Stablecoin Total Index V3**Stablecoin Total Index V4 - Full History + Full Coverage**
This indicator provides the **best of both worlds**: long historical data AND complete stablecoin coverage.
**How it works:**
- **Before May 2025:** Manual sum of 35 major stablecoins (~90% coverage)
- **After May 2025:** Switches to STABLE.C index (100 stablecoins, 100% coverage)
**Why this approach?**
TradingView's official STABLE.C index was only created on May 19, 2025. This indicator gives you **years of historical data** going back to 2017-2018, then seamlessly transitions to the official index for complete accuracy.
**Note:** There is a ~$30B jump at the May 2025 transition point. This is NOT an error - it represents the ~65 smaller stablecoins that are included in STABLE.C but don't have individual CRYPTOCAP symbols for manual tracking.
**Pre-May 2025 Coverage (35 stablecoins):**
- **Tier 1:** USDT, USDC
- **Tier 2:** DAI, USDe, USDS, FDUSD
- **Tier 3:** TUSD, USDP, GUSD, FRAX, PYUSD, LUSD, BUSD
- **Tier 4 (2024-2025):** USD1, RLUSD, GHO, crvUSD, sUSDe, USDY, USDM
- **Tier 5 (Euro):** EURC, EURT, EURS
- **Tier 6 (DeFi):** USDD, MIM, DOLA, OUSD, alUSD, sUSD, cUSD
- **Tier 7:** HUSD, USDX, USTC
- **Gold-Backed:** PAXG, XAUT
**Post-May 2025:** Full STABLE.C (100 stablecoins)
**Features:**
- Green/Red color based on direction
- 20-period SMA
- Reference lines at $100B, $200B, $300B
**Best used on Daily timeframe or higher.**
"马斯克+100万"に関するスクリプトを検索
Momentum Grid 2.1 + Top Stocks📊 MOMENTUM GRID 2.1 + TOP STOCKS
Overview
A multi-timeframe confirmation system specifically designed for NIFTY 50 and BANK NIFTY index options trading. This script combines 8 independent technical indicators into a weighted scoring model to generate high-probability CE (Call) and PE (Put) signals, while simultaneously tracking the top 5 constituent stocks for sector-wide momentum validation.
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🎯 Core Methodology
1. 8-Factor Confirmation System
Unlike traditional single-indicator approaches, this script requires multiple confirmations before generating signals. Each factor votes independently:
Trend Alignment (3 votes):
• C1: Price above/below EMA 9 (immediate trend)
• C2: EMA 9 above/below EMA 20 (short-term momentum)
• C3: EMA 20 above/below EMA 50 (intermediate trend)
Oscillator Confirmation (3 votes):
• C4: RSI above/below 50 (momentum strength)
• C5: Stochastic K above/below D (entry timing)
• C6: MACD Histogram positive/negative (momentum direction)
Advanced Momentum (2 votes):
• C7: Parabolic SAR position (trend continuation)
• C8: Squeeze Momentum direction (volatility expansion)
Mathematical Logic:
Bullish Score = C1 + C2 + C3 + C4 + C5 + C6 + C7 + C8
Signal Triggered when Score ≥ Threshold (default: 5/8)
Why This Works: By requiring 5+ confirmations, the script filters out false signals that occur when only 1-2 indicators align by chance. This dramatically reduces whipsaws in choppy markets.
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📈 Constituent Stock Analysis System
Real-Time Top 5 Stocks Tracking
The script fetches live data from the most heavily-weighted stocks in the selected index:
NIFTY 50 Constituents:
• Reliance Industries
• HDFC Bank
• Infosys
• ICICI Bank
• TCS
BANK NIFTY Constituents:
• HDFC Bank
• ICICI Bank
• Kotak Mahindra Bank
• State Bank of India
• Axis Bank
Stock Scoring Algorithm (0-6 Scale):
For each stock, the script calculates a momentum score based on:
1. Price vs EMA 9 position
2. EMA 9 vs EMA 20 relationship
3. EMA 20 vs EMA 50 hierarchy
4. RSI above/below 50
5. MACD histogram direction
6. Intraday price change direction
Signal Interpretation:
• 🚀🔥 Strong Bullish: Score ≥5 + Day Change >0.5%
• ⚠️❄️ Strong Bearish: Score ≤1 + Day Change <-0.5%
• 📈 Moderate Bullish: Score ≥3 + Positive change
• 📉 Moderate Bearish: Score ≤3 + Negative change
Why Track Constituents?
Index options are a weighted average of their components. When 4 out of 5 top stocks show strong bullish signals but the index signal is neutral, it indicates:
• Sector rotation is happening
• Underlying strength not yet reflected in index
• Early warning for potential index breakout
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🎨 Visual Dashboard System
1. Main Momentum Grid (Middle Right)
Real-time status of all 8 confirmation factors:
• Individual indicator values
• Bullish/Bearish status per indicator
• Cumulative Bull Score and Bear Score
• Visual color coding (Green = Bullish, Red = Bearish)
2. Top Stocks Status Panel (Top Right)
Live tracking table showing:
• LTP (Last Traded Price): Current stock price
• Day Change %: Intraday movement from open
• Status: Overall bullish/bearish trend
• EMA Status: Position relative to EMA 9
• Signal Emoji: Visual strength indicator
3. Scenario Guide (Bottom Right)
Auto-calculates trade parameters based on current signal:
• Side: CE (Call) or PE (Put) recommendation
• Strike Reference: Current index price
• Trigger Level: Entry confirmation level (high/low of signal bar)
• Risk Limit: Stop loss using 1.5x ATR
• Price Objective: Target using 2.5x ATR
ATR-Based Risk Management: Average True Range (14-period) adapts stop-loss and targets to current volatility, ensuring consistent risk-reward ratios across different market conditions.
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🚨 Signal Generation Logic
CE (Call) Signal Triggers When:
1. Bullish Score ≥ Threshold (5/8 default)
2. Previous bar Bullish Score < Threshold
3. Confirmation candle closes above EMA 9
4. Background turns light green
PE (Put) Signal Triggers When:
1. Bearish Score ≥ Threshold (5/8 default)
2. Previous bar Bearish Score < Threshold
3. Confirmation candle closes below EMA 9
4. Background turns light red
Signal Validation: Labels appear only when a new qualifying bar completes, preventing repainting. The tooltip shows the exact score and entry price for record-keeping.
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🔧 Customization Options
Parameter Purpose Recommendation
Index Selection Choose NIFTY 50 or BANK NIFTY Match to your trading instrument
EMA Periods Adjust trend sensitivity Default (9/20/50/100) suits 5-15 min
Signal Threshold Min confirmations required 5/8 (balanced), 6/8 (conservative)
RSI Length Momentum calculation period 14 (standard), 21 (smoother)
MACD Settings Fast/Slow/Signal periods 12/26/9 (industry standard)
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📊 Technical Indicator Details
Exponential Moving Averages (EMA)
• Why EMA vs SMA: Exponential weighting gives more importance to recent price action, making it more responsive to trend changes in fast-moving index options.
Relative Strength Index (RSI)
• Measures momentum on 0-100 scale
• 50 level acts as bull/bear dividing line
• Used for confirmation, not overbought/oversold
Stochastic Oscillator
• Compares closing price to recent range
• K line crossing above D line = bullish momentum shift
• Sensitive to short-term reversals
MACD (Moving Average Convergence Divergence)
• Histogram shows momentum acceleration/deceleration
• Positive histogram = increasing bullish momentum
• Used as tiebreaker when other signals conflict
Parabolic SAR
• Tracks stop-and-reverse points
• Dots below price = uptrend, above = downtrend
• Adds trend-following confirmation
Squeeze Momentum
• Identifies periods of low volatility (consolidation)
• Bollinger Bands inside Keltner Channels = "squeeze"
• Positive momentum during squeeze = bullish breakout setup
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💡 What Makes This Script Unique
1. Index-Specific Design: Unlike generic multi-timeframe indicators, this is purpose-built for NIFTY/BANKNIFTY options with constituent stock correlation analysis.
2. Multi-Layer Validation: Combines price action (EMAs), momentum (RSI/Stoch/MACD), and volatility (Squeeze) for comprehensive market assessment.
3. Smart Constituent Tracking: Automatically switches stock universe based on selected index, providing sector-level context that single-chart indicators miss.
4. Adaptive Risk Management: ATR-based stop-loss and targets adjust to market volatility automatically, unlike fixed-point systems.
5. No Repainting: All calculations use confirmed bars with lookahead=barmerge.lookahead_off parameter, ensuring historical backtesting accuracy.
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📚 Best Practices
Timeframe Selection:
• 5 min: Scalping (high frequency, tight stops)
• 15 min: Intraday swing trades (balanced)
• 1 hour: Positional option trades (overnight holds)
Trade Execution:
1. Wait for CE/PE label to appear
2. Check Top Stocks Status - look for 3+ stocks confirming index direction
3. Verify Scenario Guide shows acceptable risk-reward (min 1:1.5)
4. Enter on next candle open or use trigger level for limit orders
5. Place stop-loss at "Risk Limit" level
6. Scale out at "Price Objective" or trail with Parabolic SAR
False Signal Filters:
• Avoid signals during first 15 minutes of market open (high volatility)
• Skip signals when Top Stocks show conflicting directions (3 bull, 2 bear)
• Increase threshold to 6/8 during major news events
• Disable trading 30 minutes before important announcements
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⚠️ Limitations & Considerations
• Index Options Specific: Optimized for NIFTY/BANKNIFTY - may need recalibration for other instruments
• Not Suitable for Trending Markets: Works best in swing/range conditions; reduce threshold in strong trends
• Constituent Data Dependency: Relies on accurate real-time stock data; verify broker data quality
• Options Greeks Ignored: Script doesn't account for theta decay, IV changes - user must manage option selection
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🔔 Built-In Alerts
Set alerts for:
• CE Signal Generated: Bullish score crosses threshold
• PE Signal Generated: Bearish score crosses threshold
Alert messages include ticker symbol and entry price for quick execution.
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📈 Performance Optimization Tips
1. Score Correlation Check: If Bull Score and Bear Score are both high (6+/8), market is conflicted - wait for resolution.
2. Stock Divergence Strategy: When 4/5 stocks are bullish but index shows PE signal, it often indicates a false breakdown - counter-trend opportunity.
3. Squeeze Breakout Combo: Strongest signals occur when Squeeze changes from "ON" to "OFF" simultaneously with CE/PE trigger.
4. EMA Stacking: Maximum confidence signals have all three EMAs in proper order (9>20>50 for bull, reverse for bear).
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🎓 Educational Context
This methodology synthesizes:
• Multi-Timeframe Analysis: EMAs represent different trend horizons
• Oscillator Convergence: Multiple momentum tools reduce false positives
• Index Arbitrage Concepts: Constituent tracking exploits pricing inefficiencies
• Adaptive Volatility: ATR-based risk scales with market conditions
The 8-factor system mirrors institutional decision frameworks where analysts require consensus across multiple models before position changes.
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📋 Quick Reference
Bullish Setup Checklist: ✅ Bull Score ≥ 5/8
✅ Green background color
✅ 3+ top stocks showing 📈 or 🚀
✅ Price above EMA 9
✅ MACD Histogram positive
Bearish Setup Checklist: ✅ Bear Score ≥ 5/8
✅ Red background color
✅ 3+ top stocks showing 📉 or ⚠️
✅ Price below EMA 9
✅ MACD Histogram negative
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⚖️ Disclaimer
This indicator is a decision support tool, not an automated trading system. Index options involve substantial risk and can result in total loss of premium paid. The constituent stock analysis provides context but does not guarantee index price movement. Users must:
• Understand options Greeks (delta, theta, vega)
• Use proper position sizing (max 2-3% capital per trade)
• Never trade based on signals alone without market context
• Comply with SEBI regulations and broker policies
Past performance of signals does not guarantee future results.
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Version: Pine Script v6
Supported Indices: NIFTY 50, BANK NIFTY
Resource Usage: Moderate (Multi-security data requests)
Update Frequency: Real-time on current timeframe
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For support or suggestions, please comment below. If this script helps your trading, please like and follow for updates! 🚀📊
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
📊 Core Components & Methodology
🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
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📊 Core Components & Methodology
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
• Dividing the price range into configurable rows (default: 20)
• Accumulating volume at each price level over a lookback period (default: 50 bars)
• Separating buy volume (green bars close > open) from sell volume (red bars)
• Identifying three critical levels:
o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
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2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
• Bar Delta: Difference between buy and sell volume per candle
• Cumulative Delta: Sum of all bar deltas - shows net directional pressure
• Delta Moving Average: Smoothed delta (20-period) to identify trend
• Delta Divergences:
o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom)
o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top)
How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
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3. Large Order Detection
Identifies institutional-sized orders in real-time:
• Compares current bar volume to 20-period moving average
• Flags orders exceeding 2.5x average volume (configurable multiplier)
• Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
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🎯 Trading Signal Logic
Combined Setup Criteria
The script generates SHORT and LONG signals when multiple conditions align:
SHORT Signal Requirements:
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
LONG Signal Requirements:
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
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🔧 Customization Options
Setting - Purpose - Recommendation
Volume Profile Rows - Granularity of level detection - 20 (balanced)
Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing)
Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative)
HVN Threshold - Resistance zone detection - 1.3 (default)
LVN Threshold - Target zone identification - 0.6 (default)
Divergence Lookback - Pivot detection period - 5 bars (responsive)
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📈 Dashboard Indicators
The real-time panel displays:
• POC: Current Point of Control price
• Location: Whether price is at HVN resistance
• Orders: Current large buy/sell activity
• Cumulative Δ: Net order flow value + trend direction
• Divergence: Active bullish/bearish divergences
• Bar Strength: % of candle volume that's directional (>65% = strong)
• SETUP: Current trade signal (LONG/SHORT/WAIT)
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🎨 Visual System
• Yellow POC Line: Highest volume level - primary pivot
• Blue Value Area Box: Fair value zone (VAH to VAL)
• Red HVN Zones: Resistance/support from institutional accumulation
• Green LVN Zones: Low-liquidity targets for quick moves
• Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution
• Triangles: LONG (green up) and SHORT (red down) entry signals
• Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish)
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💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection
2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones
3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction
4. Provides context, not just signals - the dashboard helps you understand why a setup is forming
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⚙️ Best Practices
Timeframes:
• 5-15 min: Scalping (use 30-50 bar lookback)
• 1-4 hour: Swing trading (use 100-200 bar lookback)
Risk Management:
• Enter on signal candle close
• Stop loss: Beyond nearest HVN/LVN zone
• Target 1: Next LVN level
• Target 2: Opposite value area boundary
Filters:
• Avoid signals during major news events
• Require bar delta strength >65% for aggressive entries
• Wait for delta MA cross confirmation in ranging markets
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🚨 Alerts Available
• Long Setup Trigger
• Short Setup Trigger
• Bullish/Bearish Divergence Detection
• Large Buy/Sell Order Execution
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📚 Educational Context
This methodology is based on principles used by professional order flow traders:
• Market Profile Theory: Volume distribution reveals fair value
• Tape Reading: Large orders show institutional intent
• Auction Theory: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
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⚠️ Disclaimer
This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
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Version: 6 (Pine Script)
Type: Overlay + Separate Pane (Delta Panel)
Resource Usage: Moderate (500 bars history, 500 lines/boxes)
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For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
- Dividing the price range into configurable rows (default: 20)
- Accumulating volume at each price level over a lookback period (default: 50 bars)
- Separating buy volume (green bars close > open) from sell volume (red bars)
- Identifying three critical levels:
- POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
- VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
- HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
- LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
---
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
- **Bar Delta**: Difference between buy and sell volume per candle
- **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure
- **Delta Moving Average**: Smoothed delta (20-period) to identify trend
- **Delta Divergences**:
- **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom)
- **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top)
**How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
---
### 3. **Large Order Detection**
Identifies **institutional-sized orders** in real-time:
- Compares current bar volume to 20-period moving average
- Flags orders exceeding 2.5x average volume (configurable multiplier)
- Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
**Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
---
## 🎯 Trading Signal Logic
### Combined Setup Criteria
The script generates **SHORT** and **LONG** signals when multiple conditions align:
**SHORT Signal Requirements:**
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
**LONG Signal Requirements:**
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
---
## 🔧 Customization Options
| Setting | Purpose | Recommendation |
|---------|---------|----------------|
| **Volume Profile Rows** | Granularity of level detection | 20 (balanced) |
| **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) |
| **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) |
| **HVN Threshold** | Resistance zone detection | 1.3 (default) |
| **LVN Threshold** | Target zone identification | 0.6 (default) |
| **Divergence Lookback** | Pivot detection period | 5 bars (responsive) |
---
## 📈 Dashboard Indicators
The real-time panel displays:
- **POC**: Current Point of Control price
- **Location**: Whether price is at HVN resistance
- **Orders**: Current large buy/sell activity
- **Cumulative Δ**: Net order flow value + trend direction
- **Divergence**: Active bullish/bearish divergences
- **Bar Strength**: % of candle volume that's directional (>65% = strong)
- **SETUP**: Current trade signal (LONG/SHORT/WAIT)
---
## 🎨 Visual System
- **Yellow POC Line**: Highest volume level - primary pivot
- **Blue Value Area Box**: Fair value zone (VAH to VAL)
- **Red HVN Zones**: Resistance/support from institutional accumulation
- **Green LVN Zones**: Low-liquidity targets for quick moves
- **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution
- **Triangles**: LONG (green up) and SHORT (red down) entry signals
- **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish)
---
## 💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection
2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones
3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction
4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming
---
## ⚙️ Best Practices
**Timeframes:**
- 5-15 min: Scalping (use 30-50 bar lookback)
- 1-4 hour: Swing trading (use 100-200 bar lookback)
**Risk Management:**
- Enter on signal candle close
- Stop loss: Beyond nearest HVN/LVN zone
- Target 1: Next LVN level
- Target 2: Opposite value area boundary
**Filters:**
- Avoid signals during major news events
- Require bar delta strength >65% for aggressive entries
- Wait for delta MA cross confirmation in ranging markets
---
## 🚨 Alerts Available
- Long Setup Trigger
- Short Setup Trigger
- Bullish/Bearish Divergence Detection
- Large Buy/Sell Order Execution
---
## 📚 Educational Context
This methodology is based on principles used by professional order flow traders:
- **Market Profile Theory**: Volume distribution reveals fair value
- **Tape Reading**: Large orders show institutional intent
- **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
---
## ⚠️ Disclaimer
This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
---
**Version**: 6 (Pine Script)
**Type**: Overlay + Separate Pane (Delta Panel)
**Resource Usage**: Moderate (500 bars history, 500 lines/boxes)
---
*For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Trend TraderMost trend indicators don’t offer continuation signals or accurate bounce points, so I created this indicator that uses one of the most common trading levels (EMAs). This indicator uses the 50, 100, and 200 EMAs along with WaveTrend signals to trade trends. Buy Signals are filtered so that they only show up when the 100 EMA is above the 200. And Inverse for Sell Signals.
This indicator works well with both Stocks and Crypto. Default settings work best on 15 min, 1H, 2H, and 4H.
(Chart examples are using Heikin Ashi Candles, on Log Scale.)
*Buy and Sell Signals do not repaint.
Settings:
- Ability to show all buy and sell signals regardless of trend.
- To change the sensitivity of the buy and sell signals, change the “Average Length”
- (The lower the number the more sensitive, the higher the number the less they pop up)
- Ability to change EMA Lengths
imgur.com
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!
XAUUSD Multi-Timeframe Bias Scanner🎯 Purpose & Overview
This is a sophisticated trading indicator that analyzes XAUUSD (Gold) across 5 different timeframes simultaneously to determine market bias and trend direction.
⚙️ Core Components
2. Bias Calculation Engine
The heart of the indicator uses 5 technical factors to score each timeframe:
Technical Factors (Weighted):
Moving Average Alignment (30 points)
Bullish: EMA(9) > EMA(21) > EMA(50)
Bearish: EMA(9) < EMA(21) < EMA(50)
Price vs MA Position (20 points)
Score increases when price above MAs
Score decreases when price below MAs
RSI Momentum (20 points)
Bullish: RSI > 60 or > 50
Bearish: RSI < 40 or < 50
MACD Signals (15 points)
Bullish: MACD line > Signal line AND > 0
Bearish: MACD line < Signal line AND < 0
Volume Confirmation (15 points)
Volume spikes with price movement add confirmation
📊 Timeframe Analysis
Five Timeframes Monitored:
5-minute - Short-term noise (10% weight)
15-minute - Intraday direction (15% weight)
1-hour - Key intraday bias (25% weight)
4-hour - Primary directional bias (30% weight)
1-day - Overall trend context (20% weight)
Bias Scoring System:
0-100 Scale (50 = Neutral)
STRONG BULLISH: ≥70 (Green)
BULLISH: 55-69 (Lime)
NEUTRAL: 46-54 (Gray)
BEARISH: 31-45 (Orange)
STRONG BEARISH: ≤30 (Red)
🎨 Visual Features
1. Comprehensive Table Display
pinescript
var table biasTable = table.new(position.top_right, 3, 7, ...)
Shows a color-coded table with:
Timeframe name
Numerical bias score (0-100)
Strength description with color coding
2. Chart Visual Indicators
Background coloring based on overall bias
Label markers for strong bullish/bearish conditions
Real-time label showing all timeframe scores
3. Alert System
Triggers when overall bias crosses 70 (bullish) or 30 (bearish)
Configurable with sound options
🔄 How It Processes Data
Data Flow:
Requests security data for each timeframe using request.security()
Calculates technical indicators for each TF separately
Scores each TF based on 5 technical factors
Computes weighted overall bias
Updates visual displays and checks alert conditions
💡 Trading Applications
Bullish Scenarios:
Multiple timeframes show bullish alignment
Higher timeframe bias supports lower timeframe direction
Overall score > 70 indicates strong bullish conviction
Bearish Scenarios:
Multiple timeframes show bearish alignment
Higher timeframe bias confirms lower timeframe moves
Overall score < 30 indicates strong bearish conviction
Conflict Detection:
When timeframes show conflicting biases
Caution required - market may be consolidating
Wait for alignment before taking trades
🎚️ Customization Options
Users can modify:
Timeframe weights
Technical indicator parameters
Alert thresholds
Visual display preferences
Scoring sensitivity
📈 XAUUSD Specific Optimizations
The indicator considers Gold's unique characteristics:
High volatility periods
ATR-based volatility adjustments
Volume confirmation for breakouts
Multiple timeframe confirmation for trend reliability
This creates a powerful tool for identifying high-probability trade setups in XAUUSD by ensuring traders have a complete multi-timeframe perspective before entering positions.
Naveen Prabhu with EMA//@version=6
indicator('Naveen Prabhu with EMA', overlay = true, max_labels_count = 500, max_lines_count = 500, max_boxes_count = 500)
a = input(2, title = 'Key Vaule. \'This changes the sensitivity\'')
c = input(5, title = 'ATR Period')
h = input(false, title = 'Signals from Heikin Ashi Candles')
BULLISH_LEG = 1
BEARISH_LEG = 0
BULLISH = +1
BEARISH = -1
GREEN = #089981
RED = #F23645
BLUE = #2157f3
GRAY = #878b94
MONO_BULLISH = #b2b5be
MONO_BEARISH = #5d606b
HISTORICAL = 'Historical'
PRESENT = 'Present'
COLORED = 'Colored'
MONOCHROME = 'Monochrome'
ALL = 'All'
BOS = 'BOS'
CHOCH = 'CHoCH'
TINY = size.tiny
SMALL = size.small
NORMAL = size.normal
ATR = 'Atr'
RANGE = 'Cumulative Mean Range'
CLOSE = 'Close'
HIGHLOW = 'High/Low'
SOLID = '⎯⎯⎯'
DASHED = '----'
DOTTED = '····'
SMART_GROUP = 'Smart Money Concepts'
INTERNAL_GROUP = 'Real Time Internal Structure'
SWING_GROUP = 'Real Time Swing Structure'
BLOCKS_GROUP = 'Order Blocks'
EQUAL_GROUP = 'EQH/EQL'
GAPS_GROUP = 'Fair Value Gaps'
LEVELS_GROUP = 'Highs & Lows MTF'
ZONES_GROUP = 'Premium & Discount Zones'
modeTooltip = 'Allows to display historical Structure or only the recent ones'
styleTooltip = 'Indicator color theme'
showTrendTooltip = 'Display additional candles with a color reflecting the current trend detected by structure'
showInternalsTooltip = 'Display internal market structure'
internalFilterConfluenceTooltip = 'Filter non significant internal structure breakouts'
showStructureTooltip = 'Display swing market Structure'
showSwingsTooltip = 'Display swing point as labels on the chart'
showHighLowSwingsTooltip = 'Highlight most recent strong and weak high/low points on the chart'
showInternalOrderBlocksTooltip = 'Display internal order blocks on the chart\n\nNumber of internal order blocks to display on the chart'
showSwingOrderBlocksTooltip = 'Display swing order blocks on the chart\n\nNumber of internal swing blocks to display on the chart'
orderBlockFilterTooltip = 'Method used to filter out volatile order blocks \n\nIt is recommended to use the cumulative mean range method when a low amount of data is available'
orderBlockMitigationTooltip = 'Select what values to use for order block mitigation'
showEqualHighsLowsTooltip = 'Display equal highs and equal lows on the chart'
equalHighsLowsLengthTooltip = 'Number of bars used to confirm equal highs and equal lows'
equalHighsLowsThresholdTooltip = 'Sensitivity threshold in a range (0, 1) used for the detection of equal highs & lows\n\nLower values will return fewer but more pertinent results'
showFairValueGapsTooltip = 'Display fair values gaps on the chart'
fairValueGapsThresholdTooltip = 'Filter out non significant fair value gaps'
fairValueGapsTimeframeTooltip = 'Fair value gaps timeframe'
fairValueGapsExtendTooltip = 'Determine how many bars to extend the Fair Value Gap boxes on chart'
showPremiumDiscountZonesTooltip = 'Display premium, discount, and equilibrium zones on chart'
modeInput = input.string( HISTORICAL, 'Mode', group = SMART_GROUP, tooltip = modeTooltip, options = )
styleInput = input.string( COLORED, 'Style', group = SMART_GROUP, tooltip = styleTooltip,options = )
showTrendInput = input( false, 'Color Candles', group = SMART_GROUP, tooltip = showTrendTooltip)
showInternalsInput = input( false, 'Show Internal Structure', group = INTERNAL_GROUP, tooltip = showInternalsTooltip)
showInternalBullInput = input.string( ALL, 'Bullish Structure', group = INTERNAL_GROUP, inline = 'ibull', options = )
internalBullColorInput = input( GREEN, '', group = INTERNAL_GROUP, inline = 'ibull')
showInternalBearInput = input.string( ALL, 'Bearish Structure' , group = INTERNAL_GROUP, inline = 'ibear', options = )
internalBearColorInput = input( RED, '', group = INTERNAL_GROUP, inline = 'ibear')
internalFilterConfluenceInput = input( false, 'Confluence Filter', group = INTERNAL_GROUP, tooltip = internalFilterConfluenceTooltip)
internalStructureSize = input.string( TINY, 'Internal Label Size', group = INTERNAL_GROUP, options = )
showStructureInput = input( false, 'Show Swing Structure', group = SWING_GROUP, tooltip = showStructureTooltip)
showSwingBullInput = input.string( ALL, 'Bullish Structure', group = SWING_GROUP, inline = 'bull', options = )
swingBullColorInput = input( GREEN, '', group = SWING_GROUP, inline = 'bull')
showSwingBearInput = input.string( ALL, 'Bearish Structure', group = SWING_GROUP, inline = 'bear', options = )
swingBearColorInput = input( RED, '', group = SWING_GROUP, inline = 'bear')
swingStructureSize = input.string( SMALL, 'Swing Label Size', group = SWING_GROUP, options = )
showSwingsInput = input( false, 'Show Swings Points', group = SWING_GROUP, tooltip = showSwingsTooltip,inline = 'swings')
swingsLengthInput = input.int( 50, '', group = SWING_GROUP, minval = 10, inline = 'swings')
showHighLowSwingsInput = input( false, 'Show Strong/Weak High/Low',group = SWING_GROUP, tooltip = showHighLowSwingsTooltip)
showInternalOrderBlocksInput = input( true, 'Internal Order Blocks' , group = BLOCKS_GROUP, tooltip = showInternalOrderBlocksTooltip, inline = 'iob')
internalOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'iob')
showSwingOrderBlocksInput = input( true, 'Swing Order Blocks', group = BLOCKS_GROUP, tooltip = showSwingOrderBlocksTooltip, inline = 'ob')
swingOrderBlocksSizeInput = input.int( 5, '', group = BLOCKS_GROUP, minval = 1, maxval = 20, inline = 'ob')
orderBlockFilterInput = input.string( 'Atr', 'Order Block Filter', group = BLOCKS_GROUP, tooltip = orderBlockFilterTooltip, options = )
orderBlockMitigationInput = input.string( HIGHLOW, 'Order Block Mitigation', group = BLOCKS_GROUP, tooltip = orderBlockMitigationTooltip, options = )
internalBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Internal Bullish OB', group = BLOCKS_GROUP)
internalBearishOrderBlockColor = input.color(color.new(#f77c80, 80), 'Internal Bearish OB', group = BLOCKS_GROUP)
swingBullishOrderBlockColor = input.color(color.new(GREEN, 80), 'Bullish OB', group = BLOCKS_GROUP)
swingBearishOrderBlockColor = input.color(color.new(#b22833, 80), 'Bearish OB', group = BLOCKS_GROUP)
showEqualHighsLowsInput = input( false, 'Equal High/Low', group = EQUAL_GROUP, tooltip = showEqualHighsLowsTooltip)
equalHighsLowsLengthInput = input.int( 3, 'Bars Confirmation', group = EQUAL_GROUP, tooltip = equalHighsLowsLengthTooltip, minval = 1)
equalHighsLowsThresholdInput = input.float( 0.1, 'Threshold', group = EQUAL_GROUP, tooltip = equalHighsLowsThresholdTooltip, minval = 0, maxval = 0.5, step = 0.1)
equalHighsLowsSizeInput = input.string( TINY, 'Label Size', group = EQUAL_GROUP, options = )
showFairValueGapsInput = input( false, 'Fair Value Gaps', group = GAPS_GROUP, tooltip = showFairValueGapsTooltip)
fairValueGapsThresholdInput = input( true, 'Auto Threshold', group = GAPS_GROUP, tooltip = fairValueGapsThresholdTooltip)
fairValueGapsTimeframeInput = input.timeframe('', 'Timeframe', group = GAPS_GROUP, tooltip = fairValueGapsTimeframeTooltip)
fairValueGapsBullColorInput = input.color(color.new(#00ff68, 70), 'Bullish FVG' , group = GAPS_GROUP)
fairValueGapsBearColorInput = input.color(color.new(#ff0008, 70), 'Bearish FVG' , group = GAPS_GROUP)
fairValueGapsExtendInput = input.int( 1, 'Extend FVG', group = GAPS_GROUP, tooltip = fairValueGapsExtendTooltip, minval = 0)
showDailyLevelsInput = input( false, 'Daily', group = LEVELS_GROUP, inline = 'daily')
dailyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'daily', options = )
dailyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'daily')
showWeeklyLevelsInput = input( false, 'Weekly', group = LEVELS_GROUP, inline = 'weekly')
weeklyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'weekly', options = )
weeklyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'weekly')
showMonthlyLevelsInput = input( false, 'Monthly', group = LEVELS_GROUP, inline = 'monthly')
monthlyLevelsStyleInput = input.string( SOLID, '', group = LEVELS_GROUP, inline = 'monthly', options = )
monthlyLevelsColorInput = input( BLUE, '', group = LEVELS_GROUP, inline = 'monthly')
showPremiumDiscountZonesInput = input( false, 'Premium/Discount Zones', group = ZONES_GROUP , tooltip = showPremiumDiscountZonesTooltip)
premiumZoneColorInput = input.color( RED, 'Premium Zone', group = ZONES_GROUP)
equilibriumZoneColorInput = input.color( GRAY, 'Equilibrium Zone', group = ZONES_GROUP)
discountZoneColorInput = input.color( GREEN, 'Discount Zone', group = ZONES_GROUP)
type alerts
bool internalBullishBOS = false
bool internalBearishBOS = false
bool internalBullishCHoCH = false
bool internalBearishCHoCH = false
bool swingBullishBOS = false
bool swingBearishBOS = false
bool swingBullishCHoCH = false
bool swingBearishCHoCH = false
bool internalBullishOrderBlock = false
bool internalBearishOrderBlock = false
bool swingBullishOrderBlock = false
bool swingBearishOrderBlock = false
bool equalHighs = false
bool equalLows = false
bool bullishFairValueGap = false
bool bearishFairValueGap = false
type trailingExtremes
float top
float bottom
int barTime
int barIndex
int lastTopTime
int lastBottomTime
type fairValueGap
float top
float bottom
int bias
box topBox
box bottomBox
type trend
int bias
type equalDisplay
line l_ine = na
label l_abel = na
type pivot
float currentLevel
float lastLevel
bool crossed
int barTime = time
int barIndex = bar_index
type orderBlock
float barHigh
float barLow
int barTime
int bias
// @variable current swing pivot high
var pivot swingHigh = pivot.new(na,na,false)
// @variable current swing pivot low
var pivot swingLow = pivot.new(na,na,false)
// @variable current internal pivot high
var pivot internalHigh = pivot.new(na,na,false)
// @variable current internal pivot low
var pivot internalLow = pivot.new(na,na,false)
// @variable current equal high pivot
var pivot equalHigh = pivot.new(na,na,false)
// @variable current equal low pivot
var pivot equalLow = pivot.new(na,na,false)
// @variable swing trend bias
var trend swingTrend = trend.new(0)
// @variable internal trend bias
var trend internalTrend = trend.new(0)
// @variable equal high display
var equalDisplay equalHighDisplay = equalDisplay.new()
// @variable equal low display
var equalDisplay equalLowDisplay = equalDisplay.new()
// @variable storage for fairValueGap UDTs
var array fairValueGaps = array.new()
// @variable storage for parsed highs
var array parsedHighs = array.new()
// @variable storage for parsed lows
var array parsedLows = array.new()
// @variable storage for raw highs
var array highs = array.new()
// @variable storage for raw lows
var array lows = array.new()
// @variable storage for bar time values
var array times = array.new()
// @variable last trailing swing high and low
var trailingExtremes trailing = trailingExtremes.new()
// @variable storage for orderBlock UDTs (swing order blocks)
var array swingOrderBlocks = array.new()
// @variable storage for orderBlock UDTs (internal order blocks)
var array internalOrderBlocks = array.new()
// @variable storage for swing order blocks boxes
var array swingOrderBlocksBoxes = array.new()
// @variable storage for internal order blocks boxes
var array internalOrderBlocksBoxes = array.new()
// @variable color for swing bullish structures
var swingBullishColor = styleInput == MONOCHROME ? MONO_BULLISH : swingBullColorInput
// @variable color for swing bearish structures
var swingBearishColor = styleInput == MONOCHROME ? MONO_BEARISH : swingBearColorInput
// @variable color for bullish fair value gaps
var fairValueGapBullishColor = styleInput == MONOCHROME ? color.new(MONO_BULLISH,70) : fairValueGapsBullColorInput
// @variable color for bearish fair value gaps
var fairValueGapBearishColor = styleInput == MONOCHROME ? color.new(MONO_BEARISH,70) : fairValueGapsBearColorInput
// @variable color for premium zone
var premiumZoneColor = styleInput == MONOCHROME ? MONO_BEARISH : premiumZoneColorInput
// @variable color for discount zone
var discountZoneColor = styleInput == MONOCHROME ? MONO_BULLISH : discountZoneColorInput
// @variable bar index on current script iteration
varip int currentBarIndex = bar_index
// @variable bar index on last script iteration
varip int lastBarIndex = bar_index
// @variable alerts in current bar
alerts currentAlerts = alerts.new()
// @variable time at start of chart
var initialTime = time
// we create the needed boxes for displaying order blocks at the first execution
if barstate.isfirst
if showSwingOrderBlocksInput
for index = 1 to swingOrderBlocksSizeInput
swingOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
if showInternalOrderBlocksInput
for index = 1 to internalOrderBlocksSizeInput
internalOrderBlocksBoxes.push(box.new(na,na,na,na,xloc = xloc.bar_time,extend = extend.right))
// @variable source to use in bearish order blocks mitigation
bearishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : high
// @variable source to use in bullish order blocks mitigation
bullishOrderBlockMitigationSource = orderBlockMitigationInput == CLOSE ? close : low
// @variable default volatility measure
atrMeasure = ta.atr(200)
// @variable parsed volatility measure by user settings
volatilityMeasure = orderBlockFilterInput == ATR ? atrMeasure : ta.cum(ta.tr)/bar_index
// @variable true if current bar is a high volatility bar
highVolatilityBar = (high - low) >= (2 * volatilityMeasure)
// @variable parsed high
parsedHigh = highVolatilityBar ? low : high
// @variable parsed low
parsedLow = highVolatilityBar ? high : low
// we store current values into the arrays at each bar
parsedHighs.push(parsedHigh)
parsedLows.push(parsedLow)
highs.push(high)
lows.push(low)
times.push(time)
leg(int size) =>
var leg = 0
newLegHigh = high > ta.highest( size)
newLegLow = low < ta.lowest( size)
if newLegHigh
leg := BEARISH_LEG
else if newLegLow
leg := BULLISH_LEG
leg
startOfNewLeg(int leg) => ta.change(leg) != 0
startOfBearishLeg(int leg) => ta.change(leg) == -1
startOfBullishLeg(int leg) => ta.change(leg) == +1
drawLabel(int labelTime, float labelPrice, string tag, color labelColor, string labelStyle) =>
var label l_abel = na
if modeInput == PRESENT
l_abel.delete()
l_abel := label.new(chart.point.new(labelTime,na,labelPrice),tag,xloc.bar_time,color=color(na),textcolor=labelColor,style = labelStyle,size = size.small)
drawEqualHighLow(pivot p_ivot, float level, int size, bool equalHigh) =>
equalDisplay e_qualDisplay = equalHigh ? equalHighDisplay : equalLowDisplay
string tag = 'EQL'
color equalColor = swingBullishColor
string labelStyle = label.style_label_up
if equalHigh
tag := 'EQH'
equalColor := swingBearishColor
labelStyle := label.style_label_down
if modeInput == PRESENT
line.delete( e_qualDisplay.l_ine)
label.delete( e_qualDisplay.l_abel)
e_qualDisplay.l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time ,na,level), xloc = xloc.bar_time, color = equalColor, style = line.style_dotted)
labelPosition = math.round(0.5*(p_ivot.barIndex + bar_index - size))
e_qualDisplay.l_abel := label.new(chart.point.new(na,labelPosition,level), tag, xloc.bar_index, color = color(na), textcolor = equalColor, style = labelStyle, size = equalHighsLowsSizeInput)
getCurrentStructure(int size,bool equalHighLow = false, bool internal = false) =>
currentLeg = leg(size)
newPivot = startOfNewLeg(currentLeg)
pivotLow = startOfBullishLeg(currentLeg)
pivotHigh = startOfBearishLeg(currentLeg)
if newPivot
if pivotLow
pivot p_ivot = equalHighLow ? equalLow : internal ? internalLow : swingLow
if equalHighLow and math.abs(p_ivot.currentLevel - low ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot, low , size, false)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := low
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.bottom := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastBottomTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel < p_ivot.lastLevel ? 'LL' : 'HL', swingBullishColor, label.style_label_up)
else
pivot p_ivot = equalHighLow ? equalHigh : internal ? internalHigh : swingHigh
if equalHighLow and math.abs(p_ivot.currentLevel - high ) < equalHighsLowsThresholdInput * atrMeasure
drawEqualHighLow(p_ivot,high ,size,true)
p_ivot.lastLevel := p_ivot.currentLevel
p_ivot.currentLevel := high
p_ivot.crossed := false
p_ivot.barTime := time
p_ivot.barIndex := bar_index
if not equalHighLow and not internal
trailing.top := p_ivot.currentLevel
trailing.barTime := p_ivot.barTime
trailing.barIndex := p_ivot.barIndex
trailing.lastTopTime := p_ivot.barTime
if showSwingsInput and not internal and not equalHighLow
drawLabel(time , p_ivot.currentLevel, p_ivot.currentLevel > p_ivot.lastLevel ? 'HH' : 'LH', swingBearishColor, label.style_label_down)
drawStructure(pivot p_ivot, string tag, color structureColor, string lineStyle, string labelStyle, string labelSize) =>
var line l_ine = line.new(na,na,na,na,xloc = xloc.bar_time)
var label l_abel = label.new(na,na)
if modeInput == PRESENT
l_ine.delete()
l_abel.delete()
l_ine := line.new(chart.point.new(p_ivot.barTime,na,p_ivot.currentLevel), chart.point.new(time,na,p_ivot.currentLevel), xloc.bar_time, color=structureColor, style=lineStyle)
l_abel := label.new(chart.point.new(na,math.round(0.5*(p_ivot.barIndex+bar_index)),p_ivot.currentLevel), tag, xloc.bar_index, color=color(na), textcolor=structureColor, style=labelStyle, size = labelSize)
deleteOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
for in orderBlocks
bool crossedOderBlock = false
if bearishOrderBlockMitigationSource > eachOrderBlock.barHigh and eachOrderBlock.bias == BEARISH
crossedOderBlock := true
if internal
currentAlerts.internalBearishOrderBlock := true
else
currentAlerts.swingBearishOrderBlock := true
else if bullishOrderBlockMitigationSource < eachOrderBlock.barLow and eachOrderBlock.bias == BULLISH
crossedOderBlock := true
if internal
currentAlerts.internalBullishOrderBlock := true
else
currentAlerts.swingBullishOrderBlock := true
if crossedOderBlock
orderBlocks.remove(index)
storeOrdeBlock(pivot p_ivot,bool internal = false,int bias) =>
if (not internal and showSwingOrderBlocksInput) or (internal and showInternalOrderBlocksInput)
array a_rray = na
int parsedIndex = na
if bias == BEARISH
a_rray := parsedHighs.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.max())
else
a_rray := parsedLows.slice(p_ivot.barIndex,bar_index)
parsedIndex := p_ivot.barIndex + a_rray.indexof(a_rray.min())
orderBlock o_rderBlock = orderBlock.new(parsedHighs.get(parsedIndex), parsedLows.get(parsedIndex), times.get(parsedIndex),bias)
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
if orderBlocks.size() >= 100
orderBlocks.pop()
orderBlocks.unshift(o_rderBlock)
drawOrderBlocks(bool internal = false) =>
array orderBlocks = internal ? internalOrderBlocks : swingOrderBlocks
orderBlocksSize = orderBlocks.size()
if orderBlocksSize > 0
maxOrderBlocks = internal ? internalOrderBlocksSizeInput : swingOrderBlocksSizeInput
array parsedOrdeBlocks = orderBlocks.slice(0, math.min(maxOrderBlocks,orderBlocksSize))
array b_oxes = internal ? internalOrderBlocksBoxes : swingOrderBlocksBoxes
for in parsedOrdeBlocks
orderBlockColor = styleInput == MONOCHROME ? (eachOrderBlock.bias == BEARISH ? color.new(MONO_BEARISH,80) : color.new(MONO_BULLISH,80)) : internal ? (eachOrderBlock.bias == BEARISH ? internalBearishOrderBlockColor : internalBullishOrderBlockColor) : (eachOrderBlock.bias == BEARISH ? swingBearishOrderBlockColor : swingBullishOrderBlockColor)
box b_ox = b_oxes.get(index)
b_ox.set_top_left_point( chart.point.new(eachOrderBlock.barTime,na,eachOrderBlock.barHigh))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,eachOrderBlock.barLow))
b_ox.set_border_color( internal ? na : orderBlockColor)
b_ox.set_bgcolor( orderBlockColor)
displayStructure(bool internal = false) =>
var bullishBar = true
var bearishBar = true
if internalFilterConfluenceInput
bullishBar := high - math.max(close, open) > math.min(close, open - low)
bearishBar := high - math.max(close, open) < math.min(close, open - low)
pivot p_ivot = internal ? internalHigh : swingHigh
trend t_rend = internal ? internalTrend : swingTrend
lineStyle = internal ? line.style_dashed : line.style_solid
labelSize = internal ? internalStructureSize : swingStructureSize
extraCondition = internal ? internalHigh.currentLevel != swingHigh.currentLevel and bullishBar : true
bullishColor = styleInput == MONOCHROME ? MONO_BULLISH : internal ? internalBullColorInput : swingBullColorInput
if ta.crossover(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BEARISH ? CHOCH : BOS
if internal
currentAlerts.internalBullishCHoCH := tag == CHOCH
currentAlerts.internalBullishBOS := tag == BOS
else
currentAlerts.swingBullishCHoCH := tag == CHOCH
currentAlerts.swingBullishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BULLISH
displayCondition = internal ? showInternalsInput and (showInternalBullInput == ALL or (showInternalBullInput == BOS and tag != CHOCH) or (showInternalBullInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBullInput == ALL or (showSwingBullInput == BOS and tag != CHOCH) or (showSwingBullInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bullishColor,lineStyle,label.style_label_down,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BULLISH)
p_ivot := internal ? internalLow : swingLow
extraCondition := internal ? internalLow.currentLevel != swingLow.currentLevel and bearishBar : true
bearishColor = styleInput == MONOCHROME ? MONO_BEARISH : internal ? internalBearColorInput : swingBearColorInput
if ta.crossunder(close,p_ivot.currentLevel) and not p_ivot.crossed and extraCondition
string tag = t_rend.bias == BULLISH ? CHOCH : BOS
if internal
currentAlerts.internalBearishCHoCH := tag == CHOCH
currentAlerts.internalBearishBOS := tag == BOS
else
currentAlerts.swingBearishCHoCH := tag == CHOCH
currentAlerts.swingBearishBOS := tag == BOS
p_ivot.crossed := true
t_rend.bias := BEARISH
displayCondition = internal ? showInternalsInput and (showInternalBearInput == ALL or (showInternalBearInput == BOS and tag != CHOCH) or (showInternalBearInput == CHOCH and tag == CHOCH)) : showStructureInput and (showSwingBearInput == ALL or (showSwingBearInput == BOS and tag != CHOCH) or (showSwingBearInput == CHOCH and tag == CHOCH))
if displayCondition
drawStructure(p_ivot,tag,bearishColor,lineStyle,label.style_label_up,labelSize)
if (internal and showInternalOrderBlocksInput) or (not internal and showSwingOrderBlocksInput)
storeOrdeBlock(p_ivot,internal,BEARISH)
fairValueGapBox(leftTime,rightTime,topPrice,bottomPrice,boxColor) => box.new(chart.point.new(leftTime,na,topPrice),chart.point.new(rightTime + fairValueGapsExtendInput * (time-time ),na,bottomPrice), xloc=xloc.bar_time, border_color = boxColor, bgcolor = boxColor)
deleteFairValueGaps() =>
for in fairValueGaps
if (low < eachFairValueGap.bottom and eachFairValueGap.bias == BULLISH) or (high > eachFairValueGap.top and eachFairValueGap.bias == BEARISH)
eachFairValueGap.topBox.delete()
eachFairValueGap.bottomBox.delete()
fairValueGaps.remove(index)
// @function draw fair value gaps
// @returns fairValueGap ID
drawFairValueGaps() =>
= request.security(syminfo.tickerid, fairValueGapsTimeframeInput, [close , open , time , high , low , time , high , low ],lookahead = barmerge.lookahead_on)
barDeltaPercent = (lastClose - lastOpen) / (lastOpen * 100)
newTimeframe = timeframe.change(fairValueGapsTimeframeInput)
threshold = fairValueGapsThresholdInput ? ta.cum(math.abs(newTimeframe ? barDeltaPercent : 0)) / bar_index * 2 : 0
bullishFairValueGap = currentLow > last2High and lastClose > last2High and barDeltaPercent > threshold and newTimeframe
bearishFairValueGap = currentHigh < last2Low and lastClose < last2Low and -barDeltaPercent > threshold and newTimeframe
if bullishFairValueGap
currentAlerts.bullishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentLow,last2High,BULLISH,fairValueGapBox(lastTime,currentTime,currentLow,math.avg(currentLow,last2High),fairValueGapBullishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentLow,last2High),last2High,fairValueGapBullishColor)))
if bearishFairValueGap
currentAlerts.bearishFairValueGap := true
fairValueGaps.unshift(fairValueGap.new(currentHigh,last2Low,BEARISH,fairValueGapBox(lastTime,currentTime,currentHigh,math.avg(currentHigh,last2Low),fairValueGapBearishColor),fairValueGapBox(lastTime,currentTime,math.avg(currentHigh,last2Low),last2Low,fairValueGapBearishColor)))
getStyle(string style) =>
switch style
SOLID => line.style_solid
DASHED => line.style_dashed
DOTTED => line.style_dotted
drawLevels(string timeframe, bool sameTimeframe, string style, color levelColor) =>
= request.security(syminfo.tickerid, timeframe, [high , low , time , time],lookahead = barmerge.lookahead_on)
float parsedTop = sameTimeframe ? high : topLevel
float parsedBottom = sameTimeframe ? low : bottomLevel
int parsedLeftTime = sameTimeframe ? time : leftTime
int parsedRightTime = sameTimeframe ? time : rightTime
int parsedTopTime = time
int parsedBottomTime = time
if not sameTimeframe
int leftIndex = times.binary_search_rightmost(parsedLeftTime)
int rightIndex = times.binary_search_rightmost(parsedRightTime)
array timeArray = times.slice(leftIndex,rightIndex)
array topArray = highs.slice(leftIndex,rightIndex)
array bottomArray = lows.slice(leftIndex,rightIndex)
parsedTopTime := timeArray.size() > 0 ? timeArray.get(topArray.indexof(topArray.max())) : initialTime
parsedBottomTime := timeArray.size() > 0 ? timeArray.get(bottomArray.indexof(bottomArray.min())) : initialTime
var line topLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var line bottomLine = line.new(na, na, na, na, xloc = xloc.bar_time, color = levelColor, style = getStyle(style))
var label topLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}H',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
var label bottomLabel = label.new(na, na, xloc = xloc.bar_time, text = str.format('P{0}L',timeframe), color=color(na), textcolor = levelColor, size = size.small, style = label.style_label_left)
topLine.set_first_point( chart.point.new(parsedTopTime,na,parsedTop))
topLine.set_second_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
topLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedTop))
bottomLine.set_first_point( chart.point.new(parsedBottomTime,na,parsedBottom))
bottomLine.set_second_point(chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
bottomLabel.set_point( chart.point.new(last_bar_time + 20 * (time-time ),na,parsedBottom))
higherTimeframe(string timeframe) => timeframe.in_seconds() > timeframe.in_seconds(timeframe)
updateTrailingExtremes() =>
trailing.top := math.max(high,trailing.top)
trailing.lastTopTime := trailing.top == high ? time : trailing.lastTopTime
trailing.bottom := math.min(low,trailing.bottom)
trailing.lastBottomTime := trailing.bottom == low ? time : trailing.lastBottomTime
drawHighLowSwings() =>
var line topLine = line.new(na, na, na, na, color = swingBearishColor, xloc = xloc.bar_time)
var line bottomLine = line.new(na, na, na, na, color = swingBullishColor, xloc = xloc.bar_time)
var label topLabel = label.new(na, na, color=color(na), textcolor = swingBearishColor, xloc = xloc.bar_time, style = label.style_label_down, size = size.tiny)
var label bottomLabel = label.new(na, na, color=color(na), textcolor = swingBullishColor, xloc = xloc.bar_time, style = label.style_label_up, size = size.tiny)
rightTimeBar = last_bar_time + 20 * (time - time )
topLine.set_first_point( chart.point.new(trailing.lastTopTime, na, trailing.top))
topLine.set_second_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_point( chart.point.new(rightTimeBar, na, trailing.top))
topLabel.set_text( swingTrend.bias == BEARISH ? 'Strong High' : 'Weak High')
bottomLine.set_first_point( chart.point.new(trailing.lastBottomTime, na, trailing.bottom))
bottomLine.set_second_point(chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_point( chart.point.new(rightTimeBar, na, trailing.bottom))
bottomLabel.set_text( swingTrend.bias == BULLISH ? 'Strong Low' : 'Weak Low')
drawZone(float labelLevel, int labelIndex, float top, float bottom, string tag, color zoneColor, string style) =>
var label l_abel = label.new(na,na,text = tag, color=color(na),textcolor = zoneColor, style = style, size = size.small)
var box b_ox = box.new(na,na,na,na,bgcolor = color.new(zoneColor,80),border_color = color(na), xloc = xloc.bar_time)
b_ox.set_top_left_point( chart.point.new(trailing.barTime,na,top))
b_ox.set_bottom_right_point(chart.point.new(last_bar_time,na,bottom))
l_abel.set_point( chart.point.new(na,labelIndex,labelLevel))
// @function draw premium/discount zones
// @returns void
drawPremiumDiscountZones() =>
drawZone(trailing.top, math.round(0.5*(trailing.barIndex + last_bar_index)), trailing.top, 0.95*trailing.top + 0.05*trailing.bottom, 'Premium', premiumZoneColor, label.style_label_down)
equilibriumLevel = math.avg(trailing.top, trailing.bottom)
drawZone(equilibriumLevel, last_bar_index, 0.525*trailing.top + 0.475*trailing.bottom, 0.525*trailing.bottom + 0.475*trailing.top, 'Equilibrium', equilibriumZoneColorInput, label.style_label_left)
drawZone(trailing.bottom, math.round(0.5*(trailing.barIndex + last_bar_index)), 0.95*trailing.bottom + 0.05*trailing.top, trailing.bottom, 'Discount', discountZoneColor, label.style_label_up)
parsedOpen = showTrendInput ? open : na
candleColor = internalTrend.bias == BULLISH ? swingBullishColor : swingBearishColor
plotcandle(parsedOpen,high,low,close,color = candleColor, wickcolor = candleColor, bordercolor = candleColor)
if showHighLowSwingsInput or showPremiumDiscountZonesInput
updateTrailingExtremes()
if showHighLowSwingsInput
drawHighLowSwings()
if showPremiumDiscountZonesInput
drawPremiumDiscountZones()
if showFairValueGapsInput
deleteFairValueGaps()
getCurrentStructure(swingsLengthInput,false)
getCurrentStructure(5,false,true)
if showEqualHighsLowsInput
getCurrentStructure(equalHighsLowsLengthInput,true)
if showInternalsInput or showInternalOrderBlocksInput or showTrendInput
displayStructure(true)
if showStructureInput or showSwingOrderBlocksInput or showHighLowSwingsInput
displayStructure()
if showInternalOrderBlocksInput
deleteOrderBlocks(true)
if showSwingOrderBlocksInput
deleteOrderBlocks()
if showFairValueGapsInput
drawFairValueGaps()
if barstate.islastconfirmedhistory or barstate.islast
if showInternalOrderBlocksInput
drawOrderBlocks(true)
if showSwingOrderBlocksInput
drawOrderBlocks()
lastBarIndex := currentBarIndex
currentBarIndex := bar_index
newBar = currentBarIndex != lastBarIndex
if barstate.islastconfirmedhistory or (barstate.isrealtime and newBar)
if showDailyLevelsInput and not higherTimeframe('D')
drawLevels('D',timeframe.isdaily,dailyLevelsStyleInput,dailyLevelsColorInput)
if showWeeklyLevelsInput and not higherTimeframe('W')
drawLevels('W',timeframe.isweekly,weeklyLevelsStyleInput,weeklyLevelsColorInput)
if showMonthlyLevelsInput and not higherTimeframe('M')
drawLevels('M',timeframe.ismonthly,monthlyLevelsStyleInput,monthlyLevelsColorInput)
xATR = ta.atr(c)
nLoss = a * xATR
src = h ? request.security(ticker.heikinashi(syminfo.tickerid), timeframe.period, close, lookahead = barmerge.lookahead_off) : close
xATRTrailingStop = 0.0
iff_1 = src > nz(xATRTrailingStop , 0) ? src - nLoss : src + nLoss
iff_2 = src < nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? math.min(nz(xATRTrailingStop ), src + nLoss) : iff_1
xATRTrailingStop := src > nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? math.max(nz(xATRTrailingStop ), src - nLoss) : iff_2
pos = 0
iff_3 = src > nz(xATRTrailingStop , 0) and src < nz(xATRTrailingStop , 0) ? -1 : nz(pos , 0)
pos := src < nz(xATRTrailingStop , 0) and src > nz(xATRTrailingStop , 0) ? 1 : iff_3
xcolor = pos == -1 ? color.red : pos == 1 ? color.green : color.blue
ema = ta.ema(src, 1)
above = ta.crossover(ema, xATRTrailingStop)
below = ta.crossover(xATRTrailingStop, ema)
buy = src > xATRTrailingStop and above
sell = src < xATRTrailingStop and below
barbuy = src > xATRTrailingStop
barsell = src < xATRTrailingStop
//---------------------------------------------------------------------------------------------------------------------}
//ALERTS
//---------------------------------------------------------------------------------------------------------------------{
alertcondition(currentAlerts.internalBullishBOS, 'Internal Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.internalBullishCHoCH, 'Internal Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.internalBearishBOS, 'Internal Bearish BOS', 'Internal Bearish BOS formed')
alertcondition(currentAlerts.internalBearishCHoCH, 'Internal Bearish CHoCH', 'Internal Bearish CHoCH formed')
alertcondition(currentAlerts.swingBullishBOS, 'Bullish BOS', 'Internal Bullish BOS formed')
alertcondition(currentAlerts.swingBullishCHoCH, 'Bullish CHoCH', 'Internal Bullish CHoCH formed')
alertcondition(currentAlerts.swingBearishBOS, 'Bearish BOS', 'Bearish BOS formed')
alertcondition(currentAlerts.swingBearishCHoCH, 'Bearish CHoCH', 'Bearish CHoCH formed')
alertcondition(currentAlerts.internalBullishOrderBlock, 'Bullish Internal OB Breakout', 'Price broke bullish internal OB')
alertcondition(currentAlerts.internalBearishOrderBlock, 'Bearish Internal OB Breakout', 'Price broke bearish internal OB')
alertcondition(currentAlerts.swingBullishOrderBlock, 'Bullish Swing OB Breakout', 'Price broke bullish swing OB')
alertcondition(currentAlerts.swingBearishOrderBlock, 'Bearish Swing OB Breakout', 'Price broke bearish swing OB')
alertcondition(currentAlerts.equalHighs, 'Equal Highs', 'Equal highs detected')
alertcondition(currentAlerts.equalLows, 'Equal Lows', 'Equal lows detected')
alertcondition(currentAlerts.bullishFairValueGap, 'Bullish FVG', 'Bullish FVG formed')
alertcondition(currentAlerts.bearishFairValueGap, 'Bearish FVG', 'Bearish FVG formed')
alertcondition(buy, 'UT Long', 'UT Long')
alertcondition(sell, 'UT Short', 'UT Short')
plotshape(buy, title = 'Buy', text = 'Buy', style = shape.labelup, location = location.belowbar, color = color.new(color.green, 0), textcolor = color.new(color.white, 0), size = size.tiny)
plotshape(sell, title = 'Sell', text = 'Sell', style = shape.labeldown, location = location.abovebar, color = color.new(color.red, 0), textcolor = color.new(color.white, 0), size = size.tiny)
//--------------------------------------------------------------------------------------
// EMA ADDITIONS (Editable)
//--------------------------------------------------------------------------------------
ema5Len = input.int(5, "5 EMA Length", minval = 1)
ema9Len = input.int(9, "9 EMA Length", minval = 1)
ema5 = ta.ema(src, ema5Len)
ema9 = ta.ema(src, ema9Len)
plot(ema5, "EMA 5", color = color.red, linewidth = 2)
plot(ema9, "EMA 9", color = color.blue, linewidth = 2)
barcolor(barbuy ? color.green : na)
barcolor(barsell ? color.red : na)
MA200 Parallel ChannelDynamic MA100 Parallel Bands – Precision S/R Levels
This indicator builds a clean, parallel channel around the 100-period moving average using a fixed ±4 offset.
Because the offset mirrors the short-term MA1 fluctuations, the channel reveals highly accurate support and resistance zones that react instantly to market micro-structure.
Unlike Bollinger Bands—which expand with volatility—this tool stays perfectly parallel and trend-aligned, making breakouts and pullbacks incredibly easy to spot.
How it works:
Centerline: 100-period moving average (MA100)
Upper Band: MA100 + 4
Lower Band: MA100 – 4
MA1 used as a sensitivity reference for micro-trend behavior
Parallel structure ensures stable, predictable levels
Why it’s powerful:
The ±4 channel creates extremely precise S/R zones
Price respecting the lower band = dynamic support
Price rejecting the upper band = dynamic resistance
A clean break above or below the bands highlights strong momentum shifts
Perfect for intraday traders needing structure without noise
Perfect for:
Identifying high-probability bounce levels
Spotting early trend continuation
Confirming MA100 breakouts
Filtering weak signals and fake volatility spikes
If you want razor-sharp support & resistance levels that stay consistent across all timeframes, these MA100 parallel bands deliver exceptional clarity.
Advanced Market Profile & S/R Zones (Pro)Advanced Market Profile & S/R Zones
This indicator brings professional Auction Market Theory to your chart using a custom rolling Volume Profile algorithm. Unlike standard profiles that remain fixed, this tool dynamically calculates the "Fair Value" of the asset based on your specific lookback period (e.g., the last 100 bars).
It automatically highlights the Point of Control (POC), Value Area (VA), and suggests statistical Discount (Buy) and Premium (Sell) zones.
Key Features
Volume Splitting Algorithm:
Most basic scripts dump the entire volume of a candle into a single price point (the average). This script splits the volume across the candle's entire High-Low range. This results in a much smoother, higher-resolution bell curve that accurately reflects price action, especially on higher timeframes like Monthly charts.
Auto-generated Zones:
Green Zone (Discount): Prices below the Value Area Low (VAL). Statistically "cheap."
Red Zone (Premium): Prices above the Value Area High (VAH). Statistically "expensive."
Real-Time Dashboard:
A built-in panel displays the exact price levels for the POC, VAH, and VAL for precise limit order placement, along with the current Market Trend.
How to Use
For Intraday (Day Trading):
Settings: Set Lookback to 100 - 300.
Strategy: Watch for price to open outside the Value Area. If price breaks back inside the Value Area, target the POC (Red Line).
For Macro (Monthly/Weekly Charts):
Settings: Set Lookback to 12 (1 Year) or 60 (5 Years).
Strategy: Identify multi-year structural support. When a monthly candle enters the Green Discount Zone of a 5-year profile, it is often a high-probability institutional entry point.
Trend Logic
The Dashboard indicates trend based on price location relative to value:
Strong Bullish: Price is accepted ABOVE the Value Area.
Strong Bearish: Price is accepted BELOW the Value Area.
Neutral / In VA: Price is chopping inside the Value Area.
Disclaimer
This is a "Rolling Profile." It calculates the profile based on the current lookback window relative to the latest bar. As new bars form, the lookback window shifts, and the profile updates to reflect the new dataset.
Pair Cointegration & Static Beta Analyzer (v6)Pair Cointegration & Static Beta Analyzer (v6)
This indicator evaluates whether two instruments exhibit statistical properties consistent with cointegration and tradable mean reversion.
It uses long-term beta estimation, spread standardization, AR(1) dynamics, drift stability, tail distribution analysis, and a multi-factor scoring model.
1. Static Beta and Spread Construction
A long-horizon static beta is estimated using covariance and variance of log-returns.
This beta does not update on every bar and is used throughout the entire model.
Beta = Cov(r1, r2) / Var(r2)
Spread = PriceA - Beta * PriceB
This “frozen” beta provides structural stability and avoids rolling noise in spread construction.
2. Correlation Check
Log-price correlation ensures the instruments move together over time.
Correlation ≥ 0.85 is required before deeper cointegration diagnostics are considered meaningful.
3. Z-Score Normalization and Distribution Behavior
The spread is standardized:
Z = (Spread - MA(Spread)) / Std(Spread)
The following statistical properties are examined:
Z-Mean: Should be close to zero in a stationary process
Z-Variance: Measures amplitude of deviations
Tail Probability: Frequency of |Z| being larger than a threshold (e.g. 2)
These metrics reveal whether the spread behaves like a mean-reverting equilibrium.
4. Mean Drift Stability
A rolling mean of the spread is examined.
If the rolling mean drifts excessively, the spread may not represent a stable long-term equilibrium.
A normalized drift ratio is used:
Mean Drift Ratio = Range( RollingMean(Spread) ) / Std(Spread)
Low drift indicates stable long-run equilibrium behavior.
5. AR(1) Dynamics and Half-Life
An AR(1) model approximates mean reversion:
Spread(t) = Phi * Spread(t-1) + error
Mean reversion requires:
0 < Phi < 1
Half-life of reversion:
Half-life = -ln(2) / ln(Phi)
Valid half-life for 10-minute bars typically falls between 3 and 80 bars.
6. Composite Scoring Model (0–100)
A multi-factor weighted scoring system is applied:
Component Score
Correlation 0–20
Z-Mean 0–15
Z-Variance 0–10
Tail Probability 0–10
Mean Drift 0–15
AR(1) Phi 0–15
Half-Life 0–15
Score interpretation:
70–100: Strong Cointegration Quality
40–70: Moderate
0–40: Weak
A pair is classified as cointegrated when:
Total Score ≥ Threshold (default = 70)
7. Main Cointegration Panel
Displays:
Static beta
Log-price correlation
Z-Mean, Z-Variance, Tail Probability
Drift Ratio
AR(1) Phi and Half-life
Composite score
Overall cointegration assessment
8. Beta Hedge Position Sizing (Average-Price Based)
To provide a more stable hedge ratio, hedge sizing is computed using average prices, not instantaneous prices:
AvgPriceA = SMA(PriceA, N)
AvgPriceB = SMA(PriceB, N)
Required B per 1 A = Beta * (AvgPriceA / AvgPriceB)
Using averaged prices results in a smoother, more reliable hedge ratio, reducing noise from bar-to-bar volatility.
The panel displays:
Required B security for 1 A security (average)
This represents the beta-neutral quantity of B required to hedge one unit of A.
Overview of Classical Stationarity & Cointegration Methods
The principal econometric tools commonly used in assessing stationarity and cointegration include:
Augmented Dickey–Fuller (ADF) Test
Phillips–Perron (PP) Test
KPSS Test
Engle–Granger Cointegration Test
Phillips–Ouliaris Cointegration Test
Johansen Cointegration Test
Since these procedures rely on regression residuals, matrix operations, and distribution-based critical values that are not supported in TradingView Pine Script, a practical multi-criteria scoring approach is employed instead. This framework leverages metrics that are fully computable in Pine and offers an operational proxy for evaluating cointegration-like behavior under platform constraints.
References
Engle & Granger (1987), Co-integration and Error Correction
Poterba & Summers (1988), Mean Reversion in Stock Prices
Vidyamurthy (2004), Pairs Trading
Explanation structured with assistance from OpenAI’s ChatGPT
Regards.
SMC BOS/CHoCH + Auto Fib (5m/any TF) durane//@version=6
indicator('SMC BOS/CHoCH + Auto Fib (5m/any TF)', overlay = true, max_lines_count = 200, max_labels_count = 200)
// --------- Inputs ----------
left = input.int(3, 'Pivot Left', minval = 1)
right = input.int(3, 'Pivot Right', minval = 1)
minSwingSize = input.float(0.0, 'Min swing size (price units, 0 = disabled)', step = 0.1)
fib_levels = input.string('0.0,0.236,0.382,0.5,0.618,0.786,1.0', 'Fibonacci levels (comma separated)')
show_labels = input.bool(true, 'Show BOS/CHoCH labels')
lookbackHighLow = input.int(200, 'Lookback for structure (bars)')
// Parse fib levels
strs = str.split(fib_levels, ',')
var array fibs = array.new_float()
if barstate.isfirst
for s in strs
array.push(fibs, str.tonumber(str.trim(s)))
// --------- Find pivot highs / lows ----------
pHigh = ta.pivothigh(high, left, right)
pLow = ta.pivotlow(low, left, right)
// store last confirmed swings
var float lastSwingHighPrice = na
var int lastSwingHighBar = na
var float lastSwingLowPrice = na
var int lastSwingLowBar = na
if not na(pHigh)
// check min size
if minSwingSize == 0 or pHigh - nz(lastSwingLowPrice, pHigh) >= minSwingSize
lastSwingHighPrice := pHigh
lastSwingHighBar := bar_index - right
lastSwingHighBar
if not na(pLow)
if minSwingSize == 0 or nz(lastSwingHighPrice, pLow) - pLow >= minSwingSize
lastSwingLowPrice := pLow
lastSwingLowBar := bar_index - right
lastSwingLowBar
// --------- Detect BOS & CHoCH (simple robust logic) ----------
var int lastBOSdir = 0 // 1 = bullish BOS (price broke above), -1 = bearish BOS
var int lastBOSbar = na
var float lastBOSprice = na
// Look for price closes beyond last structural swings within lookback
// Bullish BOS: close > recent swing high
condBullBOS = not na(lastSwingHighPrice) and close > lastSwingHighPrice and bar_index - lastSwingHighBar <= lookbackHighLow
// Bearish BOS: close < recent swing low
condBearBOS = not na(lastSwingLowPrice) and close < lastSwingLowPrice and bar_index - lastSwingLowBar <= lookbackHighLow
bosTriggered = false
chochTriggered = false
if condBullBOS
bosTriggered := true
if lastBOSdir != 1
// if previous BOS direction was -1, this is CHoCH (change of character)
chochTriggered := lastBOSdir == -1
chochTriggered
lastBOSdir := 1
lastBOSbar := bar_index
lastBOSprice := close
lastBOSprice
if condBearBOS
bosTriggered := true
if lastBOSdir != -1
chochTriggered := lastBOSdir == 1
chochTriggered
lastBOSdir := -1
lastBOSbar := bar_index
lastBOSprice := close
lastBOSprice
// --------- Plot labels for BOS / CHoCH ----------
if bosTriggered and show_labels
if chochTriggered
label.new(bar_index, high, text = lastBOSdir == 1 ? 'CHoCH ↑' : 'CHoCH ↓', style = label.style_label_up, color = color.new(color.orange, 0), textcolor = color.white, yloc = yloc.abovebar)
else
label.new(bar_index, high, text = lastBOSdir == 1 ? 'BOS ↑' : 'BOS ↓', style = label.style_label_left, color = lastBOSdir == 1 ? color.green : color.red, textcolor = color.white, yloc = yloc.abovebar)
// --------- Auto Fibonacci drawing ----------
var array fib_lines = array.new_line()
var array fib_labels = array.new_label()
var int lastFibId = na
// Function to clear previous fibs
f_clear() =>
if array.size(fib_lines) > 0
for i = 0 to array.size(fib_lines) - 1
line.delete(array.get(fib_lines, i))
if array.size(fib_labels) > 0
for i = 0 to array.size(fib_labels) - 1
label.delete(array.get(fib_labels, i))
array.clear(fib_lines)
array.clear(fib_labels)
// Decide anchors for fib: if lastBOSdir==1 (bullish) anchor from lastSwingLow -> lastSwingHigh
// if lastBOSdir==-1 (bearish) anchor from lastSwingHigh -> lastSwingLow
if lastBOSdir == 1 and not na(lastSwingLowPrice) and not na(lastSwingHighPrice)
// bullish fib: low -> high
startPrice = lastSwingLowPrice
endPrice = lastSwingHighPrice
// draw
f_clear()
for i = 0 to array.size(fibs) - 1 by 1
lvl = array.get(fibs, i)
priceLevel = startPrice + (endPrice - startPrice) * lvl
ln = line.new(x1 = lastSwingLowBar, y1 = priceLevel, x2 = bar_index, y2 = priceLevel, xloc = xloc.bar_index, extend = extend.right, color = color.new(color.green, 60), width = 1, style = line.style_solid)
array.push(fib_lines, ln)
lab = label.new(bar_index, priceLevel, text = str.tostring(lvl * 100, '#.0') + '%', style = label.style_label_right, color = color.new(color.green, 80), textcolor = color.white, yloc = yloc.price)
array.push(fib_labels, lab)
if lastBOSdir == -1 and not na(lastSwingHighPrice) and not na(lastSwingLowPrice)
// bearish fib: high -> low
startPrice = lastSwingHighPrice
endPrice = lastSwingLowPrice
f_clear()
for i = 0 to array.size(fibs) - 1 by 1
lvl = array.get(fibs, i)
priceLevel = startPrice + (endPrice - startPrice) * lvl
ln = line.new(x1 = lastSwingHighBar, y1 = priceLevel, x2 = bar_index, y2 = priceLevel, xloc = xloc.bar_index, extend = extend.right, color = color.new(color.red, 60), width = 1, style = line.style_solid)
array.push(fib_lines, ln)
lab = label.new(bar_index, priceLevel, text = str.tostring(lvl * 100, '#.0') + '%', style = label.style_label_right, color = color.new(color.red, 80), textcolor = color.white, yloc = yloc.price)
array.push(fib_labels, lab)
// --------- Optional: plot lastSwing points ----------
plotshape(not na(lastSwingHighPrice) ? lastSwingHighPrice : na, title = 'LastSwingHigh', location = location.absolute, style = shape.triangledown, size = size.tiny, color = color.red, offset = 0)
plotshape(not na(lastSwingLowPrice) ? lastSwingLowPrice : na, title = 'LastSwingLow', location = location.absolute, style = shape.triangleup, size = size.tiny, color = color.green, offset = 0)
// --------- Alerts ----------
alertcondition(bosTriggered and lastBOSdir == 1, title = 'Bullish BOS', message = 'Bullish BOS detected on {{ticker}} @ {{close}}')
alertcondition(bosTriggered and lastBOSdir == -1, title = 'Bearish BOS', message = 'Bearish BOS detected on {{ticker}} @ {{close}}')
alertcondition(chochTriggered, title = 'CHoCH Detected', message = 'CHoCH detected on {{ticker}} @ {{close}}')
// End
Time-Decay Liquidity Zones [BackQuant]Time-Decay Liquidity Zones
A dynamic liquidity map that turns single-bar exhaustion events into fading, color-graded zones, so you can see where trapped traders and unfinished business still matter, and when those areas have finally stopped pulling price.
What this is
This indicator detects unusually strong impulsive moves into wicks, converts them into supply or demand “zones,” then lets those zones decay over time. Each zone carries a strength score that fades bar by bar. Zones that stop attracting or rejecting price are gradually de-emphasized and eventually removed, while the most relevant areas stay bright and obvious.
Instead of static rectangles that live forever, you get a living liquidity map where:
Zones are born from objective criteria: volatility, wick size, and optional volume spikes.
Zones “age” using a configurable decay factor and maximum lifetime.
Zone color and opacity reflect current relative strength on a unified clear → green → red gradient.
Zones freeze when broken, so you can distinguish “active reaction areas” from “historical levels that have already given way”.
Conceptual idea
Large wicks with strong volatility often mark areas where aggressive orders met hidden liquidity and got absorbed. Price may revisit these areas to test leftover interest or to relieve trapped positions. However, not every wick matters for long. As time passes and more bars print, the market “forgets” some areas.
Time-Decay Liquidity Zones turns that idea into a rule-based system:
Find bars that likely reflect strong aggressive flows into liquidity.
Mark a zone around the wick using ATR-based thickness.
Assign a strength score of 1.0 at birth.
Each bar, reduce that score by a decay factor and remove zones that fall below a threshold or live too long.
Color all surviving zones from weak to strong using a single gradient scale and a visual legend.
How events are detected
Detection lives in the Event Detection group. The script combines range, wick size, and optional volume filters into simple rules.
Volatility filter
ATR Length — computes a rolling ATR over your chosen window. This is the volatility baseline.
Min range in ATRs — bar range (High–Low) must exceed this multiple of ATR for an event to be considered. This avoids tiny bars triggering zones.
Wick filters
For each bar, the script splits the candle into body and wicks:
Upper wick = High minus the max(Open, Close).
Lower wick = min(Open, Close) minus Low.
Then it tests:
Upper wick condition — upper wick must be larger than Min wick size in ATRs × ATR.
Lower wick condition — lower wick must be larger than Min wick size in ATRs × ATR.
Only bars with a sufficiently long wick relative to volatility qualify as candidate “liquidity events”.
Volume filter
Optionally, the script requires a volume spike:
Use volume filter — if enabled, volume must exceed a rolling volume SMA by a configurable multiplier.
Volume SMA length — period for the volume average.
Volume spike multiplier — how many times above the SMA current volume needs to be.
This lets you focus only on “heavy” tests of liquidity and ignore quiet bars.
Event types
Putting it together:
Upper event (potential supply / long liquidation, etc.)
Occurs when:
Upper wick is large in ATR terms.
Full bar range is large in ATR terms.
Volume is above the spike threshold (if enabled).
Lower event (potential demand / short liquidation, etc.)
Symmetric conditions using the lower wick.
How zones are constructed
Zone geometry lives in Zone Geometry .
When an event is detected, the script builds a rectangular box that anchors to the wick and extends in the appropriate direction by an ATR-based thickness.
For upper (supply-type) zones
Bottom of the zone = event bar high.
Top of the zone = event bar high + Zone thickness in ATRs × ATR.
The zone initially spans only the event bar on the x-axis, but is extended to the right as new bars appear while the zone is active.
For lower (demand-type) zones
Top of the zone = event bar low.
Bottom of the zone = event bar low − Zone thickness in ATRs × ATR.
Same extension logic: box starts on the event bar and grows rightward while alive.
The result is a band around the wick that scales with volatility. On high-ATR charts, zones are thicker. On calm charts, they are narrower and more precise.
Zone lifecycle, decay, and removal
All lifecycle logic is controlled by the Decay & Lifetime group.
Each zone carries:
Score — a floating-point “importance” measure, starting at 1.0 when created.
Direction — +1 for upper zones, −1 for lower zones.
Birth index — bar index at creation time.
Active flag — whether the zone is still considered unbroken and extendable.
1) Active vs broken
Each confirmed bar, the script checks:
For an upper zone , the zone is counted as “broken” when the close moves above the top of the zone.
For a lower zone , the zone is counted as “broken” when the close moves below the bottom of the zone.
When a zone breaks:
Its right edge is frozen at the previous bar (no further extension).
The zone remains on the chart, but is no longer updated by price interaction. It still decays in score until removal.
This lets you see where a major level was overrun, while naturally fading its influence over time.
2) Time decay
At each confirmed bar:
Score := Score × Score decay per bar .
A decay value close to 1.0 means very slow decay and long-lived zones.
Lower values (closer to 0.9) mean faster forgetting and more current-focused zones.
You are controlling how quickly the market “forgets” past events.
3) Age and score-based removal
Zones are removed when either:
Age in bars exceeds Max bars a zone can live .
This is a hard lifetime cap.
Score falls below Minimum score before removal .
This trims zones that have decayed into irrelevance even if their age is still within bounds.
When a zone is removed, its box is deleted and all associated state is freed to keep performance and visuals clean.
Unified gradient and color logic
Color control lives in Gradient & Color . The indicator uses a single continuous gradient for all zones, above and below price, so you can read strength at a glance without guessing what palette means what.
Base colors
You set:
Mid strength color (green) — used for mid-level strength zones and as the “anchor” in the gradient.
High strength color (red) — used for the strongest zones.
Max opacity — the maximum visual opacity for the solid part of the gradient. Lower values here mean more solid; higher values mean more transparent.
The script then defines three internal points:
Clear end — same as mid color, but with a high alpha (close to transparent).
Mid end — mid color at the strongest allowed opacity.
High end — high color at the strongest allowed opacity.
Strength normalization
Within each update:
The script finds the maximum score among all existing zones.
Each zone’s strength is computed as its score divided by this maximum.
Strength is clamped into .
This means a zone with strength 1.0 is currently the strongest zone on the chart. Other zones are colored relative to that.
Piecewise gradient
Color is assigned in two stages:
For strength between 0.0 and 0.5: interpolate from “clear” green to solid green.
Weak zones are barely visible, mid-strength zones appear as solid green.
For strength between 0.5 and 1.0: interpolate from solid green to solid red.
The strongest zones shift toward the red anchor, clearly separating them from everything else.
Strength scale legend
To make the gradient readable, the indicator draws a vertical legend on the right side of the chart:
About 15 cells from top (Strong) to bottom (Weak).
Each cell uses the same gradient function as the zones themselves.
Top cell is labeled “Strong”; bottom cell is labeled “Weak”.
This legend acts as a fixed reference so you can instantly map a zone’s color to its approximate strength rank.
What it plots
At a glance, the indicator produces:
Upper liquidity zones above price, built from large upper wick events.
Lower liquidity zones below price, built from large lower wick events.
All zones colored by relative strength using the same gradient.
Zones that freeze when price breaks them, then fade out via decay and removal.
A strength scale legend on the right to interpret the gradient.
There are no extra lines, labels, or clutter. The focus is the evolving structure of liquidity zones and their visual strength.
How to read the zones
Bright red / bright green zones
These are your current “major” liquidity areas. They have high scores relative to other zones and have not yet decayed. Expect meaningful reactions, absorption attempts, or spillover moves when price interacts with them.
Faded zones
Pale, nearly transparent zones are either old, decayed, or minor. They can still matter, but priority is lower. If these are in the middle of a long consolidation, they often become background noise.
Broken but still visible zones
Zones whose extension has stopped have been overrun by closing price. They show where a key level gave way. You can use them as context for regime shifts or failed attempts.
Absence of zones
A chart with few or no zones means that, under your current thresholds, there have not been strong enough liquidity events recently. Either tighten the filters or accept that recent price action has been relatively balanced.
Use cases
1) Intraday liquidity hunting
Run the indicator on lower timeframes (e.g., 1–15 minute) with moderately fast decay.
Use the upper zones as potential sell reaction areas, the lower zones as potential buy reaction areas.
Combine with order flow, CVD, or footprint tools to see whether price is absorbing or rejecting at each zone.
2) Swing trading context
Increase ATR length and range/wick multipliers to focus only on major spikes.
Set slower decay and higher max lifetime so zones persist across multiple sessions.
Use these zones as swing inflection areas for larger setups, for example anticipating re-tests after breakouts.
3) Stop placement and invalidation
For longs, place invalidation beyond a decaying lower zone rather than in the middle of noise.
For shorts, place invalidation beyond strong upper zones.
If price closes through a strong zone and it freezes, treat that as additional evidence your prior bias may be wrong.
4) Identifying trapped flows
Upper zones formed after violent spikes up that quickly fail can mark trapped longs.
Lower zones formed after violent spikes down that quickly reverse can mark trapped shorts.
Watching how price behaves on the next touch of those zones can hint at whether those participants are being rescued or squeezed.
Settings overview
Event Detection
Use volume filter — enable or disable the volume spike requirement.
Volume SMA length — rolling window for average volume.
Volume spike multiplier — how aggressive the volume spike filter is.
ATR length — period for ATR, used in all size comparisons.
Min wick size in ATRs — minimum wick size threshold.
Min range in ATRs — minimum bar range threshold.
Zone Geometry
Zone thickness in ATRs — vertical size of each liquidity zone, scaled by ATR.
Decay & Lifetime
Score decay per bar — multiplicative decay factor for each zone score per bar.
Max bars a zone can live — hard cap on lifetime.
Minimum score before removal — score cut-off at which zones are deleted.
Gradient & Color
Mid strength color (green) — base color for mid-level zones and the lower half of the gradient.
High strength color (red) — target color for the strongest zones.
Max opacity — controls the most solid end of the gradient (0 = fully solid, 100 = fully invisible).
Tuning guidance
Fast, session-only liquidity
Shorter ATR length (e.g., 20–50).
Higher wick and range multipliers to focus only on extreme events.
Decay per bar closer to 0.95–0.98 and moderate max lifetime.
Volume filter enabled with a decent multiplier (e.g., 1.5–2.0).
Slow, structural zones
Longer ATR length (e.g., 100+).
Moderate wick and range thresholds.
Decay per bar very close to 1.0 for slow fading.
Higher max lifetime and slightly higher min score threshold so only very weak zones disappear.
Noisy, high-volatility instruments
Increase wick and range ATR multipliers to avoid over-triggering.
Consider enabling the volume filter with stronger settings.
Keep decay moderate to avoid the chart getting overloaded with old zones.
Notes
This is a structural and contextual tool, not a complete trading system. It does not account for transaction costs, execution slippage, or your specific strategy rules. Use it to:
Highlight where liquidity has recently been tested hard.
Rank these areas by decaying strength.
Guide your attention when layering in separate entry signals, risk management, and higher-timeframe context.
Time-Decay Liquidity Zones is designed to keep your chart focused on where the market has most recently “cared” about price, and to gradually forget what no longer matters. Adjust the detection, geometry, decay, and gradient to fit your product and timeframe, and let the zones show you which parts of the tape still have unfinished business.
Advanced Triple Strategy ScalperHere are the three scalping strategies presented in the video "3 Scalping Strategies That Work Every Day (Backtested & Proven)" by Asia Forex Mentor – Ezekiel Chew:
### Scalper’s Trend Filter (Triple EMA)
This strategy uses three EMAs (25, 50, 100) on the 5-minute chart to filter high-probability trades aligned with momentum .
- Only trade when all three EMAs are angled in the same direction and clearly separated (no crossing or tangling) .
- Enter when price pulls back toward the 25 or 50 EMA and then bounces back toward the 25 EMA, but do not enter if price closes below the 100 EMA .
- Set stop-loss just below the 50 EMA or swing low and aim for a risk-to-reward ratio of 1:1.5 .
### Flip Zone Trap (Reversal Catching)
This method identifies precise reversal moments where market structure shifts from weakness to strength .
- Use the 15-min chart to locate key support or resistance zones where price previously reacted .
- Wait for price to stop making lower lows and begin making higher highs (or vice versa for shorts); confirm with a trendline break AND follow-through (higher lows & highs within 5-7 candles) .
- Use confirmation candles (bullish engulfing, pin bar rejection) at the zone before entry .
### Liquidity Shift Trigger (Smart Money Trap)
This system leverages institutional stop hunts and liquidity sweeps at key zones for sniper entries .
- Start with a 15-min chart to identify structure breaks and points of interest (order blocks, flip zones, demand zones) .
- Drop to 1-min chart and wait for price to enter the refined zone and sweep liquidity (sharp wick/spike below/above key level) .
- Once liquidity is swept, wait for a clean structure shift (break of most recent internal high or low) within 5–6 candles—if confirmed, refine entry to the candle that caused the break and enter when price returns to that candle with a strong reaction .
***
### Practical Application
- These strategies are systematic, rule-based, and designed to cut out fake moves, avoid early stop-outs, and align entries with momentum and institutional activity .
- Perfect for short timeframes and volatile pairs like XAUUSD, especially if paired with additional confirmation from other technical analysis tools .
All three strategies emphasize filtering noise, waiting for momentum/trend confirmation, and avoiding impulsive entries—key principles for consistent scalping success
Smart Money Volume Matrix [Ata]Smart Money Volume Matrix
The Smart Money Volume Matrix (SMV Matrix) is an advanced volume-spread analysis (VSA) dashboard and charting tool designed to identify significant market anomalies by analyzing the relationship between price extremes and volume flow.
Unlike traditional indicators that rely solely on moving averages or oscillators, this tool performs a "Snapshot Analysis" of a defined lookback period (default: 100 bars) to rank price action based on Order Flow Dominance. It isolates the Top 10 Highest and Lowest Close prices and scrutinizes the volume behind them to categorize market sentiment into four distinct phases: Distribution, No Demand, Absorption, and Exhaustion.
Core Logic & Methodology
The script operates on a Zero-Lag Snapshot Engine. It does not print historical signals bar-by-bar; instead, it evaluates the current market structure relative to the recent history (Lookback Period).
1. Ranking Engine: The script scans the lookback period to find the Top 10 Highest Closes and Top 10 Lowest Closes.
2. Volume Classification: For each ranked bar, it calculates the "Intrabar Buy/Sell Volume" (or approximates it using candle geometry if Intrabar data is unavailable).
3. Dominance Detection: It compares Buying Volume vs. Selling Volume to determine who is in control at critical price levels.
Signal Classifications (VSA Logic)
The indicator generates labels on the chart and updates the dashboard table based on the following logic:
1. At Price Tops (Resistance Areas):
- Distribution (Supply): High Price + High Total Volume + Sellers Dominant.
Interpretation: Indicates heavy institutional selling into rising prices. Often precedes a reversal.
- Buy Climax: High Price + High Total Volume + Buyers Dominant.
Interpretation: Extreme buying frenzy. While bullish, it often marks a "trap" or temporary top due to exhaustion.
- No Demand: High Price + Low Volume.
Interpretation: Prices drifted higher but lack institutional participation. A sign of weakness.
2. At Price Bottoms (Support Areas):
- Absorption: Low Price + High Total Volume + Buyers Dominant.
Interpretation: Institutional money is absorbing selling pressure (passive buying). A strong sign of accumulation.
- Panic Sell: Low Price + High Total Volume + Sellers Dominant.
Interpretation: Extreme fear. High volume at lows typically indicates capitulation and potential hands-changing.
- Exhaustion: Low Price + Low Volume.
Interpretation: Selling pressure has dried up. The market may float upward due to lack of sellers.
Key Features
- Dashboard Matrix Table:
Displays the exact Close Price, Buy/Sell Volume, and Market State (Group) for the Top 10 ranking bars.
Smart Footer: Automatically detects the active "Resistance Zone" (derived from G1 Distribution levels) and "Support Zone" (derived from G3 Absorption levels) and reports the current price status relative to these zones (e.g., "Testing Resistance", "Breakout", "At Support").
- Smart Zones (Auto S/R):
Automatically draws Support and Resistance boxes extending into the future based on the most significant volume clusters found in the rankings. Includes logic to detect "Flips" (e.g., when Support breaks, it is labeled as a flip to Resistance).
- Average Trend Channels:
Calculates a Linear Regression trend line based specifically on the coordinates of the Top 10 Highs and Top 10 Lows, providing a "Best Fit" channel for the current market structure.
- Visual Clarity:
Labels utilize a "Smart Stacking" algorithm to prevent overlap on the chart. Guide lines connect labels to their respective candles for precise identification.
Settings & Configuration
- Matrix Settings: Lookback Period (default 100 bars) and Top Rank Count.
- Volume Engine: Choose between "Intrabar (Precise)" for accurate order flow or "Geometry (Approx)" for standard volume estimation.
- Visuals: Toggle Table, Labels, Lines, Zones, and Trend Lines. Adjust transparency and font sizes.
IMPORTANT NOTE ON SNAPSHOT LOGIC
This indicator is designed as a Real-Time Dashboard. It continuously updates the "Top 10" list as new candles form. Therefore, a label that appears on a candle may disappear if that candle falls out of the Top 10 ranking or leaves the lookback window. This is intended behavior to ensure the chart always reflects the current most critical levels, rather than a historical record of past signals. It is best used for live market analysis rather than historical back testing.
Disclaimer: This tool is for educational and analytical purposes only. Volume analysis is subjective and should be used in conjunction with other methods of technical analysis.
ATH대비 지정하락률에 도착 시 매수 - 장기홀딩 선물 전략(ATH Drawdown Re-Buy Long Only)본 스크립트는 과거 하락 데이터를 이용하여, 정해진 하락 %가 발생하는 경우 자기 자본의 정해진 %만큼을 진입하게 설계되어진 스트레티지입니다.
레버리지를 사용할 수 있으며 기본적으로 셋팅해둔 값이 내장되어있습니다.(자유롭게 바꿔서 쓰시면 됩니다.) 추가적으로 2번의 진입 외에도 다른 진입 기준, 진입 %를 설정하실 수 있으며 - ChatGPT에게 요청하면 수정해줄 것입니다.
실제 사용용도로는 KillSwitch 기능을 꺼주세요. 바 돋보기 기능을 켜주세요.
ATH Drawdown Re-Buy Long Only 전략 설명
1. 전략 개요
ATH Drawdown Re-Buy Long Only 전략은 자산의 역대 최고가(ATH, All-Time High)를 기준으로 한 하락폭(드로우다운)을 활용하여,
특정 구간마다 단계적으로 롱 포지션을 구축하는 자동 재매수(Long Only) 전략입니다.
본 전략은 다음과 같은 목적을 가지고 설계되었습니다.
급격한 조정 구간에서 체계적인 분할 매수 및 레버리지 활용
ATH를 기준으로 한 명확한 진입 규칙 제공
실시간으로
평단가
레버리지
청산가 추정
계좌 MDD
수익률
등을 시각적으로 제공하여 리스크와 포지션 상태를 직관적으로 확인할 수 있도록 지원
※ 본 전략은 교육·연구·백테스트 용도로 제공되며,
어떠한 형태의 투자 권유 또는 수익을 보장하지 않습니다.
2. 전략의 핵심 개념
2-1. ATH(역대 최고가) 기준 드로우다운
전략은 차트 상에서 항상 가장 높은 고가(High)를 ATH로 기록합니다.
새로운 고점이 형성될 때마다 ATH를 갱신하고, 해당 ATH를 기준으로 다음을 계산합니다.
현재 바의 저가(Low)가 ATH에서 몇 % 하락했는지
현재 바의 종가(Close)가 ATH에서 몇 % 하락했는지
그리고 사전에 설정한 두 개의 드로우다운 구간에서 매수를 수행합니다.
1차 진입 구간: ATH 대비 X% 하락 시
2차 진입 구간: ATH 대비 Y% 하락 시
각 구간은 ATH가 새로 갱신될 때마다 한 번씩만 작동하며,
새로운 ATH가 생성되면 다시 “1차 / 2차 진입 가능 상태”로 초기화됩니다.
2-2. 첫 포지션 100% / 300% 특수 규칙
이 전략의 중요한 특징은 **“첫 포지션 진입 시의 예외 규칙”**입니다.
전략이 현재 어떠한 포지션도 들고 있지 않은 상태에서
최초로 롱 포지션을 진입하는 시점(첫 포지션)에 대해:
기본적으로는 **자산의 100%**를 기준으로 포지션을 구축하지만,
만약 그 순간의 가격이 ATH 대비 설정값 이상(예: 약 –72.5% 이상 하락한 상황) 이라면
→ 자산의 300% 규모로 첫 포지션을 진입하도록 설계되어 있습니다.
이 규칙은 다음과 같이 동작합니다.
첫 진입이 1차 드로우다운 구간에서 발생하든,
첫 진입이 2차 드로우다운 구간에서 발생하든,
현재 하락폭이 설정된 기준 이상(예: –72.5% 이상) 이라면
→ “이 정도 하락이면 첫 진입부터 더 공격적으로 들어간다”는 의미로 300% 규모로 진입
그 이하의 하락폭이라면
→ 첫 진입은 100% 규모로 제한
즉, 전략은 다음 두 가지 모드로 동작합니다.
일반적인 상황의 첫 진입: 자산의 100%
심각한 드로우다운 구간에서의 첫 진입: 자산의 300%
이 특수 규칙은 깊은 하락에서는 공격적으로, 평소에는 상대적으로 보수적으로 진입하도록 설계된 것입니다.
3. 전략 동작 구조
3-1. 매수 조건
차트 상 High 기준으로 ATH를 추적합니다.
각 바마다 해당 ATH에서의 하락률을 계산합니다.
사용자가 설정한 두 개의 드로우다운 구간(예시):
1차 구간: 예를 들어 ATH – 50%
2차 구간: 예를 들어 ATH – 72.5%
각 구간에 대해 다음과 같은 조건을 확인합니다.
“이번 ATH 구간에서 아직 해당 구간 매수를 한 적이 없는 상태”이고,
현재 바의 저가(Low)가 해당 구간 가격 이하를 찍는 순간
→ 해당 바에서 매수 조건 충족으로 간주
실제 주문은:
해당 구간 가격에 맞춰 롱 포지션 진입(리밋/시장가 기반 시뮬레이션) 으로 처리됩니다.
3-2. ATH 갱신과 진입 기회 리셋
차트 상에서 새로운 고점(High)이 기존 ATH를 넘어서는 순간,
ATH가 갱신되고,
1차 / 2차 진입 여부를 나타내는 내부 플래그가 초기화됩니다.
이를 통해, 시장이 새로운 고점을 돌파해 나갈 때마다,
해당 구간에서 다시 한 번씩 1차·2차 드로우다운 진입 기회를 갖게 됩니다.
4. 포지션 사이징 및 레버리지
4-1. 계좌 자산(Equity) 기준 포지션 크기 결정
전략은 현재 계좌 자산을 다음과 같이 정의하여 사용합니다.
현재 자산 = 초기 자본 + 실현 손익 + 미실현 손익
각 진입 구간에서의 포지션 가치는 다음과 같이 결정됩니다.
1차 진입 구간:
“자산의 몇 %를 사용할지”를 설정값으로 입력
설정된 퍼센트를 계좌 자산에 곱한 뒤,
다시 전략 내 레버리지 배수(Leverage) 를 곱하여 실제 포지션 가치를 계산
2차 진입 구간:
동일한 방식으로, 독립된 퍼센트 설정값을 사용
즉, 포지션 가치는 다음과 같이 계산됩니다.
포지션 가치 = 현재 자산 × (해당 구간 설정 % / 100) × 레버리지 배수
그리고 이를 해당 구간의 진입 가격으로 나누어 실제 수량(토큰 단위) 를 산출합니다.
4-2. 첫 포지션의 예외 처리 (100% / 300%)
첫 포지션에 대해서는 위의 일반적인 퍼센트 설정 대신,
다음과 같은 고정 비율이 사용됩니다.
기본: 자산의 100% 규모로 첫 포지션 진입
단, 진입 시점의 ATH 대비 하락률이 설정값 이상(예: –72.5% 이상) 일 경우
→ 자산의 300% 규모로 첫 포지션 진입
이때 역시 다음 공식을 사용합니다.
포지션 가치 = 현재 자산 × (100% 또는 300%) × 레버리지
그리고 이를 가격으로 나누어 실제 진입 수량을 계산합니다.
이 규칙은:
첫 진입이 1차 구간이든 2차 구간이든 동일하게 적용되며,
“충분히 깊은 하락 구간에서는 첫 진입부터 더 크게,
평소에는 비교적 보수적으로” 라는 운용 철학을 반영합니다.
4-3. 실레버리지(Real Leverage)의 추적
전략은 각 바 단위로 다음을 추적합니다.
바가 시작할 때의 기존 포지션 크기
해당 바에서 새로 진입한 수량
이를 바탕으로, 진입이 발생한 시점에 다음을 계산합니다.
실제 레버리지 = (포지션 가치 / 현재 자산)
그리고 차트 상에 예를 들어:
Lev 2.53x 와 같은 형식의 레이블로 표시합니다.
이를 통해, 매수 시점마다 실제 계좌 레버리지가 어느 정도였는지를 직관적으로 확인할 수 있습니다.
5. 시각화 및 모니터링 요소
5-1. 차트 상 시각 요소
전략은 차트 위에 다음과 같은 정보를 직접 표시합니다.
ATH 라인
High 기준으로 계산된 역대 최고가를 주황색 선으로 표시
평단가(평균 진입가) 라인
현재 보유 포지션이 있을 때,
해당 포지션의 평균 진입가를 노란색 선으로 표시
추정 청산가(고정형 청산가) 라인
포지션 수량이 변화하는 시점을 감지하여,
당시의 평단가와 실제 레버리지를 이용해 근사적인 청산가를 계산
이를 빨간색 선으로 차트에 고정 표시
포지션이 없거나 레버리지가 1배 이하인 경우에는 청산가 라인을 제거
매수 마커 및 레이블
1차/2차 매수 조건이 충족될 때마다 해당 지점에 매수 마커를 표시
"Buy XX% @ 가격", "Lev XXx" 형태의 라벨로
진입 비율과 당시 레버리지를 함께 시각화
레이블의 위치는 설정에서 선택 가능:
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
5-2. 우측 상단 정보 테이블
차트 우측 상단에는 현재 계좌·포지션 상태를 요약한 정보 테이블이 표시됩니다.
대표적으로 다음 항목들이 포함됩니다.
Pos Qty (Token)
현재 보유 중인 포지션 수량(토큰 기준, 절대값 기준)
Pos Value (USDT)
현재 포지션의 시장 가치 (수량 × 현재 가격)
Leverage (Now)
현재 실레버리지 (포지션 가치 / 현재 자산)
DD from ATH (%)
현재 가격 기준, 최근 ATH에서의 하락률(%)
Avg Entry
현재 포지션의 평균 진입 가격
PnL (%)
현재 포지션 기준 미실현 손익률(%)
Max DD (Equity %)
전략 전체 기간 동안 기록된 계좌 기준 최대 손실(MDD, Max Drawdown)
Last Entry Price
가장 최근에 포지션을 추가로 진입한 직후의 평균 진입 가격
Last Entry Lev
위 “Last Entry Price” 시점에서의 실레버리지
Liq Price (Fixed)
위에서 설명한 고정형 추정 청산가
Return from Start (%)
전략 시작 시점(초기 자본) 대비 현재 계좌 자산의 총 수익률(%)
이 테이블을 통해 사용자는:
현재 계좌와 포지션의 상태
리스크 수준
누적 성과
를 직관적으로 파악할 수 있습니다.
6. 시간 필터 및 라벨 옵션
6-1. 전략 동작 기간 설정
전략은 옵션으로 특정 기간에만 전략을 동작시키는 시간 필터를 제공합니다.
“Use Date Range” 옵션을 활성화하면:
시작 시각과 종료 시각을 지정하여
해당 구간에 한해서만 매매가 발생하도록 제한
옵션을 비활성화하면:
전략은 전체 차트 구간에서 자유롭게 동작
6-2. 진입 라벨 위치 설정
사용자는 매수/레버리지 라벨의 위치를 선택할 수 있습니다.
바 아래 (Below Bar)
바 위 (Above Bar)
실제 가격 위치 (At Price)
이를 통해 개인 취향 및 차트 가독성에 맞추어
시각화 방식을 유연하게 조정할 수 있습니다.
7. 활용 대상 및 사용 예시
본 전략은 다음과 같은 목적에 적합합니다.
현물 또는 선물 롱 포지션 기준 장기·스윙 관점 추매 전략 백테스트
“고점 대비 하락률”을 기준으로 한 규칙 기반 운용 아이디어 검증
레버리지 사용 시
계좌 레버리지·청산가·MDD를 동시에 모니터링하고자 하는 경우
특정 자산에 대해
“새로운 고점이 형성될 때마다
일정한 규칙으로 깊은 조정 구간에서만 분할 진입하고자 할 때”
실거래에 그대로 적용하기보다는,
전략 아이디어 검증 및 리스크 프로파일 분석,
자신의 성향에 맞는 파라미터 탐색 용도로 사용하는 것을 권장합니다.
8. 한계 및 유의사항
백테스트 결과는 미래 성과를 보장하지 않습니다.
과거 데이터에 기반한 시뮬레이션일 뿐이며,
실제 시장에서는
유동성
슬리피지
수수료 체계
강제청산 규칙
등 다양한 변수가 존재합니다.
청산가는 단순화된 공식에 따른 추정치입니다.
거래소별 실제 청산 규칙, 유지 증거금, 수수료, 펀딩비 등은
본 전략의 계산과 다를 수 있으며,
청산가 추정 라인은 참고용 지표일 뿐입니다.
레버리지 및 진입 비율 설정에 따라 손실 폭이 매우 커질 수 있습니다.
특히 **“첫 포지션 300% 진입”**과 같이 매우 공격적인 설정은
시장 급락 시 계좌 손실과 청산 리스크를 크게 증가시킬 수 있으므로
신중한 검토가 필요합니다.
실거래 연동 시에는 별도의 리스크 관리가 필수입니다.
개별 손절 기준
포지션 상한선
전체 포트폴리오 내 비중 관리 등
본 전략 외부에서 추가적인 안전장치가 필요합니다.
9. 결론
ATH Drawdown Re-Buy Long Only 전략은 단순한 “저가 매수”를 넘어서,
ATH 기준으로 드로우다운을 구조적으로 활용하고,
첫 포지션에 대한 **특수 규칙(100% / 300%)**을 적용하며,
레버리지·청산가·MDD·수익률을 통합적으로 시각화함으로써,
하락 구간에서의 규칙 기반 롱 포지션 구축과
리스크 모니터링을 동시에 지원하는 전략입니다.
사용자는 본 전략을 통해:
자신의 시장 관점과 리스크 허용 범위에 맞는
드로우다운 구간
진입 비율
레버리지 설정
다양한 시나리오에 대한 백테스트와 분석
을 수행할 수 있습니다.
다시 한 번 강조하지만,
본 전략은 연구·학습·백테스트를 위한 도구이며,
실제 투자 판단과 책임은 전적으로 사용자 본인에게 있습니다.
/ENG Version.
This script is designed to use historical drawdown data and automatically enter positions when a predefined percentage drop from the all-time high occurs, using a predefined percentage of your account equity.
You can use leverage, and default parameter values are provided out of the box (you can freely change them to suit your style).
In addition to the two main entry levels, you can add more entry conditions and custom entry percentages – just ask ChatGPT to modify the script.
For actual/live usage, please turn OFF the KillSwitch function and turn ON the Bar Magnifier feature.
ATH Drawdown Re-Buy Long Only Strategy
1. Strategy Overview
The ATH Drawdown Re-Buy Long Only strategy is an automatic re-buy (Long Only) system that builds long positions step-by-step at specific drawdown levels, based on the asset’s all-time high (ATH) and its subsequent drawdown.
This strategy is designed with the following goals:
Systematic scaled buying and leverage usage during sharp correction periods
Clear, rule-based entry logic using drawdowns from ATH
Real-time visualization of:
Average entry price
Leverage
Estimated liquidation price
Account MDD (Max Drawdown)
Return / performance
This allows traders to intuitively monitor both risk and position status.
※ This strategy is provided for educational, research, and backtesting purposes only.
It does not constitute investment advice and does not guarantee any profits.
2. Core Concepts
2-1. Drawdown from ATH (All-Time High)
On the chart, the strategy always tracks the highest high as the ATH.
Whenever a new high is made, ATH is updated, and based on that ATH the following are calculated:
How many percent the current bar’s Low is below the ATH
How many percent the current bar’s Close is below the ATH
Using these, the strategy executes buys at two predefined drawdown zones:
1st entry zone: When price drops X% from ATH
2nd entry zone: When price drops Y% from ATH
Each zone is allowed to trigger only once per ATH cycle.
When a new ATH is created, the “1st / 2nd entry possible” flags are reset, and new opportunities open up for that ATH leg.
2-2. Special Rule for the First Position (100% / 300%)
A key feature of this strategy is the special rule for the very first position.
When the strategy currently holds no position and is about to open the first long position:
Under normal conditions, it builds the position using 100% of account equity.
However, if at that moment the price has dropped by at least a predefined threshold from ATH (e.g. around –72.5% or more),
→ the strategy will open the first position using 300% of account equity.
This rule works as follows:
Whether the first entry happens at the 1st drawdown zone or at the 2nd drawdown zone,
If the current drawdown from ATH is at or below the threshold (e.g. –72.5% or worse),
→ the strategy interprets this as “a sufficiently deep crash” and opens the initial position with 300% of equity.
If the drawdown is less severe than the threshold,
→ the first entry is capped at 100% of equity.
So the strategy has two modes for the first entry:
Normal market conditions: 100% of equity
Deep drawdown conditions: 300% of equity
This special rule is intended to be aggressive in extremely deep crashes while staying more conservative in normal corrections.
3. Strategy Logic & Execution
3-1. Entry Conditions
The strategy tracks the ATH using the High price.
For each bar, it calculates the drawdown from ATH.
The user defines two drawdown zones, for example:
1st zone: ATH – 50%
2nd zone: ATH – 72.5%
For each zone, the strategy checks:
If no buy has been executed yet for that zone in the current ATH leg, and
If the current bar’s Low touches or falls below that zone’s price level,
→ That bar is considered to have triggered a buy condition.
Order simulation:
The strategy simulates entering a long position at that zone’s price level
(using a limit/market-like approximation for backtesting).
3-2. ATH Reset & Entry Opportunity Reset
When a new High goes above the previous ATH:
The ATH is updated to this new high.
Internal flags that track whether the 1st and 2nd entries have been used are reset.
This means:
Each time the market makes a new ATH,
The strategy once again has a fresh opportunity to execute 1st and 2nd drawdown entries for that new ATH leg.
4. Position Sizing & Leverage
4-1. Position Size Based on Account Equity
The strategy defines current equity as:
Current Equity = Initial Capital + Realized PnL + Unrealized PnL
For each entry zone, the position value is calculated as follows:
The user inputs:
“What % of equity to use at this zone”
The strategy:
Multiplies current equity by that percentage
Then multiplies by the strategy’s leverage factor
Thus:
Position Value = Current Equity × (Zone % / 100) × Leverage
Finally, this position value is divided by the entry price to determine the actual position size in tokens.
4-2. Exception for the First Position (100% / 300%)
For the very first position (when there is no open position),
the strategy does not use the zone % parameters. Instead, it uses fixed ratios:
Default: Enter the first position with 100% of equity.
If the drawdown from ATH at that moment is greater than or equal to a predefined threshold (e.g. –72.5% or more)
→ Enter the first position with 300% of equity.
The position value is computed as:
Position Value = Current Equity × (100% or 300%) × Leverage
Then it is divided by the entry price to obtain the token quantity.
This rule:
Applies regardless of whether the first entry occurs at the 1st zone or 2nd zone.
Embeds the philosophy:
“In very deep crashes, go much larger on the first entry; otherwise, stay more conservative.”
4-3. Tracking Real Leverage
On each bar, the strategy tracks:
The existing position size at the start of the bar
The newly added size (if any) on that bar
When a new entry occurs, it calculates the real leverage at that moment:
Real Leverage = (Position Value / Current Equity)
This is then displayed on the chart as a label, for example:
Lev 2.53x
This makes it easy to see the actual leverage level at each entry point.
5. Visualization & Monitoring
5-1. On-Chart Visual Elements
The strategy plots the following directly on the chart:
ATH Line
The all-time high (based on High) is plotted as an orange line.
Average Entry Price Line
When a position is open, the average entry price of that position is plotted as a yellow line.
Estimated Liquidation Price (Fixed) Line
The strategy detects when the position size changes.
At each size change, it uses the current average entry price and real leverage to compute an approximate liquidation price.
This “fixed liquidation price” is then plotted as a red line on the chart.
If there is no position, or if leverage is 1x or lower, the liquidation line is removed.
Entry Markers & Labels
When 1st/2nd entry conditions are met, the strategy:
Marks the entry point on the chart.
Displays labels such as "Buy XX% @ Price" and "Lev XXx",
showing both entry percentage and real leverage at that time.
The label placement is configurable:
Below Bar
Above Bar
At Price
5-2. Information Table (Top-Right Panel)
In the top-right corner of the chart, the strategy displays a summary table of the current account and position status. It typically includes:
Pos Qty (Token)
Absolute size of the current position (in tokens)
Pos Value (USDT)
Market value of the current position (qty × current price)
Leverage (Now)
Current real leverage (position value / current equity)
DD from ATH (%)
Current drawdown (%) from the latest ATH, based on current price
Avg Entry
Average entry price of the current position
PnL (%)
Unrealized profit/loss (%) of the current position
Max DD (Equity %)
The maximum equity drawdown (MDD) recorded over the entire backtest period
Last Entry Price
Average entry price immediately after the most recent add-on entry
Last Entry Lev
Real leverage at the time of the most recent entry
Liq Price (Fixed)
The fixed estimated liquidation price described above
Return from Start (%)
Total return (%) of equity compared to the initial capital
Through this table, users can quickly grasp:
Current account and position status
Current risk level
Cumulative performance
6. Time Filters & Label Options
6-1. Strategy Date Range Filter
The strategy provides an option to restrict trading to a specific time range.
When “Use Date Range” is enabled:
You can specify start and end timestamps.
The strategy will only execute trades within that range.
When this option is disabled:
The strategy operates over the entire chart history.
6-2. Entry Label Placement
Users can customize where entry/leverage labels are drawn:
Below Bar (Below Bar)
Above Bar (Above Bar)
At the actual price level (At Price)
This allows you to adjust visualization according to personal preference and chart readability.
7. Use Cases & Applications
This strategy is suitable for the following purposes:
Long-term / swing-style re-buy strategies for spot or futures long positions
Testing rule-based strategies that rely on “drawdown from ATH” as a main signal
Monitoring account leverage, liquidation price, and MDD when using leverage
Handling situations where, for a given asset:
“Every time a new ATH is formed,
you want to wait for deep corrections and enter only at specific drawdown zones”
It is generally recommended to use this strategy not as a direct plug-and-play live system, but as a tool for:
Strategy idea validation
Risk profile analysis
Parameter exploration to match your personal risk tolerance and style
8. Limitations & Warnings
Backtest results do not guarantee future performance.
They are based on historical data only.
In live markets, additional factors exist:
Liquidity
Slippage
Fee structures
Exchange-specific liquidation rules
Funding fees, etc.
The liquidation price is only an approximate estimate, derived from a simplified formula.
Actual liquidation rules, maintenance margin requirements, fees, and other details differ by exchange.
The liquidation line should be treated as a reference indicator, not an exact guarantee.
Depending on the configured leverage and entry percentages, losses can be very large.
In particular, extremely aggressive settings such as “first position 300% of equity” can greatly increase the risk of large account drawdowns and liquidation during sharp market crashes.
Use such settings with extreme caution.
For live trading, additional risk management is essential:
Your own stop-loss rules
Maximum position size limits
Portfolio-level exposure controls
And other external safety mechanisms beyond this strategy
9. Conclusion
The ATH Drawdown Re-Buy Long Only strategy goes beyond simple “buy the dip” logic. It:
Systematically utilizes drawdowns from ATH as a structural signal
Applies a special first-position rule (100% / 300%)
Integrates visualization of leverage, liquidation price, MDD, and returns
All of this supports rule-based long position building in drawdown phases and comprehensive risk monitoring.
With this strategy, users can:
Explore different:
Drawdown zones
Entry percentages
Leverage levels
Run various backtests and scenario analyses
Better understand the risk/return profile that fits their own market view and risk tolerance
Once again, this strategy is intended for research, learning, and backtesting only.
All real trading decisions and their consequences are solely the responsibility of the user.
Scout Regiment - Bias# Scout Regiment - Bias Indicator
## English Documentation
### Overview
Scout Regiment - Bias is a technical indicator that measures the deviation (bias) between the current price and exponential moving averages (EMAs). It helps traders identify overbought/oversold conditions, trend strength, and potential reversal points through divergence detection.
### What is Bias?
Bias measures how far the price has moved away from a moving average, expressed as a percentage:
- **Positive Bias**: Price is above the EMA (potential overbought)
- **Negative Bias**: Price is below the EMA (potential oversold)
- **Formula**: Bias = (Price - EMA) / EMA × 100
### Key Features
#### 1. **Triple EMA Bias Lines**
The indicator calculates bias from three different EMAs:
- **EMA 55 Bias** (Default: Green/Red, 1px line)
- Short-term bias measurement
- Quick response to price changes
- Best for intraday and swing trading
- **EMA 144 Bias** (Pink, 2px line)
- Medium-term bias measurement
- Balanced response to price movements
- Ideal for swing trading
- **EMA 233 Bias** (White, 2px line)
- Long-term bias measurement
- Slower response, more stable
- Best for position trading
**Color Coding:**
- Green: Price above EMA (bullish)
- Red: Price below EMA (bearish)
#### 2. **Visual Components**
**Histogram Display**
- Shows EMA 55 bias as a histogram for easy visualization
- Green bars: Price above EMA 55
- Red bars: Price below EMA 55
- Can be toggled on/off
**Background Color**
- Light green background: Bullish bias (price above EMA 55)
- Light red background: Bearish bias (price below EMA 55)
- Optional display for cleaner charts
**Zero Line**
- White horizontal line at 0%
- Reference point for positive/negative bias
- Crossovers indicate trend changes
**Crossover Labels**
- "突破" (Breakout): When bias crosses above zero
- "跌破" (Breakdown): When bias crosses below zero
- Can be enabled/disabled for clarity
#### 3. **Divergence Detection**
The indicator automatically detects regular divergences for all three bias lines:
**Bullish Divergence (Yellow Labels)**
- Price makes lower lows
- Bias makes higher lows
- Suggests potential upward reversal
- Labels: "55涨", "144涨", "233涨"
**Bearish Divergence (Blue Labels)**
- Price makes higher highs
- Bias makes lower highs
- Suggests potential downward reversal
- Labels: "55跌", "144跌", "233跌"
**Divergence Parameters** (Customizable for each EMA):
- Left Lookback: Bars to the left of pivot (default: 5)
- Right Lookback: Bars to the right of pivot (default: 1)
- Max Lookback Range: Maximum distance between pivots (default: 60)
- Min Lookback Range: Minimum distance between pivots (default: 5)
### Configuration Settings
#### Bias Settings
- **EMA Periods**: Customize lengths for EMA 55, 144, and 233
- **Price Source**: Choose calculation source (default: close)
- **Enable/Disable**: Toggle each bias line independently
#### Display Settings
- **Show Histogram**: Toggle histogram display
- **Show Background Color**: Toggle background coloring
- **Show Crossover Labels**: Toggle breakout/breakdown labels
#### Divergence Settings (Per EMA)
- Individual controls for EMA 55, 144, and 233 divergences
- Customizable lookback parameters for precision tuning
- Adjustable range settings for different market conditions
### How to Use
#### For Trend Trading
1. **Identify Trend Direction**
- Price above zero = Uptrend
- Price below zero = Downtrend
2. **Confirm with Multiple Timeframes**
- EMA 55: Short-term trend
- EMA 144: Medium-term trend
- EMA 233: Long-term trend
3. **Trade in Direction of Bias**
- All three lines positive = Strong uptrend
- All three lines negative = Strong downtrend
#### For Mean Reversion Trading
1. **Identify Extremes**
- High positive bias (>5-10%) = Overbought
- High negative bias (<-5 to -10%) = Oversold
2. **Wait for Confirmation**
- Look for bias to turn back toward zero
- Watch for crossover labels
3. **Enter on Reversal**
- Enter long when extreme negative bias starts rising
- Enter short when extreme positive bias starts falling
#### For Divergence Trading
1. **Spot Divergence Labels**
- Yellow labels = Bullish divergence (potential buy)
- Blue labels = Bearish divergence (potential sell)
2. **Confirm with Price Action**
- Wait for price to confirm with structure break
- Look for support/resistance reactions
3. **Use Multiple EMAs**
- EMA 55 divergence: Quick reversals
- EMA 144 divergence: Reliable signals
- EMA 233 divergence: Major trend changes
#### For Multi-Timeframe Analysis
1. **Check Long-term Bias** (EMA 233)
- Determines overall market direction
2. **Find Medium-term Entry** (EMA 144)
- Look for pullbacks in long-term trend
3. **Time Short-term Entry** (EMA 55)
- Enter when short-term aligns with longer timeframes
### Trading Strategies
#### Strategy 1: Triple Confirmation
- Wait for all three bias lines to be positive (or negative)
- Enter in direction of unanimous bias
- Exit when any line crosses zero
- Best for: Strong trending markets
#### Strategy 2: Divergence Trading
- Enable all divergence detection
- Take trades only when divergence appears
- Confirm with price structure
- Best for: Range-bound and reversal setups
#### Strategy 3: Zero Line Crossover
- Enable crossover labels
- Enter long on "突破" labels
- Enter short on "跌破" labels
- Use stop loss at recent swing points
- Best for: Trend following
#### Strategy 4: Extreme Reversion
- Wait for bias to reach extremes (>10% or <-10%)
- Enter counter-trend when bias reverses
- Exit at zero line
- Best for: Ranging markets
### Best Practices
1. **Combine with Price Action**
- Don't trade bias alone
- Confirm with support/resistance
- Look for candlestick patterns
2. **Use Multiple Timeframes**
- Check higher timeframe bias
- Trade in direction of larger trend
- Use lower timeframe for entry timing
3. **Manage Risk**
- Set stop losses beyond recent swings
- Don't fight extreme bias in strong trends
- Reduce position size at extremes
4. **Customize for Your Market**
- Volatile assets: Use wider ranges
- Stable assets: Use tighter ranges
- Adjust EMA periods for your timeframe
5. **Watch for False Signals**
- Multiple small divergences = Less reliable
- Divergences at extremes = More reliable
- Confirm with other indicators
### Indicator Combinations
**With Volume:**
- High bias + Low volume = Weak move
- High bias + High volume = Strong move
**With Moving Averages:**
- Check if price is above/below key EMAs
- Bias confirms EMA trend strength
**With RSI/MACD:**
- Multiple indicator divergence = Stronger signal
- Use bias for overbought/oversold confirmation
### Performance Tips
- Disable unused features for faster loading
- Use histogram for quick visual reference
- Enable background color for trend clarity
- Use divergence detection selectively
### Common Patterns
1. **Bias Expansion**: Bias increasing = Strong trend
2. **Bias Contraction**: Bias decreasing = Trend weakening
3. **Zero Line Bounce**: Price respects EMA as support/resistance
4. **Extreme Bias**: Over-extension, watch for reversal
5. **Divergence Cluster**: Multiple EMAs diverging = High probability reversal
### Alert Conditions
You can set alerts for:
- Bias crossing above/below zero
- Extreme bias levels
- Divergence detection
- All three bias lines aligned
---
## 中文说明文档
### 概述
Scout Regiment - Bias 是一个技术指标，用于测量当前价格与指数移动平均线（EMA）之间的偏离程度（乖离率）。它帮助交易者识别超买超卖状况、趋势强度，以及通过背离检测发现潜在的反转点。
### 什么是乖离率？
乖离率衡量价格偏离移动平均线的程度，以百分比表示：
- **正乖离**：价格高于EMA（可能超买）
- **负乖离**：价格低于EMA（可能超卖）
- **计算公式**：乖离率 = (价格 - EMA) / EMA × 100
### 核心功能
#### 1. **三重EMA乖离率线**
指标计算三条不同EMA的乖离率：
- **EMA 55 乖离率**（默认：绿色/红色，1像素线）
- 短期乖离测量
- 对价格变化反应快速
- 适合日内和波段交易
- **EMA 144 乖离率**（粉色，2像素线）
- 中期乖离测量
- 对价格波动反应平衡
- 最适合波段交易
- **EMA 233 乖离率**（白色，2像素线）
- 长期乖离测量
- 反应较慢，更稳定
- 适合仓位交易
**颜色编码：**
- 绿色：价格高于EMA（看涨）
- 红色：价格低于EMA（看跌）
#### 2. **视觉组件**
**柱状图显示**
- 以柱状图形式显示EMA 55乖离率，便于可视化
- 绿色柱：价格高于EMA 55
- 红色柱：价格低于EMA 55
- 可开关显示
**背景颜色**
- 浅绿色背景：看涨乖离（价格高于EMA 55）
- 浅红色背景：看跌乖离（价格低于EMA 55）
- 可选显示，图表更清爽
**零轴**
- 零点位置的白色横线
- 正负乖离的参考点
- 穿越表示趋势变化
**穿越标签**
- "突破"：乖离率向上穿越零轴
- "跌破"：乖离率向下穿越零轴
- 可启用/禁用以保持清晰
#### 3. **背离检测**
指标自动检测所有三条乖离率线的常规背离：
**看涨背离（黄色标签）**
- 价格创新低
- 乖离率创更高的低点
- 暗示潜在向上反转
- 标签："55涨"、"144涨"、"233涨"
**看跌背离（蓝色标签）**
- 价格创新高
- 乖离率创更低的高点
- 暗示潜在向下反转
- 标签："55跌"、"144跌"、"233跌"
**背离参数**（每个EMA可自定义）：
- 左侧回溯：枢轴点左侧K线数（默认：5）
- 右侧回溯：枢轴点右侧K线数（默认：1）
- 最大回溯范围：枢轴点之间最大距离（默认：60）
- 最小回溯范围：枢轴点之间最小距离（默认：5）
### 配置设置
#### Bias设置
- **EMA周期**：自定义EMA 55、144和233的长度
- **价格源**：选择计算源（默认：收盘价）
- **启用/禁用**：独立切换每条乖离率线
#### 显示设置
- **显示柱状图**：切换柱状图显示
- **显示背景颜色**：切换背景着色
- **显示突破标签**：切换突破/跌破标签
#### 背离设置（按EMA）
- EMA 55、144和233背离的独立控制
- 可自定义回溯参数用于精确调整
- 可调整范围设置以适应不同市场状况
### 使用方法
#### 趋势交易
1. **识别趋势方向**
- 价格高于零 = 上升趋势
- 价格低于零 = 下降趋势
2. **多时间框架确认**
- EMA 55：短期趋势
- EMA 144：中期趋势
- EMA 233：长期趋势
3. **顺乖离方向交易**
- 三条线全部为正 = 强劲上升趋势
- 三条线全部为负 = 强劲下降趋势
#### 均值回归交易
1. **识别极值**
- 高正乖离（>5-10%）= 超买
- 高负乖离（<-5至-10%）= 超卖
2. **等待确认**
- 等待乖离率回归零轴
- 观察穿越标签
3. **在反转时进场**
- 极端负乖离开始上升时做多
- 极端正乖离开始下降时做空
#### 背离交易
1. **发现背离标签**
- 黄色标签 = 看涨背离（潜在买入）
- 蓝色标签 = 看跌背离（潜在卖出）
2. **用价格行为确认**
- 等待价格通过结构突破确认
- 观察支撑/阻力反应
3. **使用多个EMA**
- EMA 55背离：快速反转
- EMA 144背离：可靠信号
- EMA 233背离：重大趋势变化
#### 多时间框架分析
1. **检查长期乖离**（EMA 233）
- 确定整体市场方向
2. **寻找中期入场**（EMA 144）
- 在长期趋势中寻找回调
3. **把握短期入场时机**（EMA 55）
- 短期与长期时间框架一致时进场
### 交易策略
#### 策略1：三重确认
- 等待三条乖离率线全部为正（或负）
- 顺一致乖离方向入场
- 任一线穿越零轴时离场
- 适合：强趋势市场
#### 策略2：背离交易
- 启用所有背离检测
- 仅在出现背离时交易
- 用价格结构确认
- 适合：震荡和反转设置
#### 策略3：零轴穿越
- 启用穿越标签
- 在"突破"标签时做多
- 在"跌破"标签时做空
- 在近期波动点设置止损
- 适合：趋势跟随
#### 策略4：极值回归
- 等待乖离率达到极值（>10%或<-10%）
- 乖离率反转时逆趋势入场
- 在零轴离场
- 适合：震荡市场
### 最佳实践
1. **结合价格行为**
- 不要单独使用乖离率交易
- 用支撑/阻力确认
- 寻找K线形态
2. **使用多时间框架**
- 检查更高时间框架的乖离
- 顺大趋势方向交易
- 用低时间框架把握入场时机
3. **风险管理**
- 在近期波动之外设置止损
- 不要在强趋势中对抗极端乖离
- 在极值处减少仓位
4. **针对您的市场定制**
- 波动大的资产：使用更宽的范围
- 稳定的资产：使用更紧的范围
- 根据时间框架调整EMA周期
5. **警惕假信号**
- 多个小背离 = 可靠性较低
- 极值处的背离 = 更可靠
- 用其他指标确认
### 指标组合
**与成交量配合：**
- 高乖离 + 低成交量 = 弱势波动
- 高乖离 + 高成交量 = 强势波动
**与移动平均线配合：**
- 检查价格是否在关键EMA上方/下方
- 乖离率确认EMA趋势强度
**与RSI/MACD配合：**
- 多指标背离 = 更强信号
- 使用乖离率确认超买超卖
### 性能提示
- 禁用未使用的功能以加快加载
- 使用柱状图快速视觉参考
- 启用背景颜色以清晰显示趋势
- 有选择地使用背离检测
### 常见形态
1. **乖离扩张**：乖离率增大 = 强趋势
2. **乖离收缩**：乖离率减小 = 趋势减弱
3. **零轴反弹**：价格将EMA作为支撑/阻力
4. **极端乖离**：过度延伸，注意反转
5. **背离集群**：多个EMA背离 = 高概率反转
### 警报条件
您可以为以下情况设置警报：
- 乖离率向上/向下穿越零轴
- 极端乖离水平
- 背离检测
- 三条乖离率线对齐
---
## Technical Support
For questions or issues, please refer to the TradingView community or contact the indicator creator.
## 技术支持
如有问题，请参考TradingView社区或联系指标创建者。
CNN Fear and Greed StrategyAdaptation of the CNN Fear and Greed Index Indicator (Original by EdgeTools)
The following changes have been implemented:
Put/Call Ratio Data Source: The data source for the Put/Call Ratio has been updated.
Bond Data Source: The data sources for the bond components (Safe Haven Demand and Junk Bond Demand) have been updated.
Normalization Adjustment: The normalization method has been adjusted to allow the CNN Fear and Greed Index to display over a longer historical period, optimizing it for backtesting purposes.
Style Modification: The display style has been modified for a simpler and cleaner appearance.
Strategy Logic Addition: Added a new strategy entry condition: index >= 25 AND index crosses over its 5-period Simple Moving Average (SMA), and a corresponding exit condition of holding the position for 252 bars (days).
CNN Fear & Greed Backtest Strategy (Adapted)
This script is an adaptation of the popular CNN Fear & Greed Index, originally created by EdgeTools, with significant modifications to optimize it for long-term backtesting on the TradingView platform.
The core function of the Fear & Greed Index is to measure the current emotional state of the stock market, ranging from 0 (Extreme Fear) to 100 (Extreme Greed). It operates on the principle that excessive fear drives prices too low (a potential buying opportunity), and excessive greed drives them too high (a potential selling opportunity).
Key Components of the Index (7 Factors)
The composite index is calculated as a weighted average of seven market indicators, each normalized to a score between 0 and 100:
Market Momentum: S&P 500's current level vs. its 125-day Moving Average.
Stock Price Strength: Stocks hitting 52-week highs vs. those hitting 52-week lows.
Stock Price Breadth: Measured by the McClellan Volume Summation Index (or similar volume/breadth metric).
Put/Call Ratio: The relationship between volume of put options (bearish bets) and call options (bullish bets).
Market Volatility: The CBOE VIX Index relative to its 50-day Moving Average.
Safe Haven Demand: The relative performance of stocks (S&P 500) vs. bonds.
Junk Bond Demand: The spread between high-yield (junk) bonds and U.S. Treasury yields.
Critical Adaptations for Backtesting
To improve the index's utility for quantitative analysis, the following changes were made:
Long-Term Normalization: The original normalization method (ta.stdev over a short LENGTH) has been replaced or adjusted to use longer historical data. This change ensures the index generates consistent and comparable sentiment scores across decades of market history, which is crucial for reliable backtesting results.
Updated Data Sources: Specific ticker requests for the Put/Call Ratio and Bond components (Safe Haven and Junk Bond Demand) have been updated to use the most reliable and long-running data available on TradingView, reducing data gaps and improving chart continuity.
Simplified Visuals: The chart display is streamlined, focusing only on the final Fear & Greed Index line and key threshold levels (25, 50, 75) for quick visual assessment.
Integrated Trading Strategy
This script also includes a simple, rules-based strategy designed to test the counter-trend philosophy of the index:
Entry Logic (Long Position): A long position is initiated when the market shows increasing fear, specifically when the index score is less than or equal to the configurable FEAR_LEVEL (default 25) and the index crosses above its own short-term 5-period Simple Moving Average (SMA). This crossover acts as a confirmation that sentiment may be starting to turn around from peak fear.
Exit Logic (Time-Based): All positions are subject to a time-based exit after holding for 252 trading days (approximately one year). This fixed holding period aims to capture the typical duration of a cyclical market recovery following a major panic event.
VIX Counter-Trend StrategyVIX Panic Index VOO Bottom-Fishing Strategy
📊 Strategy Overview
This strategy utilizes the VIX (Volatility Index) as a market sentiment indicator to help investors rationally enter positions during periods of extreme market panic, using objective technical signals to avoid emotional decision-making. It is designed to capture rebound opportunities in VOO (or other US equity ETFs) following panic-driven selloffs.
🎯 Entry and Exit Conditions
Entry Conditions (both must be met):
VIX reaches or exceeds the set threshold (default 25, adjustable)
VIX death crosses below its moving average (default 5-day MA), confirming panic sentiment is beginning to recede
Exit Conditions (three modes available):
Holding Period Mode: Exit after holding for the set number of days (default 100 days)
VIX Decline Mode: Exit when VIX falls below the set threshold (default 20)
Either Condition Mode: Exit when either condition is met
⚠️ Important Warnings
Not Suitable for Leveraged ETF Bottom-Fishing: VIX reflects market volatility. Using leveraged ETFs (such as TQQQ, SOXL) increases risk due to decay effects and greater volatility, potentially causing larger losses during panic periods.
Bear Market Inaccuracy Risk: This strategy assumes markets will rebound from panic. However, during prolonged bear markets or systemic risks (such as the 2008 financial crisis or 2022 rate hike cycle), VIX may remain elevated for extended periods, triggering multiple buy signals while prices continue declining, rendering the strategy ineffective.
Recommended to Combine with Market Trend Analysis: Works better in bull market conditions. In bear markets, consider raising VIX thresholds or suspending use.
For Reference Only, Not Investment Advice: Historical performance does not guarantee future results. Please use cautiously according to your personal risk tolerance.
VIX 恐慌指數 VOO 抄底策略
📊 策略目的
本策略利用 VIX 恐慌指數作為市場情緒指標，幫助投資人在市場極度恐慌時理性進場抄底，並透過客觀的技術訊號避免情緒化操作。適合用於捕捉 VOO（或其他美股 ETF）在恐慌性下跌後的反彈機會。
🎯 進出場條件
進場條件（同時滿足）：
VIX 指數達到設定門檻以上（預設 25，可調整）
VIX 死亡交叉其均線（預設 5 日均線），確認恐慌情緒開始回落
出場條件（三種模式可選）：
持有天數模式：持有達到設定天數後出場（預設 100 天）
VIX 回落模式：VIX 降至設定門檻以下時出場（預設 20）
兩者皆可模式：任一條件滿足即出場
⚠️ 重要警語
不適合槓桿型 ETF 抄底：VIX 反映的是市場波動度，使用槓桿 ETF（如 TQQQ、SOXL）會因為衰減效應和更大波動而增加風險，可能在恐慌期間造成更大虧損。
空頭市場失準風險：本策略假設市場會從恐慌中反彈，但在長期空頭或系統性風險（如 2008 金融危機、2022 升息循環）中，VIX 可能長期處於高檔，多次觸發買入訊號卻持續下跌，導致策略失效。
建議搭配大盤趨勢判斷：在多頭格局中使用效果較佳，空頭格局建議提高 VIX 門檻或暫停使用。
僅供參考，非投資建議：歷史績效不代表未來表現，請依個人風險承受度謹慎使用。
RSI VWAP EMA ON CHART1. Understand the components
VWAP (Volume Weighted Average Price)
Green: price is above VWAP → bullish trend
Red: price is below VWAP → bearish trend
Blue: price exactly at VWAP → neutral
Acts as a dynamic trend line and support/resistance.
4 Moving Averages (MA1–MA4)
Customizable lengths and type (SMA or EMA).
Useful for trend confirmation and dynamic support/resistance.
Typically:
MA1 = fastest (short-term)
MA4 = slowest (long-term)
When price is above multiple MAs → strong bullish trend; below → bearish trend.
RSI Overlay with VWAP Alignment
RSI line normalized to price scale.
Background shading indicates momentum aligned with VWAP trend:
Green shading: RSI > 50 and price above VWAP → bullish momentum
Red shading: RSI < 50 and price below VWAP → bearish momentum
Gray areas: neutral or momentum does not align with VWAP.
2. Basic usage workflow
Trend Confirmation
Look at VWAP color: price above → bullish, below → bearish.
Check RSI + VWAP shading: green confirms bullish momentum, red confirms bearish momentum.
Check MA alignment: shorter MAs above longer MAs = stronger bullish trend; vice versa for bearish.
Entry Signals (Scalping)
Long (Buy) Setup
Price above VWAP (green)
RSI green shading (RSI > 50)
Shorter MAs above longer MAs (trend support)
Short (Sell) Setup
Price below VWAP (red)
RSI red shading (RSI < 50)
Shorter MAs below longer MAs
Exits / Stops
Exit if price closes against VWAP trend (e.g., price drops below VWAP during a bullish trade).
Use nearest MA support/resistance as stop-loss or take-profit zones.
3. Optional adjustments for scalping
RSI length / thresholds
Shorter RSI (7–10) → faster response for scalping.
Standard RSI (14) → smoother, fewer false signals.
MA lengths
Short-term: 20–50
Medium-term: 50–100
Long-term: 100–200
Can tweak for the timeframe you trade (1m, 5m, 15m).
Timeframe
VWAP works best on intraday charts (1m, 5m, 15m).
Use higher timeframe (e.g., 15m or 1h) for trend direction and lower timeframe (1m–5m) for entries.
4. Example Scalping Setup
Bullish setup (buy):
Price above VWAP → VWAP green
RSI > 50 and green shading
Shorter MAs above longer MAs
Enter on small pullback or breakout
Stop: below nearest MA or VWAP
Bearish setup (sell):
Price below VWAP → VWAP red
RSI < 50 and red shading
Shorter MAs below longer MAs
Enter on minor bounce or breakdown
Stop: above nearest MA or VWAP
5. Visual cues summary
Element Interpretation
VWAP Green Price above VWAP → bullish trend
VWAP Red Price below VWAP → bearish trend
RSI Green Shading Bullish momentum aligns with VWAP
RSI Red Shading Bearish momentum aligns with VWAP
MA Alignment Trend strength (short above long = bullish, short below long = bearish)
VWAP + 4 MAs with RSI Overlay & VWAP Alignment1. Understand the components
VWAP (Volume Weighted Average Price)
Green: price is above VWAP → bullish trend
Red: price is below VWAP → bearish trend
Blue: price exactly at VWAP → neutral
Acts as a dynamic trend line and support/resistance.
4 Moving Averages (MA1–MA4)
Customizable lengths and type (SMA or EMA).
Useful for trend confirmation and dynamic support/resistance.
Typically:
MA1 = fastest (short-term)
MA4 = slowest (long-term)
When price is above multiple MAs → strong bullish trend; below → bearish trend.
RSI Overlay with VWAP Alignment
RSI line normalized to price scale.
Background shading indicates momentum aligned with VWAP trend:
Green shading: RSI > 50 and price above VWAP → bullish momentum
Red shading: RSI < 50 and price below VWAP → bearish momentum
Gray areas: neutral or momentum does not align with VWAP.
2. Basic usage workflow
Trend Confirmation
Look at VWAP color: price above → bullish, below → bearish.
Check RSI + VWAP shading: green confirms bullish momentum, red confirms bearish momentum.
Check MA alignment: shorter MAs above longer MAs = stronger bullish trend; vice versa for bearish.
Entry Signals (Scalping)
Long (Buy) Setup
Price above VWAP (green)
RSI green shading (RSI > 50)
Shorter MAs above longer MAs (trend support)
Short (Sell) Setup
Price below VWAP (red)
RSI red shading (RSI < 50)
Shorter MAs below longer MAs
Exits / Stops
Exit if price closes against VWAP trend (e.g., price drops below VWAP during a bullish trade).
Use nearest MA support/resistance as stop-loss or take-profit zones.
3. Optional adjustments for scalping
RSI length / thresholds
Shorter RSI (7–10) → faster response for scalping.
Standard RSI (14) → smoother, fewer false signals.
MA lengths
Short-term: 20–50
Medium-term: 50–100
Long-term: 100–200
Can tweak for the timeframe you trade (1m, 5m, 15m).
Timeframe
VWAP works best on intraday charts (1m, 5m, 15m).
Use higher timeframe (e.g., 15m or 1h) for trend direction and lower timeframe (1m–5m) for entries.
4. Example Scalping Setup
Bullish setup (buy):
Price above VWAP → VWAP green
RSI > 50 and green shading
Shorter MAs above longer MAs
Enter on small pullback or breakout
Stop: below nearest MA or VWAP
Bearish setup (sell):
Price below VWAP → VWAP red
RSI < 50 and red shading
Shorter MAs below longer MAs
Enter on minor bounce or breakdown
Stop: above nearest MA or VWAP
5. Visual cues summary
Element Interpretation
VWAP Green Price above VWAP → bullish trend
VWAP Red Price below VWAP → bearish trend
RSI Green Shading Bullish momentum aligns with VWAP
RSI Red Shading Bearish momentum aligns with VWAP
MA Alignment Trend strength (short above long = bullish, short below long = bearish)
HH/HL/LH/LL - Bigger Letter MArkingAlam's Money
//@version=6
indicator("HH/HL/LH/LL - Clean Letters Only", overlay = true, max_labels_count = 500)
// Pivot confirmation bars (fixed)
L = 2
R = 2
// Confirmed pivots (appear R bars after turn)
sh = ta.pivothigh(high, L, R)
sl = ta.pivotlow(low, L, R)
// Keep last confirmed swing values
var float lastHigh = na
var float lastLow = na
// Swing highs → HH / LH
if not na(sh)
if na(lastHigh)
lastHigh := sh
else
string txtH = sh > lastHigh ? "HH" : "LH"
label.new(bar_index - R, sh, txtH, xloc.bar_index, yloc.price, color.new(color.white, 100), label.style_label_down, color.red, size.large)
lastHigh := sh
// Swing lows → HL / LL
if not na(sl)
if na(lastLow)
lastLow := sl
else
string txtL = sl > lastLow ? "HL" : "LL"
label.new(bar_index - R, sl, txtL, xloc.bar_index, yloc.price, color.new(color.white, 100), label.style_label_up, color.green, size.large)
lastLow := sl
Smart Margin Zone
SMART MARGIN ZONE - CME-BASED SUPPORT & RESISTANCE INDICATOR
TITLE FOR PUBLICATION:
Smart Margin Zone - CME Margin-Based Support and Resistance
CATEGORY:
Support and Resistance
SHORT DESCRIPTION (for preview):
Automatically plots margin zones based on CME Group requirements. These zones represent critical price levels where leveraged traders face margin calls, creating natural support and resistance through forced liquidations.
═══════════════════════════════════════════════════════════════
FULL DESCRIPTION FOR TRADINGVIEW:
═══════════════════════════════════════════════════════════════
📊 Smart Margin Zone - Professional Trading Zones Based on CME Data
This indicator automatically calculates and displays margin zones derived from official CME Group margin requirements. These zones represent critical price levels where traders using leverage receive margin calls, triggering forced position closures that create natural support and resistance levels.
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🎯 CORE CONCEPT
═══════════════════════════════════════════════════════════════
When price reaches calculated margin zones, traders using 2:1 or 4:1 leverage on CME futures receive margin calls. Brokers automatically liquidate these positions, creating waves of buying or selling pressure that form strong support and resistance levels.
This is not theoretical - it's based on actual margin requirements from CME Group, the world's largest derivatives marketplace.
═══════════════════════════════════════════════════════════════
📐 CALCULATION METHODOLOGY
═══════════════════════════════════════════════════════════════
The indicator uses the following formula to calculate zone sizes:
Zone Size = (Margin Requirement / Tick Value) × Tick Size × 1.10
Where:
• Margin Requirement = Official CME initial margin (updated November 2024)
• Tick Value = Dollar value of minimum price movement
• Tick Size = Minimum price increment
• 1.10 = 10% buffer for realistic zone width
SUPPORTED INSTRUMENTS WITH CME DATA:
Currency Pairs:
• EURUSD: $2,100 margin → 0.0168 zone size
• GBPUSD: $1,800 margin → 0.0144 zone size
• AUDUSD: $1,300 margin → 0.0065 zone size
• NZDUSD: $1,100 margin → 0.0055 zone size
• USDJPY: $3,200 margin → custom calculation
• USDCAD: $950 margin → calculated
• USDCHF: $1,650 margin → calculated
Commodities:
• Gold (XAUUSD): $8,000 margin → 80 points zone size
• Silver (XAGUSD): $6,500 margin → calculated
• WTI Crude Oil: $4,500 margin → calculated
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🔍 HOW IT WORKS
═══════════════════════════════════════════════════════════════
1. SWING POINT DETECTION
The indicator automatically identifies swing highs and swing lows using a configurable lookback period (default 10 bars). These become anchor points for zone calculations.
2. FIVE ZONE LEVELS
From each swing point, five zone levels are calculated:
• Zone 1/4 (25%) - First correction level
• Zone 1/2 (50%) - KEY ZONE for trend determination
• Zone 3/4 (75%) - Intermediate level
• Zone 1/1 (100%) - Full margin zone (strongest level)
• Zone 5/4 (125%) - Extended zone
3. TREND IDENTIFICATION
• Close above Zone 1/2 resistance = Bullish trend
• Close below Zone 1/2 support = Bearish trend
• Between zones = Range/consolidation
4. HISTORICAL CONTEXT
Current zones are displayed prominently with fills and labels. Historical zones appear as thin, semi-transparent lines for context without cluttering the chart.
═══════════════════════════════════════════════════════════════
⚙️ FEATURES
═══════════════════════════════════════════════════════════════
AUTOMATED CALCULATION:
✅ Auto-detection of swing highs and lows
✅ Real-time zone updates as new swings form
✅ CME margin data built-in for major instruments
✅ Manual override option for custom calculations
VISUAL CLARITY:
✅ Color-coded zones (red=resistance, green=support)
✅ Adjustable transparency for fills and lines
✅ Current zones bold with fills and price labels
✅ Historical zones thin and transparent
✅ Swing point markers show calculation origins
CUSTOMIZATION:
✅ Show/hide individual zone levels (1/4, 1/2, 3/4, 1/1, 5/4)
✅ Toggle historical zones on/off
✅ Adjustable lookback period (5-50 bars)
✅ Customizable colors for all elements
✅ Line width and transparency controls
✅ Zone extension options (none/right/both)
TREND ANALYSIS:
✅ Optional trend background coloring
✅ Customizable trend colors and transparency
✅ Real-time trend identification display
STATISTICS:
✅ Live statistics table showing:
- Current instrument
- Active zone size
- Calculation mode
- Current trend direction
- Number of zones displayed
ALERTS:
✅ Zone 1/2 breakout (up/down)
✅ Full margin zone 1/1 reached
✅ Customizable alert messages
═══════════════════════════════════════════════════════════════
📈 TRADING APPLICATIONS
═══════════════════════════════════════════════════════════════
ENTRY SIGNALS:
• Bounces from zone levels = potential entry points
• Zone 1/2 breakouts = trend continuation entries
• Zone rejections = reversal opportunities
RISK MANAGEMENT:
• Zone levels = logical stop-loss placement
• Zone 1/1 = maximum risk level
• Zone spacing = position sizing guide
PROFIT TARGETS:
• Next zone level = first target
• Zone 1/1 = full profit target
• Zone breakouts = extended targets
TREND CONFIRMATION:
• Price above Zone 1/2 resistance = confirmed uptrend
• Price below Zone 1/2 support = confirmed downtrend
• Consolidation between zones = wait for breakout
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📚 USAGE INSTRUCTIONS
═══════════════════════════════════════════════════════════════
GETTING STARTED:
1. Add indicator to chart of any supported instrument
2. Zones automatically calculate and display
3. Adjust swing detection period if needed (default 10 works well)
4. Customize colors and visibility to your preference
OPTIMAL SETTINGS:
• Best timeframes: H1, H4, Daily, Weekly
• Default swing length (10) suitable for most markets
• Show 2-3 historical zones for context
• Enable swing point markers to see calculation origins
INTERPRETATION:
• Watch for price reactions at zone boundaries
• Strong bounces = respect for margin level
• Clean breaks = momentum continuation
• Multiple touches = zone strength confirmation
SET ALERTS:
• Zone 1/2 breakouts for trend entries
• Zone 1/1 reaches for profit-taking
• Custom alerts for your specific strategy
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⚠️ IMPORTANT NOTES
═══════════════════════════════════════════════════════════════
DATA ACCURACY:
• CME margin requirements updated November 2024
• Margins change periodically - check CME Group website
• Manual mode available for latest margin data
• Indicator provides analysis tool, not financial advice
STATISTICAL PERFORMANCE:
• Historical data shows >60% probability of continued movement after Zone 1/2 breakout
• Zone effectiveness varies by market conditions
• Best results in trending markets with clear swings
LIMITATIONS:
• Margin requirements change - monitor CME updates
• Works best on liquid instruments with clear swings
• Not a standalone trading system
• Should be combined with additional analysis
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🔧 METHODOLOGY CREDIT
═══════════════════════════════════════════════════════════════
This indicator is based on the margin zones concept developed by Alexander Bazylev (BTrade indicator for MetaTrader platforms).
The TradingView implementation has been completely rewritten with original enhancements:
• Multiple zone levels instead of single level
• Automatic swing point detection algorithm
• Direct CME data integration
• Historical zone visualization
• Advanced customization options
• Comprehensive statistics and alerts
All code is original and specifically designed for TradingView's Pine Script v5 environment.
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💡 BEST PRACTICES
═══════════════════════════════════════════════════════════════
COMBINE WITH:
• Volume analysis for confirmation
• Trend indicators for direction bias
• Price action patterns at zones
• Higher timeframe analysis
AVOID:
• Trading against strong trends at minor zones
• Over-leveraging based solely on zone placement
• Ignoring broader market context
• Expecting perfect bounces every time
OPTIMIZE:
• Adjust swing length for different timeframes
• Shorter period (5-7) for intraday trading
• Longer period (15-20) for swing trading
• Test historical effectiveness on your instruments
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📖 EDUCATIONAL VALUE
═══════════════════════════════════════════════════════════════
This indicator helps traders understand:
• How institutional margin requirements affect price
• Where forced liquidations create pressure
• Natural support and resistance formation
• Relationship between leverage and price levels
• Market structure and key technical levels
═══════════════════════════════════════════════════════════════
🔄 VERSION HISTORY
═══════════════════════════════════════════════════════════════
Version 1.0 (Initial Release):
• CME-based zone calculation for 10 instruments
• Automatic swing high/low detection
• 5 zone levels with customizable display
• Historical zones with transparency control
• Swing point markers
• Trend background indicator
• Live statistics table
• Multiple alert conditions
• Fully customizable colors and styles
• English language interface
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📞 SUPPORT & FEEDBACK
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⚖️ DISCLAIMER
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This indicator is provided for educational and analytical purposes only. It is not financial advice and should not be the sole basis for trading decisions.
• Past performance does not guarantee future results
• Trading involves substantial risk of loss
• CME margin requirements subject to change
• Always do your own research and risk management
• Consult a financial advisor for investment advice
The creator is not responsible for any trading losses incurred through use of this indicator.
Dresteghamat-Multi timeframe Regime & Exhaustion**Dresteghamat-Multi timeframe Regime & Exhaustion**
This script is a custom decision-support dashboard that aggregates volatility, momentum, and structural data across multiple timeframes to filter market noise. It addresses the problem of "Analysis Paralysis" by automating the correlation between lower timeframe momentum and higher timeframe structure using a weighted scoring algorithm.
### 🔧 Methodology & Calculation Logic
The core engine does not simply overlay indicators; it normalizes their outputs into a unified score (-100 to +100). The logic is hidden (Protected) to preserve the proprietary weighting algorithm, but the underlying concepts are as follows:
**1. Adaptive Timeframe Selection (Context Engine)**
Instead of static monitoring, the script detects the user's current chart timeframe (`timeframe.multiplier`) and dynamically assigns two relevant Higher Timeframes (HTF) as anchors.
* *Logic:* If Current TF < 5min, the script analyzes 15m and 1H data. If Current TF < 1H, it shifts to 4H and Daily data. This ensures the analysis is contextually relevant.
**2. Regime & Volatility Filter (ATR Based)**
We use the Average True Range (ATR) to determine the market regime (Trend vs. Range).
* **Calculation:** We compare the current Swing Range (High-Low lookback) against a smoothed ATR. A high Ratio (> 2.0) indicates a Trend Regime, activating Trend-Following logic. A low ratio dampens the signals.
**3. Directional Bias (Structure + Flow)**
Direction is not determined by a single crossover. It is a fusion of:
* **Swing Structure:** Using `ta.pivothigh/low` to identify Higher Highs/Lower Lows.
* **Volume Flow:** Calculating the cumulative delta of candle bodies over a lookback period.
* **Micro-Bias:** A short-term (default 5-bar) momentum filter to detect immediate order flow changes.
**4. Exhaustion Logic (Mean Reversion Warning)**
To prevent buying at tops, the script calculates an "Exhaustion Score" based on:
* **RSI Divergence:** Detecting discrepancies between price peaks and momentum.
* **Volatility Extension:** Identifying when price has deviated significantly from its volatility mean (VRSD logic).
* **Volume Anomalies:** Detecting low volume on new highs (Supply absorption).
### 📊 How to Read the Dashboard
The table displays the raw status of each timeframe. The **"MODE"** row is the output of the algorithmic decision tree:
* **BUY/SELL ONLY:** Generated when the Current TF momentum aligns with the dynamically selected HTF structure AND the Exhaustion Score is below the threshold (default 70).
* **PULLBACK:** Triggered when the HTF Structure is bullish, but Current Momentum is bearish (indicating a corrective phase).
* **HTF EXHAUST:** A safety warning triggered when the HTF Volatility or RSI metrics hit extreme levels, overriding any entry signals.
* **WAIT:** Default state when volatility is low (Range Regime) or signals conflict.
### ⚠️ Disclaimer
This tool provides algorithmic analysis based on historical price action and volatility metrics. It does not guarantee future results.
