Luxy UT BOT Watchlist ScannerUT BOT Watchlist Scanner - User Guide
Version: 1.0
Overview
The Luxy UT BOT Watchlist Scanner is a multi-symbol monitoring tool that combines the UT Bot (Ultimate Trailing Stop) algorithm with real-time scanning capabilities. It allows traders to monitor up to 10 symbols simultaneously for trend reversals based on ATR trailing stops, without needing to manually switch between charts.
What is UT Bot?
UT Bot is a trend-following indicator that uses ATR (Average True Range) to create a dynamic trailing stop. When price crosses above the trailing line, it signals a potential uptrend (BUY). When price crosses below, it signals a potential downtrend (SELL).
Key Features
Real-Time Multi-Symbol Scanning
Monitor up to 10 symbols for UT Bot signals without switching charts. The scanner checks each symbol on your selected timeframe and displays recent flips in a table.
Customizable Timeframe
Scan symbols on any timeframe (1m to Daily) independently of your current chart timeframe. This allows you to trade on 5-minute charts while monitoring 1-hour signals across multiple symbols.
TTL (Time-To-Live) Management
Symbols appear in the table only when they flip and remain visible for a configurable duration (default: 5 minutes). This prevents clutter and focuses attention on recent opportunities.
Real-Time Alerts
Receive TradingView alerts when any monitored symbol flips. Optional daily throttling prevents alert spam on volatile tickers.
On-Chart UT Visualization
Display the UT trailing stop line and buy/sell labels directly on your current chart for manual analysis.
Who Is This For?
Day Traders
Scan multiple stocks or forex pairs for breakout signals without missing opportunities on other charts.
Swing Traders
Monitor a portfolio of assets on higher timeframes (4H, Daily) to catch major trend reversals.
Multi-Asset Traders
Track symbols across different sectors or asset classes simultaneously (stocks, crypto, forex).
Alert-Based Traders
Set up alerts and step away from the screen. Get notified only when your monitored symbols generate signals.
Advantages Over Similar Indicators
Versus Manual Chart Switching
Eliminates the need to cycle through multiple charts manually. All signals appear in one consolidated table.
Versus Single-Symbol UT Bot
Standard UT Bot indicators only work on the current chart. This scanner extends the functionality to 10 symbols at once.
Versus Screeners
Most screeners require premium subscriptions and operate outside TradingView. This tool works entirely within your existing TradingView setup.
Performance Optimized
Smart scanning logic reduces unnecessary calculations. The scanner only processes data when the target timeframe bar is confirmed, minimizing CPU load.
How To Use
Step 1: Add To Chart
Open any chart in TradingView
Click "Indicators" and search for "Luxy UT BOT Watchlist Scanner"
Add the indicator to your chart
Step 2: Configure UT Bot Settings
Sensitivity (Key × ATR)
Controls how tight or loose the trailing stop follows price.
Recommended starting points:
Scalping (1-5m charts): 0.9 - 1.2
Day Trading (5-60m charts): 1.3 - 2.2
Swing Trading (4H-D charts): 1.7 - 3.0
Lower values = more signals, faster reactions, higher noise
Higher values = fewer signals, stronger trends, less noise
ATR Period
Number of bars for volatility calculation.
Recommended starting points:
Scalping: 5-7 bars
Day Trading: 7-14 bars
Swing Trading: 10-21 bars
Shorter periods = more responsive to recent volatility
Longer periods = smoother, less reactive to noise
Step 3: Configure Watchlist Scanner
Symbols to Scan
Enter up to 10 symbols separated by commas.
Example: AAPL, MSFT, NVDA, TSLA, AMZN
For stocks, use the ticker symbol only (not exchange prefix).
For crypto, use the full pair name (BTCUSD, ETHUSD).
For forex, use standard pairs (EURUSD, GBPUSD).
Scanner Timeframe
Select the timeframe for signal detection across all symbols.
Recommended combinations:
Chart: 5m, Scanner: 15m (day trading with confirmation)
Chart: 15m, Scanner: 1H (swing trading setup)
Chart: 1H, Scanner: 4H (position trading)
The scanner timeframe can differ from your chart timeframe. This is useful for multi-timeframe analysis.
Keep Hits For (TTL)
How long symbols remain visible in the table after a flip.
Recommended settings:
Active monitoring: 5-10 minutes
Passive monitoring: 15-30 minutes
Symbols that flip again within the TTL window reset the timer.
Step 4: Set Up Alerts (Optional)
To receive notifications when any symbol flips:
Enable "Enable Runtime Alerts" in the scanner settings
Click the TradingView alert button (clock icon)
Set condition to: "Any alert() function call"
Configure your notification preferences (popup, email, webhook)
Click "Create"
Optional: One Alert Per Symbol Per Day
Enable this to limit alerts to once per calendar day per symbol. Useful for volatile tickers that flip multiple times.
Recommended Settings By Trading Style
Scalping (1-5 minute charts)
Sensitivity: 1.0
ATR Period: 5
Scanner Timeframe: 3m or 5m
TTL: 5 minutes
Best for: High-frequency traders monitoring liquid assets
Day Trading (5-60 minute charts)
Sensitivity: 1.5
ATR Period: 10
Scanner Timeframe: 15m or 30m
TTL: 10 minutes
Best for: Intraday swing trades with moderate position holding
Swing Trading (4H-Daily charts)
Sensitivity: 2.2
ATR Period: 14
Scanner Timeframe: 4H or D
TTL: 30 minutes
Best for: Multi-day positions and trend following
Conservative Approach (Low Noise)
Sensitivity: 3.0
ATR Period: 21
Scanner Timeframe: D
TTL: 30 minutes
Best for: Long-term investors wanting only strong trend changes
Note: These are configuration suggestions, not trading advice. Always test settings on historical data and adjust based on the asset's volatility and your risk tolerance.
Understanding The Table
The watchlist table appears at your selected position (default: bottom left) and displays:
SYMBOL column: Ticker symbol that flipped
SIGNAL column: BUY (green) or SELL (red)
Symbols are sorted with the most recent flip at the bottom.
The table updates in real-time as symbols are scanned. If no symbols are currently active, the table will be empty or show only the header.
Performance Notes
How The Scanner Works
The scanner processes symbols in batches to minimize load. Each bar, it scans up to 10 symbols and checks for signal changes.
The smart timing optimization ensures scanning only occurs when the target timeframe bar is confirmed, reducing unnecessary calculations by approximately 70 percent.
Symbol Limit
The maximum is 10 symbols to maintain performance. If you need to monitor more symbols, you can add the indicator multiple times with different symbol lists.
Calculation Bars
The scanner uses 300 historical bars for accurate signal detection. This ensures proper ATR calculation even when scanning symbols different from your current chart.
Troubleshooting
Table not showing any symbols
Verify symbols are entered correctly (no extra spaces)
Check that symbols are valid for your TradingView plan
Ensure "Show Watchlist Table" is enabled
Wait for at least one symbol to generate a signal
Alerts not triggering
Confirm "Enable Runtime Alerts" is on
Verify you created an alert with condition "Any alert() function call"
Check that you're viewing the chart in real-time (not replay mode)
Invalid symbol errors
Remove any exchange prefixes (use AAPL, not NASDAQ:AAPL)
For crypto, ensure you're using the correct pair format for your exchange
Some symbols may require premium data access
Too many or too few signals
Adjust the Sensitivity value (lower = more signals, higher = fewer signals)
Try a different ATR Period
Consider changing the scanner timeframe
Important Disclaimers
This indicator is a technical analysis tool only. It does not predict future price movements or guarantee trading profits.
All suggested settings are for educational purposes and should be tested in a demo environment before live trading.
The UT Bot algorithm generates signals based on historical price data and volatility. Like all technical indicators, it can produce false signals, especially in choppy or ranging markets.
Always use proper risk management, position sizing, and additional confirmation methods when making trading decisions.
Past performance of any trading strategy or methodology is not indicative of future results.
스크립트에서 "swing trading"에 대해 찾기
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!
Canuck Trading IndicatorOverview
The Canuck Trading Indicator is a versatile, overlay-based technical analysis tool designed to assist traders in identifying potential trading opportunities across various timeframes and market conditions. By combining multiple technical indicators—such as RSI, Bollinger Bands, EMAs, VWAP, MACD, Stochastic RSI, ADX, HMA, and candlestick patterns—the indicator provides clear visual signals for bullish and bearish entries, breakouts, long-term trends, and options strategies like cash-secured puts, straddles/strangles, iron condors, and short squeezes. It also incorporates 20-day and 200-day SMAs to detect Golden/Death Crosses and price positioning relative to these moving averages. A dynamic table displays key metrics, and customizable alerts help traders stay informed of market conditions.
Key Features
Multi-Timeframe Adaptability: Automatically adjusts parameters (e.g., ATR multiplier, ADX period, HMA length) based on the chart's timeframe (minute, hourly, daily, weekly, monthly) for optimal performance.
Comprehensive Signal Generation: Identifies short-term entries, breakouts, long-term bullish trends, and options strategies using a combination of momentum, trend, volatility, and candlestick patterns.
Candlestick Pattern Detection: Recognizes bullish/bearish engulfing, hammer, shooting star, doji, and strong candles for precise entry/exit signals.
Moving Average Analysis: Plots 20-day and 200-day SMAs, detects Golden/Death Crosses, and evaluates price position relative to these averages.
Dynamic Table: Displays real-time metrics, including zone status (bullish, bearish, neutral), RSI, MACD, Stochastic RSI, short/long-term trends, candlestick patterns, ADX, ROC, VWAP slope, and MA positioning.
Customizable Alerts: Over 20 alert conditions for entries, exits, overbought/oversold warnings, and MA crosses, with actionable messages including ticker, price, and suggested strategies.
Visual Clarity: Uses distinct shapes, colors, and sizes to plot signals (e.g., green triangles for bullish entries, red triangles for bearish entries) and overlays key levels like EMA, VWAP, Bollinger Bands, support/resistance, and HMA.
Options Strategy Signals: Suggests opportunities for selling cash-secured puts, straddles/strangles, iron condors, and capitalizing on short squeezes.
How to Use
Add to Chart: Apply the indicator to any TradingView chart by selecting "Canuck Trading Indicator" from the Pine Script library.
Interpret Signals:
Bullish Signals: Green triangles (short-term entry), lime diamonds (breakout), blue circles (long-term entry).
Bearish Signals: Red triangles (short-term entry), maroon diamonds (breakout).
Options Strategies: Purple squares (cash-secured puts), yellow circles (straddles/strangles), orange crosses (iron condors), white arrows (short squeezes).
Exits: X-cross shapes in corresponding colors indicate exit signals.
Monitor: Gray circles suggest holding cash or monitoring for setups.
Review Table: Check the top-right table for real-time metrics, including zone status, RSI, MACD, trends, and MA positioning.
Set Alerts: Configure alerts for specific signals (e.g., "Short-Term Bullish Entry" or "Golden Cross") to receive notifications via TradingView.
Adjust Inputs: Customize input parameters (e.g., RSI period, EMA length, ATR period) to suit your trading style or market conditions.
Input Parameters
The indicator offers a wide range of customizable inputs to fine-tune its behavior:
RSI Period (default: 14): Length for RSI calculation.
RSI Bullish Low/High (default: 35/70): RSI thresholds for bullish signals.
RSI Bearish High (default: 65): RSI threshold for bearish signals.
EMA Period (default: 15): Main EMA length (15 for day trading, 50 for swing).
Short/Long EMA Length (default: 3/20): For momentum oscillator.
T3 Smoothing Length (default: 5): Smooths momentum signals.
Long-Term EMA/RSI Length (default: 20/15): For long-term trend analysis.
Support/Resistance Lookback (default: 5): Periods for support/resistance levels.
MACD Fast/Slow/Signal (default: 12/26/9): MACD parameters.
Bollinger Bands Period/StdDev (default: 15/2): BB settings.
Stochastic RSI Period/Smoothing (default: 14/3/3): Stochastic RSI settings.
Uptrend/Short-Term/Long-Term Lookback (default: 2/2/5): Candles for trend detection.
ATR Period (default: 14): For volatility and price targets.
VWAP Sensitivity (default: 0.1%): Threshold for VWAP-based signals.
Volume Oscillator Period (default: 14): For volume surge detection.
Pattern Detection Threshold (default: 0.3%): Sensitivity for candlestick patterns.
ROC Period (default: 3): Rate of change for momentum.
VWAP Slope Period (default: 5): For VWAP trend analysis.
TradingView Publishing Compliance
Originality: The Canuck Trading Indicator is an original script, combining multiple technical indicators and custom logic to provide unique trading signals. It does not replicate existing public scripts.
No Guaranteed Profits: This indicator is a tool for technical analysis and does not guarantee profits. Trading involves risks, and users should conduct their own research and risk management.
Clear Instructions: The description and usage guide are detailed and accessible, ensuring users understand how to apply the indicator effectively.
No External Dependencies: The script uses only built-in Pine Script functions (e.g., ta.rsi, ta.ema, ta.vwap) and requires no external libraries or data sources.
Performance: The script is optimized for performance, using efficient calculations and adaptive parameters to minimize lag on various timeframes.
Visual Clarity: Signals are plotted with distinct shapes and colors, and the table provides a concise summary of market conditions, enhancing usability.
Limitations and Risks
Market Conditions: The indicator may generate false signals in choppy or low-liquidity markets. Always confirm signals with additional analysis.
Timeframe Sensitivity: Performance varies by timeframe; test settings on your preferred chart (e.g., 5-minute for day trading, daily for swing trading).
Risk Management: Use stop-losses and position sizing to manage risk, as suggested in alert messages (e.g., "Stop -20%").
Options Trading: Options strategies (e.g., straddles, iron condors) carry unique risks; consult a financial advisor before trading.
Feedback and Support
For questions, suggestions, or bug reports, please leave a comment on the TradingView script page or contact the author via TradingView. Your feedback helps improve the indicator for the community.
Disclaimer
The Canuck Trading Indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves significant risks, and past performance is not indicative of future results. Always perform your own due diligence and consult a qualified financial advisor before making trading decisions.
The SetUpps Strategy EDGE SignalThe SetUpps Trading Strategy HM-415 EDGE, DM-130 EDGE and MD-11 are price action trading signal indicators. There is no need for downloading nor installing. It is an effective signal indicator that has proven to be successful in trading. We will help you set it up within minutes so that you can start trading immediately. It works in trading most markets!
How To Use SetUpps Strategy Signals:
For a BUY, the SetUpps Signal will display a blue arrow below the candle stick facing upwards when there is a buying opportunity, a pullback or a bullish move in the market.
For a SELL, the SetUpps Signal will display a red arrow above the candle stick facing downwards when the is a selling opportunity, a pullback or a bearish move in the market.
The indicator works best in at confluence points:
1. A Trend Line
2. A Support or Resistant Level
3. Supply or Demand Zone
4. Off Pivots
5. Off a Fibonacci Level
How To Set Alerts:
Click on the Alerts button on the charts
Under 'Condition', change from the currency pair displayed to 'The SetUpps Strategy EDGE Signal'
Then under 'Option' click on 'Once Per Bar'.
Make sure that the you tick the boxes that appeal to you under the 'Alert Actions' part (usually 'Notify on App' and 'Show Popup') and then click the 'Create' button at the bottom.
If you tick the 'Notify on App' box under 'Alerts Actions' the alerts would appear on your smart device if you have the Tradingview App set on the device.
Amongst many great benefits you will 1. Have the confidence to enter trades 2. Have the ability to enter trades after a pullback (something only experienced traders can spot that) and even more importantly 3. You can trade profitably with consistency even if you get stopped out a few times because the wins are usually bigger!
The SetUpps Trading Strategy signals will analyse price action automatically when there is a high probability of a profitable trade to enter.
It does work on most markets on all time charts but we will give you our recommended time frames that works best with this indicator.
The SetUpps Strategy signal is ideal for scalping, intraday and for swing trading.
This signal allows you to enter trades with confidence.
Disclaimer:
Previous performances are not an indication of any future performances. We are not investment adviser nor do we advice you on trading. All our opinions, information, analysis, prices and/or market commentary are not advice about investments. Any SetUpps™ Trading staff or partners or representatives can not warrant the completeness, accuracy or timeliness of any information we have supplied and we shall not be liable for any losses or damages, consequential or otherwise, incurred by the use of our products which may be the result of relying on the SetUpps™ Trading strategy. © 2020 SetUpps™ Trading.
The SetUpps™ Trading indicator is built for use on Tradingview. SetUpps™ Trading is not part of Tradingview.
Auto Range DetectorAuto Range Detector
Overview
The Auto Range Detector is a Pine Script v6 indicator for TradingView, designed to identify price consolidation ranges and detect breakouts and fakeouts. It overlays dynamic and verified range boxes, highlighting zones based on inside candles, and includes real-time fakeout markers and hypothetical range marks. Custom fakeout verification reduces false signals by validating reentries in real-time. With customizable settings, this indicator is commonly used for studying range-based breakouts and reversals in any market.
How It Works
The indicator detects consolidation ranges by counting candles (default: minimum 3) within a user-defined lookback period (default: 20 bars) using TradingView’s ta.highest and ta.lowest functions—focusing on inside bars to capture true consolidation without noise. Dynamic boxes update in real-time to reflect the range’s high and low, colored based on the price’s position relative to the midline (bullish, bearish, or neutral). Verified ranges are locked in as boxes (up to 5 displayed), with colors illustrating breakout direction. Fakeouts are identified when price breaks out but reenters the range within a specified window (default: 3 bars), with arrow marks plotted when price verifies the fakeout direction. Hypothetical boxes illustrate ranges over a user-defined period (default: 10 bars) using real-time high/low updates.
Key Features
• Range Detection: Identifies consolidation zones based on a minimum number of inside candles.
• Fakeout Detection: Spots and verifies false breakouts within a user-defined window.
• Hypothetical Range Boxes: Illustrates hypothetical high/low ranges with dynamic updates.
• Color-Coded Visualization : Displays initial, bullish, bearish, and box markers with customizable colors.
• Breakout/Fakeout Markers: Marks hypothetical breakouts and verified fakeouts with labeled arrows.
• Customizable Settings: Adjust range length, minimum touches, fakeout window, and hypothetical period.
What It Displays
This indicator combines consolidation detection with real-time fakeout markers and hypothetical ranges, offering a unique approach to range trading. Its ability to identify and validate breakouts and reversals makes it a versatile tool for day trading, scalping, or swing trading in stocks, forex, futures, or crypto, enhancing trade precision.
Originality
This indicator is an original Pine v6 implementation using TradingView’s built-in ta.highest, ta.lowest, math.max, and math.min functions.
Common Ways People Use It
• Day traders reviewing range breakouts and fakeout reversals.
• Scalpers studying short-term consolidation zones.
• Technical analysts illustrating price ranges and market direction.
Configuration Notes
Configure the range detection length (default: 20 bars), minimum inside candles (default: 3), fakeout window (default: 3 bars), and hypothetical window (default: 10 bars). Customize box and arrow colors to suit your chart. Use verified boxes and breakout/fakeout arrows to identify commonly monitored trade setups.
Legal Disclaimer
These indicators are for informational and educational purposes only—not investment, financial, or trading advice. Past performance is not indicative of future results; trading involves high risk of loss. Provided "as is" with no warranties. Consult a qualified professional before decisions. By using, you assume all risk and agree to this disclaimer.
Rsi TrendLines with Breakouts [KoTa]### RSI TrendLines with Breakouts Indicator: Detailed User Guide
The "RSI TrendLines with Breakouts " indicator is a custom Pine Script tool designed for TradingView. It builds on the standard Relative Strength Index (RSI) by adding dynamic trendlines based on RSI pivots (highs and lows) across multiple user-defined periods. These trendlines act as support and resistance levels on the RSI chart, and the indicator detects breakouts when the RSI crosses these lines, generating potential buy (long) or sell (short) signals. It also includes overbought/oversold thresholds and optional breakout labels. Below, I'll provide a detailed explanation in English, covering how to use it, its purpose, advantages and disadvantages, example strategies, and ways to enhance strategies with other indicators.
How to Use the Indicator
- The indicator uses `max_lines_count=500` to handle a large number of lines without performance issues, but on very long charts, you may need to zoom in for clarity.
1. **Customizing Settings**:
The indicator has several input groups for flexibility. Access them via the gear icon next to the indicator's name on the chart.
- **RSI Settings**:
- RSI Length: Default 14. This is the period for calculating the RSI. Shorter lengths (e.g., 7-10) make it more sensitive to recent price changes; longer (e.g., 20+) smooth it out for trends.
- RSI Source: Default is close price. You can change to open, high, low, or other sources like volume-weighted for different assets.
- Overbought Level: Default 70. RSI above this suggests potential overbuying.
- Oversold Level: Default 30. RSI below this suggests potential overselling.
- **Trend Periods**:
- You can enable/disable up to 5 periods (defaults: Period 1=3, Period 2=5, Period 3=10, Period 4=20, Period 5=50). Only enabled periods will draw trendlines.
- Each period detects pivots (highs/lows) in RSI using `ta.pivothigh` and `ta.pivotlow`. Shorter periods (e.g., 3-10) capture short-term trends; longer ones (20-50) show medium-to-long-term momentum.
- Inline checkboxes allow you to toggle display for each (e.g., display_p3=true by default).
- **Color Settings**:
- Resistance/Support Color: Defaults to red for resistance (up-trendlines from RSI highs) and green for support (down-trendlines from RSI lows).
- Labels for breakouts use green for "B" (buy/long) and red for "S" (sell/short).
- **Breakout Settings**:
- Show Prev. Breakouts: If true, displays previous breakout labels (up to "Max Prev. Breakouts Label" +1, default 2+1=3).
- Show Breakouts: Separate toggles for each period (e.g., show_breakouts3). When enabled, dotted extension lines project the trendline forward, and crossovers/crossunders trigger labels like "B3" (breakout above resistance for Period 3) or "S3" (break below support).
- Note: Divergence detection is commented out in the code. If you want to enable it, uncomment the relevant sections (e.g., show_divergence input) and adjust the lookback (default 5 bars) for spotting bullish/bearish divergences between price and RSI.
2. **Interpreting the Visuals**:
- **RSI Plot**: A blue line showing the RSI value (0-100). Horizontal dashed lines at 70 (red, overbought), 30 (green, oversold), and 50 (gray, midline).
- **Trendlines**: Solid lines connecting recent RSI pivots. Green lines (support) connect lows; red lines (resistance) connect highs. Only the most recent line per direction is shown per period to avoid clutter.
- **Breakout Projections**: Dotted lines extend the current trendline forward. When RSI crosses above a red dotted resistance, a "B" label (e.g., "B1") appears above, indicating a potential bullish breakout. Crossing below a green dotted support shows an "S" label below, indicating bearish.
- **Labels**: Current breakouts are bright (green/red); previous ones fade to gray. Use these as signal alerts.
- **Alerts**: The code includes commented-out alert conditions (e.g., for breakouts or RSI crossing levels). Uncomment and set them up in TradingView's alert menu for notifications.
3. **Best Practices**:
- Use on RSI-compatible timeframes (e.g., 1H, 4H, daily) for stocks, forex, or crypto.
- Combine with price chart: Trendlines are on RSI, so check if RSI breakouts align with price action (e.g., breaking a price resistance).
- Test on historical data: Backtest signals using TradingView's replay feature.
- Avoid over-customization initially—start with defaults (Periods 3 and 5 enabled) to understand behavior.
What It Is Used For
This indicator is primarily used for **momentum-based trend analysis and breakout trading on the RSI oscillator**. Traditional RSI identifies overbought/oversold conditions, but this enhances it by drawing dynamic trendlines on RSI itself, treating RSI as a "price-like" chart for trend detection.
- **Key Purposes**:
- **Identifying Momentum Trends**: RSI trendlines show if momentum is strengthening (upward-sloping support) or weakening (downward-sloping resistance), even if price is ranging.
- **Spotting Breakouts**: Detects when RSI breaks its own support/resistance, signaling potential price reversals or continuations. For example, an RSI breakout above resistance in an oversold zone might indicate a bullish price reversal.
- **Multi-Period Analysis**: By using multiple pivot periods, it acts like a multi-timeframe tool within RSI, helping confirm short-term signals with longer-term trends.
- **Signal Generation**: Breakout labels provide entry/exit points, especially in trending markets. It's useful for swing trading, scalping, or confirming trends in larger strategies.
- **Divergence (Optional)**: If enabled, it highlights mismatches between price highs/lows and RSI, which can predict reversals (e.g., bullish divergence: price lower low, RSI higher low).
Overall, it's ideal for traders who rely on oscillators but want more visual structure, like trendline traders applying price concepts to RSI.
Advantages and Disadvantages
**Advantages**:
- **Visual Clarity**: Trendlines make RSI easier to interpret than raw numbers, helping spot support/resistance in momentum without manual drawing.
- **Multi-Period Flexibility**: Multiple periods allow analyzing short- and long-term momentum simultaneously, reducing noise from single-period RSI.
- **Breakout Signals**: Automated detection of breakouts provides timely alerts, with labels and projections for proactive trading. This can improve entry timing in volatile markets.
- **Customization**: Extensive inputs (periods, colors, breakouts) make it adaptable to different assets/timeframes. The stateful management of lines/labels prevents chart clutter.
- **Complementary to Price Action**: Enhances standard RSI by adding trend context, useful for confirming divergences or overbought/oversold trades.
- **Efficiency**: Uses efficient arrays and line management, supporting up to 500 lines for long charts without lagging TradingView.
**Disadvantages**:
- **Lagging Nature**: Based on historical pivots, signals may lag in fast-moving markets, leading to late entries. Shorter periods help but increase whipsaws.
- **False Signals**: In ranging or sideways markets, RSI trendlines can produce frequent false breakouts. It performs better in trending conditions but may underperform without filters.
- **Over-Reliance on RSI**: Ignores volume, fundamentals, or price structure—breakouts might not translate to price moves if momentum decouples from price.
- **Complexity for Beginners**: Multiple periods and settings can overwhelm new users; misconfiguration (e.g., too many periods) leads to noisy charts.
- **No Built-in Risk Management**: Signals lack stop-loss/take-profit logic; users must add these manually.
- **Divergence Limitations**: The basic (commented) divergence detection is simplistic and may miss hidden divergences or require tuning.
In summary, it's powerful for momentum traders but should be used with confirmation tools to mitigate false positives.
Example Strategies
Here are one LONG (buy) and one SHORT (sell) strategy example using the indicator. These are basic; always backtest and use risk management (e.g., 1-2% risk per trade, stop-loss at recent lows/highs).
**LONG Strategy Example: Oversold RSI Support Breakout**
- **Setup**: Use on a daily chart for stocks or crypto. Enable Periods 3 and 5 (short- and medium-term). Set oversold level to 30.
- **Entry**: Wait for RSI to be in oversold (<30). Look for a "B" breakout label (e.g., "B3" or "B5") when RSI crosses above a red resistance trendline projection. Confirm with price forming a higher low or candlestick reversal (e.g., hammer).
- **Stop-Loss**: Place below the recent price low or the RSI support level equivalent in price terms (e.g., 5-10% below entry).
- **Take-Profit**: Target RSI reaching overbought (70) or a 2:1 risk-reward ratio. Exit on a bearish RSI crossunder midline (50).
- **Example Scenario**: In a downtrending stock, RSI hits 25 and forms a support trendline. On a "B5" breakout, enter long. This captures momentum reversals after overselling.
- **Rationale**: Breakout above RSI resistance in oversold signals fading selling pressure, potential for price uptrend.
**SHORT Strategy Example: Overbought RSI Resistance Breakout**
- **Setup**: Use on a 4H chart for forex pairs. Enable Periods 10 and 20. Set overbought level to 70.
- **Entry**: Wait for RSI in overbought (>70). Enter on an "S" breakout label (e.g., "S3" or "S4") when RSI crosses below a green support trendline projection. Confirm with price showing a lower high or bearish candlestick (e.g., shooting star).
- **Stop-Loss**: Above the recent price high or RSI resistance level (e.g., 5-10% above entry).
- **Take-Profit**: Target RSI hitting oversold (30) or a 2:1 risk-reward. Exit on bullish RSI crossover midline (50).
- **Example Scenario**: In an uptrending pair, RSI peaks at 75 with a resistance trendline. On "S4" breakout, enter short. This targets momentum exhaustion after overbuying.
- **Rationale**: Break below RSI support in overbought indicates weakening buying momentum, likely price downturn.
Enhancing Strategy Validity with Other Indicators
To increase the reliability of strategies based on this indicator, combine it with complementary tools for confirmation, filtering false signals, and adding context. This creates multi-indicator strategies that reduce whipsaws and improve win rates. Focus on indicators that address RSI's weaknesses (e.g., lagging, momentum-only). Below are examples of different indicators, how to integrate them, and sample strategies.
1. **Moving Averages (e.g., SMA/EMA)**:
- **How to Use**: Overlay 50/200-period EMAs on the price chart. Use RSI breakouts only in the direction of the trend (e.g., long only if price > 200 EMA).
- **Strategy Example**: Trend-Following Long – Enter on "B" RSI breakout if price is above 200 EMA and RSI > 50. This filters reversals in uptrends. Add MACD crossover for entry timing. Advantage: Aligns momentum with price trend, reducing counter-trend trades.
2. **Volume Indicators (e.g., Volume Oscillator or OBV)**:
- **How to Use**: Require increasing volume on RSI breakouts (e.g., OBV making higher highs on bullish breakouts).
- **Strategy Example**: Volume-Confirmed Short – On "S" breakout, check if volume is rising and OBV breaks its own trendline downward. Enter short only if confirmed. This validates breakouts with real market participation, avoiding low-volume traps.
3. **Other Oscillators (e.g., MACD or Stochastic)**:
- **How to Use**: Use for divergence confirmation or overbought/oversold alignment. For instance, require Stochastic (14,3,3) to also breakout from its levels.
- **Strategy Example**: Dual-Oscillator Reversal Long – Enable divergence in the indicator. Enter on bullish RSI divergence + "B" breakout if MACD histogram flips positive. Exit on MACD bearish crossover. This strengthens reversal signals by cross-verifying momentum.
4. **Price Action Tools (e.g., Support/Resistance or Candlestick Patterns)**:
- **How to Use**: Map RSI trendlines to price levels (e.g., if RSI resistance breaks, check if price breaks a key resistance).
- **Strategy Example**: Price-Aligned Breakout Short – On "S" RSI breakout in overbought, confirm with price breaking below a drawn support line or forming a bearish engulfing candle. Use Fibonacci retracements for targets. This ensures momentum translates to price movement.
5. **Volatility Indicators (e.g., Bollinger Bands or ATR)**:
- **How to Use**: Avoid trades during low volatility (e.g., Bollinger Band squeeze) to filter ranging markets. Use ATR for dynamic stops.
- **Strategy Example**: Volatility-Filtered Long – Enter "B" breakout only if Bollinger Bands are expanding (increasing volatility) and RSI is oversold. Set stop-loss at 1.5x ATR below entry. This targets high-momentum breakouts while skipping choppy periods.
**General Tips for Building Enhanced Strategies**:
- **Layering**: Start with RSI breakout as the primary signal, add 1-2 confirmations (e.g., EMA trend + volume).
- **Backtesting**: Use TradingView's strategy tester to quantify win rates with/without additions.
- **Risk Filters**: Incorporate overall market sentiment (e.g., via VIX) or avoid trading near news events.
- **Timeframe Alignment**: Use higher timeframes for trend (e.g., daily EMA) and lower for entries (e.g., 1H RSI breakout).
- **Avoid Overloading**: Too many indicators cause paralysis; aim for synergy (e.g., trend + momentum + volume).
This indicator is a versatile tool, but success depends on context and discipline. If you need code modifications or specific backtests, provide more details!
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).
ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
[blackcat] L2 Trend LinearityOVERVIEW
The L2 Trend Linearity indicator is a sophisticated market analysis tool designed to help traders identify and visualize market trend linearity by analyzing price action relative to dynamic support and resistance zones. This powerful Pine Script indicator utilizes the Arnaud Legoux Moving Average (ALMA) algorithm to calculate weighted price calculations and generate dynamic support/resistance zones that adapt to changing market conditions. By visualizing market zones through colored candles and histograms, the indicator provides clear visual cues about market momentum and potential trading opportunities. The script generates buy/sell signals based on zone crossovers, making it an invaluable tool for both technical analysis and automated trading strategies. Whether you're a day trader, swing trader, or algorithmic trader, this indicator can help you identify market regimes, support/resistance levels, and potential entry/exit points with greater precision.
FEATURES
Dynamic Support/Resistance Zones: Calculates dynamic support (bear market zone) and resistance (bull market zone) using weighted price calculations and ALMA smoothing
Visual Market Representation: Color-coded candles and histograms provide immediate visual feedback about market conditions
Smart Signal Generation: Automatic buy/sell signals generated from zone crossovers with clear visual indicators
Customizable Parameters: Four different ALMA smoothing parameters for various timeframes and trading styles
Multi-Timeframe Compatibility: Works across different timeframes from 1-minute to weekly charts
Real-time Analysis: Provides instant feedback on market momentum and trend direction
Clear Visual Cues: Green candles indicate bullish momentum, red candles indicate bearish momentum, and white candles indicate neutral conditions
Histogram Visualization: Blue histogram shows bear market zone (below support), aqua histogram shows bull market zone (above resistance)
Signal Labels: "B" labels mark buy signals (price crosses above resistance), "S" labels mark sell signals (price crosses below support)
Overlay Functionality: Works as an overlay indicator without cluttering the chart with unnecessary elements
Highly Customizable: All parameters can be adjusted to suit different trading strategies and market conditions
HOW TO USE
Add the Indicator to Your Chart
Open TradingView and navigate to your desired trading instrument
Click on "Indicators" in the top menu and select "New"
Search for "L2 Trend Linearity" or paste the Pine Script code
Click "Add to Chart" to apply the indicator
Configure the Parameters
ALMA Length Short: Set the short-term smoothing parameter (default: 3). Lower values provide more responsive signals but may generate more false signals
ALMA Length Medium: Set the medium-term smoothing parameter (default: 5). This provides a balance between responsiveness and stability
ALMA Length Long: Set the long-term smoothing parameter (default: 13). Higher values provide more stable signals but with less responsiveness
ALMA Length Very Long: Set the very long-term smoothing parameter (default: 21). This provides the most stable support/resistance levels
Understand the Visual Elements
Green Candles: Indicate bullish momentum when price is above the bear market zone (support)
Red Candles: Indicate bearish momentum when price is below the bull market zone (resistance)
White Candles: Indicate neutral market conditions when price is between support and resistance zones
Blue Histogram: Shows bear market zone when price is below support level
Aqua Histogram: Shows bull market zone when price is above resistance level
"B" Labels: Mark buy signals when price crosses above resistance
"S" Labels: Mark sell signals when price crosses below support
Identify Market Regimes
Bullish Regime: Price consistently above resistance zone with green candles and aqua histogram
Bearish Regime: Price consistently below support zone with red candles and blue histogram
Neutral Regime: Price oscillating between support and resistance zones with white candles
Generate Trading Signals
Buy Signals: Look for price crossing above the bull market zone (resistance) with confirmation from green candles
Sell Signals: Look for price crossing below the bear market zone (support) with confirmation from red candles
Confirmation: Always wait for confirmation from candle color changes before entering trades
Optimize for Different Timeframes
Scalping: Use shorter ALMA lengths (3-5) for 1-5 minute charts
Day Trading: Use medium ALMA lengths (5-13) for 15-60 minute charts
Swing Trading: Use longer ALMA lengths (13-21) for 1-4 hour charts
Position Trading: Use very long ALMA lengths (21+) for daily and weekly charts
LIMITATIONS
Whipsaw Markets: The indicator may generate false signals in choppy, sideways markets where price oscillates rapidly between support and resistance
Lagging Nature: Like all moving average-based indicators, there is inherent lag in the calculations, which may result in delayed signals
Not a Standalone Tool: This indicator should be used in conjunction with other technical analysis tools and risk management strategies
Market Structure Dependency: Performance may vary depending on market structure and volatility conditions
Parameter Sensitivity: Different markets may require different parameter settings for optimal performance
No Volume Integration: The indicator does not incorporate volume data, which could provide additional confirmation signals
Limited Backtesting: Pine Script limitations may restrict comprehensive backtesting capabilities
Not Suitable for All Instruments: May perform differently on stocks, forex, crypto, and futures markets
Requires Confirmation: Signals should always be confirmed with other indicators or price action analysis
Not Predictive: The indicator identifies current market conditions but does not predict future price movements
NOTES
ALMA Algorithm: The indicator uses the Arnaud Legoux Moving Average (ALMA) algorithm, which is known for its excellent smoothing capabilities and reduced lag compared to traditional moving averages
Weighted Price Calculations: The bear market zone uses (2low + close) / 3, while the bull market zone uses (high + 2close) / 3, providing more weight to recent price action
Dynamic Zones: The support and resistance zones are dynamic and adapt to changing market conditions, making them more responsive than static levels
Color Psychology: The color scheme follows traditional trading psychology - green for bullish, red for bearish, and white for neutral
Signal Timing: The signals are generated on the close of each bar, ensuring they are based on complete price action
Label Positioning: Buy signals appear below the bar (red "B" label), while sell signals appear above the bar (green "S" label)
Multiple Timeframes: The indicator can be applied to multiple timeframes simultaneously for comprehensive analysis
Risk Management: Always use proper risk management techniques when trading based on indicator signals
Market Context: Consider the overall market context and trend direction when interpreting signals
Confirmation: Look for confirmation from other indicators or price action patterns before entering trades
Practice: Test the indicator on historical data before using it in live trading
Customization: Feel free to experiment with different parameter combinations to find what works best for your trading style
THANKS
Special thanks to the TradingView community and the Pine Script developers for creating such a powerful and flexible platform for technical analysis. This indicator builds upon the foundation of the ALMA algorithm and various moving average techniques developed by technical analysis pioneers. The concept of dynamic support and resistance zones has been refined over decades of market analysis, and this script represents a modern implementation of these timeless principles. We acknowledge the contributions of all traders and developers who have contributed to the evolution of technical analysis and continue to push the boundaries of what's possible with algorithmic trading tools.
Golden Duck Runner With TargetsGolden Duck Runner With Targets
Overview
The Golden Duck Runner is a comprehensive trend-following indicator designed for intraday and swing trading. It combines dual EMA analysis with pullback detection to identify high-probability entry points in trending markets.
Key Features
Core Signal Logic
Dual EMA System: Uses a fast EMA (default 18) and trend filter EMA (default 111)
Pullback Detection: Identifies when price pulls back to the fast EMA while staying above/below the trend filter
Trend Confirmation: Only generates signals in the direction of the overall trend
Visual Elements
Dynamic EMA Colors: Golden fast EMA, with trend filter changing from teal (uptrend) to orange (downtrend)
Entry Signals: Clear golden arrows marking buy/sell opportunities
Target Levels: Displays three take profit levels and stop loss with visual confirmation
Professional Dashboard: Real-time position and trend information
Risk Management
Fixed Tick-Based Targets: Consistent risk/reward ratios across all instruments
Multiple Take Profits: Three progressive profit-taking levels (30, 50, 75 ticks)
Stop Loss Protection: 36-tick stop loss with visual tracking
Position Duration Limit: Automatic closure after 20 bars if targets not reached
Alert System
Comprehensive alert notifications for:
Long and short entry signals
Individual take profit level hits (TP1, TP2, TP3)
Stop loss activation
Combined alerts for any entry or profit-taking event
How It Works
Entry Conditions
Long Signal:
Market in uptrend (Fast EMA > Trend Filter EMA)
Price pulls back below fast EMA but stays above trend filter EMA
Price closes back above fast EMA with momentum
Short Signal:
Market in downtrend (Fast EMA < Trend Filter EMA)
Price pulls back above fast EMA but stays below trend filter EMA
Price closes back below fast EMA with momentum
Exit Strategy
TP1: 30 ticks from entry (partial profit)
TP2: 50 ticks from entry (partial profit)
TP3: 75 ticks from entry (final target)
Stop Loss: 36 ticks against entry
Time Exit: 20 bars maximum hold time
Customization Options
Adjustable EMA periods for different timeframes
Configurable stop loss and take profit levels
Toggle visibility of EMAs, signals, and visual elements
Professional color scheme optimized for all chart backgrounds
Best Use Cases
Futures Trading: ES, NQ, YM, RTY with tick-based precision
Forex Pairs: Major and minor currency pairs
Crypto Markets: Bitcoin, Ethereum, and altcoins
Stock Indices: SPY, QQQ, and sector ETFs
Recommended Timeframes
Scalping: 1m, 3m, 5m charts
Intraday: 15m, 30m, 1H charts
Swing Trading: 4H, 1D charts
Educational Value
This indicator teaches traders:
Trend identification and confirmation
Pullback trading strategies
Proper risk management techniques
Multi-target profit-taking approaches
Important Notes
Not Financial Advice: This indicator is for educational and analysis purposes only
Backtesting Recommended: Test on historical data before live trading
Risk Management: Always use proper position sizing and risk controls
Market Conditions: Performance may vary in different market environments
Technical Specifications
Version: Pine Script v5
Overlay: True (plots on price chart)
Alerts: Full alert integration for automated trading systems
Performance: Optimized for real-time data processing
Compatibility: Works on all TradingView subscription levels
Disclaimer: Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. Always trade with proper risk management and never risk more than you can afford to lose.
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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Dow Theory Indicator## 🎯 Key Features of the Indicator
### 📈 Complete Implementation of Dow Theory
- Three-tier trend structure: primary trend (50 periods), secondary trend (20 periods), and minor trend (10 periods).
- Swing point analysis: automatically detects critical swing highs and lows.
- Trend confirmation mechanism: strict confirmation logic based on consecutive higher highs/higher lows or lower highs/lower lows.
- Volume confirmation: ensures price moves are supported by trading volume.
### 🕐 Flexible Timeframe Parameters
All key parameters are adjustable, making it especially suitable for U.S. equities:
Trend analysis parameters:
- Primary trend period: 20–200 (default 50; recommended 50–100 for U.S. stocks).
- Secondary trend period: 10–100 (default 20; recommended 15–30 for U.S. stocks).
- Minor trend period: 5–50 (default 10; recommended 5–15 for U.S. stocks).
Dow Theory parameters:
- Swing high/low lookback: 5–50 (default 10).
- Trend confirmation bar count: 1–10 (default 3).
- Volume confirmation period: 10–100 (default 20).
### 🇺🇸 U.S. Market Optimizations
- Session awareness: distinguishes Regular Trading Hours (9:30–16:00 EST) from pre-market and after-hours.
- Pre/post-market weighting: adjustable weighting factor for signals during extended hours.
- Earnings season filter: automatically adjusts sensitivity during earnings periods.
- U.S.-optimized default parameters.
## 🎨 Visualization
1. Trend lines: three differently colored trend lines.
2. Background fill: green (uptrend) / red (downtrend) / gray (neutral).
3. Signal markers: arrows, labels, and warning icons.
4. Swing point markers: small triangles at key turning points.
5. Info panel: real-time display of eight key metrics.
## 🚨 Alert System
- Trend turning to up/down.
- Strong bullish/bearish signals (dual confirmation).
- Volume divergence warning.
- New swing high/low formed.
## 📋 How to Use
1. Open the Pine Editor in TradingView.
2. Copy the contents of dow_theory_indicator.pine.
3. Paste and click “Add to chart.”
4. Adjust parameters based on trading style:
- Long-term investing: increase all period parameters.
- Swing trading: use the default parameters.
- Short-term trading: decrease all period parameters.
## 💡 Parameter Tips for U.S. Stocks
- Large-cap blue chips (AAPL, MSFT): primary 60–80, secondary 25–30.
- Mid-cap growth stocks: primary 40–60, secondary 18–25.
- Small-cap high-volatility stocks: primary 30–50, secondary 15–20.
RSI 3 Time FrameRSI 3 Time Frames Indicator
Overview
The RSI 3 Time Frames Indicator is designed to provide traders with a comprehensive view of the Relative Strength Index (RSI) across three different timeframes: Ripple (short-term), Wave (medium-term), and Tide (long-term). By combining insights from multiple timeframes on a single chart, traders can identify momentum, overbought/oversold conditions, and confluence zones for better decision-making.
This indicator is highly customizable, enabling you to adjust RSI timeframes, line colors, thickness, and reference levels such as oversold/overbought areas.
Features
Multi-Timeframe RSI Analysis:
Ripple RSI: Captures short-term momentum (default: 5-minute RSI) for quick entries and scalping.
Wave RSI: Provides medium-term RSI perspective (default: 15-minute RSI) for day trading setups.
Tide RSI: Gives broader trends and momentum shifts (default: 60-minute RSI) suitable for swing trading.
Key RSI Reference Levels:
Horizontal lines show critical RSI levels to help traders interpret conditions:
Oversold Zone:
20 (Oversold Extreme) → Green dotted line.
30 (Oversold) → Green dotted line.
Neutral Zone:
40 (Neutral Low) → Orange dotted line.
50 (Midpoint) → Black dotted line.
60 (Neutral High) → Orange dotted line.
Overbought Zone:
70 (Overbought) → Red dotted line.
80 (Overbought Extreme) → Red dotted line.
Customizable Options:
Adjust RSI line color, width, and timeframes to fit your trading needs.
Customize horizontal level line colors and styles (dotted, dashed, or solid).
Easy-to-Interpret Design:
All RSI lines and reference levels are visualized clearly to help you identify overbought/oversold zones, neutral levels, and overall market momentum across multiple perspectives.
Recommended Use Cases
Scalping:
Use Ripple RSI (default: 5-minute timeframe) for short-term insights into momentum-driven setups.
Day Trading:
Use Wave RSI (default: 15-minute timeframe) to analyze medium-term trends and spot entries/exits.
Swing Trading:
Use Tide RSI (default: 60-minute timeframe) for longer-term momentum shifts and confluence zones.
Multi-Timeframe Confirmation :
Look for alignment among RSI values across Ripple, Wave, and Tide to increase confidence in your trades.
How to Use the RSI 3 Time Frames Indicator
Add the Indicator to Your Chart: Import the RSI 3 Time Frames Indicator into TradingView.
Customize Settings:
Choose Ripple, Wave, and Tide RSI timeframes according to your strategy (e.g., 5-minute for short-term, 15-minute for medium-term).
Modify line colors, styles, and thickness for better clarity.
Enable/disable RSI lines or reference levels based on preference.
Interpret RSI Values Across Timeframes:
Identify overbought levels (above 70) for potential reversals.
Spot oversold levels (below 30) for buying opportunities.
Use the neutral midpoint (50) for balanced momentum, indicating neither buyers nor sellers dominate.
Combine with Other Tools:
Enhance your trading strategy by using RSI signals with price action tools like support/resistance zones, trendlines, and candlestick patterns.
Example Scenario
Let’s say you’re trading Bitcoin (BTC/USD):
Ripple RSI shows momentum building but nearing overbought (above 70).
Wave RSI confirms shorter momentum trends (above 60).
Tide RSI shows divergence as the longer timeframe RSI is falling toward oversold (below 40).
This alignment across timeframes helps you make informed decisions, such as waiting for Ripple RSI to cool off before entering a longer-term trade based on the Tide RSI oversold condition.
Disclaimer
The RSI 3 Time Frames Indicator is provided for educational and informational purposes only. It is not intended as financial advice or as a definitive trading signal. This tool should not be used in isolation for decision-making. Trading is inherently risky, and while RSI can offer valuable insights into market trends, traders should use proper risk management strategies and include other tools such as volume-based indicators, price action, fundamental research, and macroeconomic analysis in their decision-making process.
Always test any new strategies in a simulated or paper trading environment before applying them to real markets. Remember to consult with a licensed financial professional if you’re unsure whether trading is suitable for your financial situation.
Key Benefits
Enhanced flexibility with customizable RSI settings.
Clear visualization of momentum across short, medium, and long-term timeframes.
Helps traders avoid tunnel vision by providing a multi-timeframe perspective.
Final Note
The RSI 3 Time Frames Indicator is a powerful, easy-to-use tool for traders who want to leverage RSI across multiple timeframes to pinpoint high-probability setups. Customize the settings based on your strategy and use this as a companion tool for your overall trading system.
We hope you enjoy using this indicator to improve your trading and analysis! Happy trading! 😊
Session Liquidity & Sweep DetectorThe indicator is an advanced trading tool designed to give traders a complete visual and analytical overview of major market sessions. By tracking the Asia, London, and New York sessions, this indicator highlights session highs/lows, liquidity sweeps, and advanced A++ patterns to help identify high-probability trade setups.
It combines session analysis, sweep detection, and pattern recognition into a single, customizable indicator. Traders can use it for spotting breakout points, reversal setups, and areas of stop hunts or liquidity grabs.
Key Features:
1. Session Liquidity Boxes:
Automatically draws boxes representing Asia, London, and NY trading sessions on the chart.
Each session box is color-coded and fully customizable (colors, transparency, border width).
Option to display only the most recent session box, reducing chart clutter.
Helps traders visually separate trading sessions and understand session structure.
2. High/Low Sweep Detection:
Detects when price sweeps the high or low of a completed session, indicating liquidity grabs or stop-hunting behavior.
Labels are added to the chart for clear visualization:
AHS: Asia High Swept
ALS: Asia Low Swept
LHS: London High Swept
LLS: London Low Swept
Horizontal lines are drawn at swept levels to track key support/resistance points.
Sweep detection occurs only within the same trading day, preventing false signals.
3. A++ Pattern Detection:
Detects advanced Long/Short A++ patterns based on session sweep behavior:
Long A++ Pattern: Both Asia and London lows are swept, but highs remain intact.
Short A++ Pattern: Both Asia and London highs are swept, but lows remain intact.
Patterns are plotted with customizable labels to highlight potential high-probability setups.
Helps traders identify early directional bias for the trading day.
4. Customizable Visual Settings:
Box colors, sweep line colors, and label colors are fully customizable.
Label sizes can be set to “auto”, “tiny”, “small”, “normal”, “large”, or “huge”.
Sweep line width and box border width are adjustable.
Clear visualization ensures traders can analyze sessions quickly and efficiently.
5. Multi-Session Tracking:
Tracks Asia, London, and New York sessions independently.
Keeps historical session data while dynamically updating the latest session in real-time.
Allows traders to see inter-session liquidity interactions, which are key for breakout and reversal strategies.
6. Optimized for Real-Time Trading:
Updates session highs/lows bar by bar during live trading.
Works on any timeframe, making it suitable for scalping, intraday, and swing trading.
Integrates seamlessly with other indicators like FU Candle Indicator, VWAP, Order Blocks, and more for advanced strategies.
Use Cases:
Liquidity Hunting: Spot where institutional traders may be triggering stop losses or grabbing liquidity.
Breakout Analysis: Identify when price breaks through session highs/lows and confirm trade direction.
Session Pattern Trading: Use A++ patterns to anticipate strong directional moves early in the trading day.
Multi-Session Strategies: Analyze relationships between Asia, London, and NY sessions to find high-probability entries.
Scalping & Day Trading: Visualize key levels for quick trade decisions.
Ideal Users:
Forex, crypto, and futures traders who want a session-based liquidity and sweep analysis.
Traders who use high-probability patterns and breakout strategies.
Scalpers, intraday traders, and swing traders looking for clear visual cues and actionable signals.
Anyone seeking a comprehensive session overview for smarter trading decisions.
This indicator essentially combines session boxes, liquidity sweep labels (AHS, ALS, LHS, LLS), horizontal lines for swept levels, and A++ pattern detection to give traders a full view of market structure, liquidity, and potential directional bias.
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.
ADVANCED EMA RIBBON SUITE PRO [Multi-Timeframe + Alerts + Dash]🎯 ADVANCED EMA RIBBON SUITE PRO
📊 DESCRIPTION:
The most comprehensive EMA Ribbon indicator on TradingView, featuring 14 customizable
EMAs (5-200), multi-timeframe analysis, gradient ribbon visualization, smart alerts,
and a real-time dashboard. Perfect for trend following, scalping, and swing trading.
🔥 KEY FEATURES:
• 14 EMAs with Fibonacci sequence option (5, 8, 13, 21, 34, 55, 89, 144, 200)
• Multi-Timeframe (MTF) analysis - see higher timeframe trends
• Dynamic gradient ribbon with trend-based coloring
• Golden Cross & Death Cross detection with alerts
• Professional themes (Dark/Light) with 6 visual styles
• Real-time information dashboard
• Customizable transparency and colors
• Trend strength visualization
• Price position analysis
• Smart alert system for all major crossovers
📈 USE CASES:
• Trend Identification: Ribbon expansion/contraction shows trend strength
• Entry/Exit Signals: EMA crossovers provide clear trade signals
• Support/Resistance: EMAs act as dynamic S/R levels
• Multi-Timeframe Confluence: Combine timeframes for higher probability trades
• Scalping: Use faster EMAs (5-20) for quick trades
• Swing Trading: Focus on 50/200 EMAs for position trades
🎯 TRADING STRATEGIES:
1. Ribbon Squeeze: Trade breakouts when ribbon contracts
2. Golden/Death Cross: Major trend reversals at 50/200 crosses
3. Price Above/Below: Long when price above most EMAs, short when below
4. MTF Confluence: Trade when multiple timeframes align
5. Dynamic S/R: Use EMAs as trailing stop levels
⚡ OPTIMAL SETTINGS:
• Scalping: 5, 8, 13, 21 EMAs on 1-5 min charts
• Day Trading: Full ribbon on 15-60 min charts
• Swing Trading: Focus on 50, 100, 200 EMAs on daily charts
• Position Trading: Use weekly timeframe with monthly MTF
📌 KEYWORDS:
EMA, Exponential Moving Average, Ribbon, Multi-Timeframe, MTF, Golden Cross,
Death Cross, Trend Following, Scalping, Swing Trading, Dashboard, Alerts,
Support Resistance, Fibonacci, Professional, Advanced, Suite, Indicator
*Created using PineCraft AI (Link in Bio)
Mohammad - Auto TrendLinesMohammad - Auto TrendLines
Overview
An advanced automatic trendline detection system that identifies and draws both major and minor trendlines based on pivot highs and lows. This indicator uses sophisticated algorithms to detect market structure and automatically plot relevant trendlines, helping traders identify key support and resistance levels without manual chart analysis.
Key Features
Automatic Detection: Identifies pivot points and connects them to form trendlines without manual intervention
Multi-Level Analysis: Distinguishes between Major and Minor trendlines, both External and Internal
Smart Validation: Only draws trendlines that haven't been violated by price action
Comprehensive Alerts: 16 different alert conditions for breaks and reactions to trendlines
Fully Customizable: Complete control over colors, styles, widths, and display preferences for each trendline type
How It Works
The indicator uses a ZigZag algorithm with configurable pivot periods to identify significant highs and lows. It then connects these points to form trendlines, validating them against historical price action to ensure they remain relevant. The system categorizes trendlines into Major/Minor and External/Internal based on their significance in the market structure.
Use Cases
This indicator is particularly useful for:
Identifying trend continuations and potential reversals
Finding optimal entry and exit points based on trendline breaks
Setting stop-loss levels using trendline support/resistance
Confirming trade setups with multiple timeframe analysis
Automating trendline detection for systematic trading strategies
Settings/Parameters
Pivot Period: Controls the sensitivity of pivot detection (default: 5)
Display Options: Toggle visibility for each of the 8 trendline types
Style Customization: Adjust color, line style, width, and extension for each trendline
Alert Configuration: Enable/disable alerts for breaks and reactions to each trendline type
Delete Previous: Option to remove old trendlines when new ones are formed
How to Use
Add the indicator to your chart and adjust the Pivot Period based on your trading timeframe
Configure which trendline types you want to display (Major/Minor, External/Internal, Up/Down)
Set up alerts for the specific trendline interactions you want to monitor
Look for price reactions at trendlines for potential trade entries
Use trendline breaks as confirmation for trend changes
Signals
Break Alerts: Triggered when price closes beyond a trendline
React Alerts: Triggered when price touches but respects a trendline
Major External: Most significant trendlines based on major pivot points
Major Internal: Secondary major trendlines within the trend structure
Minor External: Short-term trendlines for intraday movements
Minor Internal: Smallest scale trendlines for precise entries
Trendline Types Explained
Up Trendlines: Connect ascending lows, act as support
Down Trendlines: Connect descending highs, act as resistance
External: Connect the outermost pivots
Internal: Connect pivots within the major structure
Best Timeframes
Works effectively on all timeframes:
Scalping: 1m, 5m, 15m charts
Day Trading: 15m, 1H, 4H charts
Swing Trading: 4H, Daily, Weekly charts
Position Trading: Daily, Weekly, Monthly charts
Important Notes
The indicator repaints trendlines as new pivots form - this is by design to maintain accuracy
Historical trendlines that have been broken are automatically extended to show past levels
Use multiple timeframe analysis for best results
Combine with other indicators for trade confirmation
Always use proper risk management
Alert Integration
This indicator uses the TradingFinder Alert Library for enhanced alert functionality, providing detailed notifications for all trendline interactions.
Version History
v6: Current version with full alert integration and enhanced trendline validation
Disclaimer: This indicator is for educational and informational purposes only. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management when trading.
Note: This is an overlay indicator that draws directly on your price chart. Ensure you have sufficient chart history loaded for optimal performance.
EMA 8/21 Crossover Alert IndicatorOverview of the Indicator
This is a custom Pine Script v5 indicator for TradingView titled "EMA 8/21/50 + VWAP Crossover Alert Indicator" (short title: "EMA+VWAP Cross Alert"). It's designed as an overlay indicator, meaning it plots directly on your price chart rather than in a separate pane. The primary purpose is to detect and alert on crossovers between the 8-period Exponential Moving Average (EMA) and the 21-period EMA, which can signal potential bullish or bearish momentum shifts. These are classic short-term trend reversal or continuation signals often used in trading strategies like momentum or swing trading.
To enhance analysis, it also includes:
A 50-period EMA for medium-term trend context (e.g., to confirm if the overall trend aligns with the crossover).
A Volume Weighted Average Price (VWAP) line, which provides a benchmark for the average price weighted by volume, useful for identifying intraday value areas or fair price levels.
The indicator works across all timeframes (e.g., Daily, 4H, 1H, 15M, 5M, 3M) because the calculations are based on the chart's current bars and adapt to volatility and data resolution. It's not a trading strategy (no entry/exit logic or backtesting), but an alert tool—signals are visual and can trigger notifications in TradingView. Always combine it with risk management, as crossovers can produce false signals in ranging or choppy markets.
How It Behaves Across Timeframes
Higher Timeframes (e.g., Daily/4H): Fewer crossovers, focusing on major trends. EMAs smooth out noise; VWAP might represent session averages.
Lower Timeframes (e.g., 3M/5M): More frequent signals due to sensitivity, but higher risk of whipsaws. VWAP resets per session, making it great for intraday trading.
Adaptability: All components scale with bar data—no manual adjustments needed, though tweaking inputs can optimize for specific frames.
In TradingView, you can set up these alerts to notify via popup, sound, email, SMS, or webhook (e.g., to a trading bot). Go to the chart's "Alert" button, select this indicator, and choose conditions like "Bullish Cross" or use the script's built-in alerts.
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.
Signalgo S/RSignalgo S/R
Signalgo S/R is a cutting-edge TradingView indicator engineered for traders who want to leverage support and resistance (S/R) in a way that goes far beyond traditional methods. This overview will help you understand its unique approach, inputs, entry and exit strategies, and what truly sets it apart.
How Signalgo S/R Works
Multi-Timeframe S/R Detection
Layered Analysis: Signalgo S/R continuously scans price action across a wide spectrum of timeframes, from 1 minute up to 3 months. This multi-layered approach ensures that both short-term and long-term S/R levels are dynamically tracked and updated.
Advanced Pivot Recognition: Instead of simply plotting static lines, the indicator uses a sophisticated pivot recognition system to identify only the most relevant and recent S/R levels, adapting as the market evolves.
Synchronized Structure: By aligning S/R levels across timeframes, it builds a robust market structure that highlights truly significant zones—areas where price is most likely to react.
Intelligent Breakout & Reversal Signals
Close Confirmation: The indicator only triggers a breakout or breakdown signal when price not just touches, but closes beyond a key S/R level, dramatically reducing false signals.
Multi-Timeframe Confirmation: True buy or sell signals require agreement across several timeframes, filtering out noise and improving reliability.
One-Time Event Detection: Each breakout or breakdown is recognized only once per occurrence, eliminating repetitive signals from the same event.
Inputs & User Controls
Preset Parameters:
Pivot Length: Adjusts how sensitive the S/R detection is to price swings.
Label Offset: Fine-tunes the placement of visual labels for clarity.
Trade Management Controls:
Show TP/SL Logic: Toggle to display or hide take-profit (TP) and stop-loss (SL) levels.
ATR Length & Multipliers: Adapt SL and TP distances to current volatility.
Enable Trailing Stop: Option to activate dynamic stop movement after TP1 is reached.
Entry & Exit Strategy
Entry Logic
Long (Buy) Entry: Triggered when multiple timeframes confirm a breakout above resistance, signaling strong upward momentum.
Short (Sell) Entry: Triggered when multiple timeframes confirm a breakdown below support, indicating strong downward momentum.
Exit & Trade Management
Stop Loss (SL): Automatically set based on recent volatility, always adapting to current market conditions.
Take Profits (TP1, TP2, TP3): Three profit targets are set at increasing reward multiples, allowing for partial exits or scaling out.
Trailing Stop: After the first profit target is reached, the stop loss moves to breakeven and a trailing stop is activated, locking in gains as the trade continues.
Event Markers: Each time a TP or SL is hit, a visual label is placed on the chart for full transparency.
What Separates Signalgo S/R from Traditional S/R Indicators?
True Multi-Timeframe Synchronization: Most S/R tools only look at a single timeframe or plot static levels. Signalgo S/R dynamically aligns levels across all relevant timeframes, providing a comprehensive market map.
Event-Driven, Not Static: Instead of plotting every minor swing, it intelligently filters for only the most actionable S/R levels and signals—reducing chart clutter and focusing attention on what matters.
Breakout Confirmation Logic: Requires a close beyond S/R, not just a wick, to validate breakouts or breakdowns. This greatly reduces false positives.
Automated, Adaptive Trade Management: Built-in TP/SL and trailing logic mean you get not just signals, but a full trade management suite—something rarely found in standard S/R indicators.
Visual & Alert Integration: Every signal, TP/SL event, and trailing stop is visually marked and can trigger TradingView alerts, keeping you informed in real time.
Trading Strategy Application
Scalping to Swing Trading: The multi-timeframe logic makes it suitable for all trading styles, from fast intraday moves to longer-term position trades.
Systematic, Disciplined Execution: By automating entries, exits, and risk management, Signalgo S/R helps you trade with confidence and consistency, removing emotion from the process.
Noise Reduction: The advanced filtering logic means you only see the highest-probability setups, helping you avoid common S/R “fakeouts.”
