Neeson bitcoin Dynamic ATR Trailing SystemNeeson bitcoin Dynamic ATR Trailing System: A Comprehensive Guide to Volatility-Adaptive Trend Following
Introduction
The Dynamic ATR Trailing System (DATR-TS) represents a sophisticated approach to trend following that transcends conventional moving average or breakout-based methodologies. Unlike standard trend-following systems that rely on price pattern recognition or fixed parameter oscillators, this system operates on the principle of volatility-adjusted position management—a nuanced approach that dynamically adapts to changing market conditions rather than imposing rigid rules on market behavior.
Originality and Innovation
Distinct Methodological Approach
What sets DATR-TS apart from hundreds of existing trend-following systems is its dual-layered conditional execution framework. While most trend-following systems fall into one of three broad categories—moving average crossovers, channel breakouts, or momentum oscillators—this system belongs to the more specialized category of volatility-normalized trailing stop systems.
Key Original Contributions:
Volatility-Threshold Signal Filtering: Most trend systems generate signals continuously, leading to overtrading during low-volatility periods. DATR-TS implements a proprietary volatility filter that requires minimum market movement before generating signals, effectively separating high-probatility trend opportunities from market noise.
Self-Contained Position State Management: Unlike traditional systems that require external position tracking, DATR-TS maintains an internal position state that prevents contradictory signals and creates a closed-loop decision framework.
Dynamic Risk Parameter Adjustment: The system doesn't use fixed percentage stops or rigid ATR multiples. Instead, it implements a responsive adjustment mechanism that widens stops during high volatility and tightens them during low volatility, creating an optimal balance between risk protection and opportunity capture.
Trader-Centric Visualization Philosophy: Beyond mere signal generation, the system provides a comprehensive visual feedback system designed to align with human cognitive patterns, reducing emotional decision-making through consistent color coding and information hierarchy.
Technical Implementation and Functionality
Core Operational Mechanism
DATR-TS implements a volatility-adjusted trend persistence model that operates on the principle that trending markets exhibit characteristic volatility signatures. The system specifically targets medium-term directional movements (typically lasting 5-20 days) rather than short-term scalping opportunities or long-term position trades.
The Four-Pillar Architecture:
Volatility Measurement and Normalization
Calculates Average True Range (ATR) over a user-defined period
Converts absolute volatility to percentage terms relative to price
Compares current volatility against user-defined thresholds to filter suboptimal conditions
Dynamic Trailing Stop Algorithm
Establishes an initial stop distance based on current volatility
Implements a four-state adjustment mechanism that responds to price action
Maintains stop position during trend continuation while allowing for trend reversal detection
Conditional Signal Generation
Generates entry signals only when price action meets both directional and volatility criteria
Produces exit signals based on trailing stop penetration
Incorporates position state awareness to prevent conflicting signals
Comprehensive Feedback System
Provides multi-layer visual information including dynamic stop lines, signal labels, and color-coded price action
Displays real-time metrics through an integrated dashboard
Offers configurable visualization options for different trading styles
Specific Trend-Following Methodology
DATR-TS employs a volatility-normalized trailing stop breakout approach, which differs significantly from common trend identification methods:
Not a moving average crossover system (like MACD or traditional MA crosses)
Not a channel breakout system (like Bollinger Band or Donchian Channel breaks)
Not a momentum oscillator system (like RSI or Stochastic trend following)
Not a price pattern recognition system (like head-and-shoulders or triangle breaks)
Instead, it belongs to the more specialized category of volatility-adjusted stop-and-reverse systems that:
Wait for market volatility to reach actionable levels
Establish positions when price confirms directional bias through stop penetration
Manage risk dynamically based on evolving market conditions
Exit positions when the trend exhausts itself through stop violation
Practical Application and Usage
Market Environment Optimization
Ideal Conditions:
Trending markets with sustained directional movement
Medium volatility environments (neither excessively calm nor chaotic)
Timeframes: 4-hour to daily charts for optimal signal quality
Instruments: Forex majors, commodity futures, equity indices
Suboptimal Conditions:
Ranging or consolidating markets
Extreme volatility events or news-driven spikes
Very short timeframes (below 1-hour)
Illiquid or highly manipulated instruments
Parameter Configuration Strategy
Core Parameter Philosophy:
ATR Length (Default: 21 periods)
Controls the system's memory of volatility
Shorter lengths increase sensitivity but may cause overtrading
Longer lengths provide smoother signals but may lag during volatility shifts
ATR Multiplier (Default: 6.3x)
Determines the initial risk buffer
Lower values (4-5x) create tighter stops for conservative trading
Higher values (6-8x) allow for larger trends but increase drawdown risk
Volatility Threshold (Default: 1.5%)
Filters out low-quality trading environments
Adjust based on market characteristics (higher for volatile markets)
Acts as a quality control mechanism for signals
Trading Workflow and Execution
Signal Interpretation and Action:
Entry Protocol:
Wait for BLUE "BUY" signal label appearance
Confirm volatility conditions meet threshold requirements
Enter long position at market or next reasonable opportunity
Set initial stop at displayed dynamic stop level
Position Management:
Monitor dynamic stop line for position adjustment
Allow profits to run while stop protects capital
No manual adjustment required—system manages stop automatically
Exit Protocol:
Exit on ORANGE "SELL" signal label appearance
Alternative exit if price hits dynamic stop level
System will generate new entry signal if conditions warrant re-entry
Risk Management Integration:
Position sizing based on distance to dynamic stop
Volatility filter prevents trades during unfavorable conditions
Clear visual feedback on current risk exposure
Built-in protection against overtrading
Philosophical Foundation and Market Theory
Core Trading Principles
DATR-TS embodies several foundational market principles:
Volatility Defines Opportunity
Markets don't trend continuously—they alternate between trending and ranging phases
Volatility provides the energy for trends to develop and sustain
By measuring and filtering volatility, we can focus on high-probability trend phases
Risk Should Be Proportional
Fixed percentage stops ignore market context
Dynamic stops that adjust with volatility provide more appropriate risk management
Position sizing should reflect current market conditions, not arbitrary rules
Simplicity Through Sophistication
Complex systems often fail in real-world conditions
A simple core algorithm with intelligent filtering outperforms complex multi-indicator approaches
Clear visual feedback reduces cognitive load and emotional interference
Trends Persist Until Proven Otherwise
Markets exhibit momentum characteristics
Once a trend establishes itself, it tends to continue
The trailing stop methodology captures this persistence while providing exit mechanisms
Mathematical and Statistical Foundation
The system operates on several statistical market observations:
Volatility Clustering Phenomenon
High volatility periods tend to follow high volatility periods
Low volatility periods tend to follow low volatility periods
By filtering for adequate volatility, we increase the probability of capturing meaningful trends
Trend Magnitude Distribution
Most trends are small to medium in magnitude
Very large trends are rare but account for disproportionate returns
The dynamic stop methodology allows capture of varying trend magnitudes
Autocorrelation in Price Movements
Price movements exhibit short-term positive autocorrelation during trends
This persistence allows trailing stops to capture continued movement
The system leverages this characteristic without requiring explicit autocorrelation calculation
Performance Characteristics and Expectations
Typical System Behavior
Signal Frequency:
Low to moderate signal generation (prevents overtrading)
Signals concentrated during trending market phases
Extended periods without signals during ranging conditions
Risk-Reward Profile:
Win rate typically 40-60% in trending conditions
Average win larger than average loss
Risk-reward ratios of 1:2 to 1:3 achievable
Drawdown Patterns:
Controlled through volatility adjustment
Larger drawdowns during extended ranging periods
Recovery typically follows when trending conditions resume
Comparison with Alternative Approaches
Versus Moving Average Systems:
Less prone to whipsaws during ranging markets
Better adaptation to changing volatility conditions
Clearer exit signals through stop levels
Versus Channel Breakout Systems:
More responsive to emerging trends
Lower false breakout probability
Dynamic risk adjustment rather than fixed parameters
Versus Momentum Oscillator Systems:
Better trend persistence capture
Less susceptible to overbought/oversold false signals
Clearer position management rules
Educational Value and Skill Development
Learning Opportunities
DATR-TS serves as more than just a trading tool—it provides educational value through:
Market Condition Awareness
Teaches traders to distinguish between trending and ranging markets
Develops understanding of volatility's role in trading opportunities
Encourages patience and selectivity in trade execution
Risk Management Discipline
Demonstrates dynamic position sizing principles
Illustrates the importance of adaptive stops
Reinforces the concept of risk-adjusted returns
Psychological Skill Development
Reduces emotional trading through clear rules
Builds patience through conditional execution
Develops discipline through systematic approach
Customization and Evolution
The system provides a foundation for further development:
Beginner Level:
Use default parameters for initial learning
Focus on signal recognition and execution discipline
Develop understanding of system behavior across market conditions
Intermediate Level:
Adjust parameters based on specific market characteristics
Combine with complementary analysis techniques
Develop personal variations based on trading style
Advanced Level:
Integrate with portfolio management systems
Develop automated execution frameworks
Create derivative systems for specialized applications
Conclusion: The Modern Trend-Following Paradigm
The Dynamic ATR Trailing System represents a significant evolution in trend-following methodology. By moving beyond simple price pattern recognition or fixed parameter oscillators, it embraces the complex reality of financial markets where volatility, trend persistence, and risk management interact dynamically.
This system doesn't claim to predict market direction or identify tops and bottoms. Instead, it provides a systematic framework for participating in trends when they emerge, managing risk appropriately as conditions change, and preserving capital during unfavorable environments.
For traders seeking a methodology that combines mathematical rigor with practical execution, adapts to changing market conditions rather than fighting against them, and provides clear, actionable information without cognitive overload, DATR-TS offers a sophisticated yet accessible approach to modern trend following.
The true value lies not in any single signal or parameter setting, but in the comprehensive philosophy of volatility-aware, risk-adjusted, conditionally-executed trend participation that the system embodies—a philosophy that aligns with how markets actually behave rather than how we might wish them to behave.
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Smart Wedge Pattern [The_lurker]🔺 Smart Wedge Pattern نموذج الوتد الذكي
Advanced & Intelligent Wedge Detection Engine
This is not a traditional indicator that simply draws wedge lines — it is a comprehensive intelligent engine (system) for detecting and analyzing wedge patterns (Rising & Falling Wedge) based on price geometry, market context, and statistical quality of the pattern.
This indicator was designed to address the biggest problems in common wedge indicators:
❌ Too many false patterns
❌ Ignoring prior trend
❌ No real quality assessment for patterns
A comprehensive intelligent system that combines:
Adaptive algorithm that self-calibrates automatically according to market conditions
7 strict validation layers that filter out weak patterns and keep only the highest quality
Quality scoring system that evaluates each pattern from 0 to 100
3D visualization that makes patterns visually clear in an exceptional way
Smart targets based on Fibonacci ratios with real-time achievement tracking
The Result:
➡️ Fewer patterns
➡️ Cleaner, more accurate and reliable signals
➡️ Higher quality
➡️ Real practical use
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🎯 What Are Wedge Patterns?
1- Falling Wedge — Bullish Reversal Pattern
The falling wedge forms when price moves in a converging downward channel — meaning both the upper resistance line and the lower support line are declining, but the support line declines at a less steep angle, gradually narrowing the channel.
Why does the bullish breakout occur?
Declining highs show continuous selling pressure
But rising lows (P2 < P4) reveal that buyers are entering at higher levels
Convergence indicates decreasing bearish momentum
At a certain point, buying pressure overcomes and the breakout occurs
2- Rising Wedge — Bearish Reversal Pattern
The rising wedge is the exact opposite of the falling wedge — a converging upward channel where both lines rise, but the resistance line rises at a less steep angle.
Why does the bearish breakout occur?
Rising lows show continuous buying pressure
But declining highs (P2 > P4) reveal that sellers are entering at lower levels
Convergence indicates decreasing bullish momentum
At a certain point, selling pressure overcomes and the breakout occurs
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🧠 Adaptive Pivot System — The Heart of the Smart Indicator
The Problem with Traditional Indicators
Traditional indicators use a fixed value for pivot detection (like 5 bars left and 5 bars right). This means:
In quiet markets → Many delayed signals
In volatile markets → Few missed signals
No adaptation to the nature of each market or timeframe
The Solution: Smart Adaptation Algorithm
The indicator calculates optimal pivot sensitivity on each bar using 5 weighted factors:
Final Score = (Volatility_Score × 0.30) + (Trend_Score × 0.25) +
(Stability_Score × 0.20) + (Percentile_Context × 0.15) +
(Range_Score × 0.10)
Factor Weight How It's Calculated Why It's Important
Volatility Score 30% ATR(10) / ATR(50) Detects sudden changes in volatility
Trend Score 25% ADX(14) / 50 Trending markets need different sensitivity
Stability Score 20% StdDev(ATR) / Mean(ATR) Measures volatility consistency
Percentile Context 15% ATR / Percentile(ATR, 50) Places volatility in historical context
Range Score 10% Current_Range / Average_Range Detects unusual bars
The Result: The indicator uses low sensitivity (fewer, more important pivots) in quiet markets, and high sensitivity (more pivots, faster response) in volatile markets (more accurate pivots = correct geometric patterns).
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✅ Seven Validation Layers — Why This Indicator Is Different
Every detected pattern passes through 7 strict tests before being displayed:
1- Geometric Structure Validation
Validates:
P1 precedes P2 precedes P3 precedes P4 chronologically
Distance between each two points ≥ minimum threshold
Pattern width (P1→P4) within allowed range
Highs and lows order is correct for the wedge type
2- True Convergence Check
A true wedge must show convergence:
├── Gap at P4 < Gap at P1
├── Convergence ratio = End_Gap / Start_Gap
└── Ratio must be < defined convergence threshold (default 75%)
3- Slope Validation
For Falling Wedge:
├── Resistance line slope < 0 (declining)
├── Support line slope < 0 (declining)
└── Resistance slope < Support slope (convergence)
For Rising Wedge:
├── Resistance line slope > 0 (rising)
├── Support line slope > 0 (rising)
└── Support slope > Resistance slope (convergence)
4- Prior Trend Filter
Reversal patterns need a prior trend to reverse from:
├── Measures price movement during a defined period before P1
├── Normalizes movement using ATR for fair comparison
├── Falling wedge requires prior downtrend
└── Rising wedge requires prior uptrend
5- Channel Respect
Normal mode (close check):
└── Every close between P1 and P4 must be within wedge boundaries
Strict mode (high/low check):
├── Every high must be below resistance line (+ tolerance)
└── Every low must be above support line (- tolerance)
6- Post-P4 Validation
After the fourth point forms:
├── For falling wedge: Price doesn't break support or drop below P4
└── For rising wedge: Price doesn't break resistance or rise above P4
7- Quality Scoring System
Quality = (Convergence_Score × 0.30) + (Slope_Score × 0.25) +
(Width_Score × 0.20) + (Trend_Score × 0.15) +
(Height_Score × 0.10)
├── Convergence Score: More convergence = higher quality
├── Slope Score: Consistency of upper and lower line slopes
├── Width Score: Patterns with 40-100 bar width are ideal
├── Trend Score: Prior trend strength
└── Height Score: Pattern height relative to ATR
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✅ Pattern Lifecycle Management
The indicator doesn't just draw and disappear — it follows the complete pattern:
Pattern detection
Post-fourth point monitoring
Breakout confirmation
Target calculation
Target achievement tracking
Success or cancellation marking
❌ Pattern is automatically cancelled if:
Breakout fails
Channel is broken in reverse direction
Waiting period exceeded
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✅ Smart Targets + Success Level
After breakout:
Target is calculated based on pattern height
3 target modes:
Conservative (0.618)
Balanced (1.0)
Aggressive (1.618)
Independent Success level to measure move strength before target
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🎨 Advanced Visual Display (3D Visualization)
Three-dimensional pattern representation
Visual depth reflecting pattern size
3D target zone
Dynamic colors upon target achievement
🎨 The purpose of 3D is not decoration
But reading the pattern visually with speed and clarity
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⚙️ Key Features
✅ Automatic wedge detection
✅ Smart filtering reduces false signals
✅ Real quality assessment for each pattern
✅ Realistic and customizable targets
✅ Full support for Rising & Falling Wedge
✅ Works on all markets and timeframes
✅ Professional design and high performance
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📊 Usage Scenarios
🟢 Scalping
Timeframes: 1–15 minutes
Quality ≥ 60
Conservative targets
🔵 Day Trading
Timeframes: 15m–1h
Quality ≥ 50
Balanced targets
🟣 Swing Trading
Timeframes: 4h–Daily
Quality ≥ 40
Strict channel
Aggressive targets
🟠 Cryptocurrencies
Strict convergence
Strict channel
Quality ≥ 65
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🔔 Alerts
Falling wedge breakout ⇒ Buy
Rising wedge breakout ⇒ Sell
Any wedge breakout
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⚠️ Disclaimer
This indicator is for educational and analytical purposes only. It does not represent financial, investment, or trading advice. Use it in conjunction with your own strategy and risk management. Neither TradingView nor the developer is responsible for any financial decisions or losses.
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🔺 Smart Wedge Pattern نموذج الوتد الذكي
Advanced & Intelligent Wedge Detection Engine
ليس مؤشرًا تقليديًا يرسم خطوط وتد فقط ، بل هو محرك (نظام) ذكي متكامل لاكتشاف وتحليل نماذج الوتد (Rising & Falling Wedge) اعتمادًا على الهندسة السعرية ، السياق السوقي ، والجودة الإحصائية للنموذج.
تم تصميم هذا المؤشر لمعالجة أكبر مشكلة في مؤشرات الوتد الشائعة:
❌ كثرة النماذج الوهمية
❌ تجاهل الاتجاه السابق
❌ عدم وجود تقييم حقيقي لجودة النموذج
نظام ذكي متكامل يجمع بين:
خوارزمية تكيفية تُعاير نفسها تلقائياً حسب ظروف السوق
7 طبقات تحقق صارمة تُصفّي الأنماط الضعيفة وتُبقي فقط الأعلى جودة
نظام تسجيل جودة يُقيّم كل نموذج من 0 إلى 100
تصور ثلاثي الأبعاد يجعل الأنماط واضحة بصرياً بشكل استثنائي
أهداف ذكية مبنية على نسب فيبوناتشي مع تتبع التحقق الآني
النتيجة:
➡️ نماذج أقل
➡️ إشارات أنظف أكثر دقة وموثوقية
➡️ جودة أعلى
➡️ استخدام عملي حقيقي
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🎯 ما هي نماذج الأوتاد؟
1- الوتد الهابط (Falling Wedge) — نموذج انعكاسي صعودي
الوتد الهابط يتشكل عندما يتحرك السعر في قناة هابطة متقاربة — أي أن خط المقاومة العلوي وخط الدعم السفلي كلاهما يهبطان، لكن خط الدعم يهبط بزاوية أقل حدة، مما يُضيّق القناة تدريجياً.
لماذا يحدث الكسر الصعودي؟
القمم الهابطة تُظهر ضغطاً بيعياً مستمراً
لكن القيعان الصاعدة (P2 < P4) تكشف أن المشترين يدخلون عند مستويات أعلى
التقارب يُشير إلى تناقص الزخم الهبوطي
عند نقطة معينة، يتغلب ضغط الشراء ويحدث الكسر
2- الوتد الصاعد (Rising Wedge) — نموذج انعكاسي هبوطي
الوتد الصاعد هو عكس الهابط تماماً — قناة صاعدة متقاربة حيث يصعد كلا الخطين، لكن خط المقاومة يصعد بزاوية أقل حدة.
لماذا يحدث الكسر الهبوطي؟
القيعان الصاعدة تُظهر ضغطاً شرائياً مستمراً
لكن القمم الهابطة (P2 > P4) تكشف أن البائعين يدخلون عند مستويات أدنى
التقارب يُشير إلى تناقص الزخم الصعودي
عند نقطة معينة، يتغلب ضغط البيع ويحدث الكسر
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🧠 نظام المحاور التكيفي — قلب المؤشر الذكي
المشكلة مع المؤشرات التقليدية
المؤشرات التقليدية تستخدم قيمة ثابتة لاكتشاف المحاور (مثل 5 شموع يسار و5 شموع يمين). هذا يعني:
في الأسواق الهادئة → إشارات كثيرة ومتأخرة
في الأسواق المتقلبة → إشارات قليلة وضائعة
لا تكيف مع طبيعة كل سوق أو إطار زمني
الحل: خوارزمية التكيف الذكي
المؤشر يحسب حساسية المحور المثلى في كل شمعة باستخدام 5 عوامل مرجحة:
النتيجة النهائية = (درجة_التقلب × 0.30) + (درجة_الاتجاه × 0.25) +
(درجة_الاستقرار × 0.20) + (السياق_المئوي × 0.15) +
(درجة_النطاق × 0.10)
العامل الوزن كيف يُحسب لماذا مهم
درجة التقلب 30% ATR(10) / ATR(50) يكشف التغير المفاجئ في التقلب
درجة الاتجاه 25% ADX(14) / 50 الأسواق الاتجاهية تحتاج حساسية مختلفة
درجة الاستقرار 20% StdDev(ATR) / Mean(ATR) يقيس ثبات التقلب
السياق المئوي 15% ATR / Percentile(ATR, 50) يضع التقلب في سياقه التاريخي
درجة النطاق 10% النطاق_الحالي / متوسط_النطاق يكشف الشموع غير العادية
النتيجة: المؤشر يستخدم حساسية منخفضة (محاور أقل، أكثر أهمية) في الأسواق الهادئة، وحساسية عالية (محاور أكثر، استجابة أسرع) في الأسواق المتقلبة (محاور أدق = نماذج هندسية صحيحة).
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✅ طبقات التحقق السبع — لماذا هذا المؤشر مختلف
كل نموذج مُكتشف يمر عبر 7 اختبارات صارمة قبل عرضه:
1- التحقق من البنية الهندسية
يتحقق من:
P1 يسبق P2 يسبق P3 يسبق P4 زمنياً
المسافة بين كل نقطتين ≥ الحد الأدنى المحدد
عرض النموذج (P1→P4) ضمن النطاق المسموح
ترتيب القمم والقيعان صحيح حسب نوع الوتد
2- فحص التقارب الحقيقي
الوتد الحقيقي يجب أن يُظهر تقارباً:
├── الفجوة عند P4 < الفجوة عند P1
├── نسبة التقارب = الفجوة_النهائية / الفجوة_الابتدائية
└── النسبة يجب أن تكون < عتبة التقارب المحددة (افتراضي 75%)
3- التحقق من الميل
للوتد الهابط:
├── ميل خط المقاومة < 0 (هابط)
├── ميل خط الدعم < 0 (هابط)
└── ميل المقاومة < ميل الدعم (تقارب)
للوتد الصاعد:
├── ميل خط المقاومة > 0 (صاعد)
├── ميل خط الدعم > 0 (صاعد)
└── ميل الدعم > ميل المقاومة (تقارب)
4- فلتر الاتجاه السابق
النماذج الانعكاسية تحتاج اتجاهاً سابقاً لتنعكس منه:
├── يقيس حركة السعر خلال فترة محددة قبل P1
├── يُطبّع الحركة باستخدام ATR لمقارنة عادلة
├── الوتد الهابط يحتاج اتجاهاً هابطاً سابقاً
└── الوتد الصاعد يحتاج اتجاهاً صاعداً سابقاً
5- احترام القناة
وضع عادي (فحص الإغلاق):
└── كل إغلاق بين P1 و P4 يجب أن يكون داخل حدود الوتد
وضع صارم (فحص القمة/القاع):
├── كل قمة يجب أن تكون تحت خط المقاومة (+ نسبة تسامح)
└── كل قاع يجب أن يكون فوق خط الدعم (- نسبة تسامح)
6- التحقق بعد P4
بعد تشكل النقطة الرابعة:
├── للوتد الهابط: السعر لا يكسر خط الدعم أو ينزل تحت P4
└── للوتد الصاعد: السعر لا يكسر خط المقاومة أو يصعد فوق P4
7- نظام تسجيل الجودة
الجودة = (درجة_التقارب × 0.30) + (درجة_الميل × 0.25) +
(درجة_العرض × 0.20) + (درجة_الاتجاه × 0.15) +
(درجة_الارتفاع × 0.10)
├── درجة التقارب: كلما زاد التقارب، زادت الجودة
├── درجة الميل: تناسق ميل الخطين العلوي والسفلي
├── درجة العرض: الأنماط بعرض 40-100 شمعة مثالية
├── درجة الاتجاه: قوة الاتجاه السابق
└── درجة الارتفاع: ارتفاع النموذج نسبة لـ ATR
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✅ إدارة دورة حياة النموذج (Pattern Lifecycle)
المؤشر لا يرسم ثم يختفي، بل يتابع النموذج كاملًا:
اكتشاف النموذج
مراقبة ما بعد النقطة الرابعة
تأكيد الاختراق
حساب الهدف
تتبع الوصول للهدف
تمييز النجاح أو الإلغاء
❌ يتم إلغاء النموذج تلقائيًا إذا:
فشل في الاختراق
كُسرت القناة عكسيًا
تجاوز مدة الانتظار المحددة
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✅ أهداف ذكية + Success Level
بعد الاختراق:
يتم حساب الهدف بناءً على ارتفاع النموذج
3 أوضاع للأهداف:
Conservative (0.618)
Balanced (1.0)
Aggressive (1.618)
مستوى Success مستقل لقياس قوة الحركة قبل الهدف
═════════════════════════════════════════════════════════════
🎨 عرض بصري متقدم (3D Visualization)
تمثيل ثلاثي الأبعاد للنموذج
عمق بصري يعكس حجم النموذج
منطقة هدف ثلاثية الأبعاد
ألوان ديناميكية عند تحقق الهدف
🎨 الهدف من 3D ليس الزينة
بل قراءة النموذج بصريًا بسرعة ووضوح
═════════════════════════════════════════════════════════════
⚙️ أهم المميزات
✅ اكتشاف تلقائي للأوتاد
✅ فلترة ذكية تقلل الإشارات الوهمية
✅ تقييم جودة حقيقي لكل نموذج
✅ أهداف واقعية وقابلة للتخصيص
✅ دعم كامل لـ Rising & Falling Wedge
✅ يعمل على جميع الأسواق والفريمات
✅ تصميم احترافي وأداء عالي
═════════════════════════════════════════════════════════════
📊 سيناريوهات الاستخدام
🟢 المضاربة السريعة
أطر: 1–15 دقيقة
جودة ≥ 60
أهداف محافظة
🔵 التداول اليومي
أطر: 15د–1س
جودة ≥ 50
أهداف متوازنة
🟣 التداول المتأرجح
أطر: 4س–يومي
جودة ≥ 40
قناة صارمة
أهداف عدوانية
🟠 العملات الرقمية
تقارب صارم
قناة صارمة
جودة ≥ 65
═════════════════════════════════════════════════════════════
🔔 التنبيهات
كسر وتد هابط ⇒ شراء
كسر وتد صاعد ⇒ بيع
أي كسر وتد
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⚠️ إخلاء المسؤولية
هذا المؤشر لأغراض تعليمية وتحليلية فقط. لا يُمثل نصيحة مالية أو استثمارية أو تداولية. استخدمه بالتزامن مع استراتيجيتك الخاصة وإدارة المخاطر. لا يتحمل TradingView ولا المطور مسؤولية أي قرارات مالية أو خسائر.
RSI Trend Authority [JOAT]RSI Trend Authority - VAR-RSI with OTT Trend Detection System
Introduction
RSI Trend Authority is an open-source overlay indicator that combines Variable Index Dynamic Average (VAR) smoothed RSI with the Optimized Trend Tracker (OTT) to create a complete trend detection and signal generation system. Unlike traditional RSI which oscillates in a separate pane, this indicator scales the RSI to price and overlays it directly on your chart, making trend analysis more intuitive.
The indicator generates clear BUY and SELL signals when the smoothed RSI crosses the OTT trailing stop line, providing actionable entry points with trend confirmation.
Originality and Purpose
This indicator is NOT a simple mashup of RSI and moving averages. It is an original implementation that transforms RSI into a trend-following overlay system:
Why VAR Smoothing? Traditional RSI is noisy and produces many false signals. The Variable Index Dynamic Average (VAR) is an adaptive smoothing algorithm based on the Chande Momentum Oscillator principle. It adjusts its smoothing factor based on market conditions - responding quickly during trends and smoothing out during choppy markets. This creates an RSI that filters noise while preserving genuine momentum shifts.
Why OTT Trailing Stop? The Optimized Trend Tracker (OTT) is a percentage-based trailing stop mechanism that only moves in the direction of the trend. When VAR-RSI crosses above OTT, a bullish trend is confirmed; when it crosses below, a bearish trend is confirmed. This provides clear, actionable signals rather than subjective interpretation.
Price Scaling Innovation: By scaling RSI (0-100) to price using the formula (RSI * close / 50), the indicator overlays directly on the price chart. This allows traders to see how momentum relates to actual price levels, making trend analysis more intuitive than a separate oscillator pane.
ATR Boundaries: Optional volatility-based boundaries show when price is extended relative to its normal range, helping identify potential reversal zones.
How the components work together:
VAR smoothing removes RSI noise while preserving trend information
OTT provides a dynamic trailing stop that generates clear crossover signals
Price scaling allows direct overlay on the chart for intuitive analysis
ATR boundaries add volatility context for profit target estimation
Core Components
1. VAR-RSI (Variable Index Dynamic Average RSI)
The foundation of this indicator is the VAR smoothing algorithm applied to RSI. VAR is an adaptive moving average that adjusts its smoothing factor based on the Chande Momentum Oscillator principle:
f_var_calc(float data, int length) =>
int a = 9
float b = data > nz(data ) ? data - nz(data ) : 0.0
float c = data < nz(data ) ? nz(data ) - data : 0.0
float d = math.sum(b, a)
float e = math.sum(c, a)
float f = nz((d - e) / (d + e))
float g = math.abs(f)
float h = 2.0 / (length + 1)
float x = ta.sma(data, length)
This creates an RSI that:
Responds quickly during trending conditions
Smooths out during choppy, sideways markets
Reduces false signals compared to raw RSI
2. OTT (Optimized Trend Tracker)
The OTT acts as a dynamic trailing stop that follows the VAR-RSI:
In uptrends, OTT trails below the VAR-RSI line
In downtrends, OTT trails above the VAR-RSI line
The OTT Percent parameter controls how closely it follows
When VAR-RSI crosses above OTT, a bullish trend is confirmed. When VAR-RSI crosses below OTT, a bearish trend is confirmed.
3. Price Scaling
The RSI (0-100 scale) is converted to price scale using:
float scaleFactor = close / 50.0
float varRSIScaled = varRSI * scaleFactor
This allows the indicator to overlay directly on price, showing how momentum relates to actual price levels.
Visual Components
VAR-RSI Line (Cyan/Magenta)
The main indicator line with gradient coloring:
Cyan gradient when RSI is above 50 (bullish)
Magenta gradient when RSI is below 50 (bearish)
Line thickness of 3 for clear visibility
OTT Line (Yellow Circles)
The trailing stop line displayed as circles:
Acts as dynamic support in uptrends
Acts as dynamic resistance in downtrends
Crossovers generate trading signals
Trend Fill
The area between VAR-RSI and OTT is filled:
Cyan fill during bullish trends
Magenta fill during bearish trends
Fill transparency allows price visibility
Buy position and LONG on Dashboard with a Uptrend:
ATR Boundaries (Optional)
Dotted lines showing volatility-based price boundaries:
Upper band: Close + (ATR x Multiplier)
Lower band: Close - (ATR x Multiplier)
Color matches current trend direction
Buy/Sell Signals
Clear labels appear at signal points:
BUY label below bar when VAR-RSI crosses above OTT
SELL label above bar when VAR-RSI crosses below OTT
Additional glow circles highlight signal bars
Bar Coloring
Optional feature that colors price bars:
Cyan bars during bullish trend
Magenta bars during bearish trend
Dashboard Panel
The 8-row dashboard provides comprehensive status information:
Signal: Current position - LONG or SHORT (large text)
VAR-RSI: Current smoothed RSI value (large text)
RSI State: OVERBOUGHT, OVERSOLD, BULLISH, or BEARISH
OTT Trend: UPTREND or DOWNTREND based on OTT direction
Bars Since: Number of bars since last signal
Price: Current close price (large text)
OTT Level: Current OTT trailing stop value
Input Parameters
RSI Settings:
RSI Length: Period for RSI calculation (default: 100)
Source: Price source (default: close)
VAR Settings:
VAR Length: Adaptive smoothing period (default: 50)
OTT Settings:
OTT Period: Trailing stop calculation period (default: 30)
OTT Percent: Distance percentage for trailing stop (default: 0.2)
ATR Trend Boundaries:
Show ATR Boundaries: Toggle visibility (default: enabled)
ATR Length: Period for ATR calculation (default: 14)
ATR Multiplier: Distance multiplier (default: 2.0)
Display Options:
Show Buy/Sell Signals: Toggle signal labels (default: enabled)
Show Status Table: Toggle dashboard (default: enabled)
Table Position: Choose corner placement
Color Bars by Trend: Toggle bar coloring (default: enabled)
Color Scheme:
Bullish Color: Main bullish color (default: cyan)
Bearish Color: Main bearish color (default: magenta)
OTT Line: Trailing stop color (default: yellow)
VAR-RSI Line: Main line color (default: teal)
ATR colors for boundaries
How to Use RSI Trend Authority
Signal-Based Trading:
Enter LONG when BUY signal appears (VAR-RSI crosses above OTT)
Enter SHORT when SELL signal appears (VAR-RSI crosses below OTT)
Use the OTT line as a trailing stop reference
Trend Confirmation:
Cyan fill indicates bullish trend - favor long positions
Magenta fill indicates bearish trend - favor short positions
Check RSI State in dashboard for momentum context
Using the Dashboard:
Monitor "Bars Since" to assess signal freshness
Check RSI State for overbought/oversold warnings
Use OTT Level as a reference for stop placement
ATR Boundaries:
Price near upper ATR band in uptrend suggests extension
Price near lower ATR band in downtrend suggests extension
Boundaries help identify potential reversal zones
Parameter Optimization
For Faster Signals:
Decrease RSI Length (try 50-80)
Decrease VAR Length (try 30-40)
Decrease OTT Period (try 15-25)
For Smoother Signals:
Increase RSI Length (try 120-150)
Increase VAR Length (try 60-80)
Increase OTT Period (try 40-50)
For Tighter Stops:
Decrease OTT Percent (try 0.1-0.15)
For Wider Stops:
Increase OTT Percent (try 0.3-0.5)
Alert Conditions
Three alert conditions are available:
Buy Signal: VAR-RSI crosses above OTT
Sell Signal: VAR-RSI crosses below OTT
Trend Change: OTT direction changes
Understanding the OTT Calculation
The OTT uses a percentage-based trailing mechanism:
float farkOTT = mavgOTT * ottPercent * 0.01
float longStopCalc = mavgOTT - farkOTT
float shortStopCalc = mavgOTT + farkOTT
longStop := mavgOTT > nz(longStop ) ? math.max(longStopCalc, nz(longStop )) : longStopCalc
shortStop := mavgOTT < nz(shortStop ) ? math.min(shortStopCalc, nz(shortStop )) : shortStopCalc
This ensures the trailing stop only moves in the direction of the trend, never against it.
Best Practices
Use on 1H timeframe or higher for more reliable signals
Wait for signal confirmation before entering trades
Consider RSI State when evaluating signal quality
Use ATR boundaries for profit target estimation
The longer RSI length (100) provides smoother trend detection
Combine with support/resistance analysis for better entries
Limitations
Signals may lag during rapid price movements due to smoothing
Works best in trending markets; may whipsaw in ranges
The overlay nature means RSI values are scaled, not absolute
Default parameters are optimized for crypto and forex; adjust for other markets
Technical Notes
This indicator is written in Pine Script v6 and uses:
VAR (Variable Index Dynamic Average) for adaptive smoothing
OTT (Optimized Trend Tracker) for trailing stop calculation
ATR for volatility-based boundaries
Gradient coloring for intuitive trend visualization
The source code is open and available for review and modification.
Disclaimer
This indicator is provided for educational and informational purposes only. It is not financial advice. Trading involves substantial risk of loss. Past performance does not guarantee future results. Always conduct your own analysis and use proper risk management.
-Made with passion by officialjackofalltrades
Smart Money Flow Oscillator [MarkitTick]💡This script introduces a sophisticated method for analyzing market liquidity and institutional order flow. Unlike traditional volume indicators that treat all market activity equally, the Smart Money Flow Oscillator (SMFO) employs a Logic Flow Architecture (LFA) to filter out market noise and "churn," focusing exclusively on high-impact, high-efficiency price movements. By synthesizing price action, volume, and relative efficiency, this tool aims to visualize the accumulation and distribution activities that are often attributed to "smart money" participants.
✨ Originality and Utility
Standard indicators like On-Balance Volume (OBV) or Money Flow Index (MFI) often suffer from noise because they aggregate volume based simply on the close price relative to the previous close, regardless of the quality of the move. This script differentiates itself by introducing an "Efficiency Multiplier" and a "Momentum Threshold." It only registers volume flow when a price move is considered statistically significant and structurally efficient. This creates a cleaner signal that highlights genuine supply and demand imbalances while ignoring indecisive trading ranges. It combines the trend-following nature of cumulative delta with the mean-reverting insights of an In/Out ratio, offering a dual-mode perspective on market dynamics.
🔬 Methodology
The underlying calculation of the SMFO relies on several distinct quantitative layers:
• Efficiency Analysis
The script calculates a "Relative Efficiency" ratio for every candle. This compares the current price displacement (body size) per unit of volume against the historical average.
If price moves significantly with relatively low volume, or proportional volume, it is deemed "efficient."
If significant volume occurs with little price movement (churn/absorption), the efficiency score drops.
This score is clamped between a user-defined minimum and maximum (Efficiency Cap) to prevent outliers from distorting the data.
• Momentum Thresholding
Before adding any data to the flow, the script checks if the current price change exceeds a volatility threshold derived from the previous candle's open-close range. This acts as a gatekeeper, ensuring that only "strong" moves contribute to the oscillator.
• Variable Flow Calculation
If a move passes the threshold, the script calculates the flow value by multiplying the Typical Price and Volume (Money Flow) by the calculated Efficiency Multiplier.
Bullish Flow: Strong upward movement adds to the positive delta.
Bearish Flow: Strong downward movement adds to the negative delta.
Neutral: Bars that fail the momentum threshold contribute zero flow, effectively flattening the line during consolidation.
• Calculation Modes
Cumulative Delta Flow (CDF): Sums the flow values over a rolling period. This creates a trend-following oscillator similar to OBV but smoother and more responsive to real momentum.
In/Out Ratio: Calculates the percentage of bullish inflow relative to the total absolute flow over the period. This oscillates between 0 and 100, useful for identifying overextended conditions.
📖 How to Use
Traders can utilize this oscillator to identify trend strength and potential reversals through the following signals:
• Signal Line Crossovers
The indicator plots the main Flow line (colored gradient) and a Signal line (grey).
Bullish (Green Cloud): When the Flow line crosses above the Signal line, it suggests rising buying pressure and efficient upward movement.
Bearish (Red Cloud): When the Flow line crosses below the Signal line, it suggests dominating selling pressure.
• Divergences
The script automatically detects and plots divergences between price and the oscillator:
Regular Divergence (Solid Lines): Suggests a potential trend reversal (e.g., Price makes a Lower Low while Oscillator makes a Higher Low).
Hidden Divergence (Dashed Lines): Suggests a potential trend continuation (e.g., Price makes a Higher Low while Oscillator makes a Lower Low).
"R" labels denote Regular, and "H" labels denote Hidden divergences.
• Dashboard
A dashboard table is displayed on the chart, providing real-time metrics including the current Efficiency Multiplier, Net Flow value, and the active mode status.
• In/Out Ratio Levels
When using the Ratio mode:
Values above 50 indicate net buying pressure.
Values below 50 indicate net selling pressure.
Approaching 70 or 30 can indicate overbought or oversold conditions involving volume exhaustion.
⚙️ Inputs and Settings
Calculation Mode: Choose between "Cumulative Delta Flow" (Trend focus) or "In/Out Ratio" (Oscillator focus).
Auto-Adjust Period: If enabled, automatically sets the lookback period based on the chart timeframe (e.g., 21 for Daily, 52 for Weekly).
Manual Period: The rolling lookback length for calculations if Auto-Adjust is disabled.
Efficiency Length: The period used to calculate the average body and volume for the efficiency baseline.
Eff. Min/Max Cap: Limits the impact of the efficiency multiplier to prevent extreme skewing during anomaly candles.
Momentum Threshold: A factor determining how much price must move relative to the previous candle to be considered a "strong" move.
Show Dashboard/Divergences: Toggles for visual elements.
🔍 Deconstruction of the Underlying Scientific and Academic Framework
This indicator represents a hybrid synthesis of academic Market Microstructure theory and classical technical analysis. It utilizes an advanced algorithm to quantify "Price Impact," leveraging the following theoretical frameworks:
• 1. The Amihud Illiquidity Ratio (2002)
The core logic (calculating body / volume) functions as a dynamic implementation of Yakov Amihud’s Illiquidity Ratio. It measures price displacement per unit of volume. A high efficiency score indicates that "Smart Money" has moved the price significantly with minimal resistance, effectively highlighting liquidity gaps or institutional control.
• 2. Kyle’s Lambda (1985) & Market Depth
Drawing from Albert Kyle’s research on market microstructure, the indicator approximates Kyle's Lambda to measure the elasticity of price in response to order flow. By analyzing the "efficiency" of a move, it identifies asymmetries—specifically where price reacts disproportionately to low volume—signaling potential manipulation or specific Market Maker activity.
• 3. Wyckoff’s Law of Effort vs. Result
From a classical perspective, the algorithm codifies Richard Wyckoff’s "Effort vs. Result" logic. It acts as an oscillator that detects anomalies where "Effort" (Volume) diverges from the "Result" (Price Range), predicting potential reversals.
• 4. Quantitative Advantage: Efficiency-Weighted Volume
Unlike linear indicators such as OBV or Chaikin Money Flow—which treat all volume equally—this indicator (LFA) utilizes Efficiency-Weighted Volume. By applying the efficiency_mult factor, the algorithm filters out market noise and assigns higher weight to volume that drives structural price changes, adopting a modern quantitative approach to flow analysis.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Predictive ZLEMA NavigatorThis is an advanced trend-following indicator that combines Zero-Lag Exponential Moving Averages (ZLEMA) with predictive crossover analysis to identify high-probability trade entries with exceptional timing precision.
Key Features:
1. Zero-Lag Technology
Utilizes ZLEMA calculation to eliminate the inherent lag found in traditional EMAs
Provides faster response to price movements while maintaining smooth trend identification
Default periods (34/89) align with Fibonacci sequence for natural market rhythm detection
2. Predictive Crossover System
Unique algorithm forecasts upcoming Golden Cross and Death Cross events before they occur
Displays estimated bars until next crossover, giving traders advance preparation time
Helps avoid late entries by signaling trend changes up to 200 bars in advance
3. Visual Direction Arrows
Color-coded projection arrows show the momentum trajectory of both fast and slow ZLEMAs
Adjustable projection length allows customization for different trading timeframes
Instantly identifies whether trends are strengthening or weakening
4. Multi-Layer Signal Confirmation
Clear crossover points marked with circles and confirmation ticks
Dynamic fill coloring between MAs for instant trend bias recognition
Bullish signals (green/blue) and bearish signals (orange/red) prevent confusion
Performance Characteristics:
Strengths:
Reduced Whipsaws: ZLEMA's lag reduction minimizes false signals in ranging markets
Early Detection: Predictive algorithm provides 10-50 bar advance warning of trend changes
Versatile Application: Works across all timeframes (1-minute to daily) and asset classes
Visual Clarity: Clean interface prevents information overload while maintaining comprehensive data
Optimal Use Cases:
Swing trading on 4H-Daily timeframes
Trend confirmation for breakout strategies
Portfolio rotation timing based on momentum shifts
Works exceptionally well on trending assets (crypto, indices, trending stocks)
Trading Approach:
Enter long on Golden Cross confirmation with upward direction arrows
Exit or reverse on Death Cross with downward momentum projection
Use prediction labels to scale into positions before actual crossover
Combine with volume analysis for enhanced confirmation
Built-in Alert System: Automated notifications for both bullish and bearish crossovers ensure you never miss a trading opportunity.
This indicator bridges the gap between reactive and predictive trading, giving you the speed of ZLEMA with the foresight of trend projection analysis.
DISCLAIMER: This information is provided for educational purposes only and should not be considered financial, investment, or trading advice.Happy Trading
RSI Apex: Breakout & DivergenceRSI Apex: Breakout & Divergence System
RSI Apex：突破与背离交易系统
🇬🇧 English Description
RSI Apex is a comprehensive trading system designed to capture both Trend Breakouts and Market Reversals. Unlike traditional RSI indicators that rely solely on fixed levels (70/30), RSI Apex integrates Donchian Channels, Volatility Squeeze, and the Libertus Divergence Algorithm to provide high-probability signals.
🚀 Key Features
Trend Push System (Donchian Breakout):
Detects when RSI momentum is strong enough to push the upper/lower Donchian Channel bands.
Signal: Displays ▲ (Bull) or ▼ (Bear) at levels 20/80.
Libertus Divergence (No-Lag):
Uses a real-time pivot tracking algorithm to identify divergences between Price and RSI without the lag of traditional pivot points.
Signal: Displays "Div" labels at levels 30/70.
Smart Coloring (Extreme Highlight):
Green/Red: Normal Trend.
White (Extreme): When RSI breaches 70 (Overbought) or 30 (Oversold), the line turns bright White. This highlights the most volatile zones where reversals or strong continuations occur.
Volatility Squeeze Filter:
Monitors market volatility. When the Donchian Channel compresses significantly (below historical average), the background turns Purple.
Meaning: "Calm before the storm"—expect a major move soon.
🛠 How to Use
Trend Following: Enter when you see Green/Red RSI lines accompanied by ▲ / ▼ signals. This indicates a "Trend Push."
Reversal Trading: Look for "Div" signals when the RSI line is White (Extreme). This suggests momentum is fading despite price action.
Exit/Take Profit: Watch for the "Weak" label, which appears when RSI falls back into the neutral zone.
Dashboard: Monitor real-time RSI Value, Market State (Bullish/Bearish/Extreme), and Volatility (Squeeze/Expanding) in the bottom-right table.
🇨🇳 中文简介
RSI Apex 是一套旨在捕捉趋势爆发 (Breakout) 和 市场反转 (Reversal) 的综合交易系统。与仅依赖固定 70/30 线的传统 RSI 不同，本指标融合了 唐奇安通道 (Donchian Channels)、波动率挤压 (Squeeze) 以及 Libertus 无滞后背离算法，以提供高胜率的交易信号。
🚀 核心功能
强趋势推动系统 (唐奇安突破):
检测 RSI 动能是否强劲到足以推动唐奇安通道的上轨或下轨扩张。
信号: 在 20/80 轴位置显示 ▲ (多头推动) 或 ▼ (空头推动)。
Libertus 智能背离 (无滞后):
采用实时 Pivot 追踪算法，精准识别价格与 RSI 之间的背离，解决了传统背离指标的滞后问题。
信号: 在 30/70 轴位置显示 "Div" 标签。
智能变色 (极端行情高亮):
绿色/红色: 正常趋势状态。
白色 (White): 极端区域。当 RSI 突破 70 (超买) 或跌破 30 (超卖) 时，线条会强制变为醒目的亮白色，提示此处为变盘/背离高发区。
波动率挤压 (Squeeze) 过滤器:
实时监控市场波动率。当通道宽度显著收窄（低于历史平均水平）时，背景会填充为半透明紫色。
含义: “暴风雨前的宁静”——预示着大行情即将爆发，此时应空仓等待突破方向。
🛠 使用策略
顺势交易 (Trend): 当 RSI 呈现 绿色/红色 并伴随 ▲ / ▼ 信号时进场。这代表动能极强，处于主升/主跌浪。
左侧反转 (Reversal): 重点关注 RSI 线条变为 白色 (Extreme) 时出现的 "Div" 背离信号。这通常意味着价格虽创新高，但动能已耗尽。
止盈/离场: 留意 "Weak" (衰竭) 标签，它出现在 RSI 掉回中间震荡区时。
仪表盘: 右下角面板实时显示 RSI 数值、市场状态 (极值/背离/趋势) 以及波动率状态 (挤压/扩张)。
Planetary Retrograde Periods█ PLANETARY RETROGRADE PERIODS
Visualize when planets appear to move backward through the zodiac. This indicator detects and displays retrograde motion for all 8 planets that exhibit apparent retrograde motion from Earth's perspective: Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto.
Powered by the BlueprintResearch lib_ephemeris library.
█ FEATURES
• 8 Planets Supported — Mercury, Venus, Mars, Jupiter, Saturn, Uranus, Neptune, and Pluto
• Two-Phase Visualization — Distinguishes first half (speed increasing in retrograde direction) from second half (speed decreasing toward direct motion) with different transparency levels
• Future Projections — Projects upcoming retrograde periods up to 500 bars ahead on any timeframe
• Station Markers — Clear labels for Station Retrograde (℞), Midpoint (½), and Station Direct (D)
• Timezone-Aware Labels — Future date/time labels display in your selected timezone
• Alert Conditions — Set alerts for station retrograde, station direct, or any station point
• Per-Planet Colors — Customize colors for each planet individually
• Speed-Based Detection — More accurate than longitude-based methods
█ HOW TO USE
1. Select a Planet — Choose which planet to track from the dropdown (Mercury through Pluto)
2. Enable Two-Phase Display — Toggle "Show Retrograde Halves" to see first half vs. second half shading
3. Configure Future Projections — Set how many bars ahead to scan (1-500) and enable/disable date labels
4. Set Your Timezone — Choose your timezone for accurate future date/time display
5. Customize Colors — Adjust planet colors, transparency levels, and label text color to match your chart theme
6. Create Alerts — Use TradingView's alert system with the built-in conditions for station points
█ UNDERSTANDING THE DISPLAY
Background Colors:
• First Half of the Planet’s retrograde (lighter shade)
• Second Half of the Planet’s retrograde period (darker shade)
Future Projection Lines:
• ℞ (Station Retrograde) — Yellow dotted line marking when the planet will station retrograde
• ½ (Midpoint) — Shorter line in planet color marking the halfway point of the retrograde period
• D (Station Direct) — Green dotted line marking when the planet will station direct
Labels:
• Top label shows planet symbol and station type
• Bottom label shows projected date and time (optional)
█ ACCURACY
This indicator uses speed-based detection
Timing Accuracy:
• All planets (Mercury through Pluto): Within hours to ±1 day
• Future projections maintain accuracy up to 500 bars on any timeframe
• Spot tested on Daily and Weekly charts with excellent results
For Critical Applications:
Cross-reference with professional ephemeris tools such as JPL Horizons or Swiss Ephemeris for mission-critical timing.
█ TECHNICAL DETAILS
Theory: VSOP87 (Mercury through Neptune), Meeus algorithms (Pluto)
█ REFERENCES
• Meeus, Jean. "Astronomical Algorithms" (2nd Edition, 1998)
• Bretagnon & Francou. "VSOP87 Solutions" — Astronomy and Astrophysics 202 (1988)
Auction Session Ranges (AMT Edition) [ Alerts] Auction Session Ranges (AMT Edition)
► Overview
The Session Ranges ( AMT Edition) is a session-based market structure and auction analysis tool designed to visually reveal acceptance, rejection, imbalance, and continuation across the Asia, London, and New York CME trading sessions.
Unlike typical indicators, this script is grounded in Auction Market Theory (AMT) and session-based structure, focusing on how price behaves at session extremes rather than relying on lagging calculations, oscillators, or predictive algorithms. Its purpose is to highlight areas where the market has earned the right to be traded, providing traders with a clear, rules-based framework for high-probability directional trades.
Important for backtesting: To properly backtest session extremes, Interaction Lines, and Closest Opposite Extreme Lines, you must use TradingView’s replay mode, as real-time bar-by-bar progression is required to observe how the market interacts with session extremes over time.
► Key Innovations
This is not a conventional session high/low indicator. Its originality comes from several unique design elements:
Differentiates interaction from true acceptance: Price touching an extreme does not automatically indicate directional intent.
Separates directional confirmation from range-bound indecision: Only confirmed crossings beyond the Interaction Line signal actionable bias.
Tracks failed auctions and partial acceptance: No volume profile or order book data required.
Visual, rule-based trade permission: Signals are objective, minimizing subjective interpretation.
Interaction & Closest Opposite Extreme Lines: Together, these lines map how far an auction progresses after an extreme is tested, highlighting continuation, partial acceptance, or failed auctions.
► Core Concepts Explained
1. Session Highs & Lows (Solid Lines)
Plotted continuously for each CME session (Asia, London, New York).
Represent the current auction boundaries for that session.
2. True Interaction Lines (Thick Dotted Lines)
Drawn when price touches or breaks a session extreme:
Touching session high → dotted line at the low of that candle
Touching session low → dotted line at the high of that candle
Auction context:
Touching alone ≠ acceptance
Acceptance occurs only when price moves beyond the Interaction Line and holds
Trading principle:
Price has not crossed → no directional bias → do not trade
Price crosses and holds → directional bias established
3. Acceptance vs Rejection
Accepted direction: Price crosses and holds beyond the Interaction Line
Rejected direction: Price crosses the line but immediately reverses
Neutral / No-Trade: Price trapped between extreme and Interaction Line
Important: Acceptance is conditional and dynamic. Each time price crosses back over the Interaction Line, acceptance is lost.
4. New Extremes = Continuation
Once an Interaction Line is crossed, each new session extreme in that direction reinforces the trend.
Traders should only look for continuation setups along the established directional bias.
AMT interpretation:
Repeated new extremes → directional imbalance
Failure to make new extremes → potential balance or rotation
5. Closest Opposite Extreme Lines (Thin Dotted Lines)
After acceptance, the script tracks price progress toward the opposite session extreme.
Plotted only if price reaches a user-defined percentage of the session range.
Helps identify:
Full acceptance (price reaches opposite extreme)
Partial acceptance (price stalls)
Failed auctions (price cannot progress meaningfully)
Trading guidance once Closest Lines appear:
Partial acceptance: Price stalls near the Closest Line but does not fully reach the opposite extreme → bias remains valid, but the move may be weakening; consider scaling out or tightening stops.
Full acceptance: Price reaches the opposite extreme → directional auction fully confirmed; bias continues, but expect potential rotation or balance afterward.
Failed auction (cannot progress meaningfully): Price reverses before reaching the Closest Line → signals exhaustion; avoid chasing the move and treat as potential trend failure.
Note: Only relevant after Interaction Line is crossed; if price never crosses the Interaction Line, Closest Lines have no trading significance.
► Step-by-Step Usage
Wait for a session extreme
Let price interact with the session high or low.
Observe the Interaction Line
No cross → do not trade
Cross and hold → directional bias established
Trade in the direction of new extremes only
Ignore counter-trend trades unless the Interaction Line is lost
Manage risk using structure
Interaction Line acts as a dynamic invalidation level
Use Closest Lines for context
Partial acceptance → bias valid, watch for weakening
Full acceptance → bias strong, continuation likely
Failed attempt → potential exhaustion, do not chase
Useful for trade management, scaling, and expectation setting
► Price Retests & Pullbacks
Scenario:
Price crosses above the Interaction Line (e.g., from a low interaction).
Over the next 3–4 15-minute bars, price dips back toward the Interaction Line, with wicks touching it but no decisive close below.
Interpretation:
Initial Acceptance Confirmed: Bias remains valid while price holds above/below the line.
Temporary Pullback / Retest: Market is re-evaluating the auction; testing participant agreement.
Wicks Touching the Line: Partial probing or liquidity sweep; market still respects original acceptance.
Trading Implication:
Continuation bias remains intact.
Pullbacks near the Interaction Line offer lower-risk entries.
Decisive close below → acceptance lost, signaling trend failure or invalidation.
Market Psychology:
Healthy auction behavior: extreme tested → acceptance confirmed → boundary retested for liquidity → continuation.
Failure to hold above signals weak acceptance or exhaustion.
✅ Key Takeaways:
Holding above Interaction Line → bias intact, pullback = opportunity
Closing below Interaction Line → acceptance lost, bias invalidated
Wicks touching only → normal retest, still valid
► No-Trade Conditions
Avoid trading when:
Price never crosses the Interaction Line
Price remains trapped between the extreme and the Interaction Line
Market rotates without forming new extremes
These indicate balance, not directional opportunity.
► Alerts
Optional alerts trigger when price crosses an Interaction Line for:
Asia session
London session
New York session
Alerts signal possible acceptance, not automatic trade entries.
► Who This Script Is For
Best suited for traders who:
Trade session structure in futures, indices, or FX
Follow Auction Market Theory principles
Prefer objective, rules-based confirmation
Want fewer but higher-quality trade opportunities
Not intended for:
Indicator stacking
Predictive trading
High-frequency scalping without structure
► Final Notes
This script does not tell you when to buy or sell.
It shows where the market has earned the right to be traded.
Use it as a decision filter, not a prediction engine.
Webhook Candle Sender (OHLCV)This indicator sends OHLCV (Open, High, Low, Close, Volume) candle data via webhook on every confirmed bar close.
It is designed to integrate TradingView with an external trading or analytics system (e.g. a local Flask server, paper trading engine, or algorithmic agent).
Features:
• Sends data only on bar close (no repainting)
• Works on any symbol (stocks, crypto, forex)
• Works on any timeframe
• Outputs structured JSON suitable for APIs and bots
• Uses TradingView alert() function for webhook delivery
Typical use cases:
• Algorithmic trading research
• Paper trading systems
• Backtesting external strategies
• Educational and learning purposes
This script does NOT place trades, manage risk, or provide trading signals.
It only transmits candle data.
No financial advice is provided.
TGS By ShadTGS Levels — Tesla–W.D. Gann Strategy
TGS Levels is a price-geometry indicator designed to map algorithmic decision zones on the chart using principles inspired by W.D. Gann price geometry and Tesla 3-6-9 harmonic structure.
This indicator is not a signal generator.
It provides a structured price map to help traders understand where reactions or breakouts are statistically more likely to occur.
🔹 Core Concept
Markets do not move randomly.
They rotate and expand around harmonic price cycles.
TGS Levels automatically plots a 100-unit price cycle framework (ideal for XAUUSD / Gold) and divides each cycle into hierarchical angles used by institutional and algorithmic trading models.
🔹 Level Hierarchy (Very Important)
TGS uses four types of levels, each with a different purpose:
🔴 SUPER ANGLE (+45)
Primary decision level
Price often shows strong rejection or explosive breakout
Highest importance level
🟥 MAIN ANGLES (+27, +63, +81)
High-probability reaction zones
Used for structured pullbacks, rejections, or continuation confirmation
🟠 SECONDARY ANGLES (+18, +36, +54, +72, +90)
Context & management levels
Expect hesitation, partial profit zones, or stop-tightening areas
Not recommended for direct entries
🟡 MICRO LEVELS (+3, +6, +9)
Liquidity & compression map
Help visualize absorption, stop hunts, and consolidation
For structure awareness only
🔹 What This Indicator Is Used For
✔ Identifying where price is likely to react
✔ Understanding market structure and rotation
✔ Distinguishing rejection vs breakout zones
✔ Improving trade timing when combined with:
Volatility (ATR)
Market structure (HL / LH / BOS)
Session timing (London / New York)
🔹 What This Indicator Is NOT
❌ Not a buy/sell signal
❌ Not a prediction tool
❌ Not based on indicators like RSI or MACD
TGS Levels is a price-first framework, designed to be used with price action, volatility, and structure.
🔹 Best Use Case
Asset: XAUUSD (Gold)
Execution Timeframe: M5
Sessions: London & New York
Style: Scalping / Intraday structure trading
The same logic can be adapted to other instruments by adjusting the cycle size.
🔹 How to Trade With TGS (High-Level)
When volatility is low or falling → expect rejections at main/super angles
When volatility is expanding → expect breakouts through angles
Use oscillators (like Stochastic) only for timing, not direction
Always confirm with price behavior at the level
🔹 Final Note
TGS Levels provides a clean, non-repainting price map that stays aligned when zooming or scrolling the chart.
All levels are calculated automatically and update dynamically with price.
Levels explain behavior — reactions create opportunity.
TGS By ShadTGS Levels — Tesla–W.D. Gann Strategy
TGS Levels is a price-geometry indicator designed to map algorithmic decision zones on the chart using principles inspired by W.D. Gann price geometry and Tesla 3-6-9 harmonic structure.
This indicator is not a signal generator.
It provides a structured price map to help traders understand where reactions or breakouts are statistically more likely to occur.
🔹 Core Concept
Markets do not move randomly.
They rotate and expand around harmonic price cycles.
TGS Levels automatically plots a 100-unit price cycle framework (ideal for XAUUSD / Gold) and divides each cycle into hierarchical angles used by institutional and algorithmic trading models.
🔹 Level Hierarchy (Very Important)
TGS uses four types of levels, each with a different purpose:
🔴 SUPER ANGLE (+45)
Primary decision level
Price often shows strong rejection or explosive breakout
Highest importance level
🟥 MAIN ANGLES (+27, +63, +81)
High-probability reaction zones
Used for structured pullbacks, rejections, or continuation confirmation
🟠 SECONDARY ANGLES (+18, +36, +54, +72, +90)
Context & management levels
Expect hesitation, partial profit zones, or stop-tightening areas
Not recommended for direct entries
🟡 MICRO LEVELS (+3, +6, +9)
Liquidity & compression map
Help visualize absorption, stop hunts, and consolidation
For structure awareness only
🔹 What This Indicator Is Used For
✔ Identifying where price is likely to react
✔ Understanding market structure and rotation
✔ Distinguishing rejection vs breakout zones
✔ Improving trade timing when combined with:
Volatility (ATR)
Market structure (HL / LH / BOS)
Session timing (London / New York)
🔹 What This Indicator Is NOT
❌ Not a buy/sell signal
❌ Not a prediction tool
❌ Not based on indicators like RSI or MACD
TGS Levels is a price-first framework, designed to be used with price action, volatility, and structure.
🔹 Best Use Case
Asset: XAUUSD (Gold)
Execution Timeframe: M5
Sessions: London & New York
Style: Scalping / Intraday structure trading
The same logic can be adapted to other instruments by adjusting the cycle size.
🔹 How to Trade With TGS (High-Level)
When volatility is low or falling → expect rejections at main/super angles
When volatility is expanding → expect breakouts through angles
Use oscillators (like Stochastic) only for timing, not direction
Always confirm with price behavior at the level
🔹 Final Note
TGS Levels provides a clean, non-repainting price map that stays aligned when zooming or scrolling the chart.
All levels are calculated automatically and update dynamically with price.
Levels explain behavior — reactions create opportunity.
TGS by Shad TGS Levels — Tesla–W.D. Gann Strategy
TGS Levels is a price-geometry indicator designed to map algorithmic decision zones on the chart using principles inspired by W.D. Gann price geometry and Tesla 3-6-9 harmonic structure.
This indicator is not a signal generator.
It provides a structured price map to help traders understand where reactions or breakouts are statistically more likely to occur.
🔹 Core Concept
Markets do not move randomly.
They rotate and expand around harmonic price cycles.
TGS Levels automatically plots a 100-unit price cycle framework (ideal for XAUUSD / Gold) and divides each cycle into hierarchical angles used by institutional and algorithmic trading models.
🔹 Level Hierarchy (Very Important)
TGS uses four types of levels, each with a different purpose:
🔴 SUPER ANGLE (+45)
Primary decision level
Price often shows strong rejection or explosive breakout
Highest importance level
🟥 MAIN ANGLES (+27, +63, +81)
High-probability reaction zones
Used for structured pullbacks, rejections, or continuation confirmation
🟠 SECONDARY ANGLES (+18, +36, +54, +72, +90)
Context & management levels
Expect hesitation, partial profit zones, or stop-tightening areas
Not recommended for direct entries
🟡 MICRO LEVELS (+3, +6, +9)
Liquidity & compression map
Help visualize absorption, stop hunts, and consolidation
For structure awareness only
🔹 What This Indicator Is Used For
✔ Identifying where price is likely to react
✔ Understanding market structure and rotation
✔ Distinguishing rejection vs breakout zones
✔ Improving trade timing when combined with:
Volatility (ATR)
Market structure (HL / LH / BOS)
Session timing (London / New York)
🔹 What This Indicator Is NOT
❌ Not a buy/sell signal
❌ Not a prediction tool
❌ Not based on indicators like RSI or MACD
TGS Levels is a price-first framework, designed to be used with price action, volatility, and structure.
🔹 Best Use Case
Asset: XAUUSD (Gold)
Execution Timeframe: M5
Sessions: London & New York
Style: Scalping / Intraday structure trading
The same logic can be adapted to other instruments by adjusting the cycle size.
🔹 How to Trade With TGS (High-Level)
When volatility is low or falling → expect rejections at main/super angles
When volatility is expanding → expect breakouts through angles
Use oscillators (like Stochastic) only for timing, not direction
Always confirm with price behavior at the level
🔹 Final Note
TGS Levels provides a clean, non-repainting price map that stays aligned when zooming or scrolling the chart.
All levels are calculated automatically and update dynamically with price.
Levels explain behavior — reactions create opportunity.
Quant-Action Pro: Triple Confluence EngineQuant-Action Pro: Triple Confluence Engine
Systematic Framework for Structural Price Action Analysis
Quant-Action Pro is a high-performance analytical engine designed to synchronize institutional liquidity flow with market geometry. Instead of traditional "signals," this framework identifies Structural States where three independent algorithmic layers align, providing a objective roadmap for the current price action context.
1. Core Algorithmic Matrix
The engine operates by monitoring the interaction between price and three proprietary logic layers:
A. Institutional Flow Node (SP2L) —
Logic: Monitors "Passive Liquidity Absorption" at the 20-period EMA.
Function: Identifies zones where institutional buyers/sellers are defending the trend's equilibrium. This is not a simple touch; it requires a validated "Touch-and-Hold" sequence.
B. Structural Flip Scanner (BTB) —
Logic: Detects the transition from old supply to new demand (S/R Flip).
Function: Uses a 3-phase Break-Test-Break verification to confirm that a structural breakout is backed by volume, reducing the risk of "Fake-outs."
C. Liquidity Compression Monitor (Micro Map) —
Logic: Statistical range-contraction analysis (Volatility Squeeze).
Function: Signals a High-Density State where price is coiling for an expansion move.
2. The Golden State: Triple Confluence Logic
The GOLD label represents the "Apex" of this engine. It is triggered only when the SP2L, BTB, and Micro Map layers synchronize on a single candle. In structural terms, this means:
Trend Defense (SP2L) is active.
Structural Breakout (BTB) is confirmed.
Volatility Expansion (MM) is imminent.
This Triple-Layer filtering ensures that Golden Signals only appear during periods of maximum market conviction.
3. Professional Implementation (Structural View)
MTF Trend Matrix: A built-in dashboard provides a 1H, 4H, and 1D diagnosis to ensure local setups align with the Macro Trend.
Smart Invalidation (Adaptive Trendlines): The engine draws dynamic geometry to define the current "Structural Floor/Ceiling." A decisive close beyond these lines acts as a clear Invalidation Point for the current thesis.
Mean Reversion: The system uses the 200-EMA as the primary directional filter, defining whether the market is in a "Bullish Expansion" or "Bearish Correction" state.
⚠️ Risk Disclaimer
Trading financial instruments involves significant risk. Quant-Action Pro is an educational tool designed for research and structural analysis. It does not provide financial advice. Past performance is not indicative of future results. Always use strict risk management.
Max Pain Options [QuantLabs] v5 (Balanced)Institutional Grade Options Analysis: Max Pain, Gamma & Pin Risk
For years, TradingView users have been flying blind without access to Options Chain data. QuantLabs: Max Pain & Gamma Exposure changes that. This is not just a support/resistance indicator—it is a sophisticated, algorithmic model that reverse-engineers the incentives of Market Makers using synthetic Black-Scholes logic.
This tool visualizes the "invisible hand" of the market: the hedging requirements of large dealers who are forced to buy or sell to keep their books neutral.
CORE FEATURES:
🔴 Max Pain Gravity Model The bright red line represents the "Max Pain" strike—the price level where the maximum amount of Options Open Interest (Calls + Puts) expires worthless.
Theory: As OpEx (Expiration) approaches, Market Makers maximize profits by pinning the price to this level.
Strategy: Use this as a mean-reversion target. If price is far away, look for a snap-back to the red line.
🟣 Gamma Exposure Profiles (The Purple Lines) These neon histograms show you the estimated "Gamma Walls."
Long Gamma: Dealers trade against the trend (stabilizing price).
Short Gamma: Dealers trade with the trend (accelerating volatility).
Visual: The larger the purple bar, the harder it will be for price to break through that level.
📦 Algorithmic "Pin Risk" Zones The dashed red box highlights the "Kill Zone." When price enters this area near expiration, volatility often dies as dealers pin the asset to kill retail premiums.
Warning: Do not expect breakouts while inside the Pin Zone.
📊 Institutional HUD A clean, non-intrusive dashboard provides real-time Greeks and risk analysis:
Pin Risk: High/Medium/Low probability of a pinned close.
Exp Mode: Detects if the market is in "Short Gamma" (Squeeze territory) or "Long Gamma" (Chop territory).
HOW IT WORKS (The Math): Since live options data is not available via Pine Script, this engine uses a proprietary Synthetic OI Distribution Model. It inputs Volume, Volatility (IV), and Time-to-Expiry into a modified Black-Scholes equation to probability-map where the heavy open interest likely sits.
SETTINGS & CUSTOMIZATION:
Responsiveness: Tuned for the "Goldilocks Zone" (Spread: 12, Decay: 22) to catch local liquidity walls without over-fitting.
Visuals: Designed for Dark Mode. High-contrast Neon aesthetics for maximum readability.
A program written by a beginner# TXF Choppy Market Detector (Whipsaw Filter)
## Introduction
This project is a technical indicator developed in **Pine Script v5**, specifically optimized for **Taiwan Index Futures (TXF)** intraday trading.
The TXF market is known for its frequent periods of low-volatility consolidation following sharp moves, often resulting in "whipsaws" (double-loss scenarios for trend followers). This script utilizes **volatility analysis** and **trend efficiency metrics** to filter out noise and detect potential "Stop Hunting" or "Liquidity Sweep" setups within range-bound markets.
## Methodology & Algorithms
The strategy operates on the principle of **Mean Reversion**, combining two core components:
### 1. Market Regime Filter: Choppiness Index (CHOP)
We use the Choppiness Index (originally developed by E.W. Dreiss) to determine if the market is trending or consolidating based on **Fractal Dimension** theory.
* **Logic**:
The index ranges from 0 to 100. Higher values indicate low trend efficiency (consolidation), while lower values indicate strong directional trends.
* **Condition**: `CHOP > Threshold` (Default: 50).
* **Application**: When this condition is met, the background turns **gray**, signaling a "No-Trade Zone" for trend strategies and activating the Mean Reversion logic.
### 2. Whipsaw Detection: Bollinger Bands
Bollinger Bands are used to define the dynamic statistical extremities of price action.
* **Logic**:
We identify **Fakeouts** (False Breakouts) that occur specifically during the choppy regime identified above. This is often where institutional traders hunt for liquidity (stops) before reversing the price.
#### Signal Algorithms (Pseudocode)
**A. Bull Trap (Washout High)**
A false upside breakout designed to trap long traders.
```pine
Condition:
1. Is_Choppy == true (Market is sideways)
2. High > Upper_Bollinger_Band (Price pierces the upper band)
3. Close < Upper_Bollinger_Band (Price fails to hold and closes back inside)
BTC - ALSI: Altcoin Season Index (Dynamic Eras)Title: BTC - ALSI: Altcoin Season Index (Dynamic Eras)
Overview & Philosophy
The Altcoin Season Index (ALSI) is a quantitative tool designed to answer the most critical question in crypto capital rotation: "Is it time to hold Bitcoin, or is it time to take risks on Altcoins?"
Most "Altseason" indicators suffer from Survivor Bias or Obsolescence. They either track a static list of coins that includes "dead" assets from previous cycles (ghosts of 2017), or they break completely when major tokens collapse (like LUNA or FTT).
This indicator solves this by using a Time-Varying Basket. The indicator automatically adjusts its reference list of Top 20 coins based on historical eras. This ensures the index tracks the winners of the moment—capturing the DeFi summer of 2020, the NFT craze of 2021, and the AI/Meme narratives of 2024/2025.
Methodology
The indicator calculates the percentage of the Top 20 Altcoins that are outperforming Bitcoin over a rolling window (Default: 90 Days).
The "Win" Count: For every major Altcoin performing better than BTC, the index adds a point.
Dynamic Eras: The basket of coins changes depending on the date:
2020 Era (DeFi Summer): Tracks the "Blue Chips" of the DeFi revolution like UNI, LINK, DOT, and early movers like VET and FIL.
2021 Era (Layer 1 Wars): Tracks the explosion of alternative smart contract platforms, adding winners like SOL, AVAX, MATIC, and ALGO.
2022 Era (The Survivors): Filters for resilience during the Bear Market, solidifying the status of established assets like SHIB and ATOM.
2023 Era (Infrastructure & Scale): Captures the rise of "Next-Gen" tech leading into the pre-halving year, introducing TON, APT (Aptos), and ARB (Arbitrum).
2024/25 Era (AI & Speed): Tracks the current Super-Cycle leaders, focusing on the AI narrative (TAO, RNDR), High-Performance L1s (SUI), and modern Memes (PEPE).
Chart Analysis & Strategy ( The "Alpha" )
As seen in the chart above, there is a strong correlation between ALSI Peaks and local tops in TOTAL3 (The Crypto Market Cap excluding BTC & ETH).
The Entry (Rotation): When the indicator rises above the neutral 50 line, it signals that capital is beginning to rotate out of Bitcoin and into Altcoins. This has historically been a strong confirmation signal to increase exposure to high-beta assets.
The Exit (Saturation): When the indicator hits 100 (or sustains in the Red Zone > 75), it means every single Altcoin is beating Bitcoin. Historically, this extreme exuberance often marks a local top in the TOTAL3 chart. This is the zone where smart money typically sells into strength, rather than opening new positions.
How to Read the Visuals
🚀 Altcoin Season (Red Zone > 75): Strong Altcoin dominance. The market is "Risk On."
🛡️ Bitcoin Season (Blue Zone < 25): Bitcoin dominance. Alts are bleeding against BTC. Historically, this is a defensive zone to hold BTC or Stablecoins.
Data Dashboard: A status table in the bottom-right corner displays the live Index Value, current Regime, and a System Check to ensure all 20 data feeds are active.
Settings
Lookback Period: Default 90 Days. Lowering this (e.g., to 30) makes the index faster but noisier.
Thresholds: Adjustable zones for Altcoin Season (Default: 75) and Bitcoin Season (Default: 25).
Credits & Attribution
This open-source indicator is built on the shoulders of giants. I acknowledge the original creators of the concept and the pioneers of its implementation on TradingView:
Original Concept: BlockchainCenter.net. - They established the industry standard definition: 75% of the Top 50 coins outperforming Bitcoin over 90 days = Altseason..
TradingView Implementation: Adam_Nguyen - He implemented the "Dynamic Era" logic (updating the coin list annually) on TradingView. Our code structure for the time-based switching is inspired by his methodology. See also his implementation in the chart. ( Altcoin Season Index - Adam) .
Comparison: Why use ALSI | RM?
While inspired by the above, ALSI introduces three key improvements:
Open Source: Unlike other popular TradingView versions (which are closed-source), this script is fully transparent. You can see exactly which coins are triggering the signal.
Sanitized History (Anti-Fragile): Historical Top 20 snapshots are not blindly used. "Dead" coins (like LUNA and FTT) from previous eras are manually filtered out. A raw index would crash during the Terra/FTX collapses, giving a false "Bitcoin Season" signal purely due to bad actors. The curated list preserves the integrity of the market structure signal.
Narrative Relevance: The 2024/25 basket was updated to include TAO (Bittensor) and RNDR, ensuring the index captures the dominant AI narrative, rather than tracking fading assets from the previous cycle.
You can compare the ALSI indicator with other available tradingview indicators in the chart: Different indicators for the same idea are shown in the 3 Pane window below the BTC and Total3 chart, whereas ALSI is the top pane indicator.
Important Note on Coin Selection Baskets are highly curated: Dead/irrelevant coins (FTT, LUNA, BSV) are excluded for clean signals. This prevents historical breaks and ensures Era T5 captures current narratives (AI, Memes) via TAO/RNDR. See above. Users are free to adjust the source code to test their own baskets.
Disclaimer
This script is for research and educational purposes only. Past correlations between ALSI and TOTAL3 do not guarantee future results. Market regimes can change, and "Altseasons" can be cut short by macro events.
Tags
bitcoin, btc, altseason, dominance, total3, rotation, cycle, index, alsi, Rob Maths
BALANCED Strategy: Intraday Pro + Smart DashboardWelcome to the BALANCED Strategy: Intraday Pro.
This all-in-one indicator is designed for Intraday traders looking to capture trend movements while effectively filtering out sideways market noise. It combines the power of Supertrend for direction, EMA 100 for the baseline trend, and rigorous validation via RSI and ADX.
The script also integrates a complete Risk Management system with targets based on the Golden Ratio (Fibonacci) and a real-time Dashboard.
⏳ Recommended Timeframes
This algorithm is optimized for Intraday volatility:
M5 (5 Minutes) ⭐️: Ideal for quick Scalping. The ADX filter is crucial here to avoid false signals.
M15 (15 Minutes) 🏆: The "Sweet Spot." It offers the best balance between signal frequency and trend reliability.
M30 / H1: For a "Swing Intraday" approach—calmer, fewer signals, but higher precision.
Not recommended for M1 (1 Minute) with default settings (too much noise).
🚀 How It Works
The algorithm follows a strict 3-step logic to generate high-quality signals:
1. Trend Identification (The Engine)
Supertrend: Determines the immediate direction.
EMA 100: Acts as a background trend filter. We only buy above and sell below the EMA.
2. Noise Filtering (Safety)
ADX (Average Directional Index): The signal is only validated if there is sufficient volatility (Configurable threshold, default 12) to avoid "chop markets" (flat markets).
RSI (Relative Strength Index): Strict momentum filter. Buy only if RSI > 50, Sell if RSI < 50.
3. Entry Confirmation (The Trigger)
The script doesn't just rely on a crossover. It waits for "Price Action" confirmation: the candle must close higher than the previous one (for Long) or lower (for Short) to validate the entry.
🛡️ Risk Management (Money Management)
This is the core strength of this tool. Upon signal validation, the script automatically calculates and plots:
Stop Loss (SL): Based on volatility (ATR). It places the stop at the recent Low/High with a safety padding.
Take Profit (TP): Two modes available:
Fibonacci Mode (Default): Targets the 1.618 extension (Golden Ratio) of the risk taken.
Fixed Ratio Mode: Targets a manual Risk/Reward ratio (e.g., 2.0).
📊 The Dashboard
Located at the bottom right, the smart dashboard provides vital info at a glance:
Signal Time: To check if the alert is fresh.
Type (LONG/SHORT): Color-coded (Green/Pink).
Tech Data: RSI and ADX values at the moment of the signal.
Exact Prices: Entry Level, Target (TP), and Stop Loss (SL).
⚙️ Configurable Settings
Sensitivity: Adjust the Supertrend factor (Default 2.0).
Filters: Toggle the RSI filter ON/OFF or adjust the ADX threshold.
Execution: Choose between Fibonacci Target (1.618) or a Manual Ratio.
⚠️ Disclaimer: This tool is a technical decision aid and does not constitute financial investment advice. Always use prudent risk management and backtest the indicator on your preferred assets before live use.
ICT Quant-Core: Liquidity Intelligence [Dual-Engine]🔥 THE ULTIMATE LIQUIDITY FILTERING ENGINE
Most SMC traders lose money because they "catch falling knives" on every local wick. This algorithm solves this problem by using DUAL-CORE logic and a signal quality scoring system.
This is no ordinary pivot indicator.
⚙️ HOW DOES IT WORK? (DUAL-CORE LOGIC)
The algorithm analyzes the market on two levels simultaneously:
1️⃣ MACRO CORE (Lookback 50 - "WHALE 🐋")
Tracks key levels from recent weeks/months.
This is where institutions build their positions.
Signals from this core have the highest priority (Score 10/10).
2️⃣ LOCAL CORE (Lookback 20 - "ROACH 🐟")
Tracks internal market structure and noise.
Signals are filtered by the Main Trend. If the trend is down, Local Longs are marked as "TRAP."
🧠 SMART FILTERS (QUANT LAYERS)
Instead of entering on every line touch, the script requires confirmation:
✅ RECLAIM LOGIC: Price must close back above/below the liquidity level (Swing Failure Pattern).
✅ RVOL FILTER: Requires relative volume > 1.2x the average (institutional track).
✅ SCORING SYSTEM (0-10): Each signal receives a score.
- 10/10: Macro Grab in line with the trend + high volume.
- 3/10: Local Grab against the trend (risky).
📊 ANALYTICAL DASHBOARD
In the lower right corner, you'll find the "Command Center":
- Trend Status (Distribution/Accumulation)
- Whale's Last Move (Price and Direction)
- Current Tactics (e.g., "Ignore Longs, Search for Shorts")
- Filter Status (RSI, Volume, Reclaim)
🚀 HOW TO USE IT?
1. Set the H4 timeframe.
2. Wait for a signal with a rating > 7/10.
3. Ignore "Fish/Local" signals (small icons) if they contradict the Dashboard color.
4. Entry occurs only after the candle closes (Reclaim).
DarkPool FlowDarkPool Flow is a professional-grade technical analysis tool designed to align retail traders with the dominant "smart money" flow. Unlike standard moving average crossovers that often generate false signals during consolidation, this script employs a multi-layered filtering engine to isolate high-probability trends.
The core philosophy of this indicator is that Trends are fractal. A sustainable move on a lower timeframe must be supported by momentum on a higher timeframe. By comparing a "Fast Signal Trend" against a "Slow Anchor Trend" (e.g., Daily vs. Weekly), the script identifies the market bias used by institutional algorithms.
This edition features a Smart Recovery Engine, ensuring that valid trends are not missed simply because momentum started slowly, and a Dynamic Cloud that visually represents the strength of the trend spread.
Key Features
1. Auto-Adaptive Timeframe Logic
The script eliminates the guesswork of Multi-Timeframe (MTF) selection. By enabling "Auto-Adapt," the indicator detects your current chart timeframe and automatically maps it to the mathematically correct institutional pairings:
Scalping (<15m): Uses 15-Minute Trend vs. 1-Hour Anchor.
Day Trading (15m - 1H): Uses 4-Hour Trend vs. Daily Anchor.
Swing Trading (4H - Daily): Uses Daily Trend vs. Weekly Anchor (The classic "Golden" setup).
Investing (Weekly): Uses 21-Week EMA vs. 50-Week SMA (Bull Market Support Band logic).
2. Smart Recovery Signal Engine
Standard crossover scripts often miss major moves if the specific breakout candle has low volume or weak ADX. This script utilizes a state-machine logic that "remembers" the trend direction. If a trend begins during low volatility (gray candles), the script waits. The moment volatility and momentum confirm the move, a Smart Recovery Signal is triggered, allowing you to enter an existing trend safely.
3. Chop Protection (Gray Candles)
Preservation of capital is the priority. The script analyzes the Average Directional Index (ADX) and Volatility (ATR).
Colored Candles (Green/Red): The market is trending with sufficient strength. Trading is permitted.
Gray Candles: The market is in a low-energy chop or consolidation (ADX < 20). Trading is discouraged.
4. Dynamic Trend Cloud
The space between the Fast and Slow trends is filled with a dynamic cloud.
Darker/Opaque Cloud: Indicates a widening spread, suggesting accelerating momentum.
Lighter/Transparent Cloud: Indicates a narrowing spread, suggesting the trend may be weakening or consolidating.
5. Pullback & Retest Signals (+)
While triangles mark the start of a trend, the Plus (+) signs mark low-risk opportunities to add to a position. These appear when price dips into the cloud, finds support at the "Fair Value" zone, and closes back in the direction of the trend with confirmed momentum.
User Guide & Strategy
Setup
Add the indicator to your chart.
For Beginners: Enable "Auto-Adaptive Timeframes" in the settings.
For Advanced Users: Disable Auto-Adapt and manually configure your Fast/Slow pairings (Default is Daily 50 EMA / Weekly 50 EMA).
Signal Mode: Choose "First Breakout Only" for a cleaner chart, or "All Signals" if you wish to see re-entry points during choppy starts.
Long Entry Criteria (Buy)
Trend: The Cloud must be Green (Fast Trend > Slow Trend).
Signal: A Green Triangle appears below the bar.
Confirmation: The signal candle must not be Gray.
Re-Entry: A small Green (+) sign appears, indicating a successful test of the cloud support.
Short Entry Criteria (Sell)
Trend: The Cloud must be Red (Fast Trend < Slow Trend).
Signal: A Red Triangle appears above the bar.
Confirmation: The signal candle must not be Gray.
Re-Entry: A small Red (+) sign appears, indicating a successful test of the cloud resistance.
Stop Loss & Risk Management
Stop Loss: A standard institutional stop loss is placed just beyond the Slow Trend Line (the outer edge of the cloud). If price closes beyond the Slow Trend, the macro thesis is invalid.
Take Profit: Target liquidity pools or use a trailing stop based on the Fast Trend line.
Settings Overview
Mode Selection: Toggle between Auto-Adaptive logic or Manual control.
Manual Configuration: Define the specific Timeframe, Length, and Type (EMA, SMA, WMA) for both Fast and Slow trends.
Signal Logic: Toggle "Show Pullback Signals" on/off. Switch between "First Breakout" or "All Signals."
Quality Filters: Toggle individual filters (ATR, RSI, ADX) to adjust sensitivity. Turning these off makes the script more responsive but increases false signals.
Visual Style: Customize colors for Bullish, Bearish, and Neutral (Gray) states. Adjust cloud transparency.
Disclaimer
Risk Warning: Trading financial markets involves a high degree of risk and is not suitable for all investors. You could lose some or all of your initial investment.
Educational Use Only: This script and the information provided herein are for educational and informational purposes only. They do not constitute financial advice, investment advice, trading advice, or any other recommendation.
No Guarantee: Past performance of any trading system or methodology is not necessarily indicative of future results. The "Institutional Trend" indicator is a tool to assist in technical analysis, not a crystal ball. The creators of this script assume no responsibility or liability for any trading losses or damages incurred as a result of using this tool. Always perform your own due diligence and consult with a qualified financial advisor before making investment decisions.
Kalman Ema Crosses - [JTCAPITAL]Kalman EMA Crosses - is a modified way to use Kalman Filters applied on Exponential Moving Averages (EMA Crosses) for Trend-Following.
Credits for the kalman function itself goes to @BackQuant
The Kalman filter is a recursive smoothing algorithm that reduces noise from raw price or indicator data, and in this script it is applied both directly to price and on top of EMA calculations. The goal is to create cleaner, more reliable crossover signals between two EMAs that are less prone to false triggers caused by volatility or market noise.
The indicator works by calculating in the following steps:
Source Selection
The script starts by selecting the price input (default is Close, but can be adjusted). This chosen source is the foundation for all further smoothing and EMA calculations.
Kalman Filtering on Price
Depending on user settings, the selected source is passed through one of two independent Kalman filters. The filter takes into account process noise (representing expected market randomness) and measurement noise (representing uncertainty in the price data). The Kalman filter outputs a smoothed version of price that minimizes noise and preserves underlying trend structure.
EMA Calculation
Two exponential moving averages (EMA 1 and EMA 2) are then computed on the Kalman-smoothed price. The lengths of these EMAs are fully customizable (default 15 and 25).
Kalman Filtering on EMA Values
Instead of directly using raw EMA curves, the script applies a second layer of Kalman filtering to the EMA values themselves. This step significantly reduces whipsaw behavior, creating smoother crossovers that emphasize real momentum shifts rather than temporary volatility spikes.
Trend Detection via EMA Crossovers
-A bullish trend is detected when EMA 1 (fast) crosses above EMA 2 (slow).
-A bearish trend is detected when EMA 1 crosses below EMA 2.
The detected trend state is stored and used to dynamically color the plots.
Visual Representation
Both EMAs are plotted on the chart. Their colors shift to blue during bullish phases and purple during bearish phases. The area between the two EMAs is filled with a shaded region to clearly highlight trending conditions.
Buy and Sell Conditions:
-Buy Condition: When the Kalman-smoothed EMA 1 crosses above the Kalman-smoothed EMA 2, a bullish crossover is confirmed.
-Sell Condition: When EMA 1 crosses below EMA 2, a bearish crossover is confirmed.
Users may enhance the robustness of these signals by adjusting process noise, measurement noise, or EMA lengths. Lower measurement noise values make the filter react faster (but potentially noisier), while higher values make it smoother (but slower).
Features and Parameters:
-Source: Selectable price input (Close, Open, High, Low, etc.).
-EMA 1 Length: Defines the fast EMA period.
-EMA 2 Length: Defines the slow EMA period.
-Process Noise: Controls how much randomness the Kalman filter assumes in price dynamics.
-Measurement Noise: Controls how much uncertainty is assumed in raw input data.
-Kalman Usage: Option to apply Kalman filtering either before EMA calculation (on price) or after (on EMA values).
Specifications:
Kalman Filter
The Kalman filter is an optimal recursive algorithm that estimates the state of a system from noisy measurements. In trading, it is used to smooth prices or indicator values. By balancing process noise (expected volatility) with measurement noise (data uncertainty), it generates a smoothed signal that reacts adaptively to market conditions.
Exponential Moving Average (EMA)
An EMA is a weighted moving average that emphasizes recent data more heavily than older data. This makes it more responsive than a simple moving average (SMA). EMAs are widely used to identify trends and momentum shifts.
EMA Crossovers
The crossing of a fast EMA above a slow EMA suggests bullish momentum, while the opposite suggests bearish momentum. This is a cornerstone technique in trend-following systems.
Dual Kalman Filtering
Applying Kalman both to raw price and to the EMAs themselves reduces whipsaws further. It creates crossover signals that are not only smoothed but also validated across two levels of noise reduction. This significantly enhances signal reliability compared to traditional EMA crossovers.
Process Noise
Represents the filter’s assumption about how much the underlying market can randomly change between steps. Higher values make the filter adapt faster to sudden changes, while lower values make it more stable.
Measurement Noise
Represents uncertainty in price data. A higher measurement noise value means the filter trusts the model more than the observed data, leading to smoother results. A lower value makes the filter more reactive to observed price fluctuations.
Trend Coloring & Fill
The use of dynamic colors and filled regions provides immediate visual recognition of trend states, helping traders act faster and with greater clarity.
Enjoy!
IDWM Master StructureExecutive Summary
The IDWM Master Structure is a Multi-Timeframe (MTF) trading tool designed to force discipline by aligning traders with the "Parent" trend. It functions by locking onto the "Completed Auction" of a higher timeframe candle (like a Daily or Weekly bar) and projecting that structure onto your lower timeframe chart. Its primary goal is to define the "Dealing Range"—the hard boundaries where value was previously established—so you don't get lost in the noise of smaller price movements.
1. The Principle of Completed Auctions (Hierarchy)
Most technical indicators curve dynamically with every price tick. This script acts differently because it relies on "Settled Arguments." A closed Daily candle represents a finished battle between buyers and sellers; the High and Low are the historical results of that battle.
To enforce this, the script automatically selects a "Parent" timeframe based on your view:
Scalping (charts below 15 minutes) uses the 4-Hour Auction.
Intraday trading (15 minutes to 4 Hours) uses the Daily Auction.
Swing trading (Daily chart) uses the Weekly Auction.
2. Liquidity Pools & The Sticky Range
The High and Low lines drawn by the indicator are not just support and resistance; they represent Liquidity Pools. In market theory, stop-losses (Sell Stops below Lows, Buy Stops above Highs) accumulate at these edges.
Smart money often pushes price just past these lines to grab this liquidity (a "Stop Hunt") before reversing direction. To account for this, the script uses a "Sticky Range" mechanism. It refuses to redraw the box simply because price touched the line. Instead, it uses an Average True Range (ATR) Buffer. A new structure is only formed if the candle closes decisively outside the range plus this volatility buffer. This ensures you are trading real breakouts, not liquidity sweeps.
3. Internal Range Mechanics (Premium vs. Discount)
Inside the Master Box, the script applies Equilibrium Theory to help with trade location.
The most important internal line is the Equilibrium (EQ), which marks the exact 50% point of the range.
Premium Zone (Above EQ): Price is mathematically "expensive" relative to the recent range. Algorithms generally look to establish Short positions here.
Discount Zone (Below EQ): Price is considered "cheap." Algorithms generally look to establish Long positions here.
It also plots the Master Open, which acts as a "Line in the Sand." If price is currently trading above the Master Open, the higher timeframe candle is Green (Bullish), suggesting longs have a higher probability. If below, the candle is Red (Bearish).
4. Wick Theory (Failed Auctions)
The script places special emphasis on the wicks of the Master Candle because a wick represents a "Failed Auction"—a price level the market tried to explore but ultimately rejected.
The indicator highlights the background of the wick area (from the High to the Body). On a retest, these zones often act as supply or demand blocks because the market remembers the previous failure.
It also calculates the "Consequent Encroachment," which is the 50% midpoint of the wick. The rule of thumb here is that if a candle body can close past 50% of a wick, the rejection is nullified, and price will likely travel to fill the entire wick.
5. Energy Expansion (Breakout Targets)
Market energy transfers from Consolidation (inside the box) to Expansion (the breakout). When the price finally breaks the "Sticky Range" (confirming via the ATR buffer), the script projects where that energy will go.
It uses the height of the previous range to calculate Fibonacci extensions. Specifically, it targets the 1.618 Extension, often called the "Golden Ratio." This is a statistically significant level where expansion moves tend to exhaust themselves and reverse.
6. Safety Protocol: Live Detection
A dashboard monitors the state of the parent candle. If the text turns Magenta with a warning symbol, it means the Higher Timeframe candle is "Live" (still forming).
Trading off a live structure is considered higher risk because the "Auction" isn't finished—the High or Low can still shift. The safest approach is to trade when the dashboard indicates a standard, locked, historical structure.
Simulateur Carnet d'Ordres & Liquidité [Sese] - Custom🔹 Indicator Name
Order Book & Liquidity Simulator - Custom
🔹 Concept and Functionality
This indicator is a technical analysis tool designed to visually simulate market depth (Order Book) and potential liquidity zones.
It is important to adhere to TradingView's transparency rules: This script does not access real Level 2 data (the actual exchange order book). Instead, it uses a deductive algorithm based on historical Price Action to estimate where Buy Limit (Bid) and Sell Limit (Ask) orders might be resting.
Methodology used by the script:
Pivot Detection: The indicator scans for significant Swing Highs and Swing Lows over a user-defined lookback period (Length).
Level Projection: These pivots are projected to the right as horizontal lines.
Red Lines (Ask): Represent potential resistance zones (sellers).
Blue Lines (Bid): Represent potential support zones (buyers).
Liquidity Management (Absorption): The script is dynamic. If the current price crosses a line, the indicator assumes the liquidity at that level has been consumed (orders filled). The line is then automatically deleted from the chart.
Density Profile (Right Side): Horizontal bars appear to the right of the current price. These approximate a "Time Price Opportunity" or Volume Profile, showing where the market has spent the most time recently.
🔹 User Manual (Settings)
Here is how to configure the inputs to match your trading style:
1. Detection Algorithm
Lookback Length (Candles): Determines the sensitivity of the pivots.
Low value (e.g., 10): Shows many lines (scalping/short term).
High value (e.g., 50): Shows only major structural levels (swing trading).
Volume Factor: (Technical note: In this specific code version, this variable is calculated but the lines are primarily drawn based on geometric pivots).
2. Visual Settings
Show Price Lines (Bid/Ask): Toggles the horizontal Support/Resistance lines on or off.
Show Volume Profile: Toggles the heatmap-style bars on the right side of the chart.
Extend Lines: If checked, untouched lines will extend to the right towards the current price bar.
3. Colors and Transparency Management
Customize the aesthetics to keep your chart clean:
Bid / Ask Colors: Choose your base colors (Default is Blue and Red).
Line Transparency (%): Crucial for chart visibility.
0% = Solid, bright colors.
80-90% = Very subtle, faint lines (recommended if you overlay this on other tools).
Text Size: Adjusts the size of the price labels ("BUY LIMIT" / "SELL LIMIT").
🔹 How to Read the Indicator
Rejections: Unbroken lines act as potential walls. Watch for price reaction when approaching a blue line (support) or red line (resistance).
Breakouts/Absorption: When a line disappears, it means the level has been breached. The market may then seek the next liquidity level (the next line).
Density (Right-side boxes): More opaque/visible boxes indicate a price zone "accepted" by the market (consolidation). Empty gaps suggest an imbalance where price might move through quickly.
⚠️ Disclaimer
This script is for educational and technical analysis purposes only. It is a simulation based on price history, not real-time order book data. Past performance is not indicative of future results. Trading involves risk.
Fast Autocorrelation Estimator█ Overview:
The Fast ACF and PACF Estimation indicator efficiently calculates the autocorrelation function (ACF) and partial autocorrelation function (PACF) using an online implementation. It helps traders identify patterns and relationships in financial time series data, enabling them to optimize their trading strategies and make better-informed decisions in the markets.
█ Concepts:
Autocorrelation, also known as serial correlation, is the correlation of a signal with a delayed copy of itself as a function of delay.
This indicator displays autocorrelation based on lag number. The autocorrelation is not displayed based over time on the x-axis. It's based on the lag number which ranges from 1 to 30. The calculations can be done with "Log Returns", "Absolute Log Returns" or "Original Source" (the price of the asset displayed on the chart).
When calculating autocorrelation, the resulting value will range from +1 to -1, in line with the traditional correlation statistic. An autocorrelation of +1 represents a perfect correlation (an increase seen in one time series leads to a proportionate increase in the other time series). An autocorrelation of -1, on the other hand, represents a perfect inverse correlation (an increase seen in one time series results in a proportionate decrease in the other time series). Lag number indicates which historical data point is autocorrelated. For example, if lag 3 shows significant autocorrelation, it means current data is influenced by the data three bars ago.
The Fast Online Estimation of ACF and PACF Indicator is a powerful tool for analyzing the linear relationship between a time series and its lagged values in TradingView. The indicator implements an online estimation of the Autocorrelation Function (ACF) and the Partial Autocorrelation Function (PACF) up to 30 lags, providing a real-time assessment of the underlying dependencies in your time series data. The Autocorrelation Function (ACF) measures the linear relationship between a time series and its lagged values, capturing both direct and indirect dependencies. The Partial Autocorrelation Function (PACF) isolates the direct dependency between the time series and a specific lag while removing the effect of any indirect dependencies.
This distinction is crucial in understanding the underlying relationships in time series data and making more informed decisions based on those relationships. For example, let's consider a time series with three variables: A, B, and C. Suppose that A has a direct relationship with B, B has a direct relationship with C, but A and C do not have a direct relationship. The ACF between A and C will capture the indirect relationship between them through B, while the PACF will show no significant relationship between A and C, as it accounts for the indirect dependency through B. Meaning that when ACF is significant at for lag 5, the dependency detected could be caused by an observation that came in between, and PACF accounts for that. This indicator leverages the Fast Moments algorithm to efficiently calculate autocorrelations, making it ideal for analyzing large datasets or real-time data streams. By using the Fast Moments algorithm, the indicator can quickly update ACF and PACF values as new data points arrive, reducing the computational load and ensuring timely analysis. The PACF is derived from the ACF using the Durbin-Levinson algorithm, which helps in isolating the direct dependency between a time series and its lagged values, excluding the influence of other intermediate lags.
█ How to Use the Indicator:
Interpreting autocorrelation values can provide valuable insights into the market behavior and potential trading strategies.
When applying autocorrelation to log returns, and a specific lag shows a high positive autocorrelation, it suggests that the time series tends to move in the same direction over that lag period. In this case, a trader might consider using a momentum-based strategy to capitalize on the continuation of the current trend. On the other hand, if a specific lag shows a high negative autocorrelation, it indicates that the time series tends to reverse its direction over that lag period. In this situation, a trader might consider using a mean-reversion strategy to take advantage of the expected reversal in the market.
ACF of log returns:
Absolute returns are often used to as a measure of volatility. There is usually significant positive autocorrelation in absolute returns. We will often see an exponential decay of autocorrelation in volatility. This means that current volatility is dependent on historical volatility and the effect slowly dies off as the lag increases. This effect shows the property of "volatility clustering". Which means large changes tend to be followed by large changes, of either sign, and small changes tend to be followed by small changes.
ACF of absolute log returns:
Autocorrelation in price is always significantly positive and has an exponential decay. This predictably positive and relatively large value makes the autocorrelation of price (not returns) generally less useful.
ACF of price:
█ Significance:
The significance of a correlation metric tells us whether we should pay attention to it. In this script, we use 95% confidence interval bands that adjust to the size of the sample. If the observed correlation at a specific lag falls within the confidence interval, we consider it not significant and the data to be random or IID (identically and independently distributed). This means that we can't confidently say that the correlation reflects a real relationship, rather than just random chance. However, if the correlation is outside of the confidence interval, we can state with 95% confidence that there is an association between the lagged values. In other words, the correlation is likely to reflect a meaningful relationship between the variables, rather than a coincidence. A significant difference in either ACF or PACF can provide insights into the underlying structure of the time series data and suggest potential strategies for traders. By understanding these complex patterns, traders can better tailor their strategies to capitalize on the observed dependencies in the data, which can lead to improved decision-making in the financial markets.
Significant ACF but not significant PACF: This might indicate the presence of a moving average (MA) component in the time series. A moving average component is a pattern where the current value of the time series is influenced by a weighted average of past values. In this case, the ACF would show significant correlations over several lags, while the PACF would show significance only at the first few lags and then quickly decay.
Significant PACF but not significant ACF: This might indicate the presence of an autoregressive (AR) component in the time series. An autoregressive component is a pattern where the current value of the time series is influenced by a linear combination of past values at specific lags.
Often we find both significant ACF and PACF, in that scenario simply and AR or MA model might not be sufficient and a more complex model such as ARMA or ARIMA can be used.
█ Features:
Source selection: User can choose either 'Log Returns' , 'Absolute Returns' or 'Original Source' for the input data.
Autocorrelation Selection: User can choose either 'ACF' or 'PACF' for the plot selection.
Plot Selection: User can choose either 'Autocorrelarrogram' or 'Historical Autocorrelation' for plotting the historical autocorrelation at a specified lag.
Max Lag: User can select the maximum number of lags to plot.
Precision: User can set the number of decimal points to display in the plot.
