8 bars)
Decrease lookback period for volume delta (50-100 bars)
Increase tolerance multiplier (1.2-1.5) to account for higher volatility
Higher Timeframes (Daily+):
Increase left/right bars for pivots (15-20 bars)
Extend lookback period for volume delta (300-500 bars)
Consider increasing the number of price rows (70-100) for more detailed volume analysis
Usage Guidelines-
For Trendline Analysis:
Use the trendlines as dynamic support and resistance levels
Price reactions at these levels can indicate potential trend continuation or reversal points
The filled zones around trendlines represent areas of price volatility or uncertainty
Consider the slope of the trendline as an indication of trend strength
For Volume Delta Analysis:
The horizontal delta bars show where buying or selling pressure has been concentrated
Green bars indicate areas where buying volume exceeded selling volume (demand)
Red bars indicate areas where selling volume exceeded buying volume (supply)
The highlighted supply and demand zones on the price chart represent significant price levels
These zones can act as future support or resistance areas as price revisits them
Customization Tips:
Trendline Sensitivity: Decrease left/right bars values to detect more pivots (more sensitive) or increase them for fewer, more significant pivots
Zone Width: Adjust the tolerance multiplier to make trendline zones wider or narrower based on your trading style
Volume Analysis: Increase the lookback period for a longer-term volume profile or decrease it for more recent activity
Visual Clarity: Adjust colors and transparency settings to match your chart theme and preferences
Conclusion:
This indicator provides traders with a comprehensive view of both trend dynamics and volume-based support/resistance levels. With these two analytical approaches, the indicator offers valuable insights for identifying potential entry and exit points, trend strength, and key price levels where significant market activity has occurred. The extensive customization options allow traders to adapt the indicator to various trading styles and timeframes, with optimal performance on 15-minute to daily charts depending on their trading horizon.
Chart Attached: NSE HINDZINC, EoD 12/12/25
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice. Please do boost if you like it. Happy Trading.
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
Luxy VWAP Magic - MTF Projection EngineThis indicator transforms the classic VWAP into a comprehensive trading system. Instead of switching between multiple indicators, you get everything in one place: multi-timeframe analysis, statistical bands, momentum detection, volume profiling, session tracking, and divergence signals.
What Makes This Different
Traditional VWAP indicators show a single line. This tool treats VWAP as a foundation for complete market analysis. The indicator automatically detects your asset type (stocks, crypto, forex, futures) and adjusts its behavior accordingly. Crypto traders get 24/7 session tracking. Stock traders get proper market hours handling. Everyone gets institutional-grade analytics.
Anchor Period Options
The anchor period determines when VWAP resets and recalculates. You have three categories of options:
Time-Based Anchors:
Session - Resets at market open. Best for intraday stock trading where you want fresh VWAP each day.
Day - Resets at midnight UTC. Standard option for most traders.
Week / Month / Quarter / Year - Longer reset periods for swing traders and position traders who want broader context.
Rolling Window Anchors:
Rolling 5D - A sliding 5-day window that never resets. Solves the Monday problem where weekly VWAP equals daily VWAP on first day of week.
Rolling 21D - Approximately one month of trading data in continuous calculation. Excellent for crypto and forex markets that trade 24/7 without clear session breaks.
Event-Based Anchors:
Dividends - Resets on ex-dividend dates. Track institutional cost basis from dividend events.
Splits - Resets on stock split dates. Useful for analyzing post-split trading behavior.
Earnings - Resets on earnings report dates. See where volume-weighted trading occurred since last quarterly report.
Standard Deviation Bands
Three sets of bands surround the main VWAP line:
Band 1 (Aqua) - Plus and minus one standard deviation. Approximately 68% of price action occurs within this range under normal distribution. Touches suggest minor extension.
Band 2 (Fuchsia) - Plus and minus two standard deviations. Only 5% of trading should occur outside this range statistically. Touches here indicate significant overextension and high probability of mean reversion.
Band 3 (Purple) - Plus and minus three standard deviations. Touches are rare (0.3% probability) and represent extreme conditions. Often marks climax moves or panic selling/buying.
Each band can be toggled independently. Most traders show Band 1 by default and add Band 2 and 3 for specific setups or volatile instruments.
Multi-Timeframe VWAP System
The MTF section plots previous period VWAPs as horizontal support and resistance levels:
Daily VWAP - Previous day's final VWAP value. Key intraday reference level.
Weekly VWAP - Previous week's final VWAP. Important for swing traders.
Monthly VWAP - Previous month's final VWAP. Institutional benchmark level.
Quarterly VWAP - Previous quarter's final VWAP. Major support/resistance for position traders.
Previous Day VWAP - Yesterday's closing VWAP specifically, separate from current daily calculation.
The Confluence Zone percentage setting determines how close multiple VWAPs must be to trigger a confluence alert. When two or more timeframe VWAPs converge within this threshold, you get a high-probability support/resistance zone.
Session VWAPs for Global Markets
For forex, crypto, and futures traders who operate in 24/7 markets, the indicator tracks three major global sessions:
Asia Session - UTC 21:00 to 08:00. Gold colored line. Typically lower volatility, range-bound action that sets overnight levels.
London Session - UTC 08:00 to 17:00. Orange colored line. Often determines daily direction with high volume European participation.
New York Session - UTC 13:00 to 22:00. Blue colored line. Highest volume session globally. Sharp directional moves common.
Previous session VWAP values display as horizontal lines when each session closes, acting as intraday support and resistance. The table shows which sessions are currently active with checkmarks.
On-Chart Labels and Signals
The indicator plots several types of labels directly on price action when significant events occur:
Volume Spike Labels
Fire when current bar volume exceeds configurable thresholds relative to both the previous bar and the 20-bar average. Default settings require 300% of previous bar AND 200% of average volume. Green labels indicate bullish candles. Red labels indicate bearish candles. These spikes often mark institutional entry points.
Momentum Shift Labels
Appear when VWAP acceleration changes direction. The Slowing label warns when an active trend loses steam, often preceding reversal. The Accelerating label confirms trend continuation or potential bottom during downtrends. Filters available to show only reversal signals in existing trends.
VWAP Squeeze Labels
Detect when standard deviation bands contract relative to ATR (Average True Range). Low volatility compression often precedes explosive breakout moves. When the squeeze fires (releases), a label appears with directional prediction based on VWAP slope.
Divergence Labels
Mark price/volume divergences using CVD (Cumulative Volume Delta) analysis:
Bullish divergence: Price makes lower low, but CVD makes higher low. Hidden accumulation despite price weakness.
Bearish divergence: Price makes higher high, but CVD makes lower high. Hidden distribution despite price strength.
Dynamic VWAP Coloring
The main VWAP line changes color based on its slope direction:
Green - VWAP is rising. Institutional buying pressure. Volume-weighted price increasing.
Red - VWAP is falling. Institutional selling pressure. Volume-weighted price decreasing.
Gray - VWAP is flat. Consolidation or balance between buyers and sellers.
This coloring can be disabled for a static blue line if you prefer cleaner visuals. The VWAP label next to the line shows the current trend direction and delta percentage.
Calculated Projection Cone
One of the most powerful features is the Calculated Projection Cone. Unlike traditional extrapolation methods that simply extend a trend line forward, this system analyzes what actually happened in similar market conditions throughout the chart's history.
How It Works:
The system classifies each bar into one of 27 unique market states:
Z-Score Level - LOW (oversold), MID (fair value), or HIGH (overbought) based on configurable thresholds
Trend Direction - DOWN, FLAT, or UP based on VWAP slope
Volume Profile - LOW (below 80%), NORMAL (80-150%), or HIGH (above 150%) relative volume
When you look at the current bar, the indicator:
1. Identifies the current market state (e.g., LOW Z-Score + UP Trend + HIGH Volume)
2. Searches through all historical bars on the chart that had the same state
3. Calculates what happened in those bars X bars later (where X is your projection horizon)
4. Shows you the probability of up/down and the average move size
Visual Elements:
Probability Cone - Colored green (bullish probability above 55%), red (bearish below 45%), or gold (neutral). The cone width represents the historical range of outcomes (roughly the 20th to 80th percentile).
Center Line - Shows the average expected price based on historical outcomes in similar conditions.
Probability Label - Displays direction probability and average move. Example: "67% UP (+0.8%)" means 67% of similar past cases moved up, averaging 0.8% gain.
Fallback System:
When the exact 27-state match has insufficient historical data:
First fallback: Uses Z-Score plus Trend only (9 broader states, ignoring volume)
Second fallback: Uses Z-Score only (3 states)
When fallback is active, confidence automatically adjusts
Settings:
Projection Horizon - How many bars forward to analyze outcomes (5, 10, 15, or 20 bars, default 10)
Lookback Period - Historical data window in days (30-252, default 60)
Minimum Samples - Cases needed before using fallback (5-30, default 10)
Z-Score Threshold - Bucket boundary for LOW/MID/HIGH classification (1.0, 1.5, or 2.0 sigma)
Cloud Transparency - Adjust visibility (50-95%)
Colors - Customize bullish, bearish, and neutral cone colors
Confidence Levels:
HIGH - 30 or more similar historical cases found
MEDIUM - 15-29 similar cases
LOW - Fewer than 15 cases (more uncertainty)
IMPORTANT DISCLAIMER:
The Calculated Projection is based on past patterns only. It is NOT a price prediction or financial advice. Similar market states in the past do not guarantee similar outcomes in the future. The probability shown is historical frequency, not a guarantee. Always combine with other analysis and never rely solely on projections for trading decisions.
Alert Conditions
The indicator includes over 20 pre-built alert conditions:
Price vs VWAP:
Price crosses above VWAP
Price crosses below VWAP
Band Touches:
Price touches plus or minus one sigma band
Price touches plus or minus two sigma band (extreme)
Price touches plus or minus three sigma band (very extreme)
Z-Score Extremes:
Z-Score crosses above plus two (overbought extreme)
Z-Score crosses below minus two (oversold extreme)
Momentum and Trend:
Momentum slowing
Momentum accelerating
Trend turns bullish/bearish/neutral
Volume:
Volume spike detected
CVD Direction:
Buyers take control
Sellers take control
High Probability Signals:
Bullish reversal signal (oversold plus accelerating momentum)
Bearish reversal signal (overbought plus slowing momentum)
MTF and Special:
MTF confluence zone entry
VWAP squeeze fired
Bullish/Bearish divergence detected
Any significant signal (catch-all)
All signals use confirmed bar data to prevent false alerts from incomplete candles.
Settings Overview
Settings are organized into logical groups:
VWAP Settings
Anchor Period selection
Show/Hide VWAP line
Dynamic coloring toggle
VWAP label visibility
Bands Visibility
Toggle each of three bands independently
Info Table
Show/Hide table
Table position (9 options)
Text size
Volume spike label settings with adjustable thresholds
Momentum label settings with filters
Signal labels limited to 5 most recent (auto-managed)
Probability engine lookback period
Multi-Timeframe VWAP
Enable/Disable MTF system
Show MTF in table
Show MTF lines on chart
Individual timeframe toggles
Confluence zone threshold
Squeeze detection toggle
Session VWAPs
Enable/Disable session tracking
Apply to all assets option
Show session labels
Divergence Detection
Enable/Disable divergence
Pivot lookback period
Show divergence labels
Calculated Projection
Enable/Disable projection cone
Projection horizon (5, 10, 15, or 20 bars)
Lookback period in days (30-252)
Minimum samples threshold
Z-Score classification threshold (1.0, 1.5, or 2.0 sigma)
Cloud transparency adjustment
Bullish, bearish, and neutral colors
The Info Table - Your Trading Dashboard
The right side of your chart displays a compact table with up to twelve metrics.
Row-by-Row Breakdown:
Asset and Period - Shows what the indicator detected (US Stock, Crypto, Forex, etc.) and your selected anchor period. The detection happens automatically based on exchange data, so VWAP resets and calculations match your actual trading instrument.
Delta Percentage - How far current price sits from VWAP, expressed as a percentage. Positive means price trades above fair value. Negative means below. Large delta values (beyond 1-2%) often precede mean reversion moves. Day traders watch this for overextension.
Z-Score - Statistical deviation from VWAP measured in standard deviations. Unlike raw delta, Z-Score accounts for volatility. A 2% move in a volatile biotech stock differs from 2% in a stable utility. Z-Score normalizes this. Values beyond plus or minus two sigma occur only 5% of the time statistically.
Trend Direction - Whether VWAP itself is rising, falling, or flat. Rising VWAP means the volume-weighted average price is increasing, which indicates institutional accumulation. Falling VWAP suggests distribution. This differs from price trend since it weights by volume.
Momentum State - Is the trend accelerating or slowing down? This measures the rate of change in VWAP slope. When an uptrend shows slowing momentum, it often precedes reversal. Accelerating momentum in a downtrend can signal capitulation and potential bottom.
Relative Volume - Current bar volume compared to the 20-bar average, shown as percentage. Values above 150% indicate above-average activity. Spikes above 200-300% often mark institutional involvement. Low volume (below 80%) warns of potential fake moves.
MTF Bias - Four checkmarks or X marks showing whether price sits above or below Daily, Weekly, Monthly, and Quarterly VWAP. Four checkmarks means strong bullish alignment across all timeframes. Four X marks indicates bearish alignment. Mixed readings suggest consolidation or transition.
Band Probabilities - Historical statistics showing how often price touched each standard deviation band over your lookback period. This helps you understand if mean reversion or trend following works better for your specific instrument.
Session Status - Which global trading sessions are currently active (Asia, London, New York). Shows checkmarks for active sessions. Important for forex and crypto traders who need to know when major liquidity windows open and close.
Divergence State - Whether the indicator detects bullish or bearish divergence between price and cumulative volume delta. Bullish divergence occurs when price makes lower lows but buying pressure (CVD) makes higher lows, suggesting hidden accumulation.
Confidence Score - A weighted composite of all factors displayed as a progress bar and percentage. Combines MTF alignment, Z-Score, trend direction, volume delta, momentum, and relative volume into a single 0-100 score. Higher scores indicate stronger conviction setups.
Calculated Projection - When the Projection Cone is enabled, shows the historical probability of price direction and expected move. For example: "▲ 67% (+0.8%)" means in similar market states historically, price moved up 67% of the time with an average gain of 0.8%. The system analyzes 27 unique market states based on Z-Score, Trend, and Volume conditions.
Recommended Use Cases
Day Trading Stocks:
Use Session anchor with Band 1 visible. Watch for price returning to VWAP after morning move. Volume spikes near VWAP often mark institutional accumulation zones.
Swing Trading:
Use Weekly or Rolling 21D anchor. Enable MTF lines for Daily and Weekly levels. Trade pullbacks to these levels in direction of MTF bias.
Crypto and Forex:
Enable Session VWAPs. Use Rolling anchors to avoid artificial resets. Monitor session transitions for breakout opportunities.
Mean Reversion:
Focus on Z-Score reaching plus or minus two. Add Band 2 visibility. Combine with slowing momentum for highest probability reversals.
Trend Following:
Watch MTF bias alignment. Four checkmarks plus accelerating momentum plus high volume confirms trend continuation setups.
Projection Planning:
Enable the Calculated Projection to see what happened historically in similar market conditions. Use 5-10 bars for intraday setups, 15-20 bars for swing trade planning. Focus on high probability readings (above 60%) with HIGH confidence (30 or more samples). The cone shows the probable range of outcomes based on actual historical data. Combine with other factors like MTF alignment and volume for higher conviction setups.
Important Notes
The indicator does not repaint. MTF values use previous period's confirmed data.
Rolling VWAP works best on 15-minute timeframes and above due to bar lookback requirements.
Session VWAPs apply to global markets by default (forex, crypto, futures). Enable the all-assets option for stocks if desired.
Volume data for forex represents tick volume, not actual traded volume.
All alert conditions fire only on confirmed (closed) bars to prevent false signals.
The Calculated Projection updates each bar as market state changes. This is expected behavior. The projection shows probabilities based on similar past conditions, not a fixed prediction.
Q AND A
Q: Does this indicator repaint?
A: No. The main VWAP calculation uses standard TradingView VWAP methodology. Multi-timeframe values use previous period's confirmed data with appropriate lookahead settings. All alert signals require bar confirmation.
Q: Why does my Rolling VWAP look different on 1-minute versus 15-minute charts?
A: Rolling VWAP calculates across a fixed number of trading days. On very short timeframes, the bar lookback may hit TradingView limits. For best Rolling VWAP accuracy, use 15-minute or higher timeframes.
Q: Can I use this on any instrument?
A: Yes. The indicator automatically detects asset type and adjusts behavior. Stocks use standard market hours. Crypto uses 24/7 calculations. Forex uses tick volume. Everything adapts automatically.
Q: What does the Confidence Score actually measure?
A: The score combines six weighted factors: MTF alignment (25%), Z-Score position (20%), Trend direction (20%), CVD pressure (15%), Momentum state (10%), and Relative volume (10%). Higher scores indicate more factors aligned in one direction.
Q: Why are Session VWAPs not showing on my stock chart?
A: Session VWAPs apply to 24-hour markets by default (forex, crypto, futures). For stocks, enable the Use for All Assets option in Session VWAP settings.
Q: The Divergence labels appear delayed. Is this a bug?
A: Divergence detection requires pivot confirmation, which needs bars on both sides of the pivot point. The label appears at the actual pivot location (several bars back) once confirmed. This is intentional and prevents false signals.
Q: Can I change the band colors?
A: Yes. Each of the three bands has its own color input setting. You can customize Band 1, Band 2, and Band 3 colors to match your preferences. The defaults are Aqua, Fuchsia, and Purple. The main VWAP line color adapts dynamically based on slope direction or can be set to static blue.
Q: How do I set up alerts?
A: Right-click on the chart, select Add Alert, choose this indicator, and select your desired condition from the dropdown. All conditions include descriptive alert messages with relevant data.
Q: What is the Probability Engine lookback period?
A: This setting determines how many trading days the indicator analyzes to calculate band touch rates and mean reversion statistics. Default is 60 days (approximately 3 months). Longer periods provide more stable statistics but may miss recent behavior changes.
Q: Why do I see fewer labels than expected?
A: Signal labels (Volume, Momentum, Squeeze, Divergence) are limited to 5 most recent labels on the chart to keep it clean. When a new label appears, the oldest one is automatically removed. Additionally, momentum labels have several filters: check the slope multiplier setting (higher values require stronger trends) and the Only Reversal Signals option (when enabled, labels only appear for potential reversals, not trend confirmations).
Q: What is the Calculated Projection and how accurate is it?
A: The Calculated Projection analyzes what happened in past market conditions similar to the current state. It classifies each bar by Z-Score level, Trend direction, and Volume profile (27 unique states), then shows the historical probability of up vs down and the average move size. It is NOT a price prediction or guarantee. The probability shown is how often similar conditions led to up/down moves historically, not a future guarantee. Always use it as one input among many.
Q: Why does the Projection probability change?
A: The projection updates on each bar as market state changes. If Z-Score moves from LOW to MID, or trend shifts from UP to FLAT, the system looks up a different historical category. This is expected behavior. The projection shows what happened in similar past conditions to the current bar's state.
Q: The Projection shows LOW confidence. What does that mean?
A: Confidence levels indicate sample size: HIGH means 30 or more historical cases found, MEDIUM means 15-29 cases, LOW means fewer than 15 cases. When sample size is low, the system uses a fallback: first aggregating by Z-Score plus Trend only (ignoring volume), then by Z-Score only. LOW confidence means less statistical reliability, so weight other factors more heavily in your decision.
Q: Why does the cone sometimes show 50/50 probability?
A: A 50/50 reading means that in similar past market states, price moved up roughly half the time and down half the time. This indicates a neutral or balanced condition where historical patterns provide no directional edge. Consider waiting for a higher probability setup or using other analysis methods.
CREDITS AND ACKNOWLEDGMENTS
Methodology Foundation:
VWAP (Volume Weighted Average Price) - Standard institutional benchmark calculation, widely used since the 1980s for algorithmic execution and fair value assessment
Standard Deviation Bands - Statistical volatility measurement applying normal distribution principles to price deviation from mean
Z-Score Analysis - Classic statistical normalization technique for comparing values across different volatility regimes
Cumulative Volume Delta (CVD) - Order flow analysis concept measuring aggressive buying versus selling pressure
Concept Integration:
Mean reversion probability engine - Custom historical statistics tracking for band touch rates
Momentum acceleration detection - Second derivative analysis of VWAP slope changes
VWAP Squeeze - Volatility compression concept adapted from TTM Squeeze methodology applied to VWAP bands versus ATR
Confidence scoring system - Weighted composite scoring combining multiple technical factors
Calculated Projection Cone - Probability-based projection using 27-state market classification (Z-Score, Trend, Volume) with historical outcome analysis and weighted fallback system
All calculations use standard public domain formulas and TradingView built-in functions. No proprietary third-party code was used.
For questions, feedback, or feature requests, please comment below or send a private message.
Happy Trading!
Pair Correlation Master [Macro]The Main Idea
Trading represents a constant battle between Systemic Flows (the whole market moving together) and Idiosyncratic Moves (one specific asset moving on its own).
This tool allows you to monitor a "basket" of 4 assets simultaneously (e.g., the major USD pairs). It answers the most important question in forex and multi-asset trading: "Is this move happening because the Dollar is weak, or because the Euro is strong?"
It separates the "Signal" (the unique move) from the "Noise" (the herd movement).
1. The Chart Lines: The "Race" (Macro Trend)
Think of the lines on your chart as a long-distance race. They visualize the performance of all 4 assets over the last 200 candles (adjustable).
- Bunched Together: If all lines are moving in the same direction, the market is highly correlated. (e.g., "The Dollar is selling off everywhere").
- Fanning Out: If the lines are spreading apart, specific currencies are outperforming others.
- The Zero Line: This is the starting line.
--- Above 0: The pair is in a macro uptrend.
--- Below 0: The pair is in a macro downtrend.
2. The Dashboard: The "Health Check" (Micro Data)
The table in the top right gives you the immediate statistics for right now.
- A. The Z-Score (The Rubber Band)
This measures how "stretched" price is compared to its normal behavior.
- White (< 2.0): Normal trading activity.
- Orange (> 2.0): The price is stretching. Warning sign.
- Red (> 3.0): Critical Stretch. The rubber band is pulled to its limit. Statistically, a pullback or pause is highly likely.
B. The Star (★)
The script automatically calculates the average behavior of your group. If one asset is behaving completely differently from the rest, it marks it with a Star (★).
- Example: EURUSD, GBPUSD, and NZDUSD are flat, but AUDUSD is rallying hard. AUDUSD gets the ★. This is where the unique opportunity lies.
🎯 Best Uses: 4H & Daily Timeframes
This indicator is tuned for "Macro" analysis. It works best on the "4-Hour" and "Daily" charts to filter out intraday noise and capture swing trading moves.
- Strategy 1: The "Rubber Band" Snap (Mean Reversion)
- Setup: Look for a Z-Score in the RED (> 3.0) on the Daily timeframe.
- Action: This indicates an unsustainable move. Look for reversals or exhaustion patterns to trade against the trend back toward the mean.
- Strategy 2: The "Lone Wolf" (Trend Following)
- Setup: Look for the asset with the Star (★).
- Action: If the whole basket is flat (Balanced), but the Star asset is breaking out, that creates a high-quality trend trade because that specific currency has its own catalyst (News/Earnings).
- Strategy 3: Systemic Flows (Basket Trading)
- Setup: The dashboard footer says "⚠️ SYSTEMIC MOVE."
- Action: This means everything is moving together (e.g., a massive USD crash). Don't look for unique setups; just join the trend on the strongest pair.
Dashboard Footer Key
The bottom of the table summarizes the current state of the market for you:
- Balanced / Rangebound: The market is quiet. Good for range trading.
- Focus: : Trade this specific pair. It is moving independently.
- Systemic Move: The whole basket is moving violently. Trade the momentum.
p.s. Suggestion - apply and use on the chart rather than an oscillator.
