Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD)
Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis
The Revolutionary Concept: When Physics Meets Trading
After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits.
The Core Innovation: Ergodic Theory Applied to Markets
What Makes Markets Ergodic or Non-Ergodic?
In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading:
Ergodic Markets (Mean-Reverting)
- Time averages equal ensemble averages
- Historical patterns repeat reliably
- Price oscillates around equilibrium
- Traditional indicators work well
Non-Ergodic Markets (Trending)
- Path dependency dominates
- History doesn't predict future
- Price creates new equilibrium levels
- Momentum strategies excel
The Mathematical Framework
The Ergodic Score combines three critical divergences:
Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3
Where:
Price Divergence: How far current price deviates from market consensus
Return Divergence: Momentum differential between instrument and market
Volatility Divergence: Volatility regime misalignment
Market Stress: Adaptive multiplier based on current conditions
The Ensemble Analysis Revolution
Beyond Single-Instrument Analysis
Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach:
Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves
Filters False Signals: Requires broader market confirmation
Identifies Regime Shifts: Detects when entire market structure changes
Provides Context: Shows if moves are isolated or systemic
Dynamic Threshold Adaptation
Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions:
Base Threshold = SMA(Ergodic Score, Lookback × 3)
Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity
Final Threshold = Smoothed(Base + Adaptive)
This creates context-aware signals that remain effective across different market environments.
The Confidence Engine: Know Your Signal Quality
Multi-Factor Confidence Scoring
Every signal receives a confidence score based on:
Signal Clarity (0-35%): How decisively the ergodic threshold is crossed
Momentum Strength (0-25%): Rate of ergodic change
Volatility Alignment (0-20%): Whether volatility supports the signal
Market Quality (0-20%): Price convergence and path dependency factors
Real-Time Confidence Updates
The Live Confidence metric continuously updates, showing:
- Current opportunity quality
- Market state clarity
- Historical performance influence
- Signal recency boost
- Visual Intelligence System
Adaptive Ergodic Field Bands
Dynamic bands that expand and contract based on market state:
Primary Color: Ergodic state (mean-reverting)
Danger Color: Non-ergodic state (trending)
Band Width: Expected price movement range
Squeeze Indicators: Volatility compression warnings
Quantum Wave Ribbons
Triple EMA system (8, 21, 55) revealing market flow:
Compressed Ribbons: Consolidation imminent
Expanding Ribbons: Directional move developing
Color Coding: Matches current ergodic state
Phase Transition Signals
Clear entry/exit markers at regime changes:
Bull Signals: Ergodic restoration (mean reversion opportunity)
Bear Signals: Ergodic break (trend following opportunity)
Confidence Labels: Percentage showing signal quality
Visual Intensity: Stronger signals = deeper colors
Professional Dashboard Suite
Main Analytics Panel (Top Right)
Market State Monitor
- Current regime (Ergodic/Non-Ergodic)
- Ergodic score with threshold
- Path dependency strength
- Quantum coherence percentage
Divergence Metrics
- Price divergence with severity
- Volatility regime classification
- Strategy mode recommendation
- Signal strength indicator
Live Intelligence
- Real-time confidence score
- Color-coded risk levels
- Dynamic strategy suggestions
Performance Tracking (Left Panel)
Signal Analytics
- Total historical signals
- Win rate with W/L breakdown
- Current streak tracking
- Closed trade counter
Regime Analysis
- Current market behavior
- Bars since last signal
- Recommended actions
- Average confidence trends
Strategy Command Center (Bottom Right)
Adaptive Recommendations
- Active strategy mode
- Primary approach (mean reversion/momentum)
- Suggested indicators ("weapons")
- Entry/exit methodology
- Risk management guidance
- Comprehensive Input Guide
Core Algorithm Parameters
Analysis Period (10-100 bars)
Scalping (10-15): Ultra-responsive, more signals, higher noise
Day Trading (20-30): Balanced sensitivity and stability
Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes
Divergence Threshold (0.5-5.0)
Hair Trigger (0.5-1.0): Catches every wiggle, many false signals
Balanced (1.5-2.5): Good signal-to-noise ratio
Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance
Path Memory (20-200 bars)
Short Memory (20-50): Recent behavior focus, quick adaptation
Medium Memory (50-100): Balanced historical context
Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag
Signal Spacing (5-50 bars)
Aggressive (5-10): Allows rapid-fire signals
Normal (15-25): Prevents clustering, maintains flow
Conservative (30-50): Major setups only Default: 15 - optimal trade frequency
Ensemble Configuration
Select markets for consensus analysis:
SPY: Broad market sentiment
QQQ: Technology leadership
IWM: Small-cap risk appetite
DIA: Blue-chip stability
More instruments = stronger consensus but potentially diluted signals
Visual Customization
Color Themes (6 professional options):
Quantum: Cyan/Pink - Modern trading aesthetic
Matrix: Green/Red - Classic terminal look
Heat: Blue/Red - Temperature metaphor
Neon: Cyan/Magenta - High contrast
Ocean: Turquoise/Coral - Calming palette
Sunset: Red-orange/Teal - Warm gradients
Display Controls:
- Toggle each visual component
- Adjust transparency levels
- Scale dashboard text
- Show/hide confidence scores
- Trading Strategies by Market State
- Ergodic State Strategy (Primary Color Bands)
Market Characteristics
- Price oscillates predictably
- Support/resistance hold
- Volume patterns repeat
- Mean reversion dominates
Optimal Approach
Entry: Fade moves at band extremes
Target: Middle band (equilibrium)
Stop: Just beyond outer bands
Size: Full confidence-based position
Recommended Tools
- RSI for oversold/overbought
- Bollinger Bands for extremes
- Volume profile for levels
- Non-Ergodic State Strategy (Danger Color Bands)
Market Characteristics
- Price trends persistently
- Levels break decisively
- Volume confirms direction
- Momentum accelerates
Optimal Approach
Entry: Breakout from bands
Target: Trail with expanding bands
Stop: Inside opposite band
Size: Scale in with trend
Recommended Tools
- Moving average alignment
- ADX for trend strength
- MACD for momentum
- Advanced Features Explained
Quantum Coherence Metric
Measures phase alignment between individual and ensemble behavior:
80-100%: Perfect sync - strong mean reversion setup
50-80%: Moderate alignment - mixed signals
0-50%: Decoherence - trending behavior likely
Path Dependency Analysis
Quantifies how much history influences current price:
Low (<30%): Technical patterns reliable
Medium (30-50%): Mixed influences
High (>50%): Fundamental shift occurring
Volatility Regime Classification
Contextualizes current volatility:
Normal: Standard strategies apply
Elevated: Widen stops, reduce size
Extreme: Defensive mode required
Signal Strength Indicator
Real-time opportunity quality:
- Distance from threshold
- Momentum acceleration
- Cross-validation factors
Risk Management Framework
Position Sizing by Confidence
90%+ confidence = 100% position size
70-90% confidence = 75% position size
50-70% confidence = 50% position size
<50% confidence = 25% or skip
Dynamic Stop Placement
Ergodic State: ATR × 1.0 from entry
Non-Ergodic State: ATR × 2.0 from entry
Volatility Adjustment: Multiply by current regime
Multi-Timeframe Alignment
- Check higher timeframe regime
- Confirm ensemble consensus
- Verify volume participation
- Align with major levels
What Makes EMD Unique
Original Contributions
First Ergodic Theory Trading Application: Transforms abstract physics into practical signals
Ensemble Market Analysis: Revolutionary multi-market divergence system
Adaptive Confidence Engine: Institutional-grade signal quality metrics
Quantum Coherence: Novel market alignment measurement
Smart Signal Management: Prevents clustering while maintaining responsiveness
Technical Innovations
Dynamic Threshold Adaptation: Self-adjusting sensitivity
Path Memory Integration: Historical dependency weighting
Stress-Adjusted Scoring: Market condition normalization
Real-Time Performance Tracking: Built-in strategy analytics
Optimization Guidelines
By Timeframe
Scalping (1-5 min)
Period: 10-15
Threshold: 0.5-1.0
Memory: 20-30
Spacing: 5-10
Day Trading (5-60 min)
Period: 20-30
Threshold: 1.5-2.5
Memory: 40-60
Spacing: 15-20
Swing Trading (1H-1D)
Period: 40-60
Threshold: 2.0-3.0
Memory: 80-120
Spacing: 25-35
Position Trading (1D-1W)
Period: 60-100
Threshold: 3.0-5.0
Memory: 100-200
Spacing: 40-50
By Market Condition
Trending Markets
- Increase threshold
- Extend memory
- Focus on breaks
Ranging Markets
- Decrease threshold
- Shorten memory
- Focus on restores
Volatile Markets
- Increase spacing
- Raise confidence requirement
- Reduce position size
- Integration with Other Analysis
- Complementary Indicators
For Ergodic States
- RSI divergences
- Bollinger Band squeezes
- Volume profile nodes
- Support/resistance levels
For Non-Ergodic States
- Moving average ribbons
- Trend strength indicators
- Momentum oscillators
- Breakout patterns
- Fundamental Alignment
- Check economic calendar
- Monitor sector rotation
- Consider market themes
- Evaluate risk sentiment
Troubleshooting Guide
Too Many Signals:
- Increase threshold
- Extend signal spacing
- Raise confidence minimum
Missing Opportunities
- Decrease threshold
- Reduce signal spacing
- Check ensemble settings
Poor Win Rate
- Verify timeframe alignment
- Confirm volume participation
- Review risk management
Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results.
The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose.
This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques.
Transform market chaos into trading clarity with Ergodic Market Divergence.
Created with passion for the TradingView community
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
חפש סקריפטים עבור "a股板块+沪深两市+股价不超过10元的股票+技术形态好"
Lyapunov Market Instability (LMI)Lyapunov Market Instability (LMI)
What is Lyapunov Market Instability?
Lyapunov Market Instability (LMI) is a revolutionary indicator that brings chaos theory from theoretical physics into practical trading. By calculating Lyapunov exponents—a measure of how rapidly nearby trajectories diverge in phase space—LMI quantifies market sensitivity to initial conditions. This isn't another oscillator or trend indicator; it's a mathematical lens that reveals whether markets are in chaotic (trending) or stable (ranging) regimes.
Inspired by the meditative color field paintings of Mark Rothko, this indicator transforms complex chaos mathematics into an intuitive visual experience. The elegant simplicity of the visualization belies the sophisticated theory underneath—just as Rothko's seemingly simple color blocks contain profound depth.
Theoretical Foundation (Chaos Theory & Lyapunov Exponents)
In dynamical systems, the Lyapunov exponent (λ) measures the rate of separation of infinitesimally close trajectories:
λ > 0: System is chaotic—small changes lead to dramatically different outcomes (butterfly effect)
λ < 0: System is stable—trajectories converge, perturbations die out
λ ≈ 0: Edge of chaos—transition between regimes
Phase Space Reconstruction
Using Takens' embedding theorem , we reconstruct market dynamics in higher dimensions:
Time-delay embedding: Create vectors from price at different lags
Nearest neighbor search: Find historically similar market states
Trajectory evolution: Track how these similar states diverged over time
Divergence rate: Calculate average exponential separation
Market Application
Chaotic markets (λ > threshold): Strong trends emerge, momentum dominates, use breakout strategies
Stable markets (λ < threshold): Mean reversion dominates, fade extremes, range-bound strategies work
Transition zones: Market regime about to change, reduce position size, wait for confirmation
How LMI Works
1. Phase Space Construction
Each point in time is embedded as a vector using historical prices at specific delays (τ). This reveals the market's hidden attractor structure.
2. Lyapunov Calculation
For each current state, we:
- Find similar historical states within epsilon (ε) distance
- Track how these initially similar states evolved
- Measure exponential divergence rate
- Average across multiple trajectories for robustness
3. Signal Generation
Chaos signals: When λ crosses above threshold, market enters trending regime
Stability signals: When λ crosses below threshold, market enters ranging regime
Divergence detection: Price/Lyapunov divergences signal potential reversals
4. Rothko Visualization
Color fields: Background zones represent market states with Rothko-inspired palettes
Glowing line: Lyapunov exponent with intensity reflecting market state
Minimalist design: Focus on essential information without clutter
Inputs:
📐 Lyapunov Parameters
Embedding Dimension (default: 3)
Dimensions for phase space reconstruction
2-3: Simple dynamics (crypto/forex) - captures basic momentum patterns
4-5: Complex dynamics (stocks/indices) - captures intricate market structures
Higher dimensions need exponentially more data but reveal deeper patterns
Time Delay τ (default: 1)
Lag between phase space coordinates
1: High-frequency (1m-15m charts) - captures rapid market shifts
2-3: Medium frequency (1H-4H) - balances noise and signal
4-5: Low frequency (Daily+) - focuses on major regime changes
Match to your timeframe's natural cycle
Initial Separation ε (default: 0.001)
Neighborhood size for finding similar states
0.0001-0.0005: Highly liquid markets (major forex pairs)
0.0005-0.002: Normal markets (large-cap stocks)
0.002-0.01: Volatile markets (crypto, small-caps)
Smaller = more sensitive to chaos onset
Evolution Steps (default: 10)
How far to track trajectory divergence
5-10: Fast signals for scalping - quick regime detection
10-20: Balanced for day trading - reliable signals
20-30: Slow signals for swing trading - major regime shifts only
Nearest Neighbors (default: 5)
Phase space points for averaging
3-4: Noisy/fast markets - adapts quickly
5-6: Balanced (recommended) - smooth yet responsive
7-10: Smooth/slow markets - very stable signals
📊 Signal Parameters
Chaos Threshold (default: 0.05)
Lyapunov value above which market is chaotic
0.01-0.03: Sensitive - more chaos signals, earlier detection
0.05: Balanced - optimal for most markets
0.1-0.2: Conservative - only strong trends trigger
Stability Threshold (default: -0.05)
Lyapunov value below which market is stable
-0.01 to -0.03: Sensitive - quick stability detection
-0.05: Balanced - reliable ranging signals
-0.1 to -0.2: Conservative - only deep stability
Signal Smoothing (default: 3)
EMA period for noise reduction
1-2: Raw signals for experienced traders
3-5: Balanced - recommended for most
6-10: Very smooth for position traders
🎨 Rothko Visualization
Rothko Classic: Deep reds for chaos, midnight blues for stability
Orange/Red: Warm sunset tones throughout
Blue/Black: Cool, meditative ocean depths
Purple/Grey: Subtle, sophisticated palette
Visual Options:
Market Zones : Background fields showing regime areas
Transitions: Arrows marking regime changes
Divergences: Labels for price/Lyapunov divergences
Dashboard: Real-time state and trading signals
Guide: Educational panel explaining the theory
Visual Logic & Interpretation
Main Elements
Lyapunov Line: The heart of the indicator
Above chaos threshold: Market is trending, follow momentum
Below stability threshold: Market is ranging, fade extremes
Between thresholds: Transition zone, reduce risk
Background Zones: Rothko-inspired color fields
Red zone: Chaotic regime (trending)
Gray zone: Transition (uncertain)
Blue zone: Stable regime (ranging)
Transition Markers:
Up triangle: Entering chaos - start trend following
Down triangle: Entering stability - start mean reversion
Divergence Signals:
Bullish: Price makes low but Lyapunov rising (stability breaking down)
Bearish: Price makes high but Lyapunov falling (chaos dissipating)
Dashboard Information
Market State: Current regime (Chaotic/Stable/Transitioning)
Trading Bias: Specific strategy recommendation
Lyapunov λ: Raw value for precision
Signal Strength: Confidence in current regime
Last Change: Bars since last regime shift
Action: Clear trading directive
Trading Strategies
In Chaotic Regime (λ > threshold)
Follow trends aggressively: Breakouts have high success rate
Use momentum strategies: Moving average crossovers work well
Wider stops: Expect larger swings
Pyramid into winners: Trends tend to persist
In Stable Regime (λ < threshold)
Fade extremes: Mean reversion dominates
Use oscillators: RSI, Stochastic work well
Tighter stops: Smaller expected moves
Scale out at targets: Trends don't persist
In Transition Zone
Reduce position size: Uncertainty is high
Wait for confirmation: Let regime establish
Use options: Volatility strategies may work
Monitor closely: Quick changes possible
Advanced Techniques
- Multi-Timeframe Analysis
- Higher timeframe LMI for regime context
- Lower timeframe for entry timing
- Alignment = highest probability trades
- Divergence Trading
- Most powerful at regime boundaries
- Combine with support/resistance
- Use for early reversal detection
- Volatility Correlation
- Chaos often precedes volatility expansion
- Stability often precedes volatility contraction
- Use for options strategies
Originality & Innovation
LMI represents a genuine breakthrough in applying chaos theory to markets:
True Lyapunov Calculation: Not a simplified proxy but actual phase space reconstruction and divergence measurement
Rothko Aesthetic: Transforms complex math into meditative visual experience
Regime Detection: Identifies market state changes before price makes them obvious
Practical Application: Clear, actionable signals from theoretical physics
This is not a combination of existing indicators or a visual makeover of standard tools. It's a fundamental rethinking of how we measure and visualize market dynamics.
Best Practices
Start with defaults: Parameters are optimized for broad market conditions
Match to your timeframe: Adjust tau and evolution steps
Confirm with price action: LMI shows regime, not direction
Use appropriate strategies: Chaos = trend, Stability = reversion
Respect transitions: Reduce risk during regime changes
Alerts Available
Chaos Entry: Market entering chaotic regime - prepare for trends
Stability Entry: Market entering stable regime - prepare for ranges
Bullish Divergence: Potential bottom forming
Bearish Divergence: Potential top forming
Chart Information
Script Name: Lyapunov Market Instability (LMI) Recommended Use: All markets, all timeframes Best Performance: Liquid markets with clear regimes
Academic References
Takens, F. (1981). "Detecting strange attractors in turbulence"
Wolf, A. et al. (1985). "Determining Lyapunov exponents from a time series"
Rosenstein, M. et al. (1993). "A practical method for calculating largest Lyapunov exponents"
Note: After completing this indicator, I discovered @loxx's 2022 "Lyapunov Hodrick-Prescott Oscillator w/ DSL". While both explore Lyapunov exponents, they represent independent implementations with different methodologies and applications. This indicator uses phase space reconstruction for regime detection, while his combines Lyapunov concepts with HP filtering.
Disclaimer
This indicator is for research and educational purposes only. It does not constitute financial advice or provide direct buy/sell signals. Chaos theory reveals market character, not future prices. Always use proper risk management and combine with your own analysis. Past performance does not guarantee future results.
See markets through the lens of chaos. Trade the regime, not the noise.
Bringing theoretical physics to practical trading through the meditative aesthetics of Mark Rothko
Trade with insight. Trade with anticipation.
— Dskyz , for DAFE Trading Systems
ETI IndicatorThe Ensemble Technical Indicator (ETI) is a script that combines multiple established indicators into one single powerful indicator. Specifically, it takes a number of technical indicators and then converts them into +1 to represent a bullish trend, or a -1 to represent a bearish trend. It then adds these values together and takes the running sum over the past 20 days.
The ETI is composed of the following indicators and converted to +1 or -1 using the following criteria:
Simple Moving Average (10 days) : When the price is above the 10-day simple moving averaging, +1, when below -1
Weighted Moving Average (10 days) : Similar to the SMA 10, when the the price is above the 10-day weighted moving average, +1, when below -1
Stochastic K% : If the current Stochastic K% is greater than the previous value, then +1, else -1.
Stochastic D% : Similar to the Stochastic K%, when the current Stochastic D% is greater than the previous value, +1, else -1.
MACD Difference : First subtract the MACD signal (i.e. the moving average) from the MACD value and if the current value is higher than the previous value, then +1, else -1.
William's R% : If the current William's R% is greater than the previous one, then +1, else -1.
William's Accumulation/Distribution : If the current William's AD value is greater than the previous value, then +1, else -1.
Commodity Channel Index : If the Commodity Channel Index is greater than 200 (overbought), then -1, if it is less than -200 (oversold) then +1. When it is between those values, if the current value is greater than the previous value then +1, else -1.
Relative Strength Index : If the Relative Strength Index is over 70 (overbought) then -1 and if under 30 (oversold) then +1. If the Relative Strength Indicator is between those values then if the current value is higher than the previous value +1, else -1.
Momentum (9 days) : If the momentum value is greater than 0, then +1, else -1.
Again, once these values have been calculated and converted, they are added up to produce a single value. This single value is then summed across the previous 20 candles to produce a running sum.
By coalescing multiple technical indicators into a single value across time, traders can better understand how multiple inter-related indicators are behaving at once; high scores indicate that numerous indicators are showing bullish signals indicating a potential or ongoing uptrend (and vice-versa with low scores).
Additional Features
Numerous smoothing transformations have also been added (e.g. gaussian smoothing) to remove some of the noise might exist.
Suggested Use
It is recommended that stocks are shorted when the cross below 0, and are bought when the ETI crosses above -40. Arrows can be shown on the indicator to show these points. However feel free to use levels that work best for you.
Traditionally, I have treated values above +50 as overbought and below -40 as undersold (with -80 indicating extremely oversold); however these levels could also indicate either upwards and downwards momentum so taking a position based on where the ETI is (rather than crossing levels) should be done with caution.
ICT Macro Zone Boxes w/ Individual H/L Tracking v3.1ICT Macro Zones (Grey Box Version
This indicator dynamically highlights key intraday time-based macro sessions using a clean, minimalistic grey box overlay, helping traders align with institutional trading cycles. Inspired by ICT (Inner Circle Trader) concepts, it tracks real-time highs and lows for each session and optionally extends the zone box after the session ends — making it a precision tool for intraday setups, order flow analysis, and macro-level liquidity sweeps.
### 🔍 **What It Does**
- Plots **six predefined macro sessions** used in Smart Money Concepts:
- AM Macro (09:50–10:10)
- London Close (10:50–11:10)
- Lunch Macro (11:30–13:30)
- PM Macro (14:50–15:10)
- London SB (03:00–04:00)
- PM SB (15:00–16:00)
- Each zone:
- **Tracks high and low dynamically** throughout the session.
- **Draws a consistent grey shaded box** to visualize price boundaries.
- **Displays a label** at the first bar of the session (optional).
- **Optionally extends** the box to the right after the session closes.
### 🧠 **How It Works**
- Uses Pine Script arrays to define each session’s time window, label, and color.
- Detects session entry using `time()` within a New York timezone context.
- High/Low values are updated per bar inside the session window.
- Once a session ends, the box is optionally closed and fixed in place.
- All visual zones use a standardized grey tone for clarity and consistency across charts.
### 🛠️ **Settings**
- **Shade Zone High→Low:** Enable/disable the grey macro box.
- **Extend Box After Session:** Keep the zone visible after it ends.
- **Show Entry Label:** Display a label at the start of each session.
### 🎯 **Why This Script is Unique**
Unlike basic session markers or colored backgrounds, this tool:
- Focuses on **macro moments of liquidity and reversal**, not just open/close times.
- Uses **per-session logic** to individually track price behavior inside key time windows.
- Supports **real-time high/low tracking and clean zone drawing**, ideal for Smart Money and ICT-style strategies.
Perfect — based on your list, here's a **bundle-style description** that not only explains the function of each script but also shows how they **work together** in a Smart Money/ICT workflow. This kind of cross-script explanation is exactly what TradingView wants to see to justify closed-source mashups or interdependent tools.
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📚 ICT SMC Toolkit — Script Integration Guide
This set of advanced Smart Money Concept (SMC) tools is designed for traders who follow ICT-based methodologies, combining liquidity theory, time-based precision, and engineered confluences for high-probability trades. Each indicator is optimized to work both independently and synergistically, forming a comprehensive trading framework.
---
First FVG Custom Time Range
**Purpose:**
Plots the **first Fair Value Gap (FVG)** that appears within a defined session (e.g., NY Kill Zone, Custom range). Includes optional retest alerts.
**Best Used With:**
- Use with **ICT Macro Zones (Grey Box Version)** to isolate FVGs during high-probability times like AM Macro or PM SB.
- Combine with **Liquidity Levels** to assess whether FVGs form near swing points or liquidity voids.
---
ICT SMC Liquidity Grabs and OB s
**Purpose:**
Detects **liquidity grabs** (stop hunts above/below swing highs/lows) and **bullish/bearish order blocks**. Includes optional Fibonacci OTE levels for sniper entries.
**Best Used With:**
- Use with **ICT Turtle Soup (Reversal)** for confirmation after a liquidity grab.
- Combine with **Macro Zones** to catch order blocks forming inside timed macro windows.
- Match with **Smart Swing Levels** to confirm structure breaks before entry.
ICT SMC Liquidity Levels (Smart Swing Lows)
**Purpose:**
Automatically marks swing highs/lows based on user-defined lookbacks. Tracks whether those levels have been breached or respected.
**Best Used With:**
- Combine with **Turtle Soup** to detect if a swing level was swept, then reversed.
- Use with **Liquidity Grabs** to confirm a grab occurred at a meaningful structural point.
- Align with **Macro Zones** to understand when liquidity events occur within macro session timing.
ICT Turtle Soup (Liquidity Reversal)
**Purpose:**
Implements the classic ICT Turtle Soup model. Looks for swing failure and quick reversals after a liquidity sweep — ideal for catching traps.
Best Used With:
- Confirm with **Liquidity Grabs + OBs** to identify institutional activity at the reversal point.
- Use **Liquidity Levels** to ensure the reversal is happening at valid previous swing highs/lows.
- Amplify probability when pattern appears during **Macro Zones** or near the **First FVG**.
ICT Turtle Soup Ultimate V2
**Purpose:**
An enhanced, multi-layer version of the Turtle Soup setup that includes built-in liquidity checks, OTE levels, structure validation, and customizable visual output.
**Best Used With:**
- Use as an **entry signal generator** when other indicators (e.g., OBs, liquidity grabs) are aligned.
- Pair with **Macro Zones** for high-precision timing.
- Combine with **First FVG** to anticipate price rebalancing before explosive moves.
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## 🧠 Workflow Example:
1. **Start with Macro Zones** to focus only on institutional trading windows.
2. Look for **Liquidity Grabs or Swing Sweeps** around key highs/lows.
3. Check for a **Turtle Soup Reversal** or **Order Block Reaction** near that level.
4. Confirm confluence with a **Fair Value Gap**.
5. Execute using the **OTE level** from the Liquidity Grabs + OB script.
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Let me know which script you want to publish first — I’ll tailor its **individual TradingView description** and flag its ideal **“Best Used With” partners** to help users see the value in your ecosystem.
Hippo Battlefield - Bulls VS Bears 20 bars## Hippo Battlefield – Bulls VS Bears (20 Bars)
**What it is**
A multi-dimensional momentum-and-sentiment oscillator that combines classic Bull/Bear Power with ATR- or peak-normalization, then layers on RSI and MACD-derived metrics into:
1. **A colored bar series** showing net Bull+Bear Power strength over the last 20 bars,
2. **A dynamic table** of each of those 20 BBP values (grouped into four 5-bar “quartals”), with symbols, per-bar change, and rolling averages, and
3. **A composite “Weighted BBP” histogram** blending normalized RSI, MACD, and BBP into a single view.
---
### Key Inputs
- **Length (EMA)** – look-back for the underlying EMA (default 60)
- **Normalization Length** – look-back window for peak-normalization (default 60)
- **Use ATR for Norm.** – toggle ATR-based normalization vs. highest-abs(BBP)
- **Show Tables** – toggle the bottom-right 21×11 grid of raw and average BBP values
---
### What You See
#### 1. Colored Bars (Overlay = false)
- Bars are colored by normalized BBP intensity:
- Extreme Bull (≥+10): deep blue
- Strong Bull (+5 to +10): green/yellow
- Weak Bull (+0 to +5): dark green
- Weak Bear (–0 to –5): dark red
- Strong Bear (–5 to –10): pink/red
- Extreme Bear (<–10): magenta
#### 2. Bottom-Right Table (20 Bars of Data)
- Divided into four columns (0–4, 5–9, 10–14, 15–19 bars ago) and one “average” row.
- Each cell shows:
1. Bar index (1–20),
2. Normalized BBP value (to four decimals),
3. Direction symbol (↑/↓/=),
4. Bar-to-bar change (± value),
5. A separator “|”.
- At the very bottom, each column’s 5-bar average is displayed as “Avg: X.XXXX” with a dot marker.
#### 3. Top-Center Mini-Table
- When ≥20 bars have elapsed, shows the date at 20 bars ago and the average BBP across the full 20-bar window.
#### 4. Normalized RSI Line
- Rescales the classic 14-period RSI into a –20…+20 band to align with BBP.
#### 5. MACD Lines (Hidden) & Composite Histogram
- MACD and signal lines are calculated but not plotted by default.
- A “Weighted BBP” histogram combines:
- 20% normalized RSI,
- 20% average of (MACD + signal + normalized BBP),
- 60% normalized BBP
- Plotted as columns, color-coded by strength using the same palette as the main bars.
#### 6. Middle Reference Line
- A horizontal zero line to anchor over/under-zero readings.
---
### How to Use It
- **Trend confirmation**: Strong blue/green bars alongside a rising histogram suggest bull conviction; strong reds/magentas signal bear dominance.
- **Divergence spotting**: Watch for price making new highs/lows while BBP or the histogram fails to follow.
- **Quartal analysis**: The 5-bar group averages can reveal whether recent momentum is accelerating or waning.
- **Cross-indicator weighting**: Because RSI, MACD, and raw BBP all feed into the final histogram, you get a smoothed, blended view of momentum shifts.
---
**Tip:** Tweak the EMA and normalization length to suit your preferred timeframe (e.g. shorter for intraday scalps, longer for swing trades). Enable/disable the table if you prefer a cleaner pane.
Dskyz Options Flow Flux (OFF) - FuturesDskyz Options Flow Flux (OFF) - Futures
*This is a repost due to moderator intervention on use of ™ in my scripts. I'm in the process of getting this rectified. This was originally posted around mid-night CDT.
🧠 The Dskyz Options Flow Flux (OFF) - Futures indicator is a game changer for futures traders looking to tap into institutional activity with limited resources. Designed for TradingView this tool simulates options flow data (call/put volume and open interest) for futures contracts like MNQ MES NQ and ES giving u actionable insights through volume spike detection volatility adjustments and stunning visuals like aurora flux bands and round number levels. Whether u’re a beginner learning the ropes or a pro hunting for an edge this indicator delivers real time market sentiment and key price levels to boost ur trading game
Key Features
⚡ Simulated Options Flow: Breaks down call/put volume and open interest using market momentum and volatility
📈 Spike Detection: Spots big moves in volume and open interest with customizable thresholds
🧠 Volatility Filter: Adapts to market conditions using ATR for smarter spike detection
✨ Aurora Flux Bands: Glows with market sentiment showing u bullish or bearish vibes at a glance
🎯 Round Number Levels: Marks key psychological levels where big players might step in
📊 Interactive Dashboard: Real time metrics like sentiment score and volatility factor right on ur chart
🚨 Alerts: Get notified of bullish or bearish spikes so u never miss a move
How It Works
🧠 This indicator is built to make complex options flow analysis simple even with the constraints of Pine Script. Here’s the step by step:
Simulated Volume Data (Dynamic Split):
Pulls daily volume for ur chosen futures contract (MNQ1! MES1! NQ1! ES1!)
Splits it into call and put volume based on momentum (ta.mom) and volatility (ATR vs its 20 period average)
Estimates open interest (OI) for calls and puts (1.15x for calls 1.1x for puts)
Formula: callRatio = 0.5 + (momentum / close) * 10 + (volatility - 1) * 0.1 capped between 0.3 and 0.7
Why It Matters: Mimics how big players might split their trades giving u a peek into institutional sentiment
Spike Detection:
Compares current volume/OI to short term (lookbackShort) and long term (lookbackLong) averages
Flags spikes when volume/OI exceeds the average by ur set threshold (spikeThreshold for regular highConfidenceThreshold for strong)
Adjusts for volatility so u’re not fooled by choppy markets
Output: optionsSignal (2 for strong bullish -2 for strong bearish 1 for bullish -1 for bearish 0 for neutral)
Why It Matters: Pinpoints where big money might be stepping in
Volatility Filter:
Uses ATR (10 periods) and its 20 period average to calculate a volatility factor (volFactor = ATR / avgAtr)
Scales spike thresholds based on market conditions (volAdjustedThreshold = spikeThreshold * max(1 volFactor * volFilter))
Why It Matters: Keeps ur signals reliable whether the market is calm or wild
Sentiment Score:
Calculates a call/put ratio (callVolume / putVolume) and adjusts for volatility
Converts it to a 0 to 100 score (higher = bullish lower = bearish)
Formula: sentimentScore = min(max((volAdjustedSentiment - 1) * 50 0) 100)
Why It Matters: Gives u a quick read on market bias
Round Number Detection:
Finds the nearest round number (e.g. 100 for MNQ1! 50 for MES1!)
Checks for volume spikes (volume > 3 period SMA * spikeThreshold) and if price is close (within ATR * atrMultiplier)
Updates the top activity level every 15 minutes when significant activity is detected
Why It Matters: Highlights psychological levels where price often reacts
Visuals and Dashboard:
Combines aurora flux bands glow effects round number lines and a dashboard to make insights pop (see Visual Elements below)
Plots triangles for call/put spikes (green/red for strong lime/orange for regular)
Sets up alerts for key market moves
Why It Matters: Makes complex data easy to read at a glance
Inputs and Customization
⚙️ Beginners can tweak these settings to match their trading style while pros can dig deeper for precision:
Futures Symbol (symbol): Pick ur contract (MNQ1! MES1! NQ1! ES1!). Default: MNQ1!
Short Lookback (lookbackShort): Days for short term averages. Smaller = more sensitive. Range: 1+. Default: 5
Long Lookback (lookbackLong): Days for long term averages. Range: 5+. Default: 10
Spike Threshold (spikeThreshold): How big a spike needs to be (e.g. 1.1 = 10% above average). Range: 1.0+. Default: 1.1
High Confidence Threshold (highConfidenceThreshold): For strong spikes (e.g. 3.0 = 3x average). Range: 2.0+. Default: 3.0
Volatility Filter (volFilter): Adjusts for market volatility (e.g. 1.2 = 20% stricter in volatile markets). Range: 1.0+. Default: 1.2
Aurora Flux Transparency (glowOpacity): Controls band transparency (0 = solid 100 = invisible). Range: 0 to 100. Default: 65
Show Show OFF Dashboard (showDashboard): Toggles the dashboard with key metrics. Default: true
Show Nearest Round Number (showRoundNumbers): Displays round number levels. Default: true
ATR Multiplier for Proximity (atrMultiplier): How close price needs to be to a round number (e.g. 1.5 = within 1.5x ATR). Range: 0.5+. Default: 1.5
Functions and Logic
🧠 Here’s the techy stuff pros will love:
Simulated Volume Data : Splits daily volume into call/put volume and OI using momentum and volatility
Volatility Filter: Scales thresholds with volFactor = atr / avgAtr for adaptive detection
Spike Detection: Flags spikes and assigns optionsSignal (2, -2, 1, -1, 0) for sentiment
Sentiment Score: Converts call/put ratio into a 0-100 score for quick bias reads
Round Number Detection: Identifies key levels and significant activity for trading zones
Dashboard Display: Updates real time metrics like sentiment score and volatility factor
Visual Elements
✨ These visuals make data come alive:
Gradient Background: Green (bullish) red (bearish) or yellow (neutral/choppy) at 95% transparency to show trend
Aurora Flux Bands: Stepped bands (linewidth 3) around a 14 period EMA ± ATR * 1.8. Colors shift with sentiment (green red lime orange gray) with glow effects at 85% transparency
Round Number Visualization: Stepped lines (linewidth 2) at key levels (solid if active dashed if not) with labels (black background white text size.normal)
Visual Signals: Triangles above/below bars for spikes (size.small for strong size.tiny for regular)
Dashboard: Bottom left table (2 columns 10 rows) with a black background (29% transparency) gray border and metrics:
⚡ Round Number Activity: “Detected” or “None”
📈 Trend: “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
🧠 ATR: Current 10 period ATR
📊 ATR Avg: 20 period SMA of ATR
📉 Volume Spike: “YES” (green) or “NO” (red)
📋 Call/Put Ratio: Current ratio
✨ Flux Signal: “Strong Bullish” “Strong Bearish” “Bullish” “Bearish” or “Neutral” (colored green/red/gray)
⚙️ Volatility Factor: Current volFactor
📈 Sentiment Score: 0-100 score
Usage and Strategy Recommendations
🎯 For Beginners: Use high confidence spikes (green/red triangles) for easy entries. Check the dashboard for a quick market read (sentiment score above 60 = bullish below 40 = bearish). Watch round number levels for support/resistance
💡 For Pros: Combine flux signals with round number activity for high probability setups. Adjust lookbackShort/lookbackLong for trending vs choppy markets. Use volFactor for position sizing (higher = smaller positions)
[Stop!Loss] ADR Signal ADR Signal - a technical indicator located in a separate window, which displays by default the 80%-level , as well as the 100%-level of the average daily range (ADR) for the last 10 days and compares it with the current intraday range. The indicator helps not only with the use of a mathematical-statistical method to identify a potential reversal at the moment during intraday trading, but can also serves as an effective assistant in risk management.
👉 Basic mechanics of the indicator
Firstly, this indicator tracks the performance of the standard ATR indicator on the daily chart, in other words, ADR (Average Daily Range).
Important ❗️The ATR (Average True Range) indicator was created by J. Welles Wilder Jr. He first introduced ATR in his book "New Concepts in Technical Trading Systems", published in 1978. Wilder developed this indicator to measure market volatility to help traders estimate the range of price movements. This indicator is built into TradingView, more details can be found by link: www.tradingview.com
Like ATR , ADR calculates the average true range for a specified period. In this case, the distance in points from the maximum of each day to its minimum is calculated, after which the arithmetic mean is calculated - this is ADR .
👉 Visualization
ADR Signal is located in a separate window on the chart and has 3 levels:
1) "ADR level" (green line) - the same parameter, the calculations of which are briefly described above. There is 100%-level of ATR on the daily chart (ADR).
2) "Current level" (red line) - this is the current price passage within the day, calculated in points. At the start of a new day, this parameter is reset. Therefore, in the indicator window, this line has sharp drops at the start of a new trading day: "A new trading day - the instrument's power reserve is renewed again".
3) "Signal level" (blue line) - this is an individually customized value that demonstrates a certain part of the ADR parameter.
👉 Inputs
1) - is responsible for the ATR indicator period, the value of which will always be calculated on the daily chart. The default value is "10", that is, ATR is calculated for the last 10 days (not including the current one).
2) - signal level (in %). The default value is "0.8", that is, 80%-level of the ADR parameter (set earlier) is calculated.
👉 Style
1) - by default, this level is colored "blue".
2) - by default, this level is colored "red".
3) - by default, this level is colored "green".
👉 How to use this indicator
Important❗️ The two methods of the use of the ADR Signal indicator described below will be most effective when trading intraday (which is highlighted quite well below), so it is more logical to use the indicator information on time periods H1 and below.
1) Identifying potential reversals during intraday trading:
The ADR Signal indicator can be used as a potential individual reversal strategy.
Important ❗️It should be noted that using it in it without additional confirming analysis tools will be a rather aggressive trading approach. Therefore, it is best to support the entry point in particular with other methods.
In this case, the crossing of the red line (the number of points passed within the current day, that is, from the minimum of the current day to its maximum) and the blue line (color of the Signal level based on the default settings), indicates that the trading instrument has passed 80% (based on the default settings for the "Signal level") of its average distance from the maximum to the minimum over the past 10 days (based on the default settings for the "ADR Length"). Such a situation in the context of the mathematical-statistical approach indicates a probable reversal, since the "power reserve" of this instrument is mostly exhausted, so one can expect with a higher probability, at least, a price stop and possibly a reversal. In case of crossing of the red line and the green one (ADR level), it says again that based on the mathematical-statistical approach, this trading instrument has completely exhausted its intraday "power reserve". In this situation, a stop or reversal of the price will be even more likely.
Of course, using the "Signal level" parameter, one can filter out even more reliable situations for potential price reversals within a day, namely, by specifying, for example, 1.5 in the field of this parameter. Under such conditions, in the case of crossing the red and blue lines (based on the default style settings), to say that the trading instrument has passed 150% of its average distance over the last 10 days (based on the default style settings "ADR length"). In this case, the probability of a stop or reversal of the price increases even more.
2) Use in risk management:
In terms of risk management, this indicator is more applicable to open trades. For example, if one had an open Buy-position (especially if it is an intraday trade) and the price has raised significantly during the day, then the crossing of the red line with the blue line , and especially the red line with the green line , may indicate that the price will most likely stop growing, since the "power reserve" is almost or completely exhausted for this instrument within the current day. In this case, one can, at a minimum, move the trade to breakeven or even partially fix the profit.
We will continue to discuss the methods of using this indicator and strategies based on it here. And we are always waiting for your reactions and feedback on this topic 💬.
Thank you for your support 🚀
Nifty 1m EMA Pullback Scalper Signals
### **Master the Market with the Sniper Scalping Strategy for Nifty (1-Minute Timeframe)**
Unlock the power of precision trading with this expertly crafted **Sniper Scalping Strategy**, designed specifically for the Nifty index on a lightning-fast 1-minute timeframe. Perfect for traders who thrive on quick decisions and small, consistent profits, this strategy combines multiple indicators to deliver razor-sharp entries and exits—ideal for India’s dynamic market.
#### **Why This Strategy Stands Out**
- **Pinpoint Accuracy**: Harness the synergy of the **5 EMA and 10 EMA crossover** to lock onto the short-term trend, while the **Stochastic Oscillator (14,3,3)** times your entries and exits with surgical precision.
- **Fast and Effective**: Tailored for the 1-minute chart, this strategy capitalizes on Nifty’s volatility, targeting **10-point profits** with a tight **5-point stop-loss**—keeping your risk low and rewards high.
- **Trend + Momentum**: Blend trend-following (EMAs) with momentum signals (Stochastic) for a robust, multi-dimensional approach that cuts through market noise.
#### **How It Works**
- **Buy Signal**: Enter long when the 5 EMA crosses above the 10 EMA and the Stochastic rises above 20—catching the uptrend at its sweet spot.
- **Sell Signal**: Go short when the 5 EMA dips below the 10 EMA and the Stochastic falls below 80—riding the downtrend with confidence.
- **Exit Like a Pro**: Take profits at 10 points or when the Stochastic hits overbought/oversold extremes, ensuring you’re in and out before the market shifts.
#### **Perfect for Nifty Scalpers**
Built for the fast-paced world of Nifty trading, this strategy shines during high-volatility sessions like the market open or global overlaps. Whether you’re a beginner honing your skills or a seasoned trader seeking consistency, the Sniper Scalping Strategy offers a clear, actionable framework to scalp profits with discipline and precision.
#### **Get Started**
Test it in a demo account, refine it to your style, and watch your scalping game soar. Trade smart, stay focused, and let the Sniper Scalping Strategy turn Nifty’s 1-minute moves into your edge!
FA_PA_LIBLibrary "FA_PA_LIB"
A collection of custom tools & utility functions commonly used for coding Dr Al Brooks, Price Action System with my scripts
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getTopWickPercent()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: Percent of total candle width that is occupied by the upper wick
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBottomWickPercent()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: Percent of total candle width that is occupied by the lower wick
getBarMidPoint()
Gets the current candle's midpoint wick to wick
Returns: The current candle's mid point
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage (00.00)
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
isBr()
Checks if the current bar is a Bear Bar
Returns: A boolean - true if the current bar is bear candle
isBl()
Checks if the current bar is a Bull Bar
Returns: A boolean - true if the current bar is Bull candle
isTrendBar()
Checks if the current bar is a Trend Bar. Candle that its body size is greater than 50% of entire candle size
Returns: A boolean - true if the current bar is Trend candle
isBlTrendBar()
Checks if the current bar is a Bull Trend Bar. Bullish candle that its body size is greater than 50% of entire candle size
Returns: A boolean - true if the current bar is Bull Trend candle
isBrTrendBar()
Checks if the current bar is a Bull Trend Bar. Bullish candle that its body size is greater than 50% of entire candle size
Returns: A boolean - true if the current bar is Bull Trend candle
isBlRevB()
Checks if the current bar is a Bull Reversal Bar. Bullish candle that closes on upper half of candle body
Returns: A boolean - true if the current bar is Bull Reversal candle
isBrRevB()
Checks if the current bar is a Bear Reversal Bar. BulBearish candle that closes on lower half of candle body
Returns: A boolean - true if the current bar is Bear Reversal candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)
bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=true) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isBlOB()
Detects Bullish outside bars(OB)
Returns: Returns true if the current bar is a bull outside bar
isBrOB()
Detects Bearish outside bars(OB)
Returns: Returns true if the current bar is a bear outside bar
ICT Bread and Butter Sell-SetupICT Bread and Butter Sell-Setup – TradingView Strategy
Overview:
The ICT Bread and Butter Sell-Setup is an intraday trading strategy designed to capitalize on bearish market conditions. It follows institutional order flow and exploits liquidity patterns within key trading sessions—London, New York, and Asia—to identify high-probability short entries.
Key Components of the Strategy:
🔹 London Open Setup (2:00 AM – 8:20 AM NY Time)
The London session typically sets the initial directional move of the day.
A short-term high often forms before a downward push, establishing the daily high.
🔹 New York Open Kill Zone (8:20 AM – 10:00 AM NY Time)
The New York Judas Swing (a temporary rally above London’s high) creates an opportunity for short entries.
Traders fade this move, anticipating a sell-off targeting liquidity below previous lows.
🔹 London Close Buy Setup (10:30 AM – 1:00 PM NY Time)
If price reaches a higher timeframe discount array, a retracement higher is expected.
A bullish order block or failure swing signals a possible reversal.
The risk is set just below the day’s low, targeting a 20-30% retracement of the daily range.
🔹 Asia Open Sell Setup (7:00 PM – 2:00 AM NY Time)
If institutional order flow remains bearish, a short entry is taken around the 0-GMT Open.
Expect a 15-20 pip decline as the Asian range forms.
Strategy Rules:
📉 Short Entry Conditions:
✅ New York Judas Swing occurs (price moves above London’s high before reversing).
✅ Short entry is triggered when price closes below the open.
✅ Stop-loss is set 10 pips above the session high.
✅ Take-profit targets liquidity zones on higher timeframes.
📈 Long Entry (London Close Reversal):
✅ Price reaches a higher timeframe discount array between 10:30 AM – 1:00 PM NY Time.
✅ A bullish order block confirms the reversal.
✅ Stop-loss is set 10 pips below the day’s low.
✅ Take-profit targets 20-30% of the daily range retracement.
📉 Asia Open Sell Entry:
✅ Price trades slightly above the 0-GMT Open.
✅ Short entry is taken at resistance, targeting a quick 15-20 pip move.
Why Use This Strategy?
🚀 Institutional Order Flow Tracking – Aligns with smart money concepts.
📊 Precise Session Timing – Uses market structure across London, New York, and Asia.
🎯 High-Probability Entries – Focuses on liquidity grabs and engineered stop hunts.
📉 Optimized Risk Management – Defined stop-loss and take-profit levels.
This strategy is ideal for traders looking to trade with institutions, fade liquidity grabs, and capture high-probability short setups during the trading day. 📉🔥
Relative Volume at TimeThe Relative Volume at Time indicator (RVOL) is a simple modification of the original Relative Volume at Time script available in TradingView’s public library. It doesn’t change how the indicator works but includes two small adjustments:
Added Color Options – The ability to customize the colors of the volume bars, which was important to me as I use this indicator all the time and wanted more visually suitable colors.
Renamed Short Title – The abbreviation "RVOL" replaces "RelVol", as it's a more commonly used term in trading.
Aside from these small tweaks, the indicator retains all of its original functionality, including the ability to set an anchor timeframe, choose between Regular and Cumulative volume calculation modes, and adjust unconfirmed volume for incomplete bars.
This version exists simply because I needed a more personalized display for an indicator that I rely on daily.
How It Works
The Relative Volume at Time indicator compares the current volume to the average volume at the same time in previous sessions. This helps determine if today’s activity is higher or lower than usual.
Examples
On a daily chart (1D timeframe, length = 10), each volume bar compares today's volume to the average volume at the same time over the last 10 days. If today’s volume is higher than usual at this moment, the bar will reflect that.
On an hourly chart (1H timeframe, length = 5), each hourly volume bar compares the current hour’s volume to the same hour in the past 5 days. If the 10 AM bar is high, it means today's 10 AM volume is greater than the average of the past 5 sessions at 10 AM.
On a weekly chart (1W timeframe, length = 8), the indicator compares this week’s volume to the average of the last 8 weeks. A higher bar means this week is seeing significantly more volume than usual.
This logic applies to any timeframe. It always compares the current volume to past volumes at the same point in time.
@Julien_Eche
OHLC LoggerOHLC OG - 10 Candles
The OHLC OG - 10 Candles indicator provides a clear visualization of price action by analyzing the Open, High, Low, and Close (OHLC) data of the last 10 candles. Designed for traders who rely on structured price patterns, this indicator helps in identifying market trends, key support and resistance zones, and potential breakout points.
Features:
✅ Tracks the last 10 candles to highlight significant price movements.
✅ Visualizes Open, High, Low, and Close levels for improved market analysis.
✅ Customizable settings for enhanced adaptability to different strategies.
✅ Works across all timeframes and assets (forex, stocks, crypto, etc.).
✅ Ideal for price action traders looking for structured market insights.
This indicator is perfect for traders who prefer clean and reliable price action analysis without unnecessary complexity. Whether you trade breakouts, trend reversals, or continuation patterns, OHLC OG - 10 Candles helps you stay ahead of the market.
🔹 How to Use:
Apply the indicator to your chart and observe how the OHLC levels react to price movements.
Use it to confirm trends, identify potential breakout zones, or refine entry/exit points.
Combine it with other indicators or strategies for a more comprehensive trading approach.
📌 Disclaimer: This indicator is for educational purposes only. Always conduct proper risk management before trading.
Crypto Scanner v4This guide explains a version 6 Pine Script that scans a user-provided list of cryptocurrency tokens to identify high probability tradable opportunities using several technical indicators. The script combines trend, momentum, and volume-based analyses to generate potential buying or selling signals, and it displays the results in a neatly formatted table with alerts for trading setups. Below is a detailed walkthrough of the script’s design, how traders can interpret its outputs, and recommendations for optimizing indicator inputs across different timeframes.
## Overview and Key Components
The script is designed to help traders assess multiple tokens by calculating several indicators for each one. The key components include:
- **Input Settings:**
- A comma-separated list of symbols to scan.
- Adjustable parameters for technical indicators such as ADX, RSI, MFI, and a custom Wave Trend indicator.
- Options to enable alerts and set update frequencies.
- **Indicator Calculations:**
- **ADX (Average Directional Index):** Measures trend strength. A value above the provided threshold indicates a strong trend, which is essential for validating momentum before entering a trade.
- **RSI (Relative Strength Index):** Helps determine overbought or oversold conditions. When the RSI is below the oversold level, it may present a buying opportunity, while an overbought condition (not explicitly part of this setup) could suggest selling.
- **MFI (Money Flow Index):** Similar in concept to RSI but incorporates volume, thus assessing buying and selling pressure. Values below the designated oversold threshold indicate potential undervaluation.
- **Wave Trend:** A custom indicator that calculates two components (WT1 and WT2); a crossover where WT1 moves from below to above WT2 (particularly near oversold levels) may signal a reversal and a potential entry point.
- **Scanning and Trading Zone:**
- The script identifies a *bullish setup* when the following conditions are met for a token:
- ADX exceeds the threshold (strong trend).
- Both RSI and MFI are below their oversold levels (indicating potential buying opportunities).
- A Wave Trend crossover confirms near-term reversal dynamics.
- A *trading zone* condition is also defined by specific ranges for ADX, RSI, MFI, and a limited difference between WT1 and WT2. This zone suggests that the token might be in a consolidation phase where even small moves may be significant.
- **Alerts and Table Reporting:**
- A table is generated, with each row corresponding to a token. The table contains columns for the symbol, ADX, RSI, MFI, WT1, WT2, and the trading zone status.
- Visual cues—such as different background colors—highlight tokens with a bullish setup or that are within the trading zone.
- Alerts are issued based on the detection of a bullish setup or entry into a trading zone. These alerts are limited per bar to avoid flooding the trader with notifications.
## How to Interpret the Indicator Outputs
Traders should use the indicator values as guidance, verifying them against their own analysis before making any trading decision. Here’s how to assess each output:
- **ADX:**
- **High values (above threshold):** Indicate strong trends. If other indicators confirm an oversold condition, a trader may consider a long position for a corrective reversal.
- **Low values:** Suggest that the market is not trending strongly, and caution should be taken when considering entry.
- **RSI and MFI:**
- **Below oversold levels:** These conditions are traditionally seen as signals that an asset is undervalued, potentially triggering a bounce.
- **Above typical resistance levels (not explicitly used here):** Would normally caution a trader against entering a long position.
- **Wave Trend (WT1 and WT2):**
- A crossover where WT1 moves upward above WT2 in an oversold environment can signal the beginning of a recovery or reversal, thereby reinforcing buy signals.
- **Trading Zone:**
- Being “in zone” means that the asset’s current values for ADX, RSI, MFI, and the closeness of the Wave Trend lines indicate a period of consolidation. This scenario might be suitable for both short-term scalping or as an early exit indicator, depending on further market analysis.
## Timeframe Optimization Input Table
Traders can optimize indicator inputs depending on the timeframe they use. The following table provides a set of recommended input values for various timeframes. These values are suggestions and should be adjusted based on market conditions and individual trading styles.
Timeframe ADX RSI MFI ADX RSI MFI WT Channel WT Average
5-min 10 10 10 20 30 20 7 15
15-min 12 12 12 22 30 20 9 18
1-hour 14 14 14 25 30 20 10 21
4-hour 16 16 16 27 30 20 12 24
1-day 18 18 18 30 30 20 14 28
Adjust these parameters directly in the script’s input settings to match the selected timeframe. For shorter timeframes (e.g., 5-min or 15-min), the shorter lengths help filter high-frequency noise. For longer timeframes (e.g., 1-day), longer input values may reduce false signals and capture more significant trends.
## Best Practices and Usage Tips
- **Token Limit:**
- Limit the number of tokens scanned to 10 per query line. If you need to scan more tokens, initiate a new query line. This helps manage screen real estate and ensures the table remains legible.
- **Confirming Signals:**
- Use this script as a starting point for identifying high potential trades. Each indicator’s output should be used to confirm your trading decision. Always cross-reference with additional technical analysis tools or market context.
- **Regular Review:**
- Since the script updates the table every few bars (as defined by the update frequency), review the table and alerts regularly. Market conditions change rapidly, so timely decisions are crucial.
## Conclusion
This Pine Script provides a comprehensive approach for scanning multiple cryptocurrencies using a combination of trend strength (ADX), momentum (RSI and MFI), and reversal signals (Wave Trend). By using the provided recommendation table for different timeframes and limiting the tokens to 20 per query line (with a maximum of four query lines), traders can streamline their scanning process and more effectively identify high probability tradable tokens. Ultimately, the outputs should be critically evaluated and combined with additional market research before executing any trades.
Parabolic Detector (10min, 75°)Объяснение :
Таймфрейм 10 минут:
Используется функция request.security для получения цены закрытия за последние 10 минут.
Таймфрейм задается через input.timeframe("10", ...).
Расчет угла наклона:
Изменение цены (price_change) рассчитывается как разница между текущей ценой закрытия и ценой закрытия 10 минут назад.
Угол наклона (angle) рассчитывается с использованием функции math.atan (арктангенс). Учитывается, что 10 минут = 600 секунд.
Пороговое значение 75 градусов:
Если абсолютное значение угла (math.abs(angle)) больше или равно 75 градусам, то движение считается параболическим.
Визуализация:
На графике отображается метка "PARABOLIC", если движение параболическое.
Mean Reversion Pro Strategy [tradeviZion]Mean Reversion Pro Strategy : User Guide
A mean reversion trading strategy for daily timeframe trading.
Introduction
Mean Reversion Pro Strategy is a technical trading system that operates on the daily timeframe. The strategy uses a dual Simple Moving Average (SMA) system combined with price range analysis to identify potential trading opportunities. It can be used on major indices and other markets with sufficient liquidity.
The strategy includes:
Trading System
Fast SMA for entry/exit points (5, 10, 15, 20 periods)
Slow SMA for trend reference (100, 200 periods)
Price range analysis (20% threshold)
Position management rules
Visual Elements
Gradient color indicators
Three themes (Dark/Light/Custom)
ATR-based visuals
Signal zones
Status Table
Current position information
Basic performance metrics
Strategy parameters
Optional messages
📊 Strategy Settings
Main Settings
Trading Mode
Options: Long Only, Short Only, Both
Default: Long Only
Position Size: 10% of equity
Starting Capital: $20,000
Moving Averages
Fast SMA: 5, 10, 15, or 20 periods
Slow SMA: 100 or 200 periods
Default: Fast=5, Slow=100
🎯 Entry and Exit Rules
Long Entry Conditions
All conditions must be met:
Price below Fast SMA
Price below 20% of current bar's range
Price above Slow SMA
No existing position
Short Entry Conditions
All conditions must be met:
Price above Fast SMA
Price above 80% of current bar's range
Price below Slow SMA
No existing position
Exit Rules
Long Positions
Exit when price crosses above Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
Short Positions
Exit when price crosses below Fast SMA
No fixed take-profit levels
No stop-loss (mean reversion approach)
💼 Risk Management
Position Sizing
Default: 10% of equity per trade
Initial capital: $20,000
Commission: 0.01%
Slippage: 2 points
Maximum one position at a time
Risk Control
Use daily timeframe only
Avoid trading during major news events
Consider market conditions
Monitor overall exposure
📊 Performance Dashboard
The strategy includes a comprehensive status table displaying:
Strategy Parameters
Current SMA settings
Trading direction
Fast/Slow SMA ratio
Current Status
Active position (Flat/Long/Short)
Current price with color coding
Position status indicators
Performance Metrics
Net Profit (USD and %)
Win Rate with color grading
Profit Factor with thresholds
Maximum Drawdown percentage
Average Trade value
📱 Alert Settings
Entry Alerts
Long Entry (Buy Signal)
Short Entry (Sell Signal)
Exit Alerts
Long Exit (Take Profit)
Short Exit (Take Profit)
Alert Message Format
Strategy name
Signal type and direction
Current price
Fast SMA value
Slow SMA value
💡 Usage Tips
Consider starting with Long Only mode
Begin with default settings
Keep track of your trades
Review results regularly
Adjust settings as needed
Follow your trading plan
⚠️ Disclaimer
This strategy is for educational and informational purposes only. It is not financial advice. Always:
Conduct your own research
Test thoroughly before live trading
Use proper risk management
Consider your trading goals
Monitor market conditions
Never risk more than you can afford to lose
📋 Release Notes
14 January 2025
Added New Fast & Slow SMA Options:
Fibonacci-based periods: 8, 13, 21, 144, 233, 377
Additional period: 50
Complete Fast SMA options now: 5, 8, 10, 13, 15, 20, 21, 34, 50
Complete Slow SMA options now: 100, 144, 200, 233, 377
Bug Fixes:
Fixed Maximum Drawdown calculation in the performance table
Now using strategy.max_drawdown_percent for accurate DD reporting
Previous version showed incorrect DD values
Performance metrics now accurately reflect trading results
Performance Note:
Strategy tested with Fast/Slow SMA 13/377
Test conducted with 10% equity risk allocation
Daily Timeframe
For Beginners - How to Modify SMA Levels:
Find this line in the code:
fastLength = input.int(title="Fast SMA Length", defval=5, options= )
To add a new Fast SMA period: Add the number to the options list, e.g.,
To remove a Fast SMA period: Remove the number from the options list
For Slow SMA, find:
slowLength = input.int(title="Slow SMA Length", defval=100, options= )
Modify the options list the same way
⚠️ Note: Keep the periods that make sense for your trading timeframe
💡 Tip: Test any new combinations thoroughly before live trading
"Trade with Discipline, Manage Risk, Stay Consistent" - tradeviZion
JJ Highlight Time Ranges with First 5 Minutes and LabelsTo effectively use this Pine Script as a day trader , here’s how the various elements can help you manage trades, track time sessions, and monitor price movements:
Key Components for a Day Trader:
1. First 5-Minute Highlight:
- Purpose: Day traders often rely on the first 5 minutes of the trading session to gauge market sentiment, watch for opening price gaps, or plan entries. This script draws a horizontal line at the high or low of the first 5 minutes, which can act as a key level for the rest of the day.
- How to Use: If the price breaks above or below the first 5-minute line, it can signal momentum. You might enter a long position if the price breaks above the first 5-minute high or a short if it breaks below the first 5-minute low.
2. Session Time Highlights:
- Morning Session (9:15–10:30 AM): The market often shows its strongest price action during the first hour of trading. This session is highlighted in yellow. You can use this highlight to focus on the most volatile period, as this is when large institutional moves tend to occur.
- Afternoon Session (12:30–2:55 PM): The blue highlight helps you track the mid-afternoon session, where liquidity may decrease, and price action can sometimes be choppier. Day traders should be more cautious during this period.
- How to Use: By highlighting these key times, you can:
- Focus on key breakouts during the morning session.
- Be more conservative in your trades during the afternoon, as market volatility may drop.
3. Dynamic Labels:
- Top/Bottom Positioning: The script places labels dynamically based on the selected position (Top or Bottom). This allows you to quickly glance at the session's start and identify where you are in terms of time.
- How to Use: Use these labels to remind yourself when major time segments (morning or afternoon) begin. You can adjust your trading strategy depending on the session, e.g., being more aggressive in the morning and more cautious in the afternoon.
Trading Strategy Suggestions:
1. Momentum Trades:
- After the first 5 minutes, use the high/low of that period to set up breakout trades.
- Long Entry: If the price breaks the high of the first 5 minutes (especially if there's a strong trend).
- Short Entry: If the price breaks the low of the first 5 minutes, signaling a potential downtrend.
2. Session-Based Strategy:
- Morning Session (9:15–10:30 AM):
- Look for strong breakout patterns such as support/resistance levels, moving average crossovers, or candlestick patterns (like engulfing candles or pin bars).
- This is a high liquidity period, making it ideal for executing quick trades.
- Afternoon Session (12:30–2:55 PM):
- The market tends to consolidate or show less volatility. Scalping and mean-reversion strategies work better here.
- Avoid chasing big moves unless you see a clear breakout in either direction.
3. Support and Resistance:
- The first 5-minute high/low often acts as a key support or resistance level for the rest of the day. If the price holds above or below this level, it’s an indication of trend continuation.
4. Breakout Confirmation:
- Look for breakouts from the highlighted session time ranges (e.g., 9:15 AM–10:30 AM or 12:30 PM–2:55 PM).
- If a breakout happens during a key time window, combine that with other technical indicators like volume spikes , RSI , or MACD for confirmation.
---
Example Day Trader Usage:
1. First 5 Minutes Strategy: After the market opens at 9:15 AM, watch the price action for the first 5 minutes. The high and low of these 5 minutes are critical levels. If the price breaks above the high of the first 5 minutes, it might indicate a strong bullish trend for the day. Conversely, breaking below the low may suggest bearish movement.
2. Morning Session: After the first 5 minutes, focus on the **9:15 AM–10:30 AM** window. During this time, look for breakout setups at key support/resistance levels, especially when paired with high volume or momentum indicators. This is when many institutions make large trades, so price action tends to be more volatile and predictable.
3. Afternoon Session: From 12:30 PM–2:55 PM, the market might experience lower volatility, making it ideal for scalping or range-bound strategies. You could look for reversals or fading strategies if the market becomes too quiet.
Conclusion:
As a day trader, you can use this script to:
- Track and react to key price levels during the first 5 minutes.
- Focus on high volatility in the morning session (9:15–10:30 AM) and **be cautious** during the afternoon.
- Use session-based timing to adjust your strategies based on the time of day.
Candles Volume HeatMap [BigBeluga]Candles Volume HeatMap
The Candle Volume HeatMap indicator is a unique and advanced tool that visualizes lower timeframe volume activity within higher timeframe candles, offering traders a granular perspective on volume distribution.
⚠️Important note: before using the indicator, it is necessary to apply it to the candles
🔵Key Features:
Volume HeatMap Visualization: The indicator breaks down each higher timeframe candle into 10 equal vertical segments (boxes) based on its high-to-low range. Each box represents a lower timeframe candle's volume activity, with more intense colors indicating stronger volume levels.
Lower Timeframe Integration: Automatically uses a timeframe 10x lower than the current chart. For example, on a 10-hour chart, it uses 1-hour candles to extract volume data.
POC (Point of Control): The highest volume box within each candle is marked with the volume value. The indicator also plots a horizontal POC line at the level of this box, highlighting significant areas of price interest. The POC line is removed once the price crosses it, ensuring the chart stays clean.
Delta Display (Optional): Traders can enable the Delta feature to analyze buyer vs. seller activity within each higher timeframe candle.
Delta is calculated by summing 10 lower timeframe candles: a bullish candle adds to buyers, while a bearish candle adds to sellers. Displays the net Delta percentage: positive values (white) indicate buyer dominance, while negative values (red) indicate seller dominance.
Dynamic Volume Scaling: The highest volume value in each candle is displayed inside its respective box, providing quick insights into critical price-volume levels.
🔵How It Works:
For each higher timeframe candle, the indicator analyzes 10 lower timeframe candles and maps their volume into 10 segments (boxes) between the high and low of the current candle.
The intensity of each box's color corresponds to the relative volume of the lower timeframe candle it represents.
The POC highlights the price level with the highest concentration of volume, aiding in identifying potential support/resistance zones.
Delta analysis offers additional insights into market sentiment by breaking down buyer and seller activity in each candle.
🔵Use Cases:
Spotting key volume areas within higher timeframe candles to identify support and resistance levels.
Analyzing volume concentration for potential breakout or reversal zones.
Leveraging Delta analysis to gauge market sentiment and confirm volume-based trends.
This indicator is ideal for traders seeking to combine volume analysis with price action, offering precise insights into volume distribution and market dynamics.
Original Keltner with Support And ResistanceThis indicator is based on the original Keltner Channels using typical price and calculating the 10 period average of high - low
Typical price = (high + low + close)/3
In this case, I've taken Typical price as (open + high + low + close)/4 on the advice of John Bollinger from his book Bollinger on Bollinger Bands.
Buy Line = 10 Period Typical Price Average + 10 Period Average of (High - Low)
Sell Line = 10 Period Typical Price Average - 10 Period Average of (High - Low)
This is the basis for the indicator. I've added the highest of the Buy Line and lowest of the Sell Line for the same period which acts as Support and Resistance.
If price is trending below the Lowest of Sell Line, take only sell trades and the Lowest Line acts as resistance.
If price is trending above the Highest of Buy Line, take only buy trades and the Highest Line acts as support.
EMA and ATR Indicator BY DemirkanEMA 10 and ATR Indicator BY Demirkan
The EMA 10 and ATR Indicator combines two powerful technical indicators used to analyze trends and identify potential trading opportunities.
Indicator Components:
Exponential Moving Average (EMA):
EMA 10: Calculates the weighted average of the last 10 closing prices. This indicator is effective in tracking short-term price movements. When the price is above the EMA, it is considered that the trend is upward; when it is below, it is assessed as a downward trend.
Average True Range (ATR):
ATR: A measure of market volatility. When the ATR value falls within a specified range (between 10 and 14 in this indicator), the price movement is considered significant. This helps you base your trading decisions on more solid grounds.
Usage Recommendations:
Buy Signal: When the price is above the EMA and the ATR is within the specified range, this can be interpreted as a potential buy signal.
Sell Signal: When the price is below the EMA, this can be interpreted as a potential sell signal.
Chart Displays:
EMA Line: Displayed as a blue line, allowing you to see how the EMA relates to current price levels.
Price Status: Circles are used to indicate whether the price is above or below the EMA. A green circle indicates the price is above the EMA, while a red circle indicates it is below.
Background Colors: The chart background changes to green or red to highlight buy and sell conditions.
Aesthetic Presentation:
Using the "Flag" and "Below" parameters for the Price vs EMA indicator provides an aesthetically pleasing appearance on the chart. This type of visual presentation helps users quickly and easily grasp trading signals. Additionally, this aesthetic touch makes investors' charts look more professional and appealing.
This indicator is a useful tool for traders looking to develop short-term trading strategies. However, it should always be used in conjunction with additional analysis and other indicators.
Note: This indicator is for educational purposes only and should not be taken as investment advice.
Accurate 10x Volume Spike with Corrected Next Candle AnalysisDescription :
The Volume Ten Candles indicator is a technical analysis tool that helps traders identify candles with volume exceeding the previous one by 10 times. This can indicate a potential trend reversal or continuation of the current price movement.
Signal :
The indicator generates a signal when a candle with volume exceeding the previous one by 10 times appears. The signal is displayed on the chart as an arrow or other symbol.
Statistics :
The indicator also displays statistics in the form of a table that shows the number of candles with volume exceeding the previous one by 10 times for a certain period of time. This helps traders assess the strength of the trend and make a decision about entering a trade.
Example of Use :
The Volume Ten Candles indicator can be useful for traders who want to find candles with high volume and use them to enter a trade. For example, if a candle with volume exceeding the previous one by 10 times appears, it may indicate that the market is ready for a price movement. In this case, the trader can open a trade in the direction of this movement.
It is important to note that the Volume Ten Candles indicator is not a guarantee of profit and may produce false signals. Therefore, before using the indicator, it is necessary to conduct testing on historical data and develop a trading strategy.
Statistics Table :
The table displays the number of candles with volume exceeding the previous one by 10 times for each day.
Double BBW OverlayDouble BBW Overlay Indicator
Overview
The Double BBW (Bollinger Band Width) Overlay indicator is a custom script for TradingView that combines two BBW indicators with adjustable settings. It allows traders to compare the volatility of two different periods of Bollinger Bands on the same chart. By default, the first BBW is calculated with a 10-period center line, and the second BBW with a 20-period center line, but these values can be customized.
How It Works
Bollinger Bands consist of an upper band, a lower band, and a middle band (typically a moving average). The Bollinger Band Width (BBW) measures the distance between the upper and lower bands relative to the center line. The width of these bands indicates market volatility:
Narrow Bands: Low volatility, usually preceding a breakout.
Wide Bands: High volatility, often following a strong price movement.
This indicator plots two BBW values on a non-overlay chart, making it easy to visualize and compare different market conditions over different periods.
Indicator Components
BBW 1 (default period: 10)
Calculates the BBW using a center line based on a 10-period moving average.
The width is plotted in blue by default.
BBW 2 (default period: 20)
Calculates the BBW using a center line based on a 20-period moving average.
The width is plotted in red by default.
Zero Line
A gray horizontal line at the value of 0 for reference, helping to understand the scale of BBW values.
Input Parameters
Center Line Period for BBW 1 (length1)
Default: 10
This controls the length of the moving average for the first BBW calculation. It defines how many periods are used to calculate the middle Bollinger Band for BBW 1.
Center Line Period for BBW 2 (length2)
Default: 20
This controls the length of the moving average for the second BBW calculation. It defines how many periods are used to calculate the middle Bollinger Band for BBW 2.
Standard Deviation Multiplier (mult)
Default: 2.0
This controls how far the upper and lower Bollinger Bands are from the center line. The multiplier affects how sensitive the Bollinger Bands are to price changes, with higher values producing wider bands.
How to Use
Adding the Indicator: Once the script is added to your TradingView account, simply apply the indicator to any chart. It will be displayed as a separate pane below the price chart, showing two BBW lines corresponding to the two different periods.
Customizing Periods: Use the settings panel to adjust the center line periods for BBW 1 and BBW 2 to match your desired trading strategy. For instance, you can analyze short-term versus long-term volatility by adjusting the periods.
Volatility Analysis:
When both BBW lines are narrow, it indicates low volatility across both short-term and long-term periods, which could suggest that a breakout is imminent.
If both BBW lines widen simultaneously, it shows that volatility is increasing in both timeframes, possibly indicating a strong trend.
Use Cases
Breakout Strategy: When the BBW lines contract significantly, it may signal that a low-volatility period is about to end, which is often followed by a price breakout in either direction.
Trend Strength: Comparing short-term and long-term BBW values can help determine if recent price movements are supported by broader market volatility or if they are isolated to the short term.
Chart Display
BBW 1: Blue line, representing the Bollinger Band Width calculated with a center line period of 10 (or your customized value).
BBW 2: Red line, representing the Bollinger Band Width calculated with a center line period of 20 (or your customized value).
Zero Line: A gray line at 0 is provided for reference, although BBW values are always positive.
Advantages of Using Double BBW
Comprehensive View of Volatility: By overlaying two BBW indicators with different timeframes, you can gain insights into both short-term and long-term market volatility trends.
Customizable: You can easily adjust the moving average periods and the standard deviation multiplier to match your preferred trading strategy or the characteristics of the asset you are trading.
Easy Visualization: The separate plots of BBW values make it easier to see shifts in market volatility, allowing you to spot potential trading opportunities.
Bitcoin Logarithmic Growth Curve 2024The Bitcoin logarithmic growth curve is a concept used to analyze Bitcoin's price movements over time. The idea is based on the observation that Bitcoin's price tends to grow exponentially, particularly during bull markets. It attempts to give a long-term perspective on the Bitcoin price movements.
The curve includes an upper and lower band. These bands often represent zones where Bitcoin's price is overextended (upper band) or undervalued (lower band) relative to its historical growth trajectory. When the price touches or exceeds the upper band, it may indicate a speculative bubble, while prices near the lower band may suggest a buying opportunity.
Unlike most Bitcoin growth curve indicators, this one includes a logarithmic growth curve optimized using the latest 2024 price data, making it, in our view, superior to previous models. Additionally, it features statistical confidence intervals derived from linear regression, compatible across all timeframes, and extrapolates the data far into the future. Finally, this model allows users the flexibility to manually adjust the function parameters to suit their preferences.
The Bitcoin logarithmic growth curve has the following function:
y = 10^(a * log10(x) - b)
In the context of this formula, the y value represents the Bitcoin price, while the x value corresponds to the time, specifically indicated by the weekly bar number on the chart.
How is it made (You can skip this section if you’re not a fan of math):
To optimize the fit of this function and determine the optimal values of a and b, the previous weekly cycle peak values were analyzed. The corresponding x and y values were recorded as follows:
113, 18.55
240, 1004.42
451, 19128.27
655, 65502.47
The same process was applied to the bear market low values:
103, 2.48
267, 211.03
471, 3192.87
676, 16255.15
Next, these values were converted to their linear form by applying the base-10 logarithm. This transformation allows the function to be expressed in a linear state: y = a * x − b. This step is essential for enabling linear regression on these values.
For the cycle peak (x,y) values:
2.053, 1.268
2.380, 3.002
2.654, 4.282
2.816, 4.816
And for the bear market low (x,y) values:
2.013, 0.394
2.427, 2.324
2.673, 3.504
2.830, 4.211
Next, linear regression was performed on both these datasets. (Numerous tools are available online for linear regression calculations, making manual computations unnecessary).
Linear regression is a method used to find a straight line that best represents the relationship between two variables. It looks at how changes in one variable affect another and tries to predict values based on that relationship.
The goal is to minimize the differences between the actual data points and the points predicted by the line. Essentially, it aims to optimize for the highest R-Square value.
Below are the results:
It is important to note that both the slope (a-value) and the y-intercept (b-value) have associated standard errors. These standard errors can be used to calculate confidence intervals by multiplying them by the t-values (two degrees of freedom) from the linear regression.
These t-values can be found in a t-distribution table. For the top cycle confidence intervals, we used t10% (0.133), t25% (0.323), and t33% (0.414). For the bottom cycle confidence intervals, the t-values used were t10% (0.133), t25% (0.323), t33% (0.414), t50% (0.765), and t67% (1.063).
The final bull cycle function is:
y = 10^(4.058 ± 0.133 * log10(x) – 6.44 ± 0.324)
The final bear cycle function is:
y = 10^(4.684 ± 0.025 * log10(x) – -9.034 ± 0.063)
The main Criticisms of growth curve models:
The Bitcoin logarithmic growth curve model faces several general criticisms that we’d like to highlight briefly. The most significant, in our view, is its heavy reliance on past price data, which may not accurately forecast future trends. For instance, previous growth curve models from 2020 on TradingView were overly optimistic in predicting the last cycle’s peak.
This is why we aimed to present our process for deriving the final functions in a transparent, step-by-step scientific manner, including statistical confidence intervals. It's important to note that the bull cycle function is less reliable than the bear cycle function, as the top band is significantly wider than the bottom band.
Even so, we still believe that the Bitcoin logarithmic growth curve presented in this script is overly optimistic since it goes parly against the concept of diminishing returns which we discussed in this post:
This is why we also propose alternative parameter settings that align more closely with the theory of diminishing returns.
Our recommendations:
Drawing on the concept of diminishing returns, we propose alternative settings for this model that we believe provide a more realistic forecast aligned with this theory. The adjusted parameters apply only to the top band: a-value: 3.637 ± 0.2343 and b-parameter: -5.369 ± 0.6264. However, please note that these values are highly subjective, and you should be aware of the model's limitations.
Conservative bull cycle model:
y = 10^(3.637 ± 0.2343 * log10(x) - 5.369 ± 0.6264)
Post-Open Long Strategy with ATR-based Stop Loss and Take ProfitThe "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit
The "Post-Open Long Strategy with ATR-Based Stop Loss and Take Profit" is designed to identify buying opportunities after the German and US markets open. It combines various technical indicators to filter entry signals, focusing on breakout moments following price lateralization periods.
Key Components and Their Interaction:
Bollinger Bands (BB):
Description: Uses BB with a 14-period length and standard deviation multiplier of 1.5, creating narrower bands for lower timeframes.
Role in the Strategy: Identifies low volatility phases (lateralization). The lateralization condition is met when the price is near the simple moving average of the BB, suggesting an imminent increase in volatility.
Exponential Moving Averages (EMA):
10-period EMA: Quickly detects short-term trend direction.
200-period EMA: Filters long-term trends, ensuring entries occur in a bullish market.
Interaction: Positions are entered only if the price is above both EMAs, indicating a consolidated positive trend.
Relative Strength Index (RSI):
Description: 7-period RSI with a threshold above 30.
Role in the Strategy: Confirms the market is not oversold, supporting the validity of the buy signal.
Average Directional Index (ADX):
Description: 7-period ADX with 7-period smoothing and a threshold above 10.
Role in the Strategy: Assesses trend strength. An ADX above 10 indicates sufficient momentum to justify entry.
Average True Range (ATR) for Dynamic Stop Loss and Take Profit:
Description: 14-period ATR with multipliers of 2.0 for Stop Loss and 4.0 for Take Profit.
Role in the Strategy: Adjusts exit levels based on current volatility, enhancing risk management.
Resistance Identification and Breakout:
Description: Analyzes the highs of the last 20 candles to identify resistance levels with at least two touches.
Role in the Strategy: A breakout above this level signals a potential continuation of the bullish trend.
Time Filters and Market Conditions:
Trading Hours: Operates only during the opening of the German market (8:00 - 12:00) and US market (15:30 - 19:00).
Panic Candle: The current candle must close negative, leveraging potential emotional reactions in the market.
Avoiding Entry During Pullbacks:
Description: Checks that the two previous candles are not both bearish.
Role in the Strategy: Avoids entering during a potential pullback, improving trade success probability.
Entry and Exit Conditions:
Long Entry:
The price breaks above the identified resistance.
The market is in a lateralization phase with low volatility.
The price is above the 10 and 200-period EMAs.
RSI is above 30, and ADX is above 10.
No short-term downtrend is detected.
The last two candles are not both bearish.
The current candle is a "panic candle" (negative close).
Order Execution: The order is executed at the close of the candle that meets all conditions.
Exit from Position:
Dynamic Stop Loss: Set at 2 times the ATR below the entry price.
Dynamic Take Profit: Set at 4 times the ATR above the entry price.
The position is automatically closed upon reaching the Stop Loss or Take Profit.
How to Use the Strategy:
Application on Volatile Instruments:
Ideal for financial instruments that show significant volatility during the target market opening hours, such as indices or major forex pairs.
Recommended Timeframes:
Intraday timeframes, such as 5 or 15 minutes, to capture significant post-open moves.
Parameter Customization:
The default parameters are optimized but can be adjusted based on individual preferences and the instrument analyzed.
Backtesting and Optimization:
Backtesting is recommended to evaluate performance and make adjustments if necessary.
Risk Management:
Ensure position sizing respects risk management rules, avoiding risking more than 1-2% of capital per trade.
Originality and Benefits of the Strategy:
Unique Combination of Indicators: Integrates various technical metrics to filter signals, reducing false positives.
Volatility Adaptability: The use of ATR for Stop Loss and Take Profit allows the strategy to adapt to real-time market conditions.
Focus on Post-Lateralization Breakout: Aims to capitalize on significant moves following consolidation periods, often associated with strong directional trends.
Important Notes:
Commissions and Slippage: Include commissions and slippage in settings for more realistic simulations.
Capital Size: Use a realistic trading capital for the average user.
Number of Trades: Ensure backtesting covers a sufficient number of trades to validate the strategy (ideally more than 100 trades).
Warning: Past results do not guarantee future performance. The strategy should be used as part of a comprehensive trading approach.
With this strategy, traders can identify and exploit specific market opportunities supported by a robust set of technical indicators and filters, potentially enhancing their trading decisions during key times of the day.
