Breakout with Alma & Slope - for high volatility playSometimes best not to overthink,
buy at line crosses ;)
NFA, DYOR
best for 15m-1Hr, high volatility FX,Gold etc
Long only when 3 conditions met:-
- Fast Alma crosses Slow Alma
-Angle Pointing UP
-ADX above 20
Short when
- aqua line below navy line
- navy line pointing down
- adx >20
EXIT
- Trailing Stop: The trade closes automatically if price hits the **Red Stepped Line** (this is your safety net that follows the price).
- Emergency Exit:** The trade closes immediately if the ALMA lines cross back in the opposite direction (Reversal).
Buscar en scripts para "Trailing stop"
Advanced FVG Detector Pro📊 Advanced FVG Detector Pro - Smart Money Analysis Tool
Overview
The Advanced FVG Detector Pro is a sophisticated Pine Script v6 indicator designed to identify and track Fair Value Gaps (FVGs) with institutional-grade precision. This tool goes beyond basic gap detection by incorporating volume analysis, smart money scoring, and adaptive filtering to help traders identify high-probability trading opportunities.
What are Fair Value Gaps?
Fair Value Gaps (FVGs) are price inefficiencies that occur when the market moves so quickly that it leaves behind an imbalance or "gap" in price action. These gaps often act as magnets for future price movement as the market seeks to fill these inefficiencies. Professional traders and institutions closely monitor FVGs as they represent areas of potential support, resistance, and high-probability trade setups.
🎯 Key Features
1. Smart Money Scoring System
Proprietary algorithm that rates each FVG on a 0-100 scale Combines gap size, volume strength, price location, and trend alignment Filter out low-quality setups by setting minimum score thresholdsFocus on institutional-grade opportunities with scores above 70
2. Advanced Volume Validation
Validates FVGs with volume analysis to reduce false signals Only displays gaps formed during significant volume periods Customizable volume multiplier for different market conditions
Visual volume strength indicators on chart
3. Flexible Mitigation Options
Full Fill: Traditional complete gap closure Midpoint Touch: More aggressive entry strategy
Partial Fill: Customizable percentage-based mitigation (10-90%) Choose the strategy that matches your trading style
4. ATR-Based Adaptive Filtering
Automatically adjusts to market volatility using Average True Range Works consistently across any instrument, timeframe, or volatility regime No manual recalibration needed when switching markets Filters out noise while capturing meaningful gaps
5. Real-Time Statistics Dashboard
Live tracking of total active FVGs Bullish vs Bearish gap count Mitigation rate percentage
Average Smart Money Score Toggle on/off based on preference
6. Professional Visual Design
Clean, customizable color schemes Optional midline display for precise entry planning
Labels showing gap type, score, and volume strength Automatic extension of active gaps
Mitigated gaps change color for easy identification
📈 How to Use
For Day Traders:
Use 5-15 minute timeframes
Set ATR Multiplier to 0.15-0.25
Enable volume validation
Focus on FVGs with scores above 65
For Swing Traders:
Use 1H-4H timeframes
Set ATR Multiplier to 0.5-1.0
Use "Midpoint Touch" mitigation
Focus on FVGs with scores above 70
For Position Traders:
Use Daily timeframe
Set ATR Multiplier to 0.75-1.5
Use "Full Fill" mitigation
Focus on FVGs with scores above 75
🔧 Customization Options
Detection Settings:
Minimum FVG size percentage filter
ATR-based size filtering
Maximum number of gaps to display
Smart Money Score minimum threshold
Volume Analysis:
Volume validation toggle
Volume multiplier adjustment
Volume moving average period
Visual volume strength background
Mitigation Control:
Choose mitigation type (Full/Midpoint/Partial)
Set partial fill percentage
Auto-remove mitigated gaps
Control how long mitigated gaps remain visible
Visual Customization:
Bullish/Bearish/Mitigated colors
Show/hide midlines
Show/hide labels
Box extension length
Statistics dashboard toggle
🎓 Trading Strategy Ideas
1. FVG Retest Strategy
Wait for price to create a high-score FVG (70+)
Enter on the first retest of the gap
Place stop loss beyond the gap
Target the opposite side of the gap or next FVG
2. Confluence Trading
Combine FVGs with support/resistance levels
Look for FVGs near key moving averages (20/50 EMA)
Higher probability when FVG aligns with trendlines
Use multiple timeframe analysis
3. Breakout Confirmation
FVGs often form during strong breakouts
High-volume FVGs confirm breakout strength
Enter on mitigation of breakout FVG
Trail stops as new FVGs form in trend direction
⚡ Performance Optimizations
Efficient memory management for smooth chart performance
Optimized calculations run only once per bar
Smart array management prevents memory leaks
Works smoothly even with 100+ active FVGs
🔔 Alert System
Customizable alerts for new bullish FVGs
Customizable alerts for new bearish FVGs
Mitigation alerts for active gaps
Frequency control to avoid alert spam
💡 Pro Tips
Multi-Timeframe Approach: Identify major FVGs on higher timeframes (Daily/4H) and use lower timeframes (15M/5M) for precise entries
Volume Confirmation: The highest probability setups occur when FVGs form with 2x+ average volume
Trend Alignment: Trade FVGs in the direction of the major trend for best results
Patience Pays: Wait for price to return to the FVG rather than chasing breakouts
Risk Management: Always use stop losses beyond the FVG boundaries
📚 Educational Value
This indicator is perfect for:
Learning to identify institutional order flow
Understanding market microstructure
Developing price action trading skills
Recognizing supply and demand imbalances
Improving entry and exit timing
⚠️ Disclaimer
This indicator is a tool for technical analysis and should not be used as the sole basis for trading decisions. Always combine with proper risk management, fundamental analysis, and your own trading plan. Past performance does not guarantee future results.
🔄 Updates & Support
Regular updates will include:
Additional filtering options
Enhanced multi-timeframe analysis
More customization features
Performance improvements
📊 Best Pairs/Markets
Works excellently on:
Forex pairs (EUR/USD, GBP/USD, etc.)
Cryptocurrency (BTC, ETH, etc.)
Stock indices (SPX, NQ, etc.)
Individual stocks
Commodities (Gold, Oil, etc.)
Version Information
Version: 1.0
Pine Script: Version 6
Type: Overlay Indicator
Max Boxes: 500
Max Lines: 500
Hyper Squeeze Sniper (Dual Side: Long + Short)Hyper Squeeze Sniper (Dual Side Strategy)
This script is a comprehensive Volatility Breakout System designed to identify and trade explosive price moves following periods of consolidation. It combines the classical "Squeeze" theory with Linear Regression Momentum, Volume Analysis, and an ATR-based Trailing Stop to filter false signals and manage risk effectively.
The script operates on a logic of "Compression -> Explosion -> Trend Following" suitable for both Long and Short positions.
🛠 Detailed Methodology (How it works)
1. The Squeeze Detection (Consolidation) The core concept relies on the relationship between Bollinger Bands (BB) and Keltner Channels (KC).
Condition: When the Bollinger Bands (Standard Deviation) contract and fall inside the Keltner Channels (ATR based), it indicates a period of extremely low volatility (The Squeeze).
Visual: The background turns Gray to indicate "Do Not Trade / Wait Mode".
2. Momentum Confirmation (Linear Regression) Instead of using standard lagging indicators, this script utilizes Linear Regression of the price deviation to determine the direction of the breakout.
If the Linear Regression Slope > 0, the bias is Bullish.
If the Linear Regression Slope < 0, the bias is Bearish.
3. Volume Validation To avoid fake breakouts, a Volume Spike filter is applied. A signal is only valid if the current volume exceeds its moving average by a defined multiplier (Default x1.2).
4. Risk Management: ATR Trailing Stop Once a trade is entered, the script calculates a dynamic Trailing Stop based on the Average True Range (ATR).
- Long: The stop line trails below the price and never moves down.
- Short: The stop line trails above the price and never moves up.
- Exit: The position is closed immediately when the price breaches this volatility-based safety line.
How to Use
1. Wait: Look for the Gray Background. This is the accumulation phase.
2. Entry:
LONG: Wait for a Green Triangle ▲ (Price breaks Upper BB + Vol Spike + Bullish Momentum).
SHORT: Wait for a Red Triangle ▼ (Price breaks Lower BB + Vol Spike + Bearish Momentum).
3. Exit: Close the position when the "X" mark appears or when candles cross the trailing safety line.
Settings
- BB Length/Mult: Adjust the sensitivity of the squeeze detection.
- Vol Spike Factor: Increase this to filter out low-volume breakouts.
- ATR Period/Mult: Adjust the trailing stop distance (Higher = Wider stop for swing trading).
able MACD Overview
Purpose: The indicator combines the traditional MACD (Moving Average Convergence Divergence) with a short-term “forecast” (projection) of MACD/histogram values to give early warning of momentum changes.
Typical outputs:
MACD line (fastEMA − slowEMA)
Signal line (EMA of MACD)
Histogram (MACD − signal)
Forecasted MACD or histogram projected N bars ahead
Optional buy/sell markers and alert conditions
Add the indicator to TradingView (Installation)
Open TradingView and the chart you want to apply the indicator to.
Click “Pine Editor” at the bottom of the chart.
Copy the contents of able_macd_forecast.pine into the Pine Editor window.
Click “Add to chart” (or Save then Add to chart). If it’s a study, it will appear on the chart below price.
If you plan to re-use the script, click Save and give it a meaningful name.
Inputs / Parameters (typical) Note: exact input names may differ in your script. Replace the names below with the script’s input labels when you inspect it.
Source: price source for calculations (close, hl2, etc.).
Fast Length: length for the fast EMA (commonly 12).
Slow Length: length for the slow EMA (commonly 26).
Signal Length: length for the MACD signal EMA (commonly 9).
Forecast Length / Horizon: how many bars ahead the script projects the MACD/histogram (e.g., 1–5).
Forecast Method / Smoothing: choice of projection method (linear regression, EMA extrapolation, simple slope * N, etc.) if available.
Histogram Thresholds: numeric thresholds to emphasize significant momentum (optional).
Show Forecast: toggle on/off the forecast plot.
Alerts On/Off toggles: enable or disable alert conditions baked into the indicator.
Visual / Style settings: colors, plot thickness, histogram style (columns/areas), show labels, show buy/sell arrows.
How the indicator is typically calculated (summary)
MACD line = EMA(source, fast) − EMA(source, slow)
Signal line = EMA(MACD line, signal length)
Histogram = MACD − Signal
Forecast = method-specific short-term projection of MACD or histogram (for example: extend the last slope forward, apply linear regression to MACD values and extrapolate N bars, or apply an additional smoothing and extend that value) Note: For exact math, I need to inspect the script; this is the typical approach.
How to read the indicator (signals & interpretation)
Bullish signal:
MACD line crossing above the signal line (MACD cross up).
Histogram turns positive (cross above zero).
Forecast shows MACD/histogram moving higher in the next N bars (if forecast is positive or trending up).
Bearish signal:
MACD line crossing below the signal line (MACD cross down).
Histogram turns negative (cross below zero).
Forecast shows MACD/histogram moving lower ahead.
Confirmations:
Use price action (higher highs/lows for bullish, lower highs/lows for bearish).
Volume or other momentum/confluence indicators (RSI, ADX).
Divergences:
Bullish divergence: price makes lower low while MACD histogram makes higher low.
Bearish divergence: price makes higher high while MACD histogram makes lower high.
Forecast behavior:
If the forecast leads the MACD cross (forecast crosses before the current MACD does), it’s an early warning.
Use caution: forecasts are prone to false signals; always confirm.
Common trading setups using this indicator
Conservative:
Wait for MACD to cross signal + histogram above zero + forecast already trending same direction.
Use stop below recent swing low (for long) or above recent swing high (for short).
Aggressive (early entry):
Enter when forecast turns positive while MACD still below signal (anticipating cross).
Use tighter stops and smaller position sizes.
Exit rules:
Opposite MACD cross, histogram flipping sign, or a target based on risk-reward.
Use trailing stop based on ATR or structure.
Example settings for different timeframes (starting points)
Scalping / 5–15 min:
Fast 8, Slow 21, Signal 5, Forecast 1–2
Intraday / 1H:
Fast 12, Slow 26, Signal 9, Forecast 2–3
Swing / 4H–Daily:
Fast 12, Slow 26, Signal 9, Forecast 3–5 Adjust based on the asset volatility and backtests.
Adding alerts (TradingView)
Click the “Alerts” button (clock icon) or press Alt + A.
In the Condition dropdown, select the indicator name (able_macd_forecast) and choose a plotted series or built-in alert condition (if the script uses alertcondition).
Common alert types:
MACD crosses Signal (Crossing)
Histogram crosses 0 (Crossing)
Forecast crosses 0 or Forecast trend change (if provided)
Message templates:
“{{ticker}}: MACD crossed above signal on {{interval}}”
“{{ticker}} Forecast positive: MACD forecast shows upward momentum”
Customize the message for your trade automation or notifications.
Configure frequency (Only once, Once per bar, or Once per bar close) — for signals like crossovers, “Once per bar close” is usually safer to avoid repainting issues. Note: If the script includes alertcondition() calls with explicit IDs/messages, use those directly — they are the most reliable for automation.
Backtesting / Strategy conversion
If this script is a study (indicator), you can:
Convert it to a strategy by adding strategy.* order calls (strategy.entry, strategy.close) using the entry/exit logic you prefer, or
Use TradingView’s “Bar Replay” to manually test signals across different markets/timeframes.
If you want, I can help convert or write a strategy wrapper that uses the indicator’s signals to place backtest trades (I’ll need the code).
Practical tips & best practices
Use higher timeframe confirmation for lower-timeframe entries (e.g., check daily MACD momentum before trading 15m signals).
Beware of choppy markets; MACD / forecast may produce whipsaws. Combine with trend filters (moving average direction, ADX).
If you rely on forecasted values, prefer alerts “on bar close” when possible to reduce false alerts from intra-bar noise.
Tune parameters for the specific asset (FX, crypto, stocks have different behavior).
Record each signal and outcome for a sample period (20–100 trades) to evaluate performance.
Troubleshooting
Indicator won’t add: verify Pine version in script header (//@version=4 or //@version=5). TradingView may reject scripts with unsupported version syntax.
Plots missing: check script inputs (Some scripts hide plots if toggles are off).
Alerts firing too often: change alert frequency to “Once per bar close” or adjust threshold values.
Forecast seems to repaint: some forecast methods can repaint (use “bar_index” or store values only on closed bars, or use non-repainting forecast methods). Ask me to inspect the script for repainting logic.
What I can do next (recommended)
If you paste the content of able_macd_forecast.pine here, I will:
Produce a precise, line-by-line usage guide mapping to the exact input names and default values.
Show the exact plotted series names and how to reference them for alerts.
Point out any repainting risks and suggest fixes.
Provide example alert messages that match the script’s alertcondition IDs (if any).
Optionally convert it into a strategy for backtesting, or add non-repainting forecast logic if needed.
Dynamic Support and Resistance with Trend LinesDynamic Support and Resistance with Trend Lines (DSRTL)
1. Introduction & Methodology
The DSRTL indicator is designed to provide a multidimensional analysis of market structure. Unlike traditional tools that rely solely on price pivots, this script combines Static Volume-based Zones with Dynamic Trend Lines to evaluate the price's position relative to critical market components.
The S/R Identification Technique
Instead of standard pivot points, DSRTL utilizes Volume Analysis to highlight areas of significant trader participation:
- Strategy A:
Matrix Climax: Identifies candles within the lookback period that are near price extremes (Highs/Lows) and coincide with significant buying or selling volume.
- Strategy B:
Volume Extremes: Detects candles with the absolute highest buy/sell volumes within the selected lookback window, creating extreme volume-based S/R zones.
- Result:
This creates Support/Resistance (S/R) zones that are validated by actual market activity, not just price geometry.
Dynamic Trend Lines
To complement the static zones, the indicator employs two adaptive channel methods:
- Pivot Span: Connects recent significant pivots for a fast, reactive trend corridor.
- 5-Point Channel: Segments the lookback period into 5 parts to perform a linear regression analysis, creating a stable and statistically significant channel.
2. Volume Calculation Methodology
Accurate S/R detection requires distinguishing Buy Volume from Sell Volume. DSRTL offers two calculation modes:
- Geometry (Source File): Estimates buy/sell volume based on the Close price's position relative to the High/Low of the candle.
Note: This is an approximation that works on all plan types as it does not require intrabar data.
- Intrabar (Precise): Analyzes historical lower-timeframe data (e.g., 15S) to calculate intrabar-based volume deltas with higher precision compared to the geometric method.
Note: This offers superior accuracy. It requires access to historical intrabar data (depending on your plan limits). For the best analytical results, use this mode if available.
3. The Smart Matrix Engine (3D Analysis)
The core of DSRTL is its dashboard, powered by the "Smart Matrix Engine." This engine evaluates the current price in a multi-layer market structure context (Static Volume Zones + Dynamic Channels + Volume Metrics).:
A. S-State (Static): Where is the price relative to the Volume S/R zones?
B. D-State (Dynamic): Where is the price relative to the Trend Channels?
How to read the Matrix Map:
The dashboard displays a 5x5 grid representing 25 possible market scenarios.
- Rows (S1-S5): Represent the Static State (S1=Breakout, S3=Mid-Range, S5=Breakdown).
- Columns (D1-D5): Represent the Dynamic State (D1=Overextended Up, D3=Neutral, D5=Overextended Down).
- Active Cell: Marked with a dot, indicating the specific intersection of price action and market structure.
4. Matrix Interpretations (The 25 Scenarios)
Below is the detailed logic for every possible state displayed on the dashboard, explaining the Title, Bias, and actionable Signal.
Section I: S1 - Static Breakout (Price > Static Resistance)
The price has cleared the static volume resistance zone.
- S1 / D1: HYPER EXTENSION
Bias: Extreme Bullish
Signal: Caution: Exhaustion Risk. Trail stops tight.
- S1 / D2: RESISTANCE CLASH
Bias: Bullish
Signal: Breakout confirmed but facing immediate dynamic resistance.
- S1 / D3: CHANNEL BREAKOUT
Bias: Strong Bullish
Signal: Ideal Trend Continuation. Look to buy dips.
- S1 / D4: SMART PULLBACK
Bias: Bullish (Pullback)
Signal: A pullback occurring after a breakout. Strong buy opportunity.
- S1 / D5: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakout is failing against dynamic structure. High Risk.
Section II: S2 - Inside Static Resistance
The price is currently testing the overhead resistance zone.
- S2 / D1: WEAK SPIKE
Bias: Neutral/Bullish
Signal: Testing resistance, but short-term overextended.
- S2 / D2: IRON FORTRESS (R)
Bias: Rejection Risk
Signal: Double Resistance (Static + Dynamic). High probability of rejection.
- S2 / D3: TESTING RES
Bias: Neutral
Signal: Consolidating at resistance. Wait for a clear break or rejection.
- S2 / D4: COMPRESSION (UP)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Resistance and Dynamic Support. Volatility imminent.
- S2 / D5: RES vs DOWN-TREND
Bias: Bearish
Signal: Strong downtrend meeting static resistance. Potential Short entry.
Section III: S3 - Mid-Range
The price is floating between significant Static Support and Resistance.
- S3 / D1: OVERBOUGHT RANGE
Bias: Rejection Risk (OB)
Signal: Overextended within the range. Potential fade (short).
- S3 / D2: RANGE HIGH LIMIT
Bias: Neutral/Bearish
Signal: At the top of the dynamic channel. Look for rejection signs.
- S3 / D3: NEUTRAL / CHOPPY
Bias: Neutral
Signal: Dead Center. Low probability environment. Avoid trading.
- S3 / D4: RANGE DIP BUY
Bias: Neutral/Bullish
Signal: At the bottom of the dynamic channel. Look for bounce signs.
- S3 / D5: WEAK RANGE (OS)
Bias: Bounce Risk (OS)
Signal: Oversold within the range. Potential fade (long).
Section IV: S4 - Inside Static Support
The price is currently testing the floor support zone.
- S4 / D1: SUP vs UP-TREND
Bias: Bullish
Signal: Strong uptrend meeting static support. Potential Long entry.
- S4 / D2: COMPRESSION (DN)
Bias: Conflict (Squeeze)
Signal: Squeezed between Static Support and Dynamic Resistance. Volatility imminent.
- S4 / D3: TESTING SUPPORT
Bias: Neutral
Signal: Consolidating at support. Wait for a bounce or breakdown.
- S4 / D4: IRON FLOOR (S)
Bias: Bounce Risk
Signal: Double Support (Static + Dynamic). High probability of a bounce.
- S4 / D5: WEAK DIP
Bias: Neutral/Bearish
Signal: Testing support, but short-term oversold.
Section V: S5 - Static Breakdown (Price < Static Support)
The price has dropped below the static volume support zone.
- S5 / D1: CONFLICT (DIV)
Bias: Conflict/Reversal
Signal: Major Divergence. Static breakdown is failing. High Risk.
- S5 / D2: BEAR PULLBACK
Bias: Bearish (Pullback)
Signal: A pullback occurring after a breakdown. Strong selling opportunity.
- S5 / D3: CHANNEL BREAKDOWN
Bias: Strong Bearish
Signal: Ideal Trend Continuation (Down). Sell rallies.
- S5 / D4: SUPPORT CLASH
Bias: Bearish
Signal: Breakdown confirmed but facing immediate dynamic support.
- S5 / D5: HYPER DROP (VOID)
Bias: Extreme Bearish
Signal: Caution: Climax risk. Trail stops for shorts.
DISCLAIMER & EDUCATIONAL PURPOSE
This indicator is strictly an educational tool designed to visualize complex market structure concepts. Its primary purpose is to help traders "bridge the gap" between academic theory and real-time market behavior by providing a visual representation of support, resistance, and volume dynamics.
Please Note:
1. Not a Trading Strategy: This script is an analytical assistant, not a standalone "Black Box" trading system. It does not generate buy or sell signals that should be followed blindly.
2. No Financial Advice: The data provided by this tool is for informational purposes only. It is not a recommendation to buy or sell any asset.
3. Risk Warning: Trading involves significant risk. Always use your own judgment, perform your own technical analysis, and use proper risk management. Do not use this tool as the sole basis for your trading decisions.
4. Data Precision & Platform Limits: The "Intrabar (Precise)" calculation mode relies on high-resolution historical data to provide exact results. Access to this specific data depth depends entirely on your platform's subscription capabilities. If your plan does not support this level of historical intrabar data, the Precise mode may have limited coverage. In that case, you should switch to "Geometry" mode for a fully populated view.
Luxy Super-Duper SuperTrend Predictor Engine and Buy/Sell signalA professional trend-following grading system that analyzes historical trend
patterns to provide statistical duration estimates using advanced similarity
matching and k-nearest neighbors analysis. Combines adaptive Supertrend with
intelligent duration statistics, multi-timeframe confluence, volume confirmation,
and quality scoring to identify high-probability setups with data-driven
target ranges across all timeframes.
Note: All duration estimates are statistical calculations based on historical data, not guarantees of future performance.
WHAT MAKES THIS DIFFERENT
Unlike traditional SuperTrend indicators that only tell you trend direction, this system answers the critical question: "What is the typical duration for trends like this?"
The Statistical Analysis Engine:
• Analyzes your chart's last 15+ completed SuperTrend trends (bullish and bearish separately)
• Uses k-nearest neighbors similarity matching to find historically similar setups
• Calculates statistical duration estimates based on current market conditions
• Learns from estimation errors and adapts over time (Advanced mode)
• Displays visual duration analysis box showing median, average, and range estimates
• Tracks Statistical accuracy with backtest statistics
Complete Trading System:
• Statistical trend duration analysis with three intelligence levels
• Adaptive Supertrend with dynamic ATR-based bands
• Multi-timeframe confluence analysis (6 timeframes: 5M to 1W)
• Volume confirmation with spike detection and momentum tracking
• Quality scoring system (0-70 points) rating each setup
• One-click preset optimization for all trading styles
• Anti-repaint guarantee on all signals and duration estimates
METHODOLOGY CREDITS
This indicator's approach is inspired by proven trading methodologies from respected market educators:
• Mark Minervini - Volatility Contraction Pattern (VCP) and pullback entry techniques
• William O'Neil - Volume confirmation principles and institutional buying patterns (CANSLIM methodology)
• Dan Zanger - Volatility expansion entries and momentum breakout strategies
Important: These are educational references only. This indicator does not guarantee any specific trading results. Always conduct your own analysis and risk management.
KEY FEATURES
1. TREND DURATION ANALYSIS SYSTEM - The Core Innovation
The statistical analysis engine is what sets this indicator apart from standard SuperTrend systems. It doesn't just identify trend changes - it provides statistical analysis of potential duration.
How It Works:
Step 1: Historical Tracking
• Automatically records every completed SuperTrend trend (duration in bars)
• Maintains separate databases for bullish trends and bearish trends
• Stores up to 15 most recent trends of each type
• Captures market conditions at each trend flip: volume ratio, ATR ratio, quality score, price distance from SuperTrend, proximity to support/resistance
Step 2: Similarity Matching (k-Nearest Neighbors)
• When new trend begins, system compares current conditions to ALL historical flips
• Calculates similarity score based on:
- Volume similarity (30% weight) - Is volume behaving similarly?
- Volatility similarity (30% weight) - Is ATR/volatility similar?
- Quality similarity (20% weight) - Is setup strength comparable?
- Distance similarity (10% weight) - Is price distance from ST similar?
- Support/Resistance proximity (10% weight) - Similar structural context?
• Selects the 15 MOST SIMILAR historical trends (not just all trends)
• This is like asking: "When conditions looked like this before, how long did trends last?"
Step 3: Statistical Analysis
• Calculates median duration (most common outcome)
• Calculates average duration (mean of similar trends)
• Determines realistic range (min to max of similar trends)
• Applies exponential weighting (recent trends weighted more heavily)
• Outputs confidence-weighted statistical estimate
Step 4: Advanced Intelligence (Advanced Mode Only)
The Advanced mode applies five sophisticated multipliers to refine estimates:
A) Market Structure Multiplier (±30%):
• Detects nearby support/resistance levels using pivot detection
• If flip occurs NEAR a key level: Estimate adjusted -30% (expect bounce/rejection)
• If flip occurs in open space: Estimate adjusted +30% (clear path for continuation)
• Uses configurable lookback period and ATR-based proximity threshold
B) Asset Type Multiplier (±40%):
• Adjusts duration estimates based on asset volatility characteristics
• Small Cap / Biotech: +40% (explosive, extended moves)
• Tech Growth: +20% (momentum-driven, longer trends)
• Blue Chip / Large Cap: 0% (baseline, steady trends)
• Dividend / Value: -20% (slower, grinding trends)
• Cyclical: Variable based on macro regime
• Crypto / High Volatility: +30% (parabolic potential)
C) Flip Strength Multiplier (±20%):
• Analyzes the QUALITY of the trend flip itself
• Strong flip (high volume + expanding ATR + quality score 60+): +20%
• Weak flip (low volume + contracting ATR + quality score under 40): -20%
• Logic: Historical data shows that powerful flips tend to be followed by longer trends
D) Error Learning Multiplier (±15%):
• Tracks Statistical accuracy over last 10 completed trends
• Calculates error ratio: (estimated duration / Actual Duration)
• If system consistently over-estimates: Apply -15% correction
• If system consistently under-estimates: Apply +15% correction
• Learns and adapts to current market regime
E) Regime Detection Multiplier (±20%):
• Analyzes last 3 trends of SAME TYPE (bull-to-bull or bear-to-bear)
• Compares recent trend durations to historical average
• If recent trends 20%+ longer than average: +20% adjustment (trending regime detected)
• If recent trends 20%+ shorter than average: -20% adjustment (choppy regime detected)
• Detects whether market is in trending or mean-reversion mode
Three analysis modes:
SIMPLE MODE - Basic Statistics
• Uses raw median of similar trends only
• No multipliers, no adjustments
• Best for: Beginners, clean trending markets
• Fastest calculations, minimal complexity
STANDARD MODE - Full Statistical Analysis
• Similarity matching with k-nearest neighbors
• Exponential weighting of recent trends
• Median, average, and range calculations
• Best for: Most traders, general market conditions
• Balance of accuracy and simplicity
ADVANCED MODE - Statistics + Intelligence
• Everything in Standard mode PLUS
• All 5 advanced multipliers (structure, asset type, flip strength, learning, regime)
• Highest Statistical accuracy in testing
• Best for: Experienced traders, volatile/complex markets
• Maximum intelligence, most adaptive
Visual Duration Analysis Box:
When a new trend begins (SuperTrend flip), a box appears on your chart showing:
• Analysis Mode (Simple / Standard / Advanced)
• Number of historical trends analyzed
• Median expected duration (most likely outcome)
• Average expected duration (mean of similar trends)
• Range (minimum to maximum from similar trends)
• Advanced multipliers breakdown (Advanced mode only)
• Backtest accuracy statistics (if available)
The box extends from the flip bar to the estimated endpoint based on historical data, giving you a visual target for trend duration. Box updates in real-time as trend progresses.
Backtest & Accuracy Tracking:
• System backtests its own duration estimates using historical data
• Shows accuracy metrics: how well duration estimates matched actual durations
• Tracks last 10 completed duration estimates separately
• Displays statistics in dashboard and duration analysis boxes
• Helps you understand statistical reliability on your specific symbol/timeframe
Anti-Repaint Guarantee:
• duration analysis boxes only appear AFTER bar close (barstate.isconfirmed)
• Historical duration estimates never disappear or change
• What you see in history is exactly what you would have seen real-time
• No future data leakage, no lookahead bias
2. INTELLIGENT PRESET CONFIGURATIONS - One-Click Optimization
Unlike indicators that require tedious parameter tweaking, this system includes professionally optimized presets for every trading style. Select your approach from the dropdown and ALL parameters auto-configure.
"AUTO (DETECT FROM TF)" - RECOMMENDED
The smartest option: automatically selects optimal settings based on your chart timeframe.
• 1m-5m charts → Scalping preset (ATR: 7, Mult: 2.0)
• 15m-1h charts → Day Trading preset (ATR: 10, Mult: 2.5)
• 2h-4h-D charts → Swing Trading preset (ATR: 14, Mult: 3.0)
• W-M charts → Position Trading preset (ATR: 21, Mult: 4.0)
Benefits:
• Zero configuration - works immediately
• Always matched to your timeframe
• Switch timeframe = automatic adjustment
• Perfect for traders who use multiple timeframes
"SCALPING (1-5M)" - Ultra-Fast Signals
Optimized for: 1-5 minute charts, high-frequency trading, quick profits
Target holding period: Minutes to 1-2 hours maximum
Best markets: High-volume stocks, major crypto pairs, active futures
Parameter Configuration:
• Supertrend: ATR 7, Multiplier 2.0 (very sensitive)
• Volume: MA 10, High 1.8x, Spike 3.0x (catches quick surges)
• Volume Momentum: AUTO-DISABLED (too restrictive for fast scalping)
• Quality minimum: 40 points (accepts more setups)
• Duration Analysis: Uses last 15 trends with heavy recent weighting
Trading Logic:
Speed over precision. Short ATR period and low multiplier create highly responsive SuperTrend. Volume momentum filter disabled to avoid missing fast moves. Quality threshold relaxed to catch more opportunities in rapid market conditions.
Signals per session: 5-15 typically
Hold time: Minutes to couple hours
Best for: Active traders with fast execution
"DAY TRADING (15M-1H)" - Balanced Approach
Optimized for: 15-minute to 1-hour charts, intraday moves, session-based trading
Target holding period: 30 minutes to 8 hours (within trading day)
Best markets: Large-cap stocks, major indices, established crypto
Parameter Configuration:
• Supertrend: ATR 10, Multiplier 2.5 (balanced)
• Volume: MA 20, High 1.5x, Spike 2.5x (standard detection)
• Volume Momentum: 5/20 periods (confirms intraday strength)
• Quality minimum: 50 points (good setups preferred)
• Duration Analysis: Balanced weighting of recent vs historical
Trading Logic:
The most balanced configuration. ATR 10 with multiplier 2.5 provides steady trend following that avoids noise while catching meaningful moves. Volume momentum confirms institutional participation without being overly restrictive.
Signals per session: 2-5 typically
Hold time: 30 minutes to full day
Best for: Part-time and full-time active traders
"SWING TRADING (4H-D)" - Trend Stability
Optimized for: 4-hour to Daily charts, multi-day holds, trend continuation
Target holding period: 2-15 days typically
Best markets: Growth stocks, sector ETFs, trending crypto, commodity futures
Parameter Configuration:
• Supertrend: ATR 14, Multiplier 3.0 (stable)
• Volume: MA 30, High 1.3x, Spike 2.2x (accumulation focus)
• Volume Momentum: 10/30 periods (trend stability)
• Quality minimum: 60 points (high-quality setups only)
• Duration Analysis: Favors consistent historical patterns
Trading Logic:
Designed for substantial trend moves while filtering short-term noise. Higher ATR period and multiplier create stable SuperTrend that won't flip on minor corrections. Stricter quality requirements ensure only strongest setups generate signals.
Signals per week: 2-5 typically
Hold time: Days to couple weeks
Best for: Part-time traders, swing style
"POSITION TRADING (D-W)" - Long-Term Trends
Optimized for: Daily to Weekly charts, major trend changes, portfolio allocation
Target holding period: Weeks to months
Best markets: Blue-chip stocks, major indices, established cryptocurrencies
Parameter Configuration:
• Supertrend: ATR 21, Multiplier 4.0 (very stable)
• Volume: MA 50, High 1.2x, Spike 2.0x (long-term accumulation)
• Volume Momentum: 20/50 periods (major trend confirmation)
• Quality minimum: 70 points (excellent setups only)
• Duration Analysis: Heavy emphasis on multi-year historical data
Trading Logic:
Conservative approach focusing on major trend changes. Extended ATR period and high multiplier create SuperTrend that only flips on significant reversals. Very strict quality filters ensure signals represent genuine long-term opportunities.
Signals per month: 1-2 typically
Hold time: Weeks to months
Best for: Long-term investors, set-and-forget approach
"CUSTOM" - Advanced Configuration
Purpose: Complete manual control for experienced traders
Use when: You understand the parameters and want specific optimization
Best for: Testing new approaches, unusual market conditions, specific instruments
Full control over:
• All SuperTrend parameters
• Volume thresholds and momentum periods
• Quality scoring weights
• analysis mode and multipliers
• Advanced features tuning
Preset Comparison Quick Reference:
Chart Timeframe: Scalping (1M-5M) | Day Trading (15M-1H) | Swing (4H-D) | Position (D-W)
Signals Frequency: Very High | High | Medium | Low
Hold Duration: Minutes | Hours | Days | Weeks-Months
Quality Threshold: 40 pts | 50 pts | 60 pts | 70 pts
ATR Sensitivity: Highest | Medium | Lower | Lowest
Time Investment: Highest | High | Medium | Lowest
Experience Level: Expert | Advanced | Intermediate | Beginner+
3. QUALITY SCORING SYSTEM (0-70 Points)
Every signal is rated in real-time across three dimensions:
Volume Confirmation (0-30 points):
• Volume Spike (2.5x+ average): 30 points
• High Volume (1.5x+ average): 20 points
• Above Average (1.0x+ average): 10 points
• Below Average: 0 points
Volatility Assessment (0-30 points):
• Expanding ATR (1.2x+ average): 30 points
• Rising ATR (1.0-1.2x average): 15 points
• Contracting/Stable ATR: 0 points
Volume Momentum (0-10 points):
• Strong Momentum (1.2x+ ratio): 10 points
• Rising Momentum (1.0-1.2x ratio): 5 points
• Weak/Neutral Momentum: 0 points
Score Interpretation:
60-70 points - EXCELLENT:
• All factors aligned
• High conviction setup
• Maximum position size (within risk limits)
• Primary trading opportunities
45-59 points - STRONG:
• Multiple confirmations present
• Above-average setup quality
• Standard position size
• Good trading opportunities
30-44 points - GOOD:
• Basic confirmations met
• Acceptable setup quality
• Reduced position size
• Wait for additional confirmation or trade smaller
Below 30 points - WEAK:
• Minimal confirmations
• Low probability setup
• Consider passing
• Only for aggressive traders in strong trends
Only signals meeting your minimum quality threshold (configurable per preset) generate alerts and labels.
4. MULTI-TIMEFRAME CONFLUENCE ANALYSIS
The system can simultaneously analyze trend alignment across 6 timeframes (optional feature):
Timeframes analyzed:
• 5-minute (scalping context)
• 15-minute (intraday momentum)
• 1-hour (day trading bias)
• 4-hour (swing context)
• Daily (primary trend)
• Weekly (macro trend)
Confluence Interpretation:
• 5-6/6 aligned - Very strong multi-timeframe agreement (highest confidence)
• 3-4/6 aligned - Moderate agreement (standard setup)
• 1-2/6 aligned - Weak agreement (caution advised)
Dashboard shows real-time alignment count with color-coding. Higher confluence typically correlates with longer, stronger trends.
5. VOLUME MOMENTUM FILTER - Institutional Money Flow
Unlike traditional volume indicators that just measure size, Volume Momentum tracks the RATE OF CHANGE in volume:
How it works:
• Compares short-term volume average (fast period) to long-term average (slow period)
• Ratio above 1.0 = Volume accelerating (money flowing IN)
• Ratio above 1.2 = Strong acceleration (institutional participation likely)
• Ratio below 0.8 = Volume decelerating (money flowing OUT)
Why it matters:
• Confirms trend with actual money flow, not just price
• Leading indicator (volume often leads price)
• Catches accumulation/distribution before breakouts
• More intuitive than complex mathematical filters
Integration with signals:
• Optional filter - can be enabled/disabled per preset
• When enabled: Only signals with rising volume momentum fire
• AUTO-DISABLED in Scalping mode (too restrictive for fast trading)
• Configurable fast/slow periods per trading style
6. ADAPTIVE SUPERTREND MULTIPLIER
Traditional SuperTrend uses fixed ATR multiplier. This system dynamically adjusts the multiplier (0.8x to 1.2x base) based on:
• Trend Strength: Price correlation over lookback period
• Volume Weight: Current volume relative to average
Benefits:
• Tighter bands in calm markets (less premature exits)
• Wider bands in volatile conditions (avoids whipsaws)
• Better adaptation to biotech, small-cap, and crypto volatility
• Optional - can be disabled for classic constant multiplier
7. VISUAL GRADIENT RIBBON
26-layer exponential gradient fill between price and SuperTrend line provides instant visual trend strength assessment:
Color System:
• Green shades - Bullish trend + volume confirmation (strongest)
• Blue shades - Bullish trend, normal volume
• Orange shades - Bearish trend + volume confirmation
• Red shades - Bearish trend (weakest)
Opacity varies based on:
• Distance from SuperTrend (farther = more opaque)
• Volume intensity (higher volume = stronger color)
The ribbon provides at-a-glance trend strength without cluttering your chart. Can be toggled on/off.
8. INTELLIGENT ALERT SYSTEM
Two-tier alert architecture for flexibility:
Automatic Alerts:
• Fire automatically on BUY and SELL signals
• Include full context: quality score, volume state, volume momentum
• One alert per bar close (alert.freq_once_per_bar_close)
• Message format: "BUY: Supertrend bullish + Quality: 65/70 | Volume: HIGH | Vol Momentum: STRONG (1.35x)"
Customizable Alert Conditions:
• Appear in TradingView's "Create Alert" dialog
• Three options: BUY Signal Only, SELL Signal Only, ANY Signal (BUY or SELL)
• Use TradingView placeholders: {{ticker}}, {{interval}}, {{close}}, {{time}}
• Fully customizable message templates
All alerts use barstate.isconfirmed - Zero repaint guarantee.
9. ANTI-REPAINT ARCHITECTURE
Every component guaranteed non-repainting:
• Entry signals: Only appear after bar close
• duration analysis boxes: Created only on confirmed SuperTrend flips
• Informative labels: Wait for bar confirmation
• Alerts: Fire once per closed bar
• Multi-timeframe data: Uses lookahead=barmerge.lookahead_off
What you see in history is exactly what you would have seen in real-time. No disappearing signals, no changed duration estimates.
HOW TO USE THE INDICATOR
QUICK START - 3 Steps to Trading:
Step 1: Select Your Trading Style
Open indicator settings → "Quick Setup" section → Trading Style Preset dropdown
Options:
• Auto (Detect from TF) - RECOMMENDED: Automatically configures based on your chart timeframe
• Scalping (1-5m) - For 1-5 minute charts, ultra-fast signals
• Day Trading (15m-1h) - For 15m-1h charts, balanced approach
• Swing Trading (4h-D) - For 4h-Daily charts, trend stability
• Position Trading (D-W) - For Daily-Weekly charts, long-term trends
• Custom - Manual configuration (advanced users only)
Choose "Auto" and you're done - all parameters optimize automatically.
Step 2: Understand the Signals
BUY Signal (Green Triangle Below Price):
• SuperTrend flipped bullish
• Quality score meets minimum threshold (varies by preset)
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
SELL Signal (Red Triangle Above Price):
• SuperTrend flipped bearish
• Quality score meets minimum threshold
• Volume confirmation present (if filter enabled)
• Volume momentum rising (if filter enabled)
• duration analysis box shows expected trend duration
Duration Analysis Box:
• Appears at SuperTrend flip (start of new trend)
• Shows median, average, and range duration estimates
• Extends to estimated endpoint based on historical data visually
• Updates mode-specific intelligence (Simple/Standard/Advanced)
Step 3: Use the Dashboard for Context
Dashboard (top-right corner) shows real-time metrics:
• Row 1 - Quality Score: Current setup rating (0-70)
• Row 2 - SuperTrend: Direction and current level
• Row 3 - Volume: Status (Spike/High/Normal/Low) with color
• Row 4 - Volatility: State (Expanding/Rising/Stable/Contracting)
• Row 5 - Volume Momentum: Ratio and trend
• Row 6 - Duration Statistics: Accuracy metrics and track record
Every cell has detailed tooltip - hover for full explanations.
SIGNAL INTERPRETATION BY QUALITY SCORE:
Excellent Setup (60-70 points):
• Quality Score: 60-70
• Volume: Spike or High
• Volatility: Expanding
• Volume Momentum: Strong (1.2x+)
• MTF Confluence (if enabled): 5-6/6
• Action: Primary trade - maximum position size (within risk limits)
• Statistical reliability: Highest - duration estimates most accurate
Strong Setup (45-59 points):
• Quality Score: 45-59
• Volume: High or Above Average
• Volatility: Rising
• Volume Momentum: Rising (1.0-1.2x)
• MTF Confluence (if enabled): 3-4/6
• Action: Standard trade - normal position size
• Statistical reliability: Good - duration estimates reliable
Good Setup (30-44 points):
• Quality Score: 30-44
• Volume: Above Average
• Volatility: Stable or Rising
• Volume Momentum: Neutral to Rising
• MTF Confluence (if enabled): 3-4/6
• Action: Cautious trade - reduced position size, wait for additional confirmation
• Statistical reliability: Moderate - duration estimates less certain
Weak Setup (Below 30 points):
• Quality Score: Below 30
• Volume: Low or Normal
• Volatility: Contracting or Stable
• Volume Momentum: Weak
• MTF Confluence (if enabled): 1-2/6
• Action: Pass or wait for improvement
• Statistical reliability: Low - duration estimates unreliable
USING duration analysis boxES FOR TRADE MANAGEMENT:
Entry Timing:
• Enter on SuperTrend flip (signal bar close)
• duration analysis box appears simultaneously
• Note the median duration - this is your expected hold time
Profit Targets:
• Conservative: Use MEDIAN duration as profit target (50% probability)
• Moderate: Use AVERAGE duration (mean of similar trends)
• Aggressive: Aim for MAX duration from range (best historical outcome)
Position Management:
• Scale out at median duration (take partial profits)
• Trail stop as trend extends beyond median
• Full exit at average duration or SuperTrend flip (whichever comes first)
• Re-evaluate if trend exceeds estimated range
analysis mode Selection:
• Simple: Clean trending markets, beginners, minimal complexity
• Standard: Most markets, most traders (recommended default)
• Advanced: Volatile markets, complex instruments, experienced traders seeking highest accuracy
Asset Type Configuration (Advanced Mode):
If using Advanced analysis mode, configure Asset Type for optimal accuracy:
• Small Cap: Stocks under $2B market cap, low liquidity
• Biotech / Speculative: Clinical-stage pharma, penny stocks, high-risk
• Blue Chip / Large Cap: S&P 500, mega-cap tech, stable large companies
• Tech Growth: High-growth tech (TSLA, NVDA, growth SaaS)
• Dividend / Value: Dividend aristocrats, value stocks, utilities
• Cyclical: Energy, materials, industrials (macro-driven)
• Crypto / High Volatility: Bitcoin, altcoins, highly volatile assets
Correct asset type selection improves Statistical accuracy by 15-20%.
RISK MANAGEMENT GUIDELINES:
1. Stop Loss Placement:
Long positions:
• Place stop below recent swing low OR
• Place stop below SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level (built-in volatility adjustment)
Short positions:
• Place stop above recent swing high OR
• Place stop above SuperTrend level (whichever is tighter)
• Use 1-2 ATR distance as guideline
• Recommended: SuperTrend level
2. Position Sizing by Quality Score:
• Excellent (60-70): Maximum position size (2% risk per trade)
• Strong (45-59): Standard position size (1.5% risk per trade)
• Good (30-44): Reduced position size (1% risk per trade)
• Weak (Below 30): Pass or micro position (0.5% risk - learning trades only)
3. Exit Strategy Options:
Option A - Statistical Duration-Based Exit:
• Exit at median estimated duration (conservative)
• Exit at average estimated duration (moderate)
• Trail stop beyond average duration (aggressive)
Option B - Signal-Based Exit:
• Exit on opposite signal (SELL after BUY, or vice versa)
• Exit on SuperTrend flip (trend reversal)
• Exit if quality score drops below 30 mid-trend
Option C - Hybrid (Recommended):
• Take 50% profit at median estimated duration
• Trail stop on remaining 50% using SuperTrend as trailing level
• Full exit on SuperTrend flip or quality collapse
4. Trade Filtering:
For higher win-rate (fewer trades, better quality):
• Increase minimum quality score (try 60 for swing, 50 for day trading)
• Enable volume momentum filter (ensure institutional participation)
• Require higher MTF confluence (5-6/6 alignment)
• Use Advanced analysis mode with appropriate asset type
For more opportunities (more trades, lower quality threshold):
• Decrease minimum quality score (40 for day trading, 35 for scalping)
• Disable volume momentum filter
• Lower MTF confluence requirement
• Use Simple or Standard analysis mode
SETTINGS OVERVIEW
Quick Setup Section:
• Trading Style Preset: Auto / Scalping / Day Trading / Swing / Position / Custom
Dashboard & Display:
• Show Dashboard (ON/OFF)
• Dashboard Position (9 options: Top/Middle/Bottom + Left/Center/Right)
• Text Size (Auto/Tiny/Small/Normal/Large/Huge)
• Show Ribbon Fill (ON/OFF)
• Show SuperTrend Line (ON/OFF)
• Bullish Color (default: Green)
• Bearish Color (default: Red)
• Show Entry Labels - BUY/SELL signals (ON/OFF)
• Show Info Labels - Volume events (ON/OFF)
• Label Size (Auto/Tiny/Small/Normal/Large/Huge)
Supertrend Configuration:
• ATR Length (default varies by preset: 7-21)
• ATR Multiplier Base (default varies by preset: 2.0-4.0)
• Use Adaptive Multiplier (ON/OFF) - Dynamic 0.8x-1.2x adjustment
• Smoothing Factor (0.0-0.5) - EMA smoothing applied to bands
• Neutral Bars After Flip (0-10) - Hide ST immediately after flip
Volume Momentum:
• Enable Volume Momentum Filter (ON/OFF)
• Fast Period (default varies by preset: 3-20)
• Slow Period (default varies by preset: 10-50)
Volume Analysis:
• Volume MA Length (default varies by preset: 10-50)
• High Volume Threshold (default: 1.5x)
• Spike Threshold (default: 2.5x)
• Low Volume Threshold (default: 0.7x)
Quality Filters:
• Minimum Quality Score (0-70, varies by preset)
• Require Volume Confirmation (ON/OFF)
Trend Duration Analysis:
• Show Duration Analysis (ON/OFF) - Display duration analysis boxes
• analysis mode - Simple / Standard / Advanced
• Asset Type - 7 options (Small Cap, Biotech, Blue Chip, Tech Growth, Dividend, Cyclical, Crypto)
• Use Exponential Weighting (ON/OFF) - Recent trends weighted more
• Decay Factor (0.5-0.99) - How much more recent trends matter
• Structure Lookback (3-30) - Pivot detection period for support/resistance
• Proximity Threshold (xATR) - How close to level qualifies as "near"
• Enable Error Learning (ON/OFF) - System learns from estimation errors
• Memory Depth (3-20) - How many past errors to remember
Box Visual Settings:
• duration analysis box Border Color
• duration analysis box Background Color
• duration analysis box Text Color
• duration analysis box Border Width
• duration analysis box Transparency
Multi-Timeframe (Optional Feature):
• Enable MTF Confluence (ON/OFF)
• Minimum Alignment Required (0-6)
• Individual timeframe enable/disable toggles
• Custom timeframe selection options
All preset configurations override manual inputs except when "Custom" is selected.
ADVANCED FEATURES
1. Scalpel Mode (Optional)
Advanced pullback entry system that waits for healthy retracements within established trends before signaling entry:
• Monitors price distance from SuperTrend levels
• Requires pullback to configurable range (default: 30-50%)
• Ensures trend remains intact before entry signal
• Reduces whipsaw and false breakouts
• Inspired by Mark Minervini's VCP pullback entries
Best for: Swing traders and day traders seeking precision entries
Scalpers: Consider disabling for faster entries
2. Error Learning System (Advanced analysis mode Only)
The system learns from its own estimation errors:
• Tracks last 10-20 completed duration estimates (configurable memory depth)
• Calculates error ratio for each: estimated duration / Actual Duration
• If system consistently over-estimates: Applies negative correction (-15%)
• If system consistently under-estimates: Applies positive correction (+15%)
• Adapts to current market regime automatically
This self-correction mechanism improves accuracy over time as the system gathers more data on your specific symbol and timeframe.
3. Regime Detection (Advanced analysis mode Only)
Automatically detects whether market is in trending or choppy regime:
• Compares last 3 trends to historical average
• Recent trends 20%+ longer → Trending regime (+20% to estimates)
• Recent trends 20%+ shorter → Choppy regime (-20% to estimates)
• Applied separately to bullish and bearish trends
Helps duration estimates adapt to changing market conditions without manual intervention.
4. Exponential Weighting
Option to weight recent trends more heavily than distant history:
• Default decay factor: 0.9
• Recent trends get higher weight in statistical calculations
• Older trends gradually decay in importance
• Rationale: Recent market behavior more relevant than old data
• Can be disabled for equal weighting
5. Backtest Statistics
System backtests its own duration estimates using historical data:
• Walks through past trends chronologically
• Calculates what duration estimate WOULD have been at each flip
• Compares to actual duration that occurred
• Displays accuracy metrics in duration analysis boxes and dashboard
• Helps assess statistical reliability on your specific chart
Note: Backtest uses only data available AT THE TIME of each historical flip (no lookahead bias).
TECHNICAL SPECIFICATIONS
• Pine Script Version: v6
• Indicator Type: Overlay (draws on price chart)
• Max Boxes: 500 (for duration analysis box storage)
• Max Bars Back: 5000 (for comprehensive historical analysis)
• Security Calls: 1 (for MTF if enabled - optimized)
• Repainting: NO - All signals and duration estimates confirmed on bar close
• Lookahead Bias: NO - All HTF data properly offset, all duration estimates use only historical data
• Real-time Updates: YES - Dashboard and quality scores update live
• Alert Capable: YES - Both automatic alerts and customizable alert conditions
• Multi-Symbol: Works on stocks, crypto, forex, futures, indices
Performance Optimization:
• Conditional calculations (duration analysis can be disabled to reduce load)
• Efficient array management (circular buffers for trend storage)
• Streamlined gradient rendering (26 layers, can be toggled off)
• Smart label cooldown system (prevents label spam)
• Optimized similarity matching (analyzes only relevant trends)
Data Requirements:
• Minimum 50-100 bars for initial duration analysis (builds historical database)
• Optimal: 500+ bars for robust statistical analysis
• Longer history = more accurate duration estimates
• Works on any timeframe from 1 minute to monthly
KNOWN LIMITATIONS
• Trending Markets Only: Performs best in clear trends. May generate false signals in choppy/sideways markets (use quality score filtering and regime detection to mitigate)
• Lagging Nature: Like all trend-following systems, signals occur AFTER trend establishment, not at exact tops/bottoms. Use duration analysis boxes to set realistic profit targets.
• Initial Learning Period: Duration analysis system requires 10-15 completed trends to build reliable historical database. Early duration estimates less accurate (first few weeks on new symbol/timeframe).
• Visual Load: 26-layer gradient ribbon may slow performance on older devices. Disable ribbon if experiencing lag.
• Statistical accuracy Variables: Duration estimates are statistical estimates, not guarantees. Accuracy varies by:
- Market regime (trending vs choppy)
- Asset volatility characteristics
- Quality of historical pattern matches
- Timeframe traded (higher TF = more reliable)
• Not Best Suitable For:
- Ultra-short-term scalping (sub-1-minute charts)
- Mean-reversion strategies (designed for trend-following)
- Range-bound trading (requires trending conditions)
- News-driven spikes (estimates based on technical patterns, not fundamentals)
FREQUENTLY ASKED QUESTIONS
Q: Does this indicator repaint?
A: Absolutely not. All signals, duration analysis boxes, labels, and alerts use barstate.isconfirmed checks. They only appear after the bar closes. What you see in history is exactly what you would have seen in real-time. Zero repaint guarantee.
Q: How accurate are the trend duration estimates?
A: Accuracy varies by mode, market conditions, and historical data quality:
• Simple mode: 60-70% accuracy (within ±20% of actual duration)
• Standard mode: 70-80% accuracy (within ±20% of actual duration)
• Advanced mode: 75-85% accuracy (within ±20% of actual duration)
Best accuracy achieved on:
• Higher timeframes (4H, Daily, Weekly)
• Trending markets (not choppy/sideways)
• Assets with consistent behavior (Blue Chip, Large Cap)
• After 20+ historical trends analyzed (builds robust database)
Remember: All duration estimates are statistical calculations based on historical patterns, not guarantees.
Q: Which analysis mode should I use?
A:
• Simple: Beginners, clean trending markets, want minimal complexity
• Standard: Most traders, general market conditions (RECOMMENDED DEFAULT)
• Advanced: Experienced traders, volatile/complex markets (biotech, small-cap, crypto), seeking maximum accuracy
Advanced mode requires correct Asset Type configuration for optimal results.
Q: What's the difference between the trading style presets?
A: Each preset optimizes ALL parameters for a specific trading approach:
• Scalping: Ultra-sensitive (ATR 7, Mult 2.0), more signals, shorter holds
• Day Trading: Balanced (ATR 10, Mult 2.5), moderate signals, intraday holds
• Swing Trading: Stable (ATR 14, Mult 3.0), fewer signals, multi-day holds
• Position Trading: Very stable (ATR 21, Mult 4.0), rare signals, week/month holds
Auto mode automatically selects based on your chart timeframe.
Q: Should I use Auto mode or manually select a preset?
A: Auto mode is recommended for most traders. It automatically matches settings to your timeframe and re-optimizes if you switch charts. Only use manual preset selection if:
• You want scalping settings on a 15m chart (overriding auto-detection)
• You want swing settings on a 1h chart (more conservative than auto would give)
• You're testing different approaches on same timeframe
Q: Can I use this for scalping and day trading?
A: Absolutely! The preset system is specifically designed for all trading styles:
• Select "Scalping (1-5m)" for 1-5 minute charts
• Select "Day Trading (15m-1h)" for 15m-1h charts
• Or use "Auto" mode and it configures automatically
Volume momentum filter is auto-disabled in Scalping mode for faster signals.
Q: What is Volume Momentum and why does it matter?
A: Volume Momentum compares short-term volume (fast MA) to long-term volume (slow MA). It answers: "Is money flowing into this asset faster now than historically?"
Why it matters:
• Volume often leads price (early warning system)
• Confirms institutional participation (smart money)
• No lag like price-based indicators
• More intuitive than complex mathematical filters
When the ratio is above 1.2, you have strong evidence that institutions are accumulating (bullish) or distributing (bearish).
Q: How do I set up alerts?
A: Two options:
Option 1 - Automatic Alerts:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. Choose "Any alert() function call"
4. Configure notification method (app, email, webhook)
5. You'll receive detailed alerts on every BUY and SELL signal
Option 2 - Customizable Alert Conditions:
1. Right-click on chart → Add Alert
2. Condition: Select this indicator
3. You'll see three options in dropdown:
- "BUY Signal" (long signals only)
- "SELL Signal" (short signals only)
- "ANY Signal" (both BUY and SELL)
4. Choose desired option and customize message template
5. Uses TradingView placeholders: {{ticker}}, {{close}}, {{time}}, etc.
All alerts fire only on confirmed bar close (no repaint).
Q: What is Scalpel Mode and should I use it?
A: Scalpel Mode waits for healthy pullbacks within established trends before signaling entry. It reduces whipsaws and improves entry timing.
Recommended ON for:
• Swing traders (want precision entries on pullbacks)
• Day traders (willing to wait for better prices)
• Risk-averse traders (prefer fewer but higher-quality entries)
Recommended OFF for:
• Scalpers (need immediate entries, can't wait for pullbacks)
• Momentum traders (want to enter on breakout, not pullback)
• Aggressive traders (prefer more opportunities over precision)
Q: Why do some duration estimates show wider ranges than others?
A: Range width reflects historical trend variability:
• Narrow range: Similar historical trends had consistent durations (high confidence)
• Wide range: Similar historical trends had varying durations (lower confidence)
Wide ranges often occur:
• Early in analysis (fewer historical trends to learn from)
• In volatile/choppy markets (inconsistent trend behavior)
• On lower timeframes (more noise, less consistency)
The median and average still provide useful targets even when range is wide.
Q: Can I customize the dashboard position and appearance?
A: Yes! Dashboard settings include:
• Position: 9 options (Top/Middle/Bottom + Left/Center/Right)
• Text Size: Auto, Tiny, Small, Normal, Large, Huge
• Show/Hide: Toggle entire dashboard on/off
Choose position that doesn't overlap important price action on your specific chart.
Q: Which timeframe should I trade on?
A: Depends on your trading style and time availability:
• 1-5 minute: Active scalping, requires constant monitoring
• 15m-1h: Day trading, check few times per session
• 4h-Daily: Swing trading, check once or twice daily
• Daily-Weekly: Position trading, check weekly
General principle: Higher timeframes produce:
• Fewer signals (less frequent)
• Higher quality setups (stronger confirmations)
• More reliable duration estimates (better statistical data)
• Less noise (clearer trends)
Start with Daily chart if new to trading. Move to lower timeframes as you gain experience.
Q: Does this work on all markets (stocks, crypto, forex)?
A: Yes, it works on all markets with trending characteristics:
Excellent for:
• Stocks (especially growth and momentum names)
• Crypto (BTC, ETH, major altcoins)
• Futures (indices, commodities)
• Forex majors (EUR/USD, GBP/USD, etc.)
Best results on:
• Trending markets (not range-bound)
• Liquid instruments (tight spreads, good fills)
• Volatile assets (clear trend development)
Less effective on:
• Range-bound/sideways markets
• Ultra-low volatility instruments
• Illiquid small-caps (use caution)
Configure Asset Type (in Advanced analysis mode) to match your instrument for best accuracy.
Q: How many signals should I expect per day/week?
A: Highly variable based on:
By Timeframe:
• 1-5 minute: 5-15 signals per session
• 15m-1h: 2-5 signals per day
• 4h-Daily: 2-5 signals per week
• Daily-Weekly: 1-2 signals per month
By Market Volatility:
• High volatility = more SuperTrend flips = more signals
• Low volatility = fewer flips = fewer signals
By Quality Filter:
• Higher threshold (60-70) = fewer but better signals
• Lower threshold (30-40) = more signals, lower quality
By Volume Momentum Filter:
• Enabled = Fewer signals (only volume-confirmed)
• Disabled = More signals (all SuperTrend flips)
Adjust quality threshold and filters to match your desired signal frequency.
Q: What's the difference between entry labels and info labels?
A:
Entry Labels (BUY/SELL):
• Your primary trading signals
• Based on SuperTrend flip + all confirmations (quality, volume, momentum)
• Include quality score and confirmation icons
• These are actionable entry points
Info Labels (Volume Spike):
• Additional market context
• Show volume events that may support or contradict trend
• 8-bar cooldown to prevent spam
• NOT necessarily entry points - contextual information only
Control separately: Can show entry labels without info labels (recommended for clean charts).
Q: Can I combine this with other indicators?
A: Absolutely! This works well with:
• RSI: For divergences and overbought/oversold conditions
• Support/Resistance: Confluence with key levels
• Fibonacci Retracements: Pullback targets in Scalpel Mode
• Price Action Patterns: Flags, pennants, cup-and-handle
• MACD: Additional momentum confirmation
• Bollinger Bands: Volatility context
This indicator provides trend direction and duration estimates - complement with other tools for entry refinement and additional confluence.
Q: Why did I get a low-quality signal? Can I filter them out?
A: Yes! Increase the Minimum Quality Score in settings.
If you're seeing signals with quality below your preference:
• Day Trading: Set minimum to 50
• Swing Trading: Set minimum to 60
• Position Trading: Set minimum to 70
Only signals meeting the threshold will appear. This reduces frequency but improves win-rate.
Q: How do I interpret the MTF Confluence count?
A: Shows how many of 6 timeframes agree with current trend:
• 6/6 aligned: Perfect agreement (extremely rare, highest confidence)
• 5/6 aligned: Very strong alignment (high confidence)
• 4/6 aligned: Good alignment (standard quality setup)
• 3/6 aligned: Moderate alignment (acceptable)
• 2/6 aligned: Weak alignment (caution)
• 1/6 aligned: Very weak (likely counter-trend)
Higher confluence typically correlates with longer, stronger trends. However, MTF analysis is optional - you can disable it and rely solely on quality scoring.
Q: Is this suitable for beginners?
A: Yes, but requires foundational knowledge:
You should understand:
• Basic trend-following concepts (higher highs, higher lows)
• Risk management principles (position sizing, stop losses)
• How to read candlestick charts
• What volume and volatility mean
Beginner-friendly features:
• Auto preset mode (zero configuration)
• Quality scoring (tells you signal strength)
• Dashboard tooltips (hover for explanations)
• duration analysis boxes (visual profit targets)
Recommended for beginners:
1. Start with "Auto" or "Swing Trading" preset on Daily chart
2. Use Standard Analysis Mode (not Advanced)
3. Set minimum quality to 60 (fewer but better signals)
4. Paper trade first for 2-4 weeks
5. Study methodology references (Minervini, O'Neil, Zanger)
Q: What is the Asset Type setting and why does it matter?
A: Asset Type (in Advanced analysis mode) adjusts duration estimates based on volatility characteristics:
• Small Cap: Explosive moves, extended trends (+30-40%)
• Biotech / Speculative: Parabolic potential, news-driven (+40%)
• Blue Chip / Large Cap: Baseline, steady trends (0% adjustment)
• Tech Growth: Momentum-driven, longer trends (+20%)
• Dividend / Value: Slower, grinding trends (-20%)
• Cyclical: Macro-driven, variable (±10%)
• Crypto / High Volatility: Parabolic potential (+30%)
Correct configuration improves Statistical accuracy by 15-20%. Using Blue Chip settings on a biotech stock may underestimate trend length (you'll exit too early).
Q: Can I backtest this indicator?
A: Yes! TradingView's Strategy Tester works with this indicator's signals.
To backtest:
1. Note the entry conditions (SuperTrend flip + quality threshold + filters)
2. Create a strategy script using same logic
3. Run Strategy Tester on historical data
Additionally, the indicator includes BUILT-IN duration estimate validation:
• System backtests its own duration estimates
• Shows accuracy metrics in dashboard and duration analysis boxes
• Helps assess reliability on your specific symbol/timeframe
Q: Why does Volume Momentum auto-disable in Scalping mode?
A: Scalping requires ultra-fast entries to catch quick moves. Volume Momentum filter adds friction by requiring volume confirmation before signaling, which can cause missed opportunities in rapid scalping.
Scalping preset is optimized for speed and frequency - the filter is counterproductive for that style. It remains enabled for Day Trading, Swing Trading, and Position Trading presets where patience improves results.
You can manually enable it in Custom mode if desired.
Q: How much historical data do I need for accurate duration estimates?
A:
Minimum: 50-100 bars (indicator will function but duration estimates less reliable)
Recommended: 500+ bars (robust statistical database)
Optimal: 1000+ bars (maximum Statistical accuracy)
More history = more completed trends = better pattern matching = more accurate duration estimates.
New symbols or newly-switched timeframes will have lower Statistical accuracy initially. Allow 2-4 weeks for the system to build historical database.
IMPORTANT DISCLAIMERS
No Guarantee of Profit:
This indicator is an educational tool and does not guarantee any specific trading results. All trading involves substantial risk of loss. Duration estimates are statistical calculations based on historical patterns and are not guarantees of future performance.
Past Performance:
Historical backtest results and Statistical accuracy statistics do not guarantee future performance. Market conditions change constantly. What worked historically may not work in current or future markets.
Not Financial Advice:
This indicator provides technical analysis signals and statistical duration estimates only. It is not financial, investment, or trading advice. Always consult with a qualified financial advisor before making investment decisions.
Risk Warning:
Trading stocks, options, futures, forex, and cryptocurrencies involves significant risk. You can lose all of your invested capital. Never trade with money you cannot afford to lose. Only risk capital you can lose without affecting your lifestyle.
Testing Required:
Always test this indicator on a demo account or with paper trading before risking real capital. Understand how it works in different market conditions. Verify Statistical accuracy on your specific instruments and timeframes before trusting it with real money.
User Responsibility:
You are solely responsible for your trading decisions. The developer assumes no liability for trading losses, incorrect duration estimates, software errors, or any other damages incurred while using this indicator.
Statistical Estimation Limitations:
Trend Duration estimates are statistical estimates based on historical pattern matching. They are NOT guarantees. Actual trend durations may differ significantly from duration estimates due to unforeseen news events, market regime changes, or lack of historical precedent for current conditions.
CREDITS & ACKNOWLEDGMENTS
Methodology Inspiration:
• Mark Minervini - Volatility Contraction Pattern (VCP) concepts and pullback entry techniques
• William O'Neil - Volume analysis principles and CANSLIM institutional buying patterns
• Dan Zanger - Momentum breakout strategies and volatility expansion entries
Technical Components:
• SuperTrend calculation - Classic ATR-based trend indicator (public domain)
• Statistical analysis - Standard median, average, range calculations
• k-Nearest Neighbors - Classic machine learning similarity matching concept
• Multi-timeframe analysis - Standard request.security implementation in Pine Script
For questions, feedback, or support, please comment below or send a private message.
Happy Trading!
Turtle System 1 (20/10) + N-Stop + MTF Table V7.2🐢 Description: Turtle System 1 (20/10) IndicatorThis indicator implements the original trading signals of the Turtle Trading System 1 based on the classic Donchian Channels. It incorporates a historically correct, volatility-based Trailing Stop (N-Stop) and a Multi-Timeframe (MTF) status dashboard. The script is written in Pine Script v6, optimized for performance and reliability.📊 Core Logic and ParametersThe system is a pure trend-following model, utilizing the more widely known, conservative parameters of the Turtle System 1:FunctionParameterValueDescriptionEntry$\text{Donchian Breakout}$$\mathbf{20}$Buy/Sell upon breaking the 20-day High/Low.Exit (Turtle)$\text{Donchian Breakout}$$\mathbf{10}$Close the position upon breaking the 10-day Low/High.Volatility$\mathbf{N}$ (ATR Period)$\mathbf{20}$Calculation of market volatility using the Average True Range (ATR).Stop-LossMultiplier$\mathbf{2.0} BER:SETS the initial and Trailing Stop at $\mathbf{2N}$.🛠️ Key Technical Features1. Original Turtle Trailing Stop (Section 4)The stop-loss mechanism is implemented with the historically accurate Turtle Trailing Logic. The stop is not aggressively tied to the current candle's low/high, which often causes premature exits. Instead, the stop only trails in the direction of the trend, maximizing the previous stop price against the new calculated $\text{Close} \pm 2N$:$$\text{New Trailing Stop} = \text{max}(\text{Previous Stop}, \text{Close} \pm (2 \times N))$$2. Reliable Multi-Timeframe (MTF) Status (Section 6)The indicator features a robust MTF status table.Purpose: It calculates and persistently stores the Turtle System 1 status (LONG=1, SHORT=-1, FLAT=0) for various timeframes (1H, 4H, 8H, 1D, and 1W).Method: It uses global var int variables combined with request.security(), ensuring the status is accurately maintained and updated across different bars and timeframes, providing a reliable higher-timeframe context.3. VisualizationsChannels: The 20-period (Entry) and 10-period (Exit) Donchian Channels are plotted.Stop Line: The dynamic $\mathbf{2N}$ Trailing Stop is visible as a distinct line.Signals: plotshape markers indicate Entry and Exit.MTF Table: A clean, color-coded status summary is displayed in the upper right corner.
Turtle System 2 (55/20) + N-Stop + MTF Table V7.2🐢 Description: Turtle System 2 (55/20) IndicatorThis indicator implements the trading signals of the Turtle Trading System 2 based on the classic Donchian Channels, supplemented by a historically correct, volatility-based Trailing Stop (N-Stop) and a Multi-Timeframe (MTF) status overview. The script was developed in Pine Script v6 and is optimized for performance and robustness.📊 Core Logic and ParametersThe indicator is based on the rule-based trend-following system developed by Richard Dennis and William Eckhardt, utilizing the more aggressive Entry/Exit parameters of System 2:FunctionParameterValueDescriptionEntry$\text{Donchian Breakout}$$\mathbf{55}$Buy/Sell upon breaking the 55-day High/Low.Exit (Turtle)$\text{Donchian Breakout}$$\mathbf{20}$Close the position upon breaking the 20-day Low/High.Volatility$\mathbf{N}$ (ATR Period)$\mathbf{20}$Calculation of market volatility using the Average True Range (ATR).Stop-LossMultiplier$\mathbf{2.0} BER:SETS the initial and Trailing Stop at $\mathbf{2N}$.🛠️ Technical Implementation1. Correct Trailing Stop (Section 4)In contrast to many flawed implementations, the Trailing Stop is implemented here according to the Original Turtle Logic. The stop price (current_stop_price) is not aggressively tied to the current low or high. Instead, at the close of each bar, it is only trailed in the direction of the trade (math.max for long positions) based on the formula:$$\text{New Trailing Stop} = \text{max}(\text{Previous Stop}, \text{Close} \pm (2 \times N))$$This ensures the stop is only adjusted upon sustained positive movement and is not prematurely triggered by short-term, deep price shadows.2. Reliable Multi-Timeframe (MTF) Logic (Section 6)The MTF section utilizes global var int variables (mtf_status_1h, mtf_status_D, etc.) in conjunction with the request.security() function.Purpose: Calculates and persistently stores the current Turtle System 2 status (LONG=1, SHORT=-1, FLAT=0) for the timeframes 1H, 4H, 8H, 1D, and 1W.Advantage: By persistently storing the status using the var variables, the critical error of single-update status is eliminated. The states shown in the table are reliable and accurately reflect the Turtle System's position status on the respective timeframes.3. Visual ComponentsDonchian Channels: The entry (55-period) and exit (20-period) channels are drawn with color highlighting.N-Stop Line: The dynamically calculated Trailing Stop ($\mathbf{2N}$) is displayed as a magenta line.Visual Signals: plotshape markers indicate Entry and Exit points.MTF Table: A compact status summary with color coding (Green/Red/Gray) for the higher timeframes is displayed in the upper right corner.
Smart Trail Signals NO CONDITIONSSmart Trail Signals Indicator
Overview
This is a trend-following indicator that uses a dynamic trailing stop system to identify bullish and bearish trends. It adapts to market volatility using ATR (Average True Range) and provides visual signals when the trend direction changes.
Core Components
Smart Trail System:
Calculates dynamic support (trail_up) and resistance (trail_down) levels
Adjusts trail levels based on price movement and volatility
Maintains trend direction until price crosses the opposite trail level
Key Parameters:
Length (14): Period for ATR calculation
Multiplier (2.0): Distance of trail from price relative to ATR
Sensitivity (1-5): Fine-tunes how quickly the trail adapts to price changes
How It Works
Trend Detection: Monitors whether price is above the support trail (bullish) or below the resistance trail (bearish)
Trail Movement:
In uptrends: Support trail rises with price but never decreases
In downtrends: Resistance trail falls with price but never increases
Signals: Diamond shapes appear when trend flips:
Green diamond below bar = bullish trend change
Red diamond above bar = bearish trend change
Visual Aids:
Trail line changes color (lime for uptrend, red for downtrend)
Candles colored green (bullish), red (bearish), or gray (neutral)
Best Use Cases
Identifying trend reversals on any timeframe
Following strong directional moves
Setting dynamic stop-loss levels
Works 24/7 on all instruments (stocks, crypto, forex)
RetryClaude can make mistakes. Please double-check responses. Sonnet 4.5
MTF EMA Trading SystemHere's a comprehensive description and usage guide for publishing your MTF EMA Trading System indicator on TradingView:
MTF EMA Trading System - Pro Edition
📊 Indicator Overview
The MTF EMA Trading System is an advanced multi-timeframe exponential moving average indicator designed for traders seeking high-probability setups with multiple confirmations. Unlike simple EMA crossover systems, this indicator combines trend alignment, momentum, volume analysis, and previous day confluence to generate reliable long and short signals with optimal risk-reward ratios.
✨ Key Features
1. Multi-Timeframe EMA Analysis
Configure 5 independent EMAs (default: 9, 21, 50, 100, 200)
Each EMA can pull data from ANY timeframe (5m, 15m, 1H, 4H, 1D, etc.)
Color-coded lines with customizable widths
End-of-line labels showing EMA period and timeframe (e.g., "EMA200 ")
Perfect for analyzing higher timeframe trends on lower timeframe charts
2. Advanced Signal Generation (Beyond Simple Crosses)
The system requires MULTIPLE confirmations before generating a signal:
LONG Signals Require:
✅ Price action trigger (EMA cross, bounce from key EMA, or pullback setup)
✅ Bullish EMA alignment (EMAs in proper ascending order)
✅ Volume spike confirmation (configurable threshold)
✅ RSI momentum confirmation (bullish but not overbought)
✅ Sufficient EMA separation (avoids choppy/whipsaw conditions)
✅ Price above previous day's low (confluence with support)
SHORT Signals Require:
✅ Price action trigger (EMA cross, rejection from key EMA, or pullback setup)
✅ Bearish EMA alignment (EMAs in proper descending order)
✅ Volume spike confirmation
✅ RSI momentum confirmation (bearish but not oversold)
✅ Sufficient EMA separation
✅ Price below previous day's high (confluence with resistance)
3. Real-Time Dashboard
Displays critical market conditions at a glance:
Overall trend direction (Bullish/Bearish/Neutral)
Price position relative to all EMAs
Volume status (spike or normal)
RSI momentum reading
EMA confluence strength
EMA separation quality
Current ATR value
Previous day high/low levels
Current signal status (LONG/SHORT/WAIT)
Risk-reward ratio
4. Clean Visual Design
Large, clear trade signal markers (green triangles for LONG, red triangles for SHORT)
No chart clutter - only essential information displayed
Customizable signal sizes
Professional color-coded dashboard
5. Built-In Risk Management
ATR-based calculations for stop loss placement
1:2 risk-reward ratio by default
All levels displayed in dashboard for easy reference
🎯 How to Use This Indicator
Step 1: Initial Setup
Add the indicator to your TradingView chart
Configure your preferred timeframes for each EMA:
EMA 9: Leave blank (uses chart timeframe) - Fast reaction to price
EMA 21: Leave blank or set to 15m - Key pivot level
EMA 50: Set to 1H - Intermediate trend
EMA 100: Set to 4H - Major trend filter
EMA 200: Set to 1D - Overall market bias
Adjust signal settings based on your trading style:
Conservative: Keep all confirmations enabled
Aggressive: Disable volume or momentum requirements
Scalping: Reduce min EMA separation to 0.2-0.3%
Step 2: Reading the Dashboard
Before taking any trade, check the dashboard:
Trend: Only take LONG signals in bullish trends, SHORT signals in bearish trends
Position: Confirm price is on the correct side of EMAs
Volume: Green spike = strong confirmation
RSI: Avoid extremes (>70 or <30)
Confluence: "Strong" = high probability setup
Separation: "Good" = trending market, avoid "Low" separation
Step 3: Trade Entry
For LONG Trades:
Wait for green triangle to appear below price
Verify dashboard shows:
Bullish or Neutral trend
Volume spike (preferred)
RSI between 50-70
Good separation
Enter at market or on next bar
Set stop loss at: Entry - (ATR × 2)
Set target at: Entry + (ATR × 4)
For SHORT Trades:
Wait for red triangle to appear above price
Verify dashboard shows:
Bearish or Neutral trend
Volume spike (preferred)
RSI between 30-50
Good separation
Enter at market or on next bar
Set stop loss at: Entry + (ATR × 2)
Set target at: Entry - (ATR × 4)
Step 4: Trade Management
Use the ATR values from dashboard for position sizing
Trail stops using the fastest EMA (EMA 9) as price moves in your favor
Exit partial position at 1:1 risk-reward, let remainder run to target
Exit immediately if dashboard trend changes against your position
💡 Best Practices
Timeframe Recommendations:
Scalping: 1m-5m chart with 5m, 15m, 1H, 4H, 1D EMAs
Day Trading: 5m-15m chart with 15m, 1H, 4H, 1D EMAs
Swing Trading: 1H-4H chart with 4H, 1D, 1W EMAs
Position Trading: 1D chart with 1D, 1W, 1M EMAs
Market Conditions:
Best in: Trending markets with clear direction
Avoid: Tight consolidation, low volume periods, major news events
Filter trades: Only take signals aligned with higher timeframe trend
Risk Management:
Never risk more than 1-2% per trade
Use ATR from dashboard to calculate position size
Respect the stop loss levels
Don't force trades when dashboard shows weak conditions
⚙️ Customization Options
EMA Settings (for each of 5 EMAs):
Length (period)
Timeframe (multi-timeframe capability)
Color
Line width
Show/hide toggle
Signal Settings:
Volume confirmation (on/off)
Volume spike threshold (1.0-3.0x)
Momentum confirmation (on/off)
RSI overbought/oversold levels
Minimum EMA separation percentage
ATR period and stop multiplier
Display Settings:
Show/hide EMA labels
Show/hide trade signals
Signal marker size (tiny/small/normal/large)
Show/hide dashboard
🔔 Alert Setup
The indicator includes 4 alert conditions:
LONG Signal - Fires when all long confirmations are met
SHORT Signal - Fires when all short confirmations are met
Bullish Setup - Early warning when trend aligns bullish with volume
Bearish Setup - Early warning when trend aligns bearish with volume
To set up alerts:
Right-click on chart → Add Alert
Select "MTF EMA Trading System"
Choose your desired alert condition
Configure notification method (popup, email, SMS, webhook)
📈 Performance Tips
Increase Win Rate:
Only trade in direction of higher timeframe trend
Wait for volume spike confirmation
Avoid trades during first 30 minutes and last 15 minutes of session
Skip trades when separation is "Low"
Reduce False Signals:
Increase minimum EMA separation to 0.7-1.0%
Enable all confirmation requirements
Only trade when confluence shows "Strong"
Combine with support/resistance levels
Optimize for Your Market:
Stocks: Use 9, 21, 50, 100, 200 EMAs
Forex: Consider 8, 13, 21, 55, 89 EMAs (Fibonacci)
Crypto: May need wider ATR multiplier (2.5-3.0x) for volatility
⚠️ Important Notes
This indicator is designed to reduce false signals by requiring multiple confirmations
No indicator is 100% accurate - always use proper risk management
Backtesting recommended before live trading
Market conditions change - adjust settings as needed
Works best in liquid markets with clear price action
🎓 Conclusion
The MTF EMA Trading System transforms simple moving average analysis into a sophisticated, multi-confirmation trading strategy. By combining trend alignment, momentum, volume, and confluence, it helps traders identify high-probability setups while filtering out noise and false signals. The clean interface and comprehensive dashboard make it suitable for both beginners and experienced traders across all markets and timeframes.
ATR x Trend x Volume SignalsATR x Trend x Volume Signals is a multi-factor indicator that combines volatility, trend, and volume analysis into one adaptive framework. It is designed for traders who use technical confluence and prefer clear, rule-based setups.
🎯 Purpose
This tool identifies high-probability market moments when volatility structure (ATR), momentum direction (CCI-based trend logic), and volume expansion all align. It helps filter out noise and focus on clean, actionable trade conditions.
⚙️ Structure
The indicator consists of three main analytical layers:
1️⃣ ATR Trailing Stop – calculates two adaptive ATR lines (fast and slow) that define volatility context, trend bias, and potential reversal points.
2️⃣ Trend Indicator (CCI + ATR) – uses a CCI-based logic combined with ATR smoothing to determine the dominant trend direction and reduce false flips.
3️⃣ Volume Analysis – evaluates volume deviations from their historical average using standard deviation. Bars are highlighted as medium, high, or extra-high volume depending on intensity.
💡 Signal Logic
A Buy Signal (green) appears when all of the following are true:
• The ATR (slow) line is green.
• The Trend Indicator is blue.
• A bullish candle closes above both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
A Sell Signal (red) appears when:
• The ATR (slow) line is red.
• The Trend Indicator is red.
• A bearish candle closes below both the ATR (slow) and the Trend Indicator.
• The candle shows medium, high, or extra-high volume.
Only one signal can appear per ATR trend phase. A new signal is generated only after the ATR direction changes.
❌ Exit Logic
Exit markers are shown when price crosses the slow ATR line. This behavior simulates a trailing stop exit. The exit is triggered one bar after entry to prevent same-bar exits.
⏰ Session Filter
Signals are generated only between the user-defined session start and end times (default: 14:00–18:00 chart time). This allows the trader to limit signal generation to active trading hours.
💬 Practical Use
It is recommended to trade with a fixed risk-reward ratio such as 1 : 1.5. Stop-loss placement should be beyond the slow ATR line and adjusted gradually as the trade develops.
For better confirmation, the Trend Indicator timeframe should be higher than the chart timeframe (for example: trading on 1 min → set Trend Indicator timeframe to 15 min; trading on 5 min → set to 1 hour).
🧠 Main Features
• Dual ATR volatility structure (fast and slow)
• CCI-based trend direction filtering
• Volume deviation heatmap logic
• Time-restricted signal generation
• Dynamic trailing-stop exit system
• Non-repainting logic
• Fully optimized for Pine Script v6
📊 Usage Tip
Best results are achieved when combining this indicator with additional technical context such as support-resistance, higher-timeframe confirmation, or market structure analysis.
📈 Credits
Inspired by:
• ATR Trailing Stop by Ceyhun
• Trend Magic by Kivanc Ozbilgic
• Heatmap Volume by xdecow
TrendShield Pro | DinkanWorldSmart Trailing Trend System Powered by EMA + ATR
TrendShield Pro is a powerful trend detection and trailing stop indicator designed for traders who rely on pure price movement and volatility tracking.
It dynamically adapts to market conditions using a combination of EMA (Exponential Moving Average) and ATR (Average True Range) to identify the active trend and place a visual trailing stop line.
🔍 How It Works
TrendShield Pro combines trend direction and volatility to create a self-adjusting trailing system:
EMA (Exponential Moving Average):
Smooths price fluctuations and identifies the overall market bias.
ATR (Average True Range):
Measures volatility to determine how far the trailing stop should follow the trend.
Dynamic Bands:
Two invisible thresholds are formed — up and down — around the EMA using the ATR and your chosen Factor value.
Trailing Logic:
When the EMA is rising, the Trailing Stop (TUp) locks in higher lows.
When the EMA is falling, the Trailing Stop (TDown) locks in lower highs.
The indicator switches trend automatically based on price crossing these trailing levels.
🧭 Visuals & Features
Green Trailing Line (Demand Trend): Indicates an active bullish trend.
Red Trailing Line (Supply Trend): Indicates an active bearish trend.
Arrow Signals:
🟢 Up Arrow → Bullish Trend Reversal
🔴 Down Arrow → Bearish Trend Reversal
Diamond Markers: Show points where the trailing line shifts, marking dynamic volatility changes.
⚙️ Inputs
Input Description
EMA Period Length of the Exponential Moving Average
ATR Period Period used for Average True Range calculation
Factor Multiplier for ATR-based volatility expansion
Kalman Filter [DCAUT]█ Kalman Filter
📊 ORIGINALITY & INNOVATION
The Kalman Filter represents an important adaptation of aerospace signal processing technology to financial market analysis. Originally developed by Rudolf E. Kalman in 1960 for navigation and guidance systems, this implementation brings the algorithm's noise reduction capabilities to price trend analysis.
This implementation addresses a common challenge in technical analysis: the trade-off between smoothness and responsiveness. Traditional moving averages must choose between being smooth (with increased lag) or responsive (with increased noise). The Kalman Filter improves upon this limitation through its recursive estimation approach, which continuously balances historical trend information with current price data based on configurable noise parameters.
The key advancement lies in the algorithm's adaptive weighting mechanism. Rather than applying fixed weights to historical data like conventional moving averages, the Kalman Filter dynamically adjusts its trust between the predicted trend and observed prices. This allows it to provide smoother signals during stable periods while maintaining responsiveness during genuine trend changes, helping to reduce whipsaws in ranging markets while not missing significant price movements.
📐 MATHEMATICAL FOUNDATION
The Kalman Filter operates through a two-phase recursive process:
Prediction Phase:
The algorithm first predicts the next state based on the previous estimate:
State Prediction: Estimates the next value based on current trend
Error Covariance Prediction: Calculates uncertainty in the prediction
Update Phase:
Then updates the prediction based on new price observations:
Kalman Gain Calculation: Determines the weight given to new measurements
State Update: Combines prediction with observation based on calculated gain
Error Covariance Update: Adjusts uncertainty estimate for next iteration
Core Parameters:
Process Noise (Q): Represents uncertainty in the trend model itself. Higher values indicate the trend can change more rapidly, making the filter more responsive to price changes.
Measurement Noise (R): Represents uncertainty in price observations. Higher values indicate less trust in individual price points, resulting in smoother output.
Kalman Gain Formula:
The Kalman Gain determines how much weight to give new observations versus predictions:
K = P(k|k-1) / (P(k|k-1) + R)
Where:
K is the Kalman Gain (0 to 1)
P(k|k-1) is the predicted error covariance
R is the measurement noise parameter
When K approaches 1, the filter trusts new measurements more (responsive).
When K approaches 0, the filter trusts its prediction more (smooth).
This dynamic adjustment mechanism allows the filter to adapt to changing market conditions automatically, providing an advantage over fixed-weight moving averages.
📊 COMPREHENSIVE SIGNAL ANALYSIS
Visual Trend Indication:
The Kalman Filter line provides color-coded trend information:
Green Line: Indicates the filter value is rising, suggesting upward price momentum
Red Line: Indicates the filter value is falling, suggesting downward price momentum
Gray Line: Indicates sideways movement with no clear directional bias
Crossover Signals:
Price-filter crossovers generate trading signals:
Golden Cross: Price crosses above the Kalman Filter line, suggests potential bullish momentum development, may indicate a favorable environment for long positions, filter will naturally turn green as it adapts to price moving higher
Death Cross: Price crosses below the Kalman Filter line, suggests potential bearish momentum development, may indicate consideration for position reduction or shorts, filter will naturally turn red as it adapts to price moving lower
Trend Confirmation:
The filter serves as a dynamic trend baseline:
Price Consistently Above Filter: Confirms established uptrend
Price Consistently Below Filter: Confirms established downtrend
Frequent Crossovers: Suggests ranging or choppy market conditions
Signal Reliability Factors:
Signal quality varies based on market conditions:
Higher reliability in trending markets with sustained directional moves
Lower reliability in choppy, range-bound conditions with frequent reversals
Parameter adjustment can help adapt to different market volatility levels
🎯 STRATEGIC APPLICATIONS
Trend Following Strategy:
Use the Kalman Filter as a dynamic trend baseline:
Enter long positions when price crosses above the filter
Enter short positions when price crosses below the filter
Exit when price crosses back through the filter in the opposite direction
Monitor filter slope (color) for trend strength confirmation
Dynamic Support/Resistance:
The filter can act as a moving support or resistance level:
In uptrends: Filter often provides dynamic support for pullbacks
In downtrends: Filter often provides dynamic resistance for bounces
Price rejections from the filter can offer entry opportunities in trend direction
Filter breaches may signal potential trend reversals
Multi-Timeframe Analysis:
Combine Kalman Filters across different timeframes:
Higher timeframe filter identifies primary trend direction
Lower timeframe filter provides precise entry and exit timing
Trade only in direction of higher timeframe trend for better probability
Use lower timeframe crossovers for position entry/exit within major trend
Volatility-Adjusted Configuration:
Adapt parameters to match market conditions:
Low Volatility Markets (Forex majors, stable stocks): Use lower process noise for stability, use lower measurement noise for sensitivity
Medium Volatility Markets (Most equities): Process noise default (0.05) provides balanced performance, measurement noise default (1.0) for general-purpose filtering
High Volatility Markets (Cryptocurrencies, volatile stocks): Use higher process noise for responsiveness, use higher measurement noise for noise reduction
Risk Management Integration:
Use filter as a trailing stop-loss level in trending markets
Tighten stops when price moves significantly away from filter (overextension)
Wider stops in early trend formation when filter is just establishing direction
Consider position sizing based on distance between price and filter
📋 DETAILED PARAMETER CONFIGURATION
Source Selection:
Determines which price data feeds the algorithm:
OHLC4 (default): Uses average of open, high, low, close for balanced representation
Close: Focuses purely on closing prices for end-of-period analysis
HL2: Uses midpoint of high and low for range-based analysis
HLC3: Typical price, gives more weight to closing price
HLCC4: Weighted close price, emphasizes closing values
Process Noise (Q) - Adaptation Speed Control:
This parameter controls how quickly the filter adapts to changes:
Technical Meaning:
Represents uncertainty in the underlying trend model
Higher values allow the estimated trend to change more rapidly
Lower values assume the trend is more stable and slow-changing
Practical Impact:
Lower Values: Produces very smooth output with minimal noise, slower to respond to genuine trend changes, best for long-term trend identification, reduces false signals in choppy markets
Medium Values: Balanced responsiveness and smoothness, suitable for swing trading applications, default (0.05) works well for most markets
Higher Values: More responsive to price changes, may produce more false signals in ranging markets, better for short-term trading and day trading, captures trend changes earlier, adjust freely based on market characteristics
Measurement Noise (R) - Smoothing Control:
This parameter controls how much the filter trusts individual price observations:
Technical Meaning:
Represents uncertainty in price measurements
Higher values indicate less trust in individual price points
Lower values make each price observation more influential
Practical Impact:
Lower Values: More reactive to each price change, less smoothing with more noise in output, may produce choppy signals
Medium Values: Balanced smoothing and responsiveness, default (1.0) provides general-purpose filtering
Higher Values: Heavy smoothing for very noisy markets, reduces whipsaws significantly but increases lag in trend change detection, best for cryptocurrency and highly volatile assets, can use larger values for extreme smoothing
Parameter Interaction:
The ratio between Process Noise and Measurement Noise determines overall behavior:
High Q / Low R: Very responsive, minimal smoothing
Low Q / High R: Very smooth, maximum lag reduction
Balanced Q and R: Middle ground for most applications
Optimization Guidelines:
Start with default values (Q=0.05, R=1.0)
If too many false signals: Increase R or decrease Q
If missing trend changes: Decrease R or increase Q
Test across different market conditions before live use
Consider different settings for different timeframes
📈 PERFORMANCE ANALYSIS & COMPETITIVE ADVANTAGES
Comparison with Traditional Moving Averages:
Versus Simple Moving Average (SMA):
The Kalman Filter typically responds faster to genuine trend changes
Produces smoother output than SMA of comparable length
Better noise reduction in ranging markets
More configurable for different market conditions
Versus Exponential Moving Average (EMA):
Similar responsiveness but with better noise filtering
Less prone to whipsaws in choppy conditions
More adaptable through dual parameter control (Q and R)
Can be tuned to match or exceed EMA responsiveness while maintaining smoothness
Versus Hull Moving Average (HMA):
Different noise reduction approach (recursive estimation vs. weighted calculation)
Kalman Filter offers more intuitive parameter adjustment
Both reduce lag effectively, but through different mechanisms
Kalman Filter may handle sudden volatility changes more gracefully
Response Characteristics:
Lag Time: Moderate and configurable through parameter adjustment
Noise Reduction: Good to excellent, particularly in volatile conditions
Trend Detection: Effective across multiple timeframes
False Signal Rate: Typically lower than simple moving averages in ranging markets
Computational Efficiency: Efficient recursive calculation suitable for real-time use
Optimal Use Cases:
Markets with mixed trending and ranging periods
Assets with moderate to high volatility requiring noise filtering
Multi-timeframe analysis requiring consistent methodology
Systematic trading strategies needing reliable trend identification
Situations requiring balance between responsiveness and smoothness
Known Limitations:
Parameters require adjustment for different market volatility levels
May still produce false signals during extreme choppy conditions
No single parameter set works optimally for all market conditions
Requires complementary indicators for comprehensive analysis
Historical performance characteristics may not persist in changing market conditions
USAGE NOTES
This indicator is designed for technical analysis and educational purposes. The Kalman Filter's effectiveness varies with market conditions, tending to perform better in markets with clear trending phases interrupted by consolidation. Like all technical indicators, it has limitations and should not be used as the sole basis for trading decisions, but rather as part of a comprehensive trading approach.
Algorithm performance varies with market conditions, and past characteristics do not guarantee future results. Always test thoroughly with different parameter settings across various market conditions before using in live trading. No technical indicator can predict future price movements with certainty, and all trading involves risk of loss.
Signal Core Basic [NevoxCore]⯁ OVERVIEW
Signal Core Basic is a clean and functional ATR-based trailing stop with BUY/SELL signals.
It modernizes the classic "UT-style" concept with adaptive sensitivity, multi-source inputs (Close, Heikin-Ashi, ZLEMA, KAMA), and compact visuals.
The tool is designed for traders who want a clear, minimal, and reliable base indicator without repainting issues.
⯁ HOW IT WORKS
Calculates an ATR-based trailing stop (nLoss = Key × ATR).
Adaptive mode scales sensitivity depending on trend strength (trend/range detection).
Trailing stop flips when price crosses from one regime to the other.
BUY/SELL signals trigger only when confirmed and not blocked by cooldown.
Label ring-buffer ensures chart stays clean (max 50 labels).
Bar coloring optional (solid), auto-disabled when classic red/green colors are enabled.
⯁ KEY FEATURES
ATR-based trailing stop with adjustable sensitivity.
Adaptive key (trend/range aware).
Multiple compute sources: Close, Heikin-Ashi, ZLEMA, KAMA.
Global confirm-on-close switch (no repaint).
Early-flip protection (cooldown).
Compact BUY/SELL labels with auto-cleanup (max 50).
Optional solid bar coloring.
Alerts with ticker, timeframe, and price included.
⯁ SETTINGS (quick overview)
Visual: Classic Colors, Show Labels, Plot Trailing Stop, Barcolor ON/OFF.
Source & Sensitivity: Key Value, ATR Length, Compute Source.
Advanced: Adaptive Key toggle with min/max bounds.
Global: Confirm on bar close.
Extras: Cooldown protection (bars).
⯁ ALERTS (built-in)
Basic Long: BUY signal.
Basic Short: SELL signal.
Each alert includes {{ticker}} {{interval}} @ {{close}}.
⯁ HOW TO USE
Use as a trailing stop and regime filter.
Combine BUY/SELL signals with your strategy rules.
Enable cooldown for cleaner signals in choppy markets.
Try ZLEMA or Heikin-Ashi as compute source for smoother performance.
⯁ WHY IT’S DIFFERENT
Unlike generic UT-style scripts, Signal Core Basic adds adaptive sensitivity, multiple input sources, and strict non-repaint safety.
The visuals follow NevoxCore’s design standards: compact, minimal, and clean — ready for live trading with alerts.
⯁ DISCLAIMER
Backtest and paper-trade before using live. Not financial advice.
Performance depends on market, timeframe, and parameters.
RSI Momentum ScalperOverview
The "RSI Momentum Scalper" is a Pine Script v5 strategy crafted for trading highly volatile markets, with a special focus on newly listed cryptocurrencies. This strategy harnesses the Relative Strength Index (RSI) alongside volume analysis and momentum thresholds to pinpoint short-term trading opportunities. It supports both long and short trades, managed with customizable take profit, stop loss, and trailing stop levels, which are visually plotted on the chart for easy tracking.
Why I Created This Strategy
I developed the "RSI Momentum Scalper" because I was seeking a reliable trading strategy tailored to newly listed, highly volatile cryptocurrencies. These assets often experience rapid price fluctuations, rendering traditional strategies less effective. I aimed to create a tool that could exploit momentum and volume spikes while managing risk through adaptable exit parameters. This strategy is designed to address that need, offering a flexible approach for traders in dynamic crypto markets.
How It Works
The strategy utilizes RSI to identify momentum shifts, combined with volume confirmation, to trigger long or short entries. Trades are controlled with take profit, stop loss, and trailing stop levels, which adjust dynamically as the price moves in your favor. The trailing stop helps lock in profits, while the plotted exit levels provide clear visual cues for trade management.
Customizable Settings
The script is highly customizable, allowing you to adjust it to various market conditions and trading styles. Here’s a brief overview of the key settings:
Trade Mode: Select "Both," "Long Only," or "Short Only" to determine the trade direction.
(Default: Both)
RSI Length: Sets the lookback period for the RSI calculation (2 to 30).
(Default: 8)
A shorter length increases RSI sensitivity, suitable for volatile assets.
RSI Overbought: Defines the upper RSI threshold (60 to 99) for short entries.
(Default: 90)
Higher values signal stronger overbought conditions.
RSI Oversold: Defines the lower RSI threshold (1 to 40) for long entries.
(Default: 10)
Lower values indicate stronger oversold conditions.
RSI Momentum Threshold: Sets the minimum RSI momentum change (1 to 15) to trigger entries.
(Default: 14)
Adjusts the sensitivity to price momentum.
Volume Multiplier: Multiplies the volume moving average to filter high-volume bars (1.0 to 3.0).
(Default: 1)
Higher values require stronger volume confirmation.
Volume MA Length: Sets the lookback period for the volume moving average (5 to 50).
(Default: 13)
Influences the volume trend sensitivity.
Take Profit %: Sets the profit target as a percentage of the entry price (0.1 to 10.0).
(Default: 4.15)
Determines when to close a winning trade.
Stop Loss %: Sets the loss limit as a percentage of the entry price (0.1 to 6.0).
(Default: 1.85)
Protects against significant losses.
Trailing Stop %: Sets the trailing stop distance as a percentage (0.1 to 4.0).
(Default: 2.55)
Locks in profits as the price moves favorably.
Visual Features
Exit Levels: Take profit (green), fixed stop loss (red), and trailing stop (orange) levels are plotted when in a position.
Performance Table: Displays win rate, total trades, and net profit in the top-right corner.
How to Use
Add the strategy to your chart in TradingView.
Adjust the input settings based on the cryptocurrency and timeframe you’re trading.
Monitor the plotted exit levels for trade management.
Use the performance table to assess the strategy’s performance over time.
Notes
Test the strategy on a demo account or with historical data before live trading.
The strategy is optimized for short-term scalping; adjust settings for longer timeframes if needed.
Order Block Volumatic FVG StrategyInspired by: Volumatic Fair Value Gaps —
License: CC BY-NC-SA 4.0 (Creative Commons Attribution–NonCommercial–ShareAlike).
This script is a non-commercial derivative work that credits the original author and keeps the same license.
What this strategy does
This turns BigBeluga’s visual FVG concept into an entry/exit strategy. It scans bullish and bearish FVG boxes, measures how deep price has mitigated into a box (as a percentage), and opens a long/short when your mitigation threshold and filters are satisfied. Risk is managed with a fixed Stop Loss % and a Trailing Stop that activates only after a user-defined profit trigger.
Additions vs. the original indicator
✅ Strategy entries based on % mitigation into FVGs (long/short).
✅ Lower-TF volume split using upticks/downticks; fallback if LTF data is missing (distributes prior bar volume by close’s position in its H–L range) to avoid NaN/0.
✅ Per-FVG total volume filter (min/max) so you can skip weak boxes.
✅ Age filter (min bars since the FVG was created) to avoid fresh/immature boxes.
✅ Bull% / Bear% share filter (the 46%/53% numbers you see inside each FVG).
✅ Optional candle confirmation and cooldown between trades.
✅ Risk management: fixed SL % + Trailing Stop with a profit trigger (doesn’t trail until your trigger is reached).
✅ Pine v6 safety: no unsupported args, no indexof/clamp/when, reverse-index deletes, guards against zero/NaN.
How a trade is decided (logic overview)
Detect FVGs (same rules as the original visual logic).
For each FVG currently intersected by the bar, compute:
Mitigation % (how deep price has entered the box).
Bull%/Bear% split (internal volume share).
Total volume (printed on the box) from LTF aggregation or fallback.
Age (bars) since the box was created.
Apply your filters:
Mitigation ≥ Long/Short threshold.
Volume between your min and max (if enabled).
Age ≥ min bars (if enabled).
Bull% / Bear% within your limits (if enabled).
(Optional) the current candle must be in trade direction (confirm).
If multiple FVGs qualify on the same bar, the strategy uses the most recent one.
Enter long/short (no pyramiding).
Exit with:
Fixed Stop Loss %, and
Trailing Stop that only starts after price reaches your profit trigger %.
Input settings (quick guide)
Mitigation source: close or high/low. Use high/low for intrabar touches; close is stricter.
Mitigation % thresholds: minimal mitigation for Long and Short.
TOTAL Volume filter: skip FVGs with too little/too much total volume (per box).
Bull/Bear share filter: require, e.g., Long only if Bull% ≥ 50; avoid Short when Bull% is high (Short Bull% max).
Age filter (bars): e.g., ≥ 20–30 bars to avoid fresh boxes.
Confirm candle: require candle direction to match the trade.
Cooldown (bars): minimum bars between entries.
Risk:
Stop Loss % (fixed from entry price).
Activate trailing at +% profit (the trigger).
Trailing distance % (the trailing gap once active).
Lower-TF aggregation:
Auto: TF/Divisor → picks 1/3/5m automatically.
Fixed: choose 1/3/5/15m explicitly.
If LTF can’t be fetched, fallback allocates prior bar’s volume by its close position in the bar’s H–L.
Suggested starting presets (you should optimize per market)
Mitigation: 60–80% for both Long/Short.
Bull/Bear share:
Long: Bull% ≥ 50–70, Bear% ≤ 100.
Short: Bull% ≤ 60 (avoid shorting into strong support), Bear% ≥ 0–70 as you prefer.
Age: ≥ 20–30 bars.
Volume: pick a min that filters noise for your symbol/timeframe.
Risk: SL 4–6%, trailing trigger 1–2%, distance 1–2% (crypto example).
Set slippage/fees in Strategy Properties.
Notes, limitations & best practices
Data differences: The LTF split uses request.security_lower_tf. If the exchange/data feed has sparse LTF data, the fallback kicks in (it’s deliberate to avoid NaNs but is a heuristic).
Real-time vs backtest: The current bar can update until close; results on historical bars use closed data. Use “Bar Replay” to understand intrabar effects.
No pyramiding: Only one position at a time. Modify pyramiding in the header if you need scaling.
Assets: For spot/crypto, TradingView “volume” is exchange volume; in some markets it may be tick volume—interpret filters accordingly.
Risk disclosure: Past performance ≠ future results. Use appropriate position sizing and risk controls; this is not financial advice.
Credits
Visual FVG concept and original implementation: BigBeluga.
This derivative strategy adds entry/exit logic, volume/age/share filters, robust LTF handling, and risk management while preserving the original spirit.
License remains CC BY-NC-SA 4.0 (non-commercial, attribution required, share-alike).
AVGO Advanced Day Trading Strategy📈 Overview
The AVGO Advanced Day Trading Strategy is a comprehensive, multi-timeframe trading system designed for active day traders seeking consistent performance with robust risk management. Originally optimized for AVGO (Broadcom), this strategy adapts well to other liquid stocks and can be customized for various trading styles.
🎯 Key Features
Multiple Entry Methods
EMA Crossover: Classic trend-following signals using fast (9) and medium (16) EMAs
MACD + RSI Confluence: Momentum-based entries combining MACD crossovers with RSI positioning
Price Momentum: Consecutive price action patterns with EMA and RSI confirmation
Hybrid System: Advanced multi-trigger approach combining all methodologies
Advanced Technical Arsenal
When enabled, the strategy analyzes 8+ additional indicators for confluence:
Volume Price Trend (VPT): Measures volume-weighted price momentum
On-Balance Volume (OBV): Tracks cumulative volume flow
Accumulation/Distribution Line: Identifies institutional money flow
Williams %R: Momentum oscillator for entry timing
Rate of Change Suite: Multi-timeframe momentum analysis (5, 14, 18 periods)
Commodity Channel Index (CCI): Cyclical turning points
Average Directional Index (ADX): Trend strength measurement
Parabolic SAR: Dynamic support/resistance levels
🛡️ Risk Management System
Position Sizing
Risk-based position sizing (default 1% per trade)
Maximum position limits (default 25% of equity)
Daily loss limits with automatic position closure
Multiple Profit Targets
Target 1: 1.5% gain (50% position exit)
Target 2: 2.5% gain (30% position exit)
Target 3: 3.6% gain (20% position exit)
Configurable exit percentages and target levels
Stop Loss Protection
ATR-based or percentage-based stop losses
Optional trailing stops
Dynamic stop adjustment based on market volatility
📊 Technical Specifications
Primary Indicators
EMAs: 9 (Fast), 16 (Medium), 50 (Long)
VWAP: Volume-weighted average price filter
RSI: 6-period momentum oscillator
MACD: 8/13/5 configuration for faster signals
Volume Confirmation
Volume filter requiring 1.6x average volume
19-period volume moving average baseline
Optional volume confirmation bypass
Market Structure Analysis
Bollinger Bands (20-period, 2.0 multiplier)
Squeeze detection for breakout opportunities
Fractal and pivot point analysis
⏰ Trading Hours & Filters
Time Management
Configurable trading hours (default: 9:30 AM - 3:30 PM EST)
Weekend and holiday filtering
Session-based trade management
Market Condition Filters
Trend alignment requirements
VWAP positioning filters
Volatility-based entry conditions
📱 Visual Features
Information Dashboard
Real-time display of:
Current entry method and signals
Bullish/bearish signal counts
RSI and MACD status
Trend direction and strength
Position status and P&L
Volume and time filter status
Chart Visualization
EMA plots with customizable colors
Entry signal markers
Target and stop level lines
Background color coding for trends
Optional Bollinger Bands and SAR display
🔔 Alert System
Entry Alerts
Customizable alerts for long and short entries
Method-specific alert messages
Signal confluence notifications
Advanced Alerts
Strong confluence threshold alerts
Custom alert messages with signal counts
Risk management alerts
⚙️ Customization Options
Strategy Parameters
Enable/disable long or short trades
Adjustable risk parameters
Multiple entry method selection
Advanced indicator on/off toggle
Visual Customization
Color schemes for all indicators
Dashboard position and size options
Show/hide various chart elements
Background color preferences
📋 Default Settings
Initial Capital: $100,000
Commission: 0.1%
Default Position Size: 10% of equity
Risk Per Trade: 1.0%
RSI Length: 6 periods
MACD: 8/13/5 configuration
Stop Loss: 1.1% or ATR-based
🎯 Best Use Cases
Day Trading: Designed for intraday opportunities
Swing Trading: Adaptable for longer-term positions
Momentum Trading: Excellent for trending markets
Risk-Conscious Trading: Built-in risk management protocols
⚠️ Important Notes
Paper Trading Recommended: Test thoroughly before live trading
Market Conditions: Performance varies with market volatility
Customization: Adjust parameters based on your risk tolerance
Educational Purpose: Use as a learning tool and customize for your needs
🏆 Performance Features
Detailed performance metrics
Trade-by-trade analysis capability
Customizable risk/reward ratios
Comprehensive backtesting support
This strategy is for educational purposes. Past performance does not guarantee future results. Always practice proper risk management and consider your financial situation before trading.
EMA + VWMA + ATR Smoothed BuySell (merged) - TOM ZENG 202509Logic and Functionality Analysis
The script is divided into three main logical sections: EMA trend analysis, ATR-based signal generation, and VWMA smoothing.
1. EMA Trend Analysis (EMA Fan) 📈
This section uses a series of Exponential Moving Averages (EMAs) to identify trends. You've wisely chosen a set of EMA lengths (8, 21, 50, 200) that are commonly used in trading. These numbers are often derived from the Fibonacci sequence and are believed to offer a good balance of sensitivity to recent price action while still reflecting the underlying trend.
Purpose: The EMAs serve as dynamic support and resistance levels. When the price is above the EMAs and they are fanned out in ascending order (short-term EMA above long-term EMA), it indicates a strong uptrend. Conversely, a descending order indicates a downtrend.
Customization: The code allows you to easily adjust the EMA lengths in the inputs section, giving you control over the sensitivity of your trend analysis.
2. ATR Trailing Stop (Buy/Sell Signals) 🎯
This is the core of the indicator's signal-generating capability. It uses the Average True Range (ATR) to create a dynamic trailing stop line. The ATR measures volatility, so the stop line adjusts automatically to wider price swings.
Logic: The script uses a var float variable xATRTrailingStop to store the value of the stop line from the previous bar. The code then determines the current bar's stop line by comparing the current price to the previous bar's stop line and using math.max and math.min to smoothly move the line along with the trend.
Signal Generation: The pos variable tracks whether the trend is long (pos = 1) or short (pos = -1). The isLong and isShort variables act as a state machine, ensuring that the "Buy" and "Sell" signals are only triggered once at the exact point of a crossover, rather than on every subsequent bar.
Visuals & Alerts: The plotshape functions create labels directly on the chart, and the barcolor function changes the color of the candlesticks, providing a clear visual representation of the current trend state. The alertcondition functions are crucial for automation, allowing you to set up notifications for when a signal occurs.
3. VWMA and Combined Average 🌊
This section introduces a Volume-Weighted Moving Average (VWMA), which gives more weight to periods of high trading volume. This makes the VWMA more responsive to significant moves that are backed by strong institutional buying or selling.
Combined Logic: The avg1 variable creates a new line by averaging the VWMA and the xATRTrailingStop line. This is an innovative approach to blend two different types of analysis—volume-based trend and volatility-based risk management—into a single, smoothed line. It can act as an additional filter or a unique trading signal on its own.
Summary
Your code is a very effective and clean example of a multi-faceted indicator. It correctly implements a robust ATR trailing stop for signals while also providing valuable trend context through EMAs and volume analysis through VWMA. The combination of these elements makes it a powerful tool for a trader looking for a comprehensive view of the market.
RSI Crossover AlertRSI Crossover Alert Indicator - User Guide
The RSI Crossover Alert Indicator is a comprehensive technical analysis tool that detects multiple types of RSI crossovers and generates real-time alerts. It combines traditional RSI analysis with signal lines, divergence detection, and multi-level crossing alerts.
1. Multiple Crossover Detection
- RSI/Signal Line Cross: Signals a primary trend change.
- RSI/Second Signal Cross: Confirmation signals for stronger trends.
- Level Crossings: Crosses of Overbought 70, Oversold 30, and Midline 50.
- Divergence Detection: Hidden and regular divergences for reversal signals.
2. Alert Types
- Alert: RSI > Signal
Description: Bullish momentum is building.
Signal: Consider long positions.
- Alert: RSI < Signal
Description: Bearish momentum is building.
Signal: Consider short positions.
- Alert: RSI > 70
Description: Entering the overbought zone.
Signal: Prepare for a potential reversal.
- Alert: RSI < 30
Description: Entering the oversold zone.
Signal: Watch for a bounce opportunity.
- Alert: RSI crosses 50
Description: A shift in momentum.
Signal: Trend confirmation.
3. Visual Components
- Lines: RSI blue, Signal orange, Second Signal purple
- Histogram: Visualizes momentum by showing the difference between RSI and the Signal line.
- Background Zones: Red overbought, Green oversold
- Markers: Up/down triangles to indicate crossovers.
- Info Table: Real-time RSI values and status.
Strategy 1: Classic Crossover
- Entry Long: RSI crosses above the Signal Line AND RSI is below 50.
- Entry Short: RSI crosses below the Signal Line AND RSI is above 50.
- Take Profit: On the opposite signal.
- Stop Loss: At the recent swing high/low.
Strategy 2: Extreme Zone Reversal
- Entry Long: RSI is below 30 and crosses above the Signal Line.
- Entry Short: RSI is above 70 and crosses below the Signal Line.
- Risk Management: Higher win rate but fewer signals. Use a minimum 2:1 risk-reward ratio.
Strategy 3: Divergence Trading
- Setup: Enable divergence alerts and look for price/RSI divergence. Wait for an RSI crossover for confirmation.
- Entry: Enter on the crossover after the divergence appears. Place the stop loss beyond the starting point of the divergence.
Strategy 4: Multi-Timeframe Confirmation
1. Check the higher timeframe e.g. Daily to identify the main trend.
2. Use the current timeframe e.g. 4H/1H for your entry.
3. Only enter in the direction of the main trend.
4. Use the RSI crossover as the entry trigger.
Optimal Settings by Market
- Forex Major Pairs
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 70/30
- Crypto High Volatility
RSI Length: 10-12, Signal Length: 6-8, Overbought/Oversold: 75/25
- Stocks Trending
RSI Length: 14-21, Signal Length: 9-12, Overbought/Oversold: 70/30
- Commodities
RSI Length: 14, Signal Length: 9, Overbought/Oversold: 80/20
Risk Management Rules
1. Position Sizing: Never risk more than 1-2% on a single trade. Reduce size in ranging markets.
2. Stop Loss Placement: Place stops beyond the recent swing high/low for crossovers. Using an ATR-based stop is also effective.
3. Profit Taking: Take partial profits at a 1:1 risk-reward ratio. Switch to a trailing stop after reaching 2:1.
1. Filtering Signals
- Combine with volume indicators.
- Confirm the trend on a higher timeframe.
- Wait for candlestick pattern confirmation.
2. Avoid Common Mistakes
- Don't trade every single crossover.
- Avoid taking signals against a strong trend.
- Do not ignore risk management.
3. Market Conditions
- Trending Market: Focus on midline 50 crosses.
- Ranging Market: Look for reversals from overbought/oversold levels.
- Volatile Market: Widen the overbought/oversold levels.
- If you get too many false signals:
Increase the signal line period, add other confirmation indicators, or use a higher timeframe.
- If you are missing major moves:
Decrease the RSI length, shorten the signal line period, or check your alert settings.
Recommended Combinations
1. RSI + MACD: For dual momentum confirmation.
2. RSI + Bollinger Bands: For volatility-adjusted signals.
3. RSI + Volume: To confirm the strength of a signal.
4. RSI + Moving Averages: To use as a trend filter.
This indicator provides a comprehensive RSI analysis. Success depends on proper configuration, risk management, and combining signals with the overall market context. Start with the default settings, then optimize based on your trading style and market conditions.
Markov Chain [3D] | FractalystWhat exactly is a Markov Chain?
This indicator uses a Markov Chain model to analyze, quantify, and visualize the transitions between market regimes (Bull, Bear, Neutral) on your chart. It dynamically detects these regimes in real-time, calculates transition probabilities, and displays them as animated 3D spheres and arrows, giving traders intuitive insight into current and future market conditions.
How does a Markov Chain work, and how should I read this spheres-and-arrows diagram?
Think of three weather modes: Sunny, Rainy, Cloudy.
Each sphere is one mode. The loop on a sphere means “stay the same next step” (e.g., Sunny again tomorrow).
The arrows leaving a sphere show where things usually go next if they change (e.g., Sunny moving to Cloudy).
Some paths matter more than others. A more prominent loop means the current mode tends to persist. A more prominent outgoing arrow means a change to that destination is the usual next step.
Direction isn’t symmetric: moving Sunny→Cloudy can behave differently than Cloudy→Sunny.
Now relabel the spheres to markets: Bull, Bear, Neutral.
Spheres: market regimes (uptrend, downtrend, range).
Self‑loop: tendency for the current regime to continue on the next bar.
Arrows: the most common next regime if a switch happens.
How to read: Start at the sphere that matches current bar state. If the loop stands out, expect continuation. If one outgoing path stands out, that switch is the typical next step. Opposite directions can differ (Bear→Neutral doesn’t have to match Neutral→Bear).
What states and transitions are shown?
The three market states visualized are:
Bullish (Bull): Upward or strong-market regime.
Bearish (Bear): Downward or weak-market regime.
Neutral: Sideways or range-bound regime.
Bidirectional animated arrows and probability labels show how likely the market is to move from one regime to another (e.g., Bull → Bear or Neutral → Bull).
How does the regime detection system work?
You can use either built-in price returns (based on adaptive Z-score normalization) or supply three custom indicators (such as volume, oscillators, etc.).
Values are statistically normalized (Z-scored) over a configurable lookback period.
The normalized outputs are classified into Bull, Bear, or Neutral zones.
If using three indicators, their regime signals are averaged and smoothed for robustness.
How are transition probabilities calculated?
On every confirmed bar, the algorithm tracks the sequence of detected market states, then builds a rolling window of transitions.
The code maintains a transition count matrix for all regime pairs (e.g., Bull → Bear).
Transition probabilities are extracted for each possible state change using Laplace smoothing for numerical stability, and frequently updated in real-time.
What is unique about the visualization?
3D animated spheres represent each regime and change visually when active.
Animated, bidirectional arrows reveal transition probabilities and allow you to see both dominant and less likely regime flows.
Particles (moving dots) animate along the arrows, enhancing the perception of regime flow direction and speed.
All elements dynamically update with each new price bar, providing a live market map in an intuitive, engaging format.
Can I use custom indicators for regime classification?
Yes! Enable the "Custom Indicators" switch and select any three chart series as inputs. These will be normalized and combined (each with equal weight), broadening the regime classification beyond just price-based movement.
What does the “Lookback Period” control?
Lookback Period (default: 100) sets how much historical data builds the probability matrix. Shorter periods adapt faster to regime changes but may be noisier. Longer periods are more stable but slower to adapt.
How is this different from a Hidden Markov Model (HMM)?
It sets the window for both regime detection and probability calculations. Lower values make the system more reactive, but potentially noisier. Higher values smooth estimates and make the system more robust.
How is this Markov Chain different from a Hidden Markov Model (HMM)?
Markov Chain (as here): All market regimes (Bull, Bear, Neutral) are directly observable on the chart. The transition matrix is built from actual detected regimes, keeping the model simple and interpretable.
Hidden Markov Model: The actual regimes are unobservable ("hidden") and must be inferred from market output or indicator "emissions" using statistical learning algorithms. HMMs are more complex, can capture more subtle structure, but are harder to visualize and require additional machine learning steps for training.
A standard Markov Chain models transitions between observable states using a simple transition matrix, while a Hidden Markov Model assumes the true states are hidden (latent) and must be inferred from observable “emissions” like price or volume data. In practical terms, a Markov Chain is transparent and easier to implement and interpret; an HMM is more expressive but requires statistical inference to estimate hidden states from data.
Markov Chain: states are observable; you directly count or estimate transition probabilities between visible states. This makes it simpler, faster, and easier to validate and tune.
HMM: states are hidden; you only observe emissions generated by those latent states. Learning involves machine learning/statistical algorithms (commonly Baum–Welch/EM for training and Viterbi for decoding) to infer both the transition dynamics and the most likely hidden state sequence from data.
How does the indicator avoid “repainting” or look-ahead bias?
All regime changes and matrix updates happen only on confirmed (closed) bars, so no future data is leaked, ensuring reliable real-time operation.
Are there practical tuning tips?
Tune the Lookback Period for your asset/timeframe: shorter for fast markets, longer for stability.
Use custom indicators if your asset has unique regime drivers.
Watch for rapid changes in transition probabilities as early warning of a possible regime shift.
Who is this indicator for?
Quants and quantitative researchers exploring probabilistic market modeling, especially those interested in regime-switching dynamics and Markov models.
Programmers and system developers who need a probabilistic regime filter for systematic and algorithmic backtesting:
The Markov Chain indicator is ideally suited for programmatic integration via its bias output (1 = Bull, 0 = Neutral, -1 = Bear).
Although the visualization is engaging, the core output is designed for automated, rules-based workflows—not for discretionary/manual trading decisions.
Developers can connect the indicator’s output directly to their Pine Script logic (using input.source()), allowing rapid and robust backtesting of regime-based strategies.
It acts as a plug-and-play regime filter: simply plug the bias output into your entry/exit logic, and you have a scientifically robust, probabilistically-derived signal for filtering, timing, position sizing, or risk regimes.
The MC's output is intentionally "trinary" (1/0/-1), focusing on clear regime states for unambiguous decision-making in code. If you require nuanced, multi-probability or soft-label state vectors, consider expanding the indicator or stacking it with a probability-weighted logic layer in your scripting.
Because it avoids subjectivity, this approach is optimal for systematic quants, algo developers building backtested, repeatable strategies based on probabilistic regime analysis.
What's the mathematical foundation behind this?
The mathematical foundation behind this Markov Chain indicator—and probabilistic regime detection in finance—draws from two principal models: the (standard) Markov Chain and the Hidden Markov Model (HMM).
How to use this indicator programmatically?
The Markov Chain indicator automatically exports a bias value (+1 for Bullish, -1 for Bearish, 0 for Neutral) as a plot visible in the Data Window. This allows you to integrate its regime signal into your own scripts and strategies for backtesting, automation, or live trading.
Step-by-Step Integration with Pine Script (input.source)
Add the Markov Chain indicator to your chart.
This must be done first, since your custom script will "pull" the bias signal from the indicator's plot.
In your strategy, create an input using input.source()
Example:
//@version=5
strategy("MC Bias Strategy Example")
mcBias = input.source(close, "MC Bias Source")
After saving, go to your script’s settings. For the “MC Bias Source” input, select the plot/output of the Markov Chain indicator (typically its bias plot).
Use the bias in your trading logic
Example (long only on Bull, flat otherwise):
if mcBias == 1
strategy.entry("Long", strategy.long)
else
strategy.close("Long")
For more advanced workflows, combine mcBias with additional filters or trailing stops.
How does this work behind-the-scenes?
TradingView’s input.source() lets you use any plot from another indicator as a real-time, “live” data feed in your own script (source).
The selected bias signal is available to your Pine code as a variable, enabling logical decisions based on regime (trend-following, mean-reversion, etc.).
This enables powerful strategy modularity : decouple regime detection from entry/exit logic, allowing fast experimentation without rewriting core signal code.
Integrating 45+ Indicators with Your Markov Chain — How & Why
The Enhanced Custom Indicators Export script exports a massive suite of over 45 technical indicators—ranging from classic momentum (RSI, MACD, Stochastic, etc.) to trend, volume, volatility, and oscillator tools—all pre-calculated, centered/scaled, and available as plots.
// Enhanced Custom Indicators Export - 45 Technical Indicators
// Comprehensive technical analysis suite for advanced market regime detection
//@version=6
indicator('Enhanced Custom Indicators Export | Fractalyst', shorttitle='Enhanced CI Export', overlay=false, scale=scale.right, max_labels_count=500, max_lines_count=500)
// |----- Input Parameters -----| //
momentum_group = "Momentum Indicators"
trend_group = "Trend Indicators"
volume_group = "Volume Indicators"
volatility_group = "Volatility Indicators"
oscillator_group = "Oscillator Indicators"
display_group = "Display Settings"
// Common lengths
length_14 = input.int(14, "Standard Length (14)", minval=1, maxval=100, group=momentum_group)
length_20 = input.int(20, "Medium Length (20)", minval=1, maxval=200, group=trend_group)
length_50 = input.int(50, "Long Length (50)", minval=1, maxval=200, group=trend_group)
// Display options
show_table = input.bool(true, "Show Values Table", group=display_group)
table_size = input.string("Small", "Table Size", options= , group=display_group)
// |----- MOMENTUM INDICATORS (15 indicators) -----| //
// 1. RSI (Relative Strength Index)
rsi_14 = ta.rsi(close, length_14)
rsi_centered = rsi_14 - 50
// 2. Stochastic Oscillator
stoch_k = ta.stoch(close, high, low, length_14)
stoch_d = ta.sma(stoch_k, 3)
stoch_centered = stoch_k - 50
// 3. Williams %R
williams_r = ta.stoch(close, high, low, length_14) - 100
// 4. MACD (Moving Average Convergence Divergence)
= ta.macd(close, 12, 26, 9)
// 5. Momentum (Rate of Change)
momentum = ta.mom(close, length_14)
momentum_pct = (momentum / close ) * 100
// 6. Rate of Change (ROC)
roc = ta.roc(close, length_14)
// 7. Commodity Channel Index (CCI)
cci = ta.cci(close, length_20)
// 8. Money Flow Index (MFI)
mfi = ta.mfi(close, length_14)
mfi_centered = mfi - 50
// 9. Awesome Oscillator (AO)
ao = ta.sma(hl2, 5) - ta.sma(hl2, 34)
// 10. Accelerator Oscillator (AC)
ac = ao - ta.sma(ao, 5)
// 11. Chande Momentum Oscillator (CMO)
cmo = ta.cmo(close, length_14)
// 12. Detrended Price Oscillator (DPO)
dpo = close - ta.sma(close, length_20)
// 13. Price Oscillator (PPO)
ppo = ta.sma(close, 12) - ta.sma(close, 26)
ppo_pct = (ppo / ta.sma(close, 26)) * 100
// 14. TRIX
trix_ema1 = ta.ema(close, length_14)
trix_ema2 = ta.ema(trix_ema1, length_14)
trix_ema3 = ta.ema(trix_ema2, length_14)
trix = ta.roc(trix_ema3, 1) * 10000
// 15. Klinger Oscillator
klinger = ta.ema(volume * (high + low + close) / 3, 34) - ta.ema(volume * (high + low + close) / 3, 55)
// 16. Fisher Transform
fisher_hl2 = 0.5 * (hl2 - ta.lowest(hl2, 10)) / (ta.highest(hl2, 10) - ta.lowest(hl2, 10)) - 0.25
fisher = 0.5 * math.log((1 + fisher_hl2) / (1 - fisher_hl2))
// 17. Stochastic RSI
stoch_rsi = ta.stoch(rsi_14, rsi_14, rsi_14, length_14)
stoch_rsi_centered = stoch_rsi - 50
// 18. Relative Vigor Index (RVI)
rvi_num = ta.swma(close - open)
rvi_den = ta.swma(high - low)
rvi = rvi_den != 0 ? rvi_num / rvi_den : 0
// 19. Balance of Power (BOP)
bop = (close - open) / (high - low)
// |----- TREND INDICATORS (10 indicators) -----| //
// 20. Simple Moving Average Momentum
sma_20 = ta.sma(close, length_20)
sma_momentum = ((close - sma_20) / sma_20) * 100
// 21. Exponential Moving Average Momentum
ema_20 = ta.ema(close, length_20)
ema_momentum = ((close - ema_20) / ema_20) * 100
// 22. Parabolic SAR
sar = ta.sar(0.02, 0.02, 0.2)
sar_trend = close > sar ? 1 : -1
// 23. Linear Regression Slope
lr_slope = ta.linreg(close, length_20, 0) - ta.linreg(close, length_20, 1)
// 24. Moving Average Convergence (MAC)
mac = ta.sma(close, 10) - ta.sma(close, 30)
// 25. Trend Intensity Index (TII)
tii_sum = 0.0
for i = 1 to length_20
tii_sum += close > close ? 1 : 0
tii = (tii_sum / length_20) * 100
// 26. Ichimoku Cloud Components
ichimoku_tenkan = (ta.highest(high, 9) + ta.lowest(low, 9)) / 2
ichimoku_kijun = (ta.highest(high, 26) + ta.lowest(low, 26)) / 2
ichimoku_signal = ichimoku_tenkan > ichimoku_kijun ? 1 : -1
// 27. MESA Adaptive Moving Average (MAMA)
mama_alpha = 2.0 / (length_20 + 1)
mama = ta.ema(close, length_20)
mama_momentum = ((close - mama) / mama) * 100
// 28. Zero Lag Exponential Moving Average (ZLEMA)
zlema_lag = math.round((length_20 - 1) / 2)
zlema_data = close + (close - close )
zlema = ta.ema(zlema_data, length_20)
zlema_momentum = ((close - zlema) / zlema) * 100
// |----- VOLUME INDICATORS (6 indicators) -----| //
// 29. On-Balance Volume (OBV)
obv = ta.obv
// 30. Volume Rate of Change (VROC)
vroc = ta.roc(volume, length_14)
// 31. Price Volume Trend (PVT)
pvt = ta.pvt
// 32. Negative Volume Index (NVI)
nvi = 0.0
nvi := volume < volume ? nvi + ((close - close ) / close ) * nvi : nvi
// 33. Positive Volume Index (PVI)
pvi = 0.0
pvi := volume > volume ? pvi + ((close - close ) / close ) * pvi : pvi
// 34. Volume Oscillator
vol_osc = ta.sma(volume, 5) - ta.sma(volume, 10)
// 35. Ease of Movement (EOM)
eom_distance = high - low
eom_box_height = volume / 1000000
eom = eom_box_height != 0 ? eom_distance / eom_box_height : 0
eom_sma = ta.sma(eom, length_14)
// 36. Force Index
force_index = volume * (close - close )
force_index_sma = ta.sma(force_index, length_14)
// |----- VOLATILITY INDICATORS (10 indicators) -----| //
// 37. Average True Range (ATR)
atr = ta.atr(length_14)
atr_pct = (atr / close) * 100
// 38. Bollinger Bands Position
bb_basis = ta.sma(close, length_20)
bb_dev = 2.0 * ta.stdev(close, length_20)
bb_upper = bb_basis + bb_dev
bb_lower = bb_basis - bb_dev
bb_position = bb_dev != 0 ? (close - bb_basis) / bb_dev : 0
bb_width = bb_dev != 0 ? (bb_upper - bb_lower) / bb_basis * 100 : 0
// 39. Keltner Channels Position
kc_basis = ta.ema(close, length_20)
kc_range = ta.ema(ta.tr, length_20)
kc_upper = kc_basis + (2.0 * kc_range)
kc_lower = kc_basis - (2.0 * kc_range)
kc_position = kc_range != 0 ? (close - kc_basis) / kc_range : 0
// 40. Donchian Channels Position
dc_upper = ta.highest(high, length_20)
dc_lower = ta.lowest(low, length_20)
dc_basis = (dc_upper + dc_lower) / 2
dc_position = (dc_upper - dc_lower) != 0 ? (close - dc_basis) / (dc_upper - dc_lower) : 0
// 41. Standard Deviation
std_dev = ta.stdev(close, length_20)
std_dev_pct = (std_dev / close) * 100
// 42. Relative Volatility Index (RVI)
rvi_up = ta.stdev(close > close ? close : 0, length_14)
rvi_down = ta.stdev(close < close ? close : 0, length_14)
rvi_total = rvi_up + rvi_down
rvi_volatility = rvi_total != 0 ? (rvi_up / rvi_total) * 100 : 50
// 43. Historical Volatility
hv_returns = math.log(close / close )
hv = ta.stdev(hv_returns, length_20) * math.sqrt(252) * 100
// 44. Garman-Klass Volatility
gk_vol = math.log(high/low) * math.log(high/low) - (2*math.log(2)-1) * math.log(close/open) * math.log(close/open)
gk_volatility = math.sqrt(ta.sma(gk_vol, length_20)) * 100
// 45. Parkinson Volatility
park_vol = math.log(high/low) * math.log(high/low)
parkinson = math.sqrt(ta.sma(park_vol, length_20) / (4 * math.log(2))) * 100
// 46. Rogers-Satchell Volatility
rs_vol = math.log(high/close) * math.log(high/open) + math.log(low/close) * math.log(low/open)
rogers_satchell = math.sqrt(ta.sma(rs_vol, length_20)) * 100
// |----- OSCILLATOR INDICATORS (5 indicators) -----| //
// 47. Elder Ray Index
elder_bull = high - ta.ema(close, 13)
elder_bear = low - ta.ema(close, 13)
elder_power = elder_bull + elder_bear
// 48. Schaff Trend Cycle (STC)
stc_macd = ta.ema(close, 23) - ta.ema(close, 50)
stc_k = ta.stoch(stc_macd, stc_macd, stc_macd, 10)
stc_d = ta.ema(stc_k, 3)
stc = ta.stoch(stc_d, stc_d, stc_d, 10)
// 49. Coppock Curve
coppock_roc1 = ta.roc(close, 14)
coppock_roc2 = ta.roc(close, 11)
coppock = ta.wma(coppock_roc1 + coppock_roc2, 10)
// 50. Know Sure Thing (KST)
kst_roc1 = ta.roc(close, 10)
kst_roc2 = ta.roc(close, 15)
kst_roc3 = ta.roc(close, 20)
kst_roc4 = ta.roc(close, 30)
kst = ta.sma(kst_roc1, 10) + 2*ta.sma(kst_roc2, 10) + 3*ta.sma(kst_roc3, 10) + 4*ta.sma(kst_roc4, 15)
// 51. Percentage Price Oscillator (PPO)
ppo_line = ((ta.ema(close, 12) - ta.ema(close, 26)) / ta.ema(close, 26)) * 100
ppo_signal = ta.ema(ppo_line, 9)
ppo_histogram = ppo_line - ppo_signal
// |----- PLOT MAIN INDICATORS -----| //
// Plot key momentum indicators
plot(rsi_centered, title="01_RSI_Centered", color=color.purple, linewidth=1)
plot(stoch_centered, title="02_Stoch_Centered", color=color.blue, linewidth=1)
plot(williams_r, title="03_Williams_R", color=color.red, linewidth=1)
plot(macd_histogram, title="04_MACD_Histogram", color=color.orange, linewidth=1)
plot(cci, title="05_CCI", color=color.green, linewidth=1)
// Plot trend indicators
plot(sma_momentum, title="06_SMA_Momentum", color=color.navy, linewidth=1)
plot(ema_momentum, title="07_EMA_Momentum", color=color.maroon, linewidth=1)
plot(sar_trend, title="08_SAR_Trend", color=color.teal, linewidth=1)
plot(lr_slope, title="09_LR_Slope", color=color.lime, linewidth=1)
plot(mac, title="10_MAC", color=color.fuchsia, linewidth=1)
// Plot volatility indicators
plot(atr_pct, title="11_ATR_Pct", color=color.yellow, linewidth=1)
plot(bb_position, title="12_BB_Position", color=color.aqua, linewidth=1)
plot(kc_position, title="13_KC_Position", color=color.olive, linewidth=1)
plot(std_dev_pct, title="14_StdDev_Pct", color=color.silver, linewidth=1)
plot(bb_width, title="15_BB_Width", color=color.gray, linewidth=1)
// Plot volume indicators
plot(vroc, title="16_VROC", color=color.blue, linewidth=1)
plot(eom_sma, title="17_EOM", color=color.red, linewidth=1)
plot(vol_osc, title="18_Vol_Osc", color=color.green, linewidth=1)
plot(force_index_sma, title="19_Force_Index", color=color.orange, linewidth=1)
plot(obv, title="20_OBV", color=color.purple, linewidth=1)
// Plot additional oscillators
plot(ao, title="21_Awesome_Osc", color=color.navy, linewidth=1)
plot(cmo, title="22_CMO", color=color.maroon, linewidth=1)
plot(dpo, title="23_DPO", color=color.teal, linewidth=1)
plot(trix, title="24_TRIX", color=color.lime, linewidth=1)
plot(fisher, title="25_Fisher", color=color.fuchsia, linewidth=1)
// Plot more momentum indicators
plot(mfi_centered, title="26_MFI_Centered", color=color.yellow, linewidth=1)
plot(ac, title="27_AC", color=color.aqua, linewidth=1)
plot(ppo_pct, title="28_PPO_Pct", color=color.olive, linewidth=1)
plot(stoch_rsi_centered, title="29_StochRSI_Centered", color=color.silver, linewidth=1)
plot(klinger, title="30_Klinger", color=color.gray, linewidth=1)
// Plot trend continuation
plot(tii, title="31_TII", color=color.blue, linewidth=1)
plot(ichimoku_signal, title="32_Ichimoku_Signal", color=color.red, linewidth=1)
plot(mama_momentum, title="33_MAMA_Momentum", color=color.green, linewidth=1)
plot(zlema_momentum, title="34_ZLEMA_Momentum", color=color.orange, linewidth=1)
plot(bop, title="35_BOP", color=color.purple, linewidth=1)
// Plot volume continuation
plot(nvi, title="36_NVI", color=color.navy, linewidth=1)
plot(pvi, title="37_PVI", color=color.maroon, linewidth=1)
plot(momentum_pct, title="38_Momentum_Pct", color=color.teal, linewidth=1)
plot(roc, title="39_ROC", color=color.lime, linewidth=1)
plot(rvi, title="40_RVI", color=color.fuchsia, linewidth=1)
// Plot volatility continuation
plot(dc_position, title="41_DC_Position", color=color.yellow, linewidth=1)
plot(rvi_volatility, title="42_RVI_Volatility", color=color.aqua, linewidth=1)
plot(hv, title="43_Historical_Vol", color=color.olive, linewidth=1)
plot(gk_volatility, title="44_GK_Volatility", color=color.silver, linewidth=1)
plot(parkinson, title="45_Parkinson_Vol", color=color.gray, linewidth=1)
// Plot final oscillators
plot(rogers_satchell, title="46_RS_Volatility", color=color.blue, linewidth=1)
plot(elder_power, title="47_Elder_Power", color=color.red, linewidth=1)
plot(stc, title="48_STC", color=color.green, linewidth=1)
plot(coppock, title="49_Coppock", color=color.orange, linewidth=1)
plot(kst, title="50_KST", color=color.purple, linewidth=1)
// Plot final indicators
plot(ppo_histogram, title="51_PPO_Histogram", color=color.navy, linewidth=1)
plot(pvt, title="52_PVT", color=color.maroon, linewidth=1)
// |----- Reference Lines -----| //
hline(0, "Zero Line", color=color.gray, linestyle=hline.style_dashed, linewidth=1)
hline(50, "Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-50, "Lower Midline", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(25, "Upper Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
hline(-25, "Lower Threshold", color=color.gray, linestyle=hline.style_dotted, linewidth=1)
// |----- Enhanced Information Table -----| //
if show_table and barstate.islast
table_position = position.top_right
table_text_size = table_size == "Tiny" ? size.tiny : table_size == "Small" ? size.small : size.normal
var table info_table = table.new(table_position, 3, 18, bgcolor=color.new(color.white, 85), border_width=1, border_color=color.gray)
// Headers
table.cell(info_table, 0, 0, 'Category', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 1, 0, 'Indicator', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
table.cell(info_table, 2, 0, 'Value', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.blue, 70))
// Key Momentum Indicators
table.cell(info_table, 0, 1, 'MOMENTUM', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 1, 'RSI Centered', text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 2, 1, str.tostring(rsi_centered, '0.00'), text_color=color.purple, text_size=table_text_size)
table.cell(info_table, 0, 2, '', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 1, 2, 'Stoch Centered', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 2, str.tostring(stoch_centered, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 3, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 3, 'Williams %R', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 3, str.tostring(williams_r, '0.00'), text_color=color.red, text_size=table_text_size)
table.cell(info_table, 0, 4, '', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 1, 4, 'MACD Histogram', text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 2, 4, str.tostring(macd_histogram, '0.000'), text_color=color.orange, text_size=table_text_size)
table.cell(info_table, 0, 5, '', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 1, 5, 'CCI', text_color=color.green, text_size=table_text_size)
table.cell(info_table, 2, 5, str.tostring(cci, '0.00'), text_color=color.green, text_size=table_text_size)
// Key Trend Indicators
table.cell(info_table, 0, 6, 'TREND', text_color=color.navy, text_size=table_text_size, bgcolor=color.new(color.navy, 90))
table.cell(info_table, 1, 6, 'SMA Momentum %', text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 2, 6, str.tostring(sma_momentum, '0.00'), text_color=color.navy, text_size=table_text_size)
table.cell(info_table, 0, 7, '', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 1, 7, 'EMA Momentum %', text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 2, 7, str.tostring(ema_momentum, '0.00'), text_color=color.maroon, text_size=table_text_size)
table.cell(info_table, 0, 8, '', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 1, 8, 'SAR Trend', text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 2, 8, str.tostring(sar_trend, '0'), text_color=color.teal, text_size=table_text_size)
table.cell(info_table, 0, 9, '', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 1, 9, 'Linear Regression', text_color=color.lime, text_size=table_text_size)
table.cell(info_table, 2, 9, str.tostring(lr_slope, '0.000'), text_color=color.lime, text_size=table_text_size)
// Key Volatility Indicators
table.cell(info_table, 0, 10, 'VOLATILITY', text_color=color.yellow, text_size=table_text_size, bgcolor=color.new(color.yellow, 90))
table.cell(info_table, 1, 10, 'ATR %', text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 2, 10, str.tostring(atr_pct, '0.00'), text_color=color.yellow, text_size=table_text_size)
table.cell(info_table, 0, 11, '', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 1, 11, 'BB Position', text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 2, 11, str.tostring(bb_position, '0.00'), text_color=color.aqua, text_size=table_text_size)
table.cell(info_table, 0, 12, '', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 1, 12, 'KC Position', text_color=color.olive, text_size=table_text_size)
table.cell(info_table, 2, 12, str.tostring(kc_position, '0.00'), text_color=color.olive, text_size=table_text_size)
// Key Volume Indicators
table.cell(info_table, 0, 13, 'VOLUME', text_color=color.blue, text_size=table_text_size, bgcolor=color.new(color.blue, 90))
table.cell(info_table, 1, 13, 'Volume ROC', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 13, str.tostring(vroc, '0.00'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 14, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 14, 'EOM', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 14, str.tostring(eom_sma, '0.000'), text_color=color.red, text_size=table_text_size)
// Key Oscillators
table.cell(info_table, 0, 15, 'OSCILLATORS', text_color=color.purple, text_size=table_text_size, bgcolor=color.new(color.purple, 90))
table.cell(info_table, 1, 15, 'Awesome Osc', text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 2, 15, str.tostring(ao, '0.000'), text_color=color.blue, text_size=table_text_size)
table.cell(info_table, 0, 16, '', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 1, 16, 'Fisher Transform', text_color=color.red, text_size=table_text_size)
table.cell(info_table, 2, 16, str.tostring(fisher, '0.000'), text_color=color.red, text_size=table_text_size)
// Summary Statistics
table.cell(info_table, 0, 17, 'SUMMARY', text_color=color.black, text_size=table_text_size, bgcolor=color.new(color.gray, 70))
table.cell(info_table, 1, 17, 'Total Indicators: 52', text_color=color.black, text_size=table_text_size)
regime_color = rsi_centered > 10 ? color.green : rsi_centered < -10 ? color.red : color.gray
regime_text = rsi_centered > 10 ? "BULLISH" : rsi_centered < -10 ? "BEARISH" : "NEUTRAL"
table.cell(info_table, 2, 17, regime_text, text_color=regime_color, text_size=table_text_size)
This makes it the perfect “indicator backbone” for quantitative and systematic traders who want to prototype, combine, and test new regime detection models—especially in combination with the Markov Chain indicator.
How to use this script with the Markov Chain for research and backtesting:
Add the Enhanced Indicator Export to your chart.
Every calculated indicator is available as an individual data stream.
Connect the indicator(s) you want as custom input(s) to the Markov Chain’s “Custom Indicators” option.
In the Markov Chain indicator’s settings, turn ON the custom indicator mode.
For each of the three custom indicator inputs, select the exported plot from the Enhanced Export script—the menu lists all 45+ signals by name.
This creates a powerful, modular regime-detection engine where you can mix-and-match momentum, trend, volume, or custom combinations for advanced filtering.
Backtest regime logic directly.
Once you’ve connected your chosen indicators, the Markov Chain script performs regime detection (Bull/Neutral/Bear) based on your selected features—not just price returns.
The regime detection is robust, automatically normalized (using Z-score), and outputs bias (1, -1, 0) for plug-and-play integration.
Export the regime bias for programmatic use.
As described above, use input.source() in your Pine Script strategy or system and link the bias output.
You can now filter signals, control trade direction/size, or design pairs-trading that respect true, indicator-driven market regimes.
With this framework, you’re not limited to static or simplistic regime filters. You can rigorously define, test, and refine what “market regime” means for your strategies—using the technical features that matter most to you.
Optimize your signal generation by backtesting across a universe of meaningful indicator blends.
Enhance risk management with objective, real-time regime boundaries.
Accelerate your research: iterate quickly, swap indicator components, and see results with minimal code changes.
Automate multi-asset or pairs-trading by integrating regime context directly into strategy logic.
Add both scripts to your chart, connect your preferred features, and start investigating your best regime-based trades—entirely within the TradingView ecosystem.
References & Further Reading
Ang, A., & Bekaert, G. (2002). “Regime Switches in Interest Rates.” Journal of Business & Economic Statistics, 20(2), 163–182.
Hamilton, J. D. (1989). “A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle.” Econometrica, 57(2), 357–384.
Markov, A. A. (1906). "Extension of the Limit Theorems of Probability Theory to a Sum of Variables Connected in a Chain." The Notes of the Imperial Academy of Sciences of St. Petersburg.
Guidolin, M., & Timmermann, A. (2007). “Asset Allocation under Multivariate Regime Switching.” Journal of Economic Dynamics and Control, 31(11), 3503–3544.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. New York Institute of Finance.
Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns.” Journal of Finance, 47(5), 1731–1764.
Zucchini, W., MacDonald, I. L., & Langrock, R. (2017). Hidden Markov Models for Time Series: An Introduction Using R (2nd ed.). Chapman and Hall/CRC.
On Quantitative Finance and Markov Models:
Lo, A. W., & Hasanhodzic, J. (2009). The Heretics of Finance: Conversations with Leading Practitioners of Technical Analysis. Bloomberg Press.
Patterson, S. (2016). The Man Who Solved the Market: How Jim Simons Launched the Quant Revolution. Penguin Press.
TradingView Pine Script Documentation: www.tradingview.com
TradingView Blog: “Use an Input From Another Indicator With Your Strategy” www.tradingview.com
GeeksforGeeks: “What is the Difference Between Markov Chains and Hidden Markov Models?” www.geeksforgeeks.org
What makes this indicator original and unique?
- On‑chart, real‑time Markov. The chain is drawn directly on your chart. You see the current regime, its tendency to stay (self‑loop), and the usual next step (arrows) as bars confirm.
- Source‑agnostic by design. The engine runs on any series you select via input.source() — price, your own oscillator, a composite score, anything you compute in the script.
- Automatic normalization + regime mapping. Different inputs live on different scales. The script standardizes your chosen source and maps it into clear regimes (e.g., Bull / Bear / Neutral) without you micromanaging thresholds each time.
- Rolling, bar‑by‑bar learning. Transition tendencies are computed from a rolling window of confirmed bars. What you see is exactly what the market did in that window.
- Fast experimentation. Switch the source, adjust the window, and the Markov view updates instantly. It’s a rapid way to test ideas and feel regime persistence/switch behavior.
Integrate your own signals (using input.source())
- In settings, choose the Source . This is powered by input.source() .
- Feed it price, an indicator you compute inside the script, or a custom composite series.
- The script will automatically normalize that series and process it through the Markov engine, mapping it to regimes and updating the on‑chart spheres/arrows in real time.
Credits:
Deep gratitude to @RicardoSantos for both the foundational Markov chain processing engine and inspiring open-source contributions, which made advanced probabilistic market modeling accessible to the TradingView community.
Special thanks to @Alien_Algorithms for the innovative and visually stunning 3D sphere logic that powers the indicator’s animated, regime-based visualization.
Disclaimer
This tool summarizes recent behavior. It is not financial advice and not a guarantee of future results.
Parabolic Stoch SAR VisualizerParabolic Stoch SAR Visualizer — Momentum-Driven Trend Precision Tool
Overview:
Parabolic Stoch SAR Visualizer is a thoughtfully engineered hybrid indicator that blends momentum oscillation and trend-following mechanics into one robust system. By applying a custom Parabolic SAR calculation directly on a double-smoothed stochastic oscillator (rather than on price), it generates cleaner signals with enhanced trend detection and fewer false positives than typical Parabolic RSI or standard SAR variants.
Unique Functionality:
Momentum smoothing : The base stochastic %K undergoes double smoothing via consecutive simple moving averages, significantly cutting down random noise and erratic swings common in raw stochastic readings. This stabilizes momentum tracking, isolating true price strength and weakness.
Custom Parabolic SAR on smoothed momentum : Traditional SAR algorithms operate on price data, acting as trailing stops. This indicator repurposes SAR to work on smoothed stochastic values, effectively converting it into a momentum-driven directional filter. This yields a more adaptive and responsive trend signal focused on genuine momentum shifts instead of price noise.
Bounded SAR range and adjustable acceleration : SAR values are mathematically restricted between 0 and 100, aligning with the stochastic scale to prevent distortions. Traders can customize acceleration parameters (start, increment, max) to fine-tune trend sensitivity relative to market volatility or specific strategies.
Signal clarity through filterin g: Minimum bar spacing and minimum SAR movement thresholds between plotted dots reduce chart clutter, highlighting only meaningful trend changes and filtering out insignificant fluctuations.
Enhanced visuals : The oscillator line smoothly transitions its color gradient between defined uptrend and downtrend hues, intuitively signaling momentum strength. Parabolic SAR dots are offset from the oscillator line with multi-layered glow effects, making trend flips easy to spot at a glance.
Trading Application:
Trend identification : Momentum-based SAR dots offer precise marking of trend shifts, helping traders avoid false breakouts and premature trades.
Entry and exit timing : Combining the double-smoothed stochastic oscillator and SAR dots creates a reliable framework to confirm momentum shifts and optimal trade entries or exits.
Customizable for volatility regimes : Adjustable acceleration and filtering parameters allow scalpers to increase signal sensitivity, while swing traders can dial back noise for smoother trend recognition.
Visual clarity for fast decisions : Gradient color coding and glowing SAR dots facilitate immediate momentum assessment without complex analysis, empowering quicker, more confident trade actions.
Advantages over Parabolic RSI and similar indicators:
Parabolic RSI’s direct application of SAR on RSI often results in noisy, choppy signals prone to whipsaws. This indicator’s double-smoothed stochastic foundation delivers a cleaner, steadier signal.
Applying SAR to smoothed momentum rather than price transforms it into a directional filter that better captures true market strength with reduced lag.
Adaptive plotting thresholds and enhanced visuals minimize clutter and ambiguity, improving trader focus and execution speed.
Hurst Exponent Adaptive Filter (HEAF) [PhenLabs]📊 PhenLabs - Hurst Exponent Adaptive Filter (HEAF)
Version: PineScript™ v6
📌 Description
The Hurst Exponent Adaptive Filter (HEAF) is an advanced Pine Script indicator designed to dynamically adjust moving average calculations based on real time market regimes detected through the Hurst Exponent. The intention behind the creation of this indicator was not a buy/sell indicator but rather a tool to help sharpen traders ability to distinguish regimes in the market mathematically rather than guessing. By analyzing price persistence, it identifies whether the market is trending, mean-reverting, or exhibiting random walk behavior, automatically adapting the MA length to provide more responsive alerts in volatile conditions and smoother outputs in stable ones. This helps traders avoid false signals in choppy markets and capitalize on strong trends, making it ideal for adaptive trading strategies across various timeframes and assets.
Unlike traditional moving averages, HEAF incorporates fractal dimension analysis via the Hurst Exponent to create a self-tuning filter that evolves with market conditions. Traders benefit from visual cues like color coded regimes, adaptive bands for volatility channels, and an information panel that suggests appropriate strategies, enhancing decision making without constant manual adjustments by the user.
🚀 Points of Innovation
Dynamic MA length adjustment using Hurst Exponent for regime-aware filtering, reducing lag in trends and noise in ranges.
Integrated market regime classification (trending, mean-reverting, random) with visual and alert-based notifications.
Customizable color themes and adaptive bands that incorporate ATR for volatility-adjusted channels.
Built-in information panel providing real-time strategy recommendations based on detected regimes.
Power sensitivity parameter to fine-tune adaptation aggressiveness, allowing personalization for different trading styles.
Support for multiple MA types (EMA, SMA, WMA) within an adaptive framework.
🔧 Core Components
Hurst Exponent Calculation: Computes the fractal dimension of price series over a user-defined lookback to detect market persistence or anti-persistence.
Adaptive Length Mechanism: Maps Hurst values to MA lengths between minimum and maximum bounds, using a power function for sensitivity control.
Moving Average Engine: Applies the chosen MA type (EMA, SMA, or WMA) to the adaptive length for the core filter line.
Adaptive Bands: Creates upper and lower channels using ATR multiplied by a band factor, scaled to the current adaptive length.
Regime Detection: Classifies market state with thresholds (e.g., >0.55 for trending) and triggers alerts on regime changes.
Visualization System: Includes gradient fills, regime-colored MA lines, and an info panel for at-a-glance insights.
🔥 Key Features
Regime-Adaptive Filtering: Automatically shortens MA in mean-reverting markets for quick responses and lengthens it in trends for smoother signals, helping traders stay aligned with market dynamics.
Custom Alerts: Notifies on regime shifts and band breakouts, enabling timely strategy adjustments like switching to trend-following in bullish regimes.
Visual Enhancements: Color-coded MA lines, gradient band fills, and an optional info panel that displays market state and trading tips, improving chart readability.
Flexible Settings: Adjustable lookback, min/max lengths, sensitivity power, MA type, and themes to suit various assets and timeframes.
Band Breakout Signals: Highlights potential overbought/oversold conditions via ATR-based channels, useful for entry/exit timing.
🎨 Visualization
Main Adaptive MA Line: Plotted with regime-based colors (e.g., green for trending) to visually indicate market state and filter position relative to price.
Adaptive Bands: Upper and lower lines with gradient fills between them, showing volatility channels that widen in random regimes and tighten in trends.
Price vs. MA Fills: Color-coded areas between price and MA (e.g., bullish green above MA in trending modes) for quick trend strength assessment.
Information Panel: Top-right table displaying current regime (e.g., "Trending Market") and strategy suggestions like "Follow trends" or "Trade ranges."
📖 Usage Guidelines
Core Settings
Hurst Lookback Period
Default: 100
Range: 20-500
Description: Sets the period for Hurst Exponent calculation; longer values provide more stable regime detection but may lag, while shorter ones are more responsive to recent changes.
Minimum MA Length
Default: 10
Range: 5-50
Description: Defines the shortest possible adaptive MA length, ideal for fast responses in mean-reverting conditions.
Maximum MA Length
Default: 200
Range: 50-500
Description: Sets the longest adaptive MA length for smoothing in strong trends; adjust based on asset volatility.
Sensitivity Power
Default: 2.0
Range: 1.0-5.0
Description: Controls how aggressively the length adapts to Hurst changes; higher values make it more sensitive to regime shifts.
MA Type
Default: EMA
Options: EMA, SMA, WMA
Description: Chooses the moving average calculation method; EMA is more responsive, while SMA/WMA offer different weighting.
🖼️ Visual Settings
Show Adaptive Bands
Default: True
Description: Toggles visibility of upper/lower bands for volatility channels.
Band Multiplier
Default: 1.5
Range: 0.5-3.0
Description: Scales band width using ATR; higher values create wider channels for conservative signals.
Show Information Panel
Default: True
Description: Displays regime info and strategy tips in a top-right panel.
MA Line Width
Default: 2
Range: 1-5
Description: Adjusts thickness of the main MA line for better visibility.
Color Theme
Default: Blue
Options: Blue, Classic, Dark Purple, Vibrant
Description: Selects color scheme for MA, bands, and fills to match user preferences.
🚨 Alert Settings
Enable Alerts
Default: True
Description: Activates notifications for regime changes and band breakouts.
✅ Best Use Cases
Trend-Following Strategies: In detected trending regimes, use the adaptive MA as a trailing stop or entry filter for momentum trades.
Range Trading: During mean-reverting periods, monitor band breakouts for buying dips or selling rallies within channels.
Risk Management in Random Markets: Reduce exposure when random walk is detected, using tight stops suggested in the info panel.
Multi-Timeframe Analysis: Apply on higher timeframes for regime confirmation, then drill down to lower ones for entries.
Volatility-Based Entries: Use upper/lower band crossovers as signals in adaptive channels for overbought/oversold trades.
⚠️ Limitations
Lagging in Transitions: Regime detection may delay during rapid market shifts, requiring confirmation from other tools.
Not a Standalone System: Best used in conjunction with other indicators; random regimes can lead to whipsaws if traded aggressively.
Parameter Sensitivity: Optimal settings vary by asset and timeframe, necessitating backtesting.
💡 What Makes This Unique
Hurst-Driven Adaptation: Unlike static MAs, it uses fractal analysis to self-tune, providing regime-specific filtering that's rare in standard indicators.
Integrated Strategy Guidance: The info panel offers actionable tips tied to regimes, bridging analysis and execution.
Multi-Regime Visualization: Combines adaptive bands, colored fills, and alerts in one tool for comprehensive market state awareness.
🔬 How It Works
Hurst Exponent Computation:
Calculates log returns over the lookback period to derive the rescaled range (R/S) ratio.
Normalizes to a 0-1 value, where >0.55 indicates trending, <0.45 mean-reverting, and in-between random.
Length Adaptation:
Maps normalized Hurst to an MA length via a power function, clamping between min and max.
Applies the selected MA type to close prices using this dynamic length.
Visualization and Signals:
Plots the MA with regime colors, adds ATR-based bands, and fills areas for trend strength.
Triggers alerts on regime changes or band crosses, with the info panel suggesting strategies like momentum riding in trends.
💡 Note:
For optimal results, backtest settings on your preferred assets and combine with volume or momentum indicators. Remember, no indicator guarantees profits—use with proper risk management. Access premium features and support at PhenLabs.
Time-Decaying Percentile Oscillator [BackQuant]Time-Decaying Percentile Oscillator
1. Big-picture idea
Traditional percentile or stochastic oscillators treat every bar in the look-back window as equally important. That is fine when markets are slow, but if volatility regime changes quickly yesterday’s print should matter more than last month’s. The Time-Decaying Percentile Oscillator attempts to fix that blind spot by assigning an adjustable weight to every past price before it is ranked. The result is a percentile score that “breathes” with market tempo much faster to flag new extremes yet still smooth enough to ignore random noise.
2. What the script actually does
Build a weight curve
• You pick a look-back length (default 28 bars).
• You decide whether weights fall Linearly , Exponentially , by Power-law or Logarithmically .
• A decay factor (lower = faster fade) shapes how quickly the oldest price loses influence.
• The array is normalised so all weights still sum to 1.
Rank prices by weighted mass
• Every close in the window is paired with its weight.
• The pairs are sorted from low to high.
• The cumulative weight is walked until it equals your chosen percentile level (default 50 = median).
• That price becomes the Time-Decayed Percentile .
Find dispersion with robust statistics
• Instead of a fragile standard deviation the script measures weighted Median-Absolute-Deviation about the new percentile.
• You multiply that deviation by the Deviation Multiplier slider (default 1.0) to get a non-parametric volatility band.
Build an adaptive channel
• Upper band = percentile + (multiplier × deviation)
• Lower band = percentile – (multiplier × deviation)
Normalise into a 0-100 oscillator
• The current close is mapped inside that band:
0 = lower band, 50 = centre, 100 = upper band.
• If the channel squeezes, tiny moves still travel the full scale; if volatility explodes, it automatically widens.
Optional smoothing
• A second-stage moving average (EMA, SMA, DEMA, TEMA, etc.) tames the jitter.
• Length 22 EMA by default—change it to tune reaction speed.
Threshold logic
• Upper Threshold 70 and Lower Threshold 30 separate standard overbought/oversold states.
• Extreme bands 85 and 15 paint background heat when aggressive fade or breakout trades might trigger.
Divergence engine
• Looks back twenty bars.
• Flags Bullish divergence when price makes a lower low but oscillator refuses to confirm (value < 40).
• Flags Bearish divergence when price prints a higher high but oscillator stalls (value > 60).
3. Component walk-through
• Source – Any price series. Close by default, switch to typical price or custom OHLC4 for futures spreads.
• Look-back Period – How many bars to rank. Short = faster, long = slower.
• Base Percentile Level – 50 shows relative position around the median; set to 25 / 75 for quartile tracking or 90 / 10 for extreme tails.
• Deviation Multiplier – Higher values widen the dynamic channel, lowering whipsaw but delaying signals.
• Decay Settings
– Type decides the curve shape. Exponential (default 1.16) mimics EMA logic.
– Factor < 1 shrinks influence faster; > 1 spreads influence flatter.
– Toggle Enable Time Decay off to compare with classic equal-weight stochastic.
• Smoothing Block – Choose one of seven MA flavours plus length.
• Thresholds – Overbought / Oversold / Extreme levels. Push them out when working on very mean-reverting assets like FX; pull them in for trend monsters like crypto.
• Display toggles – Show or hide threshold lines, extreme filler zones, bar colouring, divergence labels.
• Colours – Bullish green, bearish red, neutral grey. Every gradient step is automatically blended to generate a heat map across the 0-100 range.
4. How to read the chart
• Oscillator creeping above 70 = market auctioning near the top of its adaptive range.
• Fast poke above 85 with no follow-through = exhaustion fade candidate.
• Slow grind that lives above 70 for many bars = valid bullish trend, not a fade.
• Cross back through 50 shows balance has shifted; treat it like a micro trend change.
• Divergence arrows add extra confidence when you already see two-bar reversal candles at range extremes.
• Background shading (semi-transparent red / green) warns of extreme states and throttles your position size.
5. Practical trading playbook
Mean-reversion scalps
1. Wait for oscillator to reach your desired OB/ OS levels
2. Check the slope of the smoothing MA—if it is flattening the squeeze is mature.
3. Look for a one- or two-bar reversal pattern.
4. Enter against the move; first target = midline 50, second target = opposite threshold.
5. Stop loss just beyond the extreme band.
Trend continuation pullbacks
1. Identify a clean directional trend on the price chart.
2. During the trend, TDP will oscillate between midline and extreme of that side.
3. Buy dips when oscillator hits OS levels, and the same for OB levels & shorting
4. Exit when oscillator re-tags the same-side extreme or prints divergence.
Volatility regime filter
• Use the Enable Time Decay switch as a regime test.
• If equal-weight oscillator and decayed oscillator diverge widely, market is entering a new volatility regime—tighten stops and trade smaller.
Divergence confirmation for other indicators
• Pair TDP divergence arrows with MACD histogram or RSI to filter false positives.
• The weighted nature means TDP often spots divergence a bar or two earlier than standard RSI.
Swing breakout strategy
1. During consolidation, band width compresses and oscillator oscillates around 50.
2. Watch for sudden expansion where oscillator blasts through extreme bands and stays pinned.
3. Enter with momentum in breakout direction; trail stop behind upper or lower band as it re-expands.
6. Customising decay mathematics
Linear – Each older bar loses the same fixed amount of influence. Intuitive and stable; good for slow swing charts.
Exponential – Influence halves every “decay factor” steps. Mirrors EMA thinking and is fastest to react.
Power-law – Mid-history bars keep more authority than exponential but oldest data still fades. Handy for commodities where seasonality matters.
Logarithmic – The gentlest curve; weight drops sharply at first then levels off. Mimics how traders remember dramatic moves for weeks but forget ordinary noise quickly.
Turn decay off to verify the tool’s added value; most users never switch back.
7. Alert catalogue
• TD Overbought / TD Oversold – Cross of regular thresholds.
• TD Extreme OB / OS – Breach of danger zones.
• TD Bullish / Bearish Divergence – High-probability reversal watch.
• TD Midline Cross – Momentum shift that often precedes a window where trend-following systems perform.
8. Visual hygiene tips
• If you already plot price on a dark background pick Bullish Color and Bearish Color default; change to pastel tones for light themes.
• Hide threshold lines after you memorise the zones to declutter scalping layouts.
• Overlay mode set to false so the oscillator lives in its own panel; keep height about 30 % of screen for best resolution.
9. Final notes
Time-Decaying Percentile Oscillator marries robust statistical ranking, adaptive dispersion and decay-aware weighting into a simple oscillator. It respects both recent order-flow shocks and historical context, offers granular control over responsiveness and ships with divergence and alert plumbing out of the box. Bolt it onto your price action framework, trend-following system or volatility mean-reversion playbook and see how much sooner it recognises genuine extremes compared to legacy oscillators.
Backtest thoroughly, experiment with decay curves on each asset class and remember: in trading, timing beats timidity but patience beats impulse. May this tool help you find that edge.
