Range Filter Strategy [Arabic Real Backtest]استراتيجية مرشح النطاق - اختبار واقعي
نظرة عامة
استراتيجية مرشح النطاق المتقدمة مصممة للاختبار الواقعي مع توقيت تنفيذ دقيق وإدارة مخاطر شاملة. تم بناؤها خصيصًا لأسواق العملات الرقمية مع معلمات قابلة للتخصيص لأصول وفترات زمنية مختلفة.
الخوارزمية الأساسية
تقنية مرشح النطاق:
* حساب متوسط النطاق السلس باستخدام فلترة مزدوجة للـ EMA
* فلترة أسعار استنادًا إلى النطاق الديناميكي لتحديد اتجاه الاتجاه
* نظام فلترة ضد الضوضاء لتقليل الإشارات الخاطئة
* تتبع الزخم الاتجاهي مع عدادات للأعلى/للأسفل
الميزات الرئيسية
**التنفيذ الفوري (بدون تأخير)**
* معالجة الأوامر عند كل نقطة: تنفيذ فوري دون انتظار إغلاق الشمعة
* تكامل مكبر الشمعة للحصول على دقة داخل الشمعة
* الحساب في كل نقطة لضمان الاستجابة القصوى
* تجاوز OHLC القياسي لزيادة الدقة
**محاكاة الأسعار الواقعية**
* تسعير الدخول باستخدام HL2 (High+Low)/2 لملء واقعي
* محاكاة للبُعد العازل للسعر القابل للتخصيص
* إنشاء انزلاق عشوائي (من 0 إلى الحد الأقصى للانزلاق)
* التحقق من سيولة السوق قبل الدخول
**فلترة الإشارات المتقدمة**
* فلترة استنادًا إلى الحجم مع نسبة قابلة للتخصيص
* نظام تأكيد الإشارة اختياري (من 1 إلى 3 شموع)
* منطق مضاد للتكرار لمنع الإشارات المكررة
* التحكم في حد التداول اليومي
**إدارة المخاطر**
* نسب ثابتة للمخاطرة: العائد مع حساب دقيق للنقاط
* تنفيذ وقف الخسارة وجني الأرباح تلقائيًا
* إدارة حجم المركز
* تحديد الحد الأقصى للصفقات اليومية
**نظام التنبيهات**
* تنبيهات فورية متزامنة مع تنفيذ الاستراتيجية
* أنواع متعددة من التنبيهات: إعداد، دخول، خروج، حالة
* تخصيص تنسيق الرسائل مع تضمين السعر/الوقت
* تكامل مع لوحة تنبيهات TradingView
المعلمات الافتراضية
محسن لرسوم بيانية لفترة 5 دقائق لبيتكوين:
* فترة العينة: 100
* معامل النطاق: 3.0
* المخاطرة: 50 نقطة
* المكافأة: 100 نقطة (نسبة 1:2)
* بُعد الانتشار: 2.0 نقطة
* الحد الأقصى للانزلاق: 1.0 نقطة
منطق الإشارة
**شروط الدخول الطويل:**
* السعر فوق خط مرشح النطاق
* تأكيد الزخم الصاعد
* تلبية متطلبات الحجم (إذا تم تمكينها)
* اكتمال فترة التأكيد (إذا تم تمكينها)
* لم يتم تجاوز حد الصفقات اليومية
**شروط الدخول القصير:**
* السعر تحت خط مرشح النطاق
* تأكيد الزخم الهابط
* تلبية متطلبات الحجم (إذا تم تمكينها)
* اكتمال فترة التأكيد (إذا تم تمكينها)
* لم يتم تجاوز حد الصفقات اليومية
العناصر البصرية
* خط مرشح النطاق مع تلوين الاتجاه
* الأشرطة العليا والسفلى المستهدفة
* علامات إشارات الدخول
* صناديق نسبة المخاطرة/العائد
* لوحة إعدادات حية
خيارات التخصيص
**التكيف مع السوق:**
* تعديل فترة العينة لبيانات الزمن المختلفة
* تعديل معامل النطاق لمستويات التقلب المختلفة
* تكوين الانتشار/الانزلاق لوسطاء مختلفين
* تحديد النسب المناسبة للمخاطرة/العائد حسب أسلوب التداول
**ضوابط الفلترة:**
* تمكين/تعطيل فلترة الحجم
* تعديل متطلبات التأكيد
* تعيين حدود الصفقات اليومية
* تخصيص تفضيلات التنبيه
الميزات المتعلقة بالأداء
* نتائج اختبار واقعية متوافقة مع التداول المباشر
* القضاء على تحيز المستقبل
* محاكاة تنفيذ الأوامر بشكل صحيح
* إحصائيات تداول شاملة
تكوين التنبيه
**أنواع التنبيهات المتاحة:**
* إشارات الدخول مع معلومات التداول الكاملة
* تنبيهات الإعداد للتحضير المبكر
* إشعارات الخروج لإدارة المراكز
* فلترة التغيرات في الاتجاه لظروف السوق
**تنسيق الرسائل:**
رمز - الإجراء | السعر: XX.XX | الوقف: XX.XX | الهدف: XX.XX | الوقت: HH\:MM
التوصيات لاستخدام الاستراتيجية
**الإعدادات المثلى:**
* بيتكوين/العملات الرقمية الرئيسية: المعلمات الافتراضية
* الفوركس: تقليل فترة العينة إلى 50-70، المعامل إلى 2.0-2.5
* الأسهم: تقليل فترة العينة إلى 30-50، المعامل إلى 1.0-1.8
* الذهب: فترة العينة 60-80، المعامل 1.5-2.0
**تكوين TradingView:**
* إعادة الحساب: "على كل نقطة"
* الأوامر: "استخدام مكبر الشمعة"
* البيانات: يوصى باستخدام التغذية الحية
إخلاء المسؤولية
تم تصميم هذه الاستراتيجية لأغراض تعليمية وتحليلية. الأداء السابق لا يضمن النتائج المستقبلية. يجب دائمًا إجراء اختبارات شاملة على التداول الورقي قبل التنفيذ المباشر. يجب أخذ ظروف السوق، تنفيذ الوسيط، والتحمل الشخصي للمخاطر في الاعتبار عند استخدام أي نظام تداول آلي.
Range Filter Strategy - Real Backtesting
# Overview
Advanced Range Filter strategy designed for realistic backtesting with precise execution timing and comprehensive risk management. Built specifically for cryptocurrency markets with customizable parameters for different assets and timeframes.
Core Algorithm
Range Filter Technology:
- Smooth Average Range calculation using dual EMA filtering
- Dynamic range-based price filtering to identify trend direction
- Anti-noise filtering system to reduce false signals
- Directional momentum tracking with upward/downward counters
Key Features
Real-Time Execution (No Delay)
- Process orders on tick: Immediate execution without waiting for bar close
- Bar magnifier integration for intrabar precision
- Calculate on every tick for maximum responsiveness
- Standard OHLC bypass for enhanced accuracy
Realistic Price Simulation
- HL2 entry pricing (High+Low)/2 for realistic fills
- Configurable spread buffer simulation
- Random slippage generation (0 to max slippage)
- Market liquidity validation before entry
Advanced Signal Filtering
- Volume-based filtering with customizable ratio
- Optional signal confirmation system (1-3 bars)
- Anti-repetition logic to prevent duplicate signals
- Daily trade limit controls
Risk Management
- Fixed Risk:Reward ratios with precise point calculation
- Automatic stop loss and take profit execution
- Position size management
- Maximum daily trades limitation
Alert System
- Real-time alerts synchronized with strategy execution
- Multiple alert types: Setup, Entry, Exit, Status
- Customizable message formatting with price/time inclusion
- TradingView alert panel integration
Default Parameters
Optimized for BTC 5-minute charts:
- Sampling Period: 100
- Range Multiplier: 3.0
- Risk: 50 points
- Reward: 100 points (1:2 R:R)
- Spread Buffer: 2.0 points
- Max Slippage: 1.0 points
Signal Logic
Long Entry Conditions:
- Price above Range Filter line
- Upward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Short Entry Conditions:
- Price below Range Filter line
- Downward momentum confirmed
- Volume requirements met (if enabled)
- Confirmation period completed (if enabled)
- Daily trade limit not exceeded
Visual Elements
- Range Filter line with directional coloring
- Upper and lower target bands
- Entry signal markers
- Risk/Reward ratio boxes
- Real-time settings dashboard
Customization Options
Market Adaptation:
- Adjust Sampling Period for different timeframes
- Modify Range Multiplier for various volatility levels
- Configure spread/slippage for different brokers
- Set appropriate R:R ratios for trading style
Filtering Controls:
- Enable/disable volume filtering
- Adjust confirmation requirements
- Set daily trade limits
- Customize alert preferences
Performance Features
- Realistic backtesting results aligned with live trading
- Elimination of look-ahead bias
- Proper order execution simulation
- Comprehensive trade statistics
Alert Configuration
Alert Types Available:
- Entry signals with complete trade information
- Setup alerts for early preparation
- Exit notifications for position management
- Filter direction changes for market context
Message Format:
Symbol - Action | Price: XX.XX | Stop: XX.XX | Target: XX.XX | Time: HH:MM
Usage Recommendations
Optimal Settings:
- Bitcoin/Major Crypto: Default parameters
- Forex: Reduce sampling period to 50-70, multiplier to 2.0-2.5
- Stocks: Reduce sampling period to 30-50, multiplier to 1.0-1.8
- Gold: Sampling period 60-80, multiplier 1.5-2.0
TradingView Configuration:
- Recalculate: "On every tick"
- Orders: "Use bar magnifier"
- Data: Real-time feed recommended
Risk Disclaimer
This strategy is designed for educational and analytical purposes. Past performance does not guarantee future results. Always test thoroughly on paper trading before live implementation. Consider market conditions, broker execution, and personal risk tolerance when using any automated trading system.
Cari skrip untuk "bitcoin"
Drawdown Distribution Analysis (DDA) ACADEMIC FOUNDATION AND RESEARCH BACKGROUND
The Drawdown Distribution Analysis indicator implements quantitative risk management principles, drawing upon decades of academic research in portfolio theory, behavioral finance, and statistical risk modeling. This tool provides risk assessment capabilities for traders and portfolio managers seeking to understand their current position within historical drawdown patterns.
The theoretical foundation of this indicator rests on modern portfolio theory as established by Markowitz (1952), who introduced the fundamental concepts of risk-return optimization that continue to underpin contemporary portfolio management. Sharpe (1966) later expanded this framework by developing risk-adjusted performance measures, most notably the Sharpe ratio, which remains a cornerstone of performance evaluation in financial markets.
The specific focus on drawdown analysis builds upon the work of Chekhlov, Uryasev and Zabarankin (2005), who provided the mathematical framework for incorporating drawdown measures into portfolio optimization. Their research demonstrated that traditional mean-variance optimization often fails to capture the full risk profile of investment strategies, particularly regarding sequential losses. More recent work by Goldberg and Mahmoud (2017) has brought these theoretical concepts into practical application within institutional risk management frameworks.
Value at Risk methodology, as comprehensively outlined by Jorion (2007), provides the statistical foundation for the risk measurement components of this indicator. The coherent risk measures framework developed by Artzner et al. (1999) ensures that the risk metrics employed satisfy the mathematical properties required for sound risk management decisions. Additionally, the focus on downside risk follows the framework established by Sortino and Price (1994), while the drawdown-adjusted performance measures implement concepts introduced by Young (1991).
MATHEMATICAL METHODOLOGY
The core calculation methodology centers on a peak-tracking algorithm that continuously monitors the maximum price level achieved and calculates the percentage decline from this peak. The drawdown at any time t is defined as DD(t) = (P(t) - Peak(t)) / Peak(t) × 100, where P(t) represents the asset price at time t and Peak(t) represents the running maximum price observed up to time t.
Statistical distribution analysis forms the analytical backbone of the indicator. The system calculates key percentiles using the ta.percentile_nearest_rank() function to establish the 5th, 10th, 25th, 50th, 75th, 90th, and 95th percentiles of the historical drawdown distribution. This approach provides a complete picture of how the current drawdown compares to historical patterns.
Statistical significance assessment employs standard deviation bands at one, two, and three standard deviations from the mean, following the conventional approach where the upper band equals μ + nσ and the lower band equals μ - nσ. The Z-score calculation, defined as Z = (DD - μ) / σ, enables the identification of statistically extreme events, with thresholds set at |Z| > 2.5 for extreme drawdowns and |Z| > 3.0 for severe drawdowns, corresponding to confidence levels exceeding 99.4% and 99.7% respectively.
ADVANCED RISK METRICS
The indicator incorporates several risk-adjusted performance measures that extend beyond basic drawdown analysis. The Sharpe ratio calculation follows the standard formula Sharpe = (R - Rf) / σ, where R represents the annualized return, Rf represents the risk-free rate, and σ represents the annualized volatility. The system supports dynamic sourcing of the risk-free rate from the US 10-year Treasury yield or allows for manual specification.
The Sortino ratio addresses the limitation of the Sharpe ratio by focusing exclusively on downside risk, calculated as Sortino = (R - Rf) / σd, where σd represents the downside deviation computed using only negative returns. This measure provides a more accurate assessment of risk-adjusted performance for strategies that exhibit asymmetric return distributions.
The Calmar ratio, defined as Annual Return divided by the absolute value of Maximum Drawdown, offers a direct measure of return per unit of drawdown risk. This metric proves particularly valuable for comparing strategies or assets with different risk profiles, as it directly relates performance to the maximum historical loss experienced.
Value at Risk calculations provide quantitative estimates of potential losses at specified confidence levels. The 95% VaR corresponds to the 5th percentile of the drawdown distribution, while the 99% VaR corresponds to the 1st percentile. Conditional VaR, also known as Expected Shortfall, estimates the average loss in the worst 5% of scenarios, providing insight into tail risk that standard VaR measures may not capture.
To enable fair comparison across assets with different volatility characteristics, the indicator calculates volatility-adjusted drawdowns using the formula Adjusted DD = Raw DD / (Volatility / 20%). This normalization allows for meaningful comparison between high-volatility assets like cryptocurrencies and lower-volatility instruments like government bonds.
The Risk Efficiency Score represents a composite measure ranging from 0 to 100 that combines the Sharpe ratio and current percentile rank to provide a single metric for quick asset assessment. Higher scores indicate superior risk-adjusted performance relative to historical patterns.
COLOR SCHEMES AND VISUALIZATION
The indicator implements eight distinct color themes designed to accommodate different analytical preferences and market contexts. The EdgeTools theme employs a corporate blue palette that matches the design system used throughout the edgetools.org platform, ensuring visual consistency across analytical tools.
The Gold theme specifically targets precious metals analysis with warm tones that complement gold chart analysis, while the Quant theme provides a grayscale scheme suitable for analytical environments that prioritize clarity over aesthetic appeal. The Behavioral theme incorporates psychology-based color coding, using green to represent greed-driven market conditions and red to indicate fear-driven environments.
Additional themes include Ocean, Fire, Matrix, and Arctic schemes, each designed for specific market conditions or user preferences. All themes function effectively with both dark and light mode trading platforms, ensuring accessibility across different user interface configurations.
PRACTICAL APPLICATIONS
Asset allocation and portfolio construction represent primary use cases for this analytical framework. When comparing multiple assets such as Bitcoin, gold, and the S&P 500, traders can examine Risk Efficiency Scores to identify instruments offering superior risk-adjusted performance. The 95% VaR provides worst-case scenario comparisons, while volatility-adjusted drawdowns enable fair comparison despite varying volatility profiles.
The practical decision framework suggests that assets with Risk Efficiency Scores above 70 may be suitable for aggressive portfolio allocations, scores between 40 and 70 indicate moderate allocation potential, and scores below 40 suggest defensive positioning or avoidance. These thresholds should be adjusted based on individual risk tolerance and market conditions.
Risk management and position sizing applications utilize the current percentile rank to guide allocation decisions. When the current drawdown ranks above the 75th percentile of historical data, indicating that current conditions are better than 75% of historical periods, position increases may be warranted. Conversely, when percentile rankings fall below the 25th percentile, indicating elevated risk conditions, position reductions become advisable.
Institutional portfolio monitoring applications include hedge fund risk dashboard implementations where multiple strategies can be monitored simultaneously. Sharpe ratio tracking identifies deteriorating risk-adjusted performance across strategies, VaR monitoring ensures portfolios remain within established risk limits, and drawdown duration tracking provides valuable information for investor reporting requirements.
Market timing applications combine the statistical analysis with trend identification techniques. Strong buy signals may emerge when risk levels register as "Low" in conjunction with established uptrends, while extreme risk levels combined with downtrends may indicate exit or hedging opportunities. Z-scores exceeding 3.0 often signal statistically oversold conditions that may precede trend reversals.
STATISTICAL SIGNIFICANCE AND VALIDATION
The indicator provides 95% confidence intervals around current drawdown levels using the standard formula CI = μ ± 1.96σ. This statistical framework enables users to assess whether current conditions fall within normal market variation or represent statistically significant departures from historical patterns.
Risk level classification employs a dynamic assessment system based on percentile ranking within the historical distribution. Low risk designation applies when current drawdowns perform better than 50% of historical data, moderate risk encompasses the 25th to 50th percentile range, high risk covers the 10th to 25th percentile range, and extreme risk applies to the worst 10% of historical drawdowns.
Sample size considerations play a crucial role in statistical reliability. For daily data, the system requires a minimum of 252 trading days (approximately one year) but performs better with 500 or more observations. Weekly data analysis benefits from at least 104 weeks (two years) of history, while monthly data requires a minimum of 60 months (five years) for reliable statistical inference.
IMPLEMENTATION BEST PRACTICES
Parameter optimization should consider the specific characteristics of different asset classes. Equity analysis typically benefits from 500-day lookback periods with 21-day smoothing, while cryptocurrency analysis may employ 365-day lookback periods with 14-day smoothing to account for higher volatility patterns. Fixed income analysis often requires longer lookback periods of 756 days with 34-day smoothing to capture the lower volatility environment.
Multi-timeframe analysis provides hierarchical risk assessment capabilities. Daily timeframe analysis supports tactical risk management decisions, weekly analysis informs strategic positioning choices, and monthly analysis guides long-term allocation decisions. This hierarchical approach ensures that risk assessment occurs at appropriate temporal scales for different investment objectives.
Integration with complementary indicators enhances the analytical framework. Trend indicators such as RSI and moving averages provide directional bias context, volume analysis helps confirm the severity of drawdown conditions, and volatility measures like VIX or ATR assist in market regime identification.
ALERT SYSTEM AND AUTOMATION
The automated alert system monitors five distinct categories of risk events. Risk level changes trigger notifications when drawdowns move between risk categories, enabling proactive risk management responses. Statistical significance alerts activate when Z-scores exceed established threshold levels of 2.5 or 3.0 standard deviations.
New maximum drawdown alerts notify users when historical maximum levels are exceeded, indicating entry into uncharted risk territory. Poor risk efficiency alerts trigger when the composite risk efficiency score falls below 30, suggesting deteriorating risk-adjusted performance. Sharpe ratio decline alerts activate when risk-adjusted performance turns negative, indicating that returns no longer compensate for the risk undertaken.
TRADING STRATEGIES
Conservative risk parity strategies can be implemented by monitoring Risk Efficiency Scores across a diversified asset portfolio. Monthly rebalancing maintains equal risk contribution from each asset, with allocation reductions triggered when risk levels reach "High" status and complete exits executed when "Extreme" risk levels emerge. This approach typically results in lower overall portfolio volatility, improved risk-adjusted returns, and reduced maximum drawdown periods.
Tactical asset rotation strategies compare Risk Efficiency Scores across different asset classes to guide allocation decisions. Assets with scores exceeding 60 receive overweight allocations, while assets scoring below 40 receive underweight positions. Percentile rankings provide timing guidance for allocation adjustments, creating a systematic approach to asset allocation that responds to changing risk-return profiles.
Market timing strategies with statistical edges can be constructed by entering positions when Z-scores fall below -2.5, indicating statistically oversold conditions, and scaling out when Z-scores exceed 2.5, suggesting overbought conditions. The 95% VaR serves as a stop-loss reference point, while trend confirmation indicators provide additional validation for position entry and exit decisions.
LIMITATIONS AND CONSIDERATIONS
Several statistical limitations affect the interpretation and application of these risk measures. Historical bias represents a fundamental challenge, as past drawdown patterns may not accurately predict future risk characteristics, particularly during structural market changes or regime shifts. Sample dependence means that results can be sensitive to the selected lookback period, with shorter periods providing more responsive but potentially less stable estimates.
Market regime changes can significantly alter the statistical parameters underlying the analysis. During periods of structural market evolution, historical distributions may provide poor guidance for future expectations. Additionally, many financial assets exhibit return distributions with fat tails that deviate from normal distribution assumptions, potentially leading to underestimation of extreme event probabilities.
Practical limitations include execution risk, where theoretical signals may not translate directly into actual trading results due to factors such as slippage, timing delays, and market impact. Liquidity constraints mean that risk metrics assume perfect liquidity, which may not hold during stressed market conditions when risk management becomes most critical.
Transaction costs are not incorporated into risk-adjusted return calculations, potentially overstating the attractiveness of strategies that require frequent trading. Behavioral factors represent another limitation, as human psychology may override statistical signals, particularly during periods of extreme market stress when disciplined risk management becomes most challenging.
TECHNICAL IMPLEMENTATION
Performance optimization ensures reliable operation across different market conditions and timeframes. All technical analysis functions are extracted from conditional statements to maintain Pine Script compliance and ensure consistent execution. Memory efficiency is achieved through optimized variable scoping and array usage, while computational speed benefits from vectorized calculations where possible.
Data quality requirements include clean price data without gaps or errors that could distort distribution analysis. Sufficient historical data is essential, with a minimum of 100 bars required and 500 or more preferred for reliable statistical inference. Time alignment across related assets ensures meaningful comparison when conducting multi-asset analysis.
The configuration parameters are organized into logical groups to enhance usability. Core settings include the Distribution Analysis Period (100-2000 bars), Drawdown Smoothing Period (1-50 bars), and Price Source selection. Advanced metrics settings control risk-free rate sourcing, either from live market data or fixed rate specification, along with toggles for various risk-adjusted metric calculations.
Display options provide flexibility in visual presentation, including color theme selection from eight available schemes, automatic dark mode optimization, and control over table display, position lines, percentile bands, and standard deviation overlays. These options ensure that the indicator can be adapted to different analytical workflows and visual preferences.
CONCLUSION
The Drawdown Distribution Analysis indicator provides risk management tools for traders seeking to understand their current position within historical risk patterns. By combining established statistical methodology with practical usability features, the tool enables evidence-based risk assessment and portfolio optimization decisions.
The implementation draws upon established academic research while providing practical features that address real-world trading requirements. Dynamic risk-free rate integration ensures accurate risk-adjusted performance calculations, while multiple color schemes accommodate different analytical preferences and use cases.
Academic compliance is maintained through transparent methodology and acknowledgment of limitations. The tool implements peer-reviewed statistical techniques while clearly communicating the constraints and assumptions underlying the analysis. This approach ensures that users can make informed decisions about the appropriate application of the risk assessment framework within their broader trading and investment processes.
BIBLIOGRAPHY
Artzner, P., Delbaen, F., Eber, J.M. and Heath, D. (1999) 'Coherent Measures of Risk', Mathematical Finance, 9(3), pp. 203-228.
Chekhlov, A., Uryasev, S. and Zabarankin, M. (2005) 'Drawdown Measure in Portfolio Optimization', International Journal of Theoretical and Applied Finance, 8(1), pp. 13-58.
Goldberg, L.R. and Mahmoud, O. (2017) 'Drawdown: From Practice to Theory and Back Again', Journal of Risk Management in Financial Institutions, 10(2), pp. 140-152.
Jorion, P. (2007) Value at Risk: The New Benchmark for Managing Financial Risk. 3rd edn. New York: McGraw-Hill.
Markowitz, H. (1952) 'Portfolio Selection', Journal of Finance, 7(1), pp. 77-91.
Sharpe, W.F. (1966) 'Mutual Fund Performance', Journal of Business, 39(1), pp. 119-138.
Sortino, F.A. and Price, L.N. (1994) 'Performance Measurement in a Downside Risk Framework', Journal of Investing, 3(3), pp. 59-64.
Young, T.W. (1991) 'Calmar Ratio: A Smoother Tool', Futures, 20(1), pp. 40-42.
BUY in HASH RibbonsHash Ribbons Indicator (BUY Signal)
A TradingView Pine Script v6 implementation for identifying Bitcoin miner capitulation (“Springs”) and recovery phases based on hash rate data. It marks potential low-risk buying opportunities by tracking short- and long-term moving averages of the network hash rate.
⸻
Key Features
• Hash Rate SMAs
• Short-term SMA (default: 30 days)
• Long-term SMA (default: 60 days)
• Phase Markers
• Gray circle: Short SMA crosses below long SMA (start of capitulation)
• White circles: Ongoing capitulation, with brighter white when the short SMA turns upward
• Yellow circle: Short SMA crosses back above long SMA (end of capitulation)
• Orange circle: Buy signal once hash rate recovery aligns with bullish price momentum (10-day price SMA crosses above 20-day price SMA)
• Display Modes
• Ribbons: Plots the two SMAs as colored bands—red for capitulation, green for recovery
• Oscillator: Shows the percentage difference between SMAs as a histogram (red for negative, blue for positive)
• Optional Overlays
• Bitcoin halving dates (2012, 2016, 2020, 2024) with dashed lines and labels
• Raw hash rate data in EH/s
• Alerts
• Configurable alerts for capitulation start, recovery, and buy signals
⸻
How It Works
1. Data Source: Fetches daily hash rate values from a selected provider (e.g., IntoTheBlock, Quandl).
2. Capitulation Detection: When the 30-day SMA falls below the 60-day SMA, miners are likely capitulating.
3. Recovery Identification: A rising 30-day SMA during capitulation signals miner recovery.
4. Buy Signal: Confirmed when the hash rate recovery coincides with a bullish shift in price momentum (10-day price SMA > 20-day price SMA).
⸻
Inputs
Hash Rate Short SMA: 30 days
Hash Rate Long SMA: 60 days
Plot Signals: On
Plot Halvings: Off
Plot Raw Hash Rate: Off
⸻
Considerations
• Timeframe: Best applied on daily charts to capture meaningful miner behavior.
• Data Reliability: Ensure the chosen hash rate source provides consistent, gap-free data.
• Risk Management: Use alongside other technical indicators (e.g., RSI, MACD) and fundamental analysis.
• Backtesting: Evaluate performance over different market cycles before live deployment.
Pi Cycle | AlchimistOfCryptoPi Cycle Top Indicator - A Powerful Market Phase Detector
Developed by AlchimistOfCrypto
🧪 The Pi Cycle uses mathematical harmony to identify Bitcoin market cycle tops
with remarkable precision. Just as elements react at specific temperatures,
Bitcoin price behaves predictably when these two moving averages converge! 🧬
⚗️ The formula measures when the 111-day SMA crosses below the 350-day SMA × 2,
creating a perfect alchemical reaction that has successfully identified the
major cycle tops in 2013, 2017, and 2021.
🔬 Like the Golden Ratio in nature, this indicator reveals the hidden
mathematical structure within Bitcoin's chaotic price movements.
🧮 When the reaction occurs, prepare for molecular breakdown! 🔥
DAX Inducere Simplă v1.3 – Confirmare InducereDAX Inducere Simplă v1.3 – Confirmare Inducere ,signals before fvg mss and displacement
MVRV Altcoins📌 Technical Description of Indicator: MVRV Altcoins
This advanced script calculates the Market Value to Realized Value (MVRV) ratio across multiple cryptocurrencies simultaneously. It offers two analytical modes: Normal and Z-Score, optimized for visual comparison and real-time monitoring of up to 13 predefined assets. If a user applies the indicator to a symbol that is not among the 13 programmed assets, the default behavior displays the Bitcoin chart as a fallback reference.
🔍 What Is MVRV and Why Is It Important?
MVRV is an on-chain metric designed to assess whether a cryptocurrency is overvalued or undervalued by comparing its market capitalization to its realized capitalization.
- Market Cap: The total circulating supply multiplied by the current market price.
- Realized Cap: The sum value of all coins based on the price at the time they last moved on-chain, offering a time-weighted valuation.
Normal Calculation:
MVRV_Normal = Market Cap / Realized Cap
This version reflects investor profitability and identifies potential accumulation or distribution zones.
📊 Z-Score Calculation:
MVRV_ZScore = (Market Cap − Realized Cap) / Standard Deviation of Market Cap
This formula evaluates how extreme the current market conditions are compared to historical norms. It normalizes the difference using statistical dispersion, turning it into a volatility-aware metric that better reflects valuation extremes.
🔎 How Market Cap Is Computed
Unlike conventional indicators relying on consolidated feeds, this script uses modular components from CoinMetrics to construct the active capitalization more accurately, especially for altcoins. Here's the breakdown:
Active Capitalization = MARKETCAPFF + MARKETCAPACTSPLY
Realized Capitalization = MARKETCAPREAL
Component Definitions:
- MARKETCAPFF: Market Cap Free Float — total valuation based only on truly circulating coins.
- MARKETCAPACTSPLY: Capitalization from actively circulating supply — filters dormant or locked coins.
- MARKETCAPREAL: Realized Cap — historical valuation weighted by the last on-chain movement of each coin.
This method offers enhanced precision and compatibility across assets that may lack comprehensive data from centralized providers.
⚙️ User-Configurable Parameters
- MVRV Mode: Choose between Normal and Z-Score.
- Percentage Scale View: If enabled, visual output is scaled using predefined divisors (100 / 3.5 or 100 / 6).
- Thresholds for Analysis:
- Normal mode: Define overbought and oversold levels (default 1.0 and 3.5).
- Z-Score mode: Configure statistical boundaries (default 0.0 and 6.0).
- Table Controls:
- Adjustable position on screen (9 options).
- Font size customization: tiny, small, normal, large.
- Color scheme personalization:
- Header: text and background
- Body: text and background
- Central column separator color
📊 Multicrypto Table Architecture
The indicator renders a high-performance visual table displaying data from up to 13 assets simultaneously. Each asset is represented as a vertical column featuring eigth historical data points plus the most recent value.
- Assets are displayed in two blocks separated by a decorative column.
- Each value is rounded to one decimal place for clarity.
- Cells are styled dynamically based on user settings.
🎨 Decorative Column Separator
Since the entire table is built as a unified structure, a color-configurable empty column is inserted mid-table to act as a visual divider. This approach improves readability and aesthetic balance without duplicating code or splitting table logic.
🔁 Default Behavior on Unsupported Assets
If the active chart is not one of the 13 predefined assets, the indicator will automatically display Bitcoin’s data. This ensures the chart remains functional and informative even outside the target asset group.
🎯 Color Interpretation by Condition
The MVRV value for each asset is highlighted using a traffic light system:
- Green: Undervalued (below oversold threshold)
- Red: Overvalued (above overbought threshold)
- Yellow: Neutral zone
This coding simplifies decision-making and visual scanning across assets.
Final Notes
This indicator is modular and fully adaptable, with well-commented sections designed for efficient customization. Its multiactive architecture makes it a valuable tool for crypto analysts tracking diversified portfolios beyond Bitcoin and Ethereum.
It supports visual storytelling across assets, comparative historical evaluation, and identification of strategic zones — whether for accumulation, distribution, or monitoring on-chain sentiment.
Fear Volatility Gate [by Oberlunar]The Fear Volatility Gate by Oberlunar is a filter designed to enhance operational prudence by leveraging volatility-based risk indices. Its architecture is grounded in the empirical observation that sudden shifts in implied volatility often precede instability across financial markets. By dynamically interpreting signals from globally recognized "fear indices", such as the VIX, the indicator aims to identify periods of elevated systemic uncertainty and, accordingly, restrict or flag potential trade entries.
The rationale behind the Fear Volatility Gate is rooted in the understanding that implied volatility represents a forward-looking estimate of market risk. When volatility indices rise sharply, it reflects increased demand for options and a broader perception of uncertainty. In such contexts, price movements can become less predictable, more erratic, and often decoupled from technical structures. Rather than relying on price alone, this filter provides an external perspective—derived from derivative markets—on whether current conditions justify caution.
The indicator operates in two primary modes: single-source and composite . In the single-source configuration, a user-defined volatility index is monitored individually. In composite mode, the filter can synthesize input from multiple indices simultaneously, offering a more comprehensive macro-risk assessment. The filtering logic is adaptable, allowing signals to be combined using inclusive (ANY), strict (ALL), or majority consensus logic. This allows the trader to tailor sensitivity based on the operational context or asset class.
The indices available for selection cover a broad spectrum of market sectors. In the equity domain, the filter supports the CBOE Volatility Index ( CBOE:VIX VIX) for the S&P 500, the Nasdaq-100 Volatility Index ( CBOE:VXN VXN), the Russell 2000 Volatility Index ( CBOEFTSE:RVX RVX), and the Dow Jones Volatility Index ( CBOE:VXD VXD). For commodities, it integrates the Crude Oil Volatility Index ( CBOE:OVX ), the Gold Volatility Index ( CBOE:GVZ ), and the Silver Volatility Index ( CBOE:VXSLV ). From the fixed income perspective, it includes the ICE Bank of America MOVE Index ( OKX:MOVEUSD ), the Volatility Index for the TLT ETF ( CBOE:VXTLT VXTLT), and the 5-Year Treasury Yield Index ( CBOE:FVX.P FVX). Within the cryptocurrency space, it incorporates the Bitcoin Volmex Implied Volatility Index ( VOLMEX:BVIV BVIV), the Ethereum Volmex Implied Volatility Index ( VOLMEX:EVIV EVIV), the Deribit Bitcoin Volatility Index ( DERIBIT:DVOL DVOL), and the Deribit Ethereum Volatility Index ( DERIBIT:ETHDVOL ETHDVOL). Additionally, the user may define a custom instrument for specialized tracking.
To determine whether market conditions are considered high-risk, the indicator supports three modes of evaluation.
The moving average cross mode compares a fast Hull Moving Average to a slower one, triggering a signal when short-term volatility exceeds long-term expectations.
The Z-score mode standardizes current volatility relative to historical mean and standard deviation, identifying significant deviations that may indicate abnormal market stress.
The percentile mode ranks the current value against a historical distribution, providing a relative perspective particularly useful when dealing with non-normal or skewed distributions.
When at least one selected index meets the condition defined by the chosen mode, and if the filtering logic confirms it, the indicator can mark the trading environment as “blocked”. This status is visually highlighted through background color changes and symbolic markers on the chart. An optional tabular interface provides detailed diagnostics, including raw values, fast-slow MA comparison, Z-scores, percentile levels, and binary risk status for each active index.
The Fear Volatility Gate is not a predictive tool in itself but rather a dynamic constraint layer that reinforces discipline under conditions of macro instability. It is particularly valuable when trading systems are exposed to highly leveraged or short-duration strategies, where market noise and sentiment can temporarily override structural price behavior. By synchronizing trading signals with volatility regimes, the filter promotes a more cautious, informed approach to decision-making.
This approach does not assume that all volatility spikes are harmful or that market corrections are imminent. Rather, it acknowledges that periods of elevated implied volatility statistically coincide with increased execution risk, slippage, and spread widening, all of which may erode the profitability of even the most technically accurate setups.
Therefore, the Fear Volatility Gate acts as a protective mechanism.
Oberlunar 👁️⭐
Ultimate Market Structure [Alpha Extract]Ultimate Market Structure
A comprehensive market structure analysis tool that combines advanced swing point detection, imbalance zone identification, and intelligent break analysis to identify high-probability trading opportunities.Utilizing a sophisticated trend scoring system, this indicator classifies market conditions and provides clear signals for structure breaks, directional changes, and fair value gap detection with institutional-grade precision.
🔶 Advanced Swing Point Detection
Identifies pivot highs and lows using configurable lookback periods with optional close-based analysis for cleaner signals. The system automatically labels swing points as Higher Highs (HH), Lower Highs (LH), Higher Lows (HL), and Lower Lows (LL) while providing advanced classifications including "rising_high", "falling_high", "rising_low", "falling_low", "peak_high", and "valley_low" for nuanced market analysis.
swingHighPrice = useClosesForStructure ? ta.pivothigh(close, swingLength, swingLength) : ta.pivothigh(high, swingLength, swingLength)
swingLowPrice = useClosesForStructure ? ta.pivotlow(close, swingLength, swingLength) : ta.pivotlow(low, swingLength, swingLength)
classification = classifyStructurePoint(structureHighPrice, upperStructure, true)
significance = calculateSignificance(structureHighPrice, upperStructure, true)
🔶 Significance Scoring System
Each structure point receives a significance level on a 1-5 scale based on its distance from previous points, helping prioritize the most important levels. This intelligent scoring system ensures traders focus on the most meaningful structure breaks while filtering out minor noise.
🔶 Comprehensive Trend Analysis
Calculates momentum, strength, direction, and confidence levels using volatility-normalized price changes and multi-timeframe correlation. The system provides real-time trend state tracking with bullish (+1), bearish (-1), or neutral (0) direction assessment and 0-100 confidence scoring.
// Calculate trend momentum using rate of change and volatility
calculateTrendMomentum(lookback) =>
priceChange = (close - close ) / close * 100
avgVolatility = ta.atr(lookback) / close * 100
momentum = priceChange / (avgVolatility + 0.0001)
momentum
// Calculate trend strength using multiple timeframe correlation
calculateTrendStrength(shortPeriod, longPeriod) =>
shortMA = ta.sma(close, shortPeriod)
longMA = ta.sma(close, longPeriod)
separation = math.abs(shortMA - longMA) / longMA * 100
strength = separation * slopeAlignment
❓How It Works
🔶 Imbalance Zone Detection
Identifies Fair Value Gaps (FVGs) between consecutive candles where price gaps create unfilled areas. These zones are displayed as semi-transparent boxes with optional center line mitigation tracking, highlighting potential support and resistance levels where institutional players often react.
// Detect Fair Value Gaps
detectPriceImbalance() =>
currentHigh = high
currentLow = low
refHigh = high
refLow = low
if currentOpen > currentClose
if currentHigh - refLow < 0
upperBound = currentClose - (currentClose - refLow)
lowerBound = currentClose - (currentClose - currentHigh)
centerPoint = (upperBound + lowerBound) / 2
newZone = ImbalanceZone.new(
zoneBox = box.new(bar_index, upperBound, rightEdge, lowerBound,
bgcolor=bullishImbalanceColor, border_color=hiddenColor)
)
🔶 Structure Break Analysis
Determines Break of Structure (BOS) for trend continuation and Directional Change (DC) for trend reversals with advanced classification as "continuation", "reversal", or "neutral". The system compares pre-trend and post-trend states for each break, providing comprehensive trend change momentum analysis.
🔶 Intelligent Zone Management
Features partial mitigation tracking when price enters but doesn't fully fill zones, with automatic zone boundary adjustment during partial fills. Smart array management keeps only recent structure points for optimal performance while preventing duplicate signals from the same level.
🔶 Liquidity Zone Detection
Automatically identifies potential liquidity zones at key structure points for institutional trading analysis. The system tracks broken structure points and provides adaptive zone extension with configurable time-based limits for imbalance areas.
🔶 Visual Structure Mapping
Provides clear visual indicators including swing labels with color-coded significance levels, dashed lines connecting break points with BOS/DC labels, and break signals for continuation and reversal patterns. The adaptive zones feature smart management with automatic mitigation tracking.
🔶 Market Structure Interpretation
HH/HL patterns indicate bullish market structure with trend continuation likelihood, while LH/LL patterns signal bearish structure with downtrend continuation expected. BOS signals represent structure breaks in trend direction for continuation opportunities, while DC signals warn of potential reversals.
🔶 Performance Optimization
Automatic cleanup of old structure points (keeps last 8 points), recent break tracking (keeps last 5 break events), and efficient array management ensure smooth performance across all timeframes and market conditions.
Why Choose Ultimate Market Structure ?
This indicator provides traders with institutional-grade market structure analysis, combining multiple analytical approaches into one comprehensive tool. By identifying key structure levels, imbalance zones, and break patterns with advanced significance scoring, it helps traders understand market dynamics and position themselves for high-probability trade setups in alignment with smart money concepts. The sophisticated trend scoring system and intelligent zone management make it an essential tool for any serious trader looking to decode market structure with precision and confidence.
RSI Mansfield +RSI Mansfield+ – Adaptive Relative Strength Indicator with Divergences
Overview
RSI Mansfield+ is an advanced relative strength indicator that compares your instrument’s performance against a configurable benchmark index or asset (e.g., Bitcoin Dominance, S&P 500). It combines Mansfield normalization, adaptive smoothing techniques, and automatic detection of bullish and bearish divergences (regular and hidden), delivering a comprehensive tool for assessing relative strength across any market and timeframe.
Originality and Motivation
Unlike traditional relative strength scripts, this indicator introduces several distinctive improvements:
Mansfield Normalization: Scales the ratio between the asset and the benchmark relative to its moving average, transforming it into a normalized oscillator that fluctuates around zero, making it easier to spot outperformance or underperformance.
Adaptive Smoothing: Automatically selects whether to use EMA or SMA based on the market type (crypto or stocks) and timeframe (intraday, daily, weekly, monthly), avoiding manual configuration and providing more robust results under varying volatility conditions.
Divergence Detection: Identifies four types of divergences in the Mansfield oscillator to help anticipate potential reversal points or trend confirmations.
Multi-Market Support: Offers benchmark selection among major crypto and global stock indices from a single input.
These enhancements make RSI Mansfield+ more practical and powerful than conventional relative strength scripts with static benchmarks or without divergence capabilities.
Core Concepts
Relative Strength (RS): Compares price evolution between your asset and the selected benchmark.
Mansfield Normalization: Measures how much the RS deviates from its historical moving average, expressed as a scaled oscillator.
Divergences: Detects regular and hidden bullish or bearish divergences within the Mansfield oscillator.
Timeframe Adaptation: Dynamically adjusts moving average lengths based on timeframe and market type.
How It Works
Benchmark Selection
Choose among over 10 indices or market domains (BTC Dominance, ETH Dominance, S&P 500, European indices, etc.).
Ratio Calculation
Computes the price-to-benchmark ratio and smooths it with the adaptive moving average.
Normalization and Scaling
Transforms deviations into a Mansfield oscillator centered around zero.
Dynamic Coloring
Green indicates relative outperformance, red signals underperformance.
Divergence Detection
Automatically identifies bullish and bearish (regular and hidden) divergences by comparing oscillator pivots against price pivots.
Baseline Reference
A clear zero line helps interpret relative strength trends.
Usage Guidelines
Benchmark Comparison
Ideal for traders analyzing whether an asset is outperforming or lagging its sector or market.
Divergence Analysis
Helps detect potential reversal or continuation signals in relative strength.
Multi-Timeframe Compatibility
Can be applied to intraday, daily, weekly, or monthly charts.
Interpretation
Oscillator >0 and green: outperforming the benchmark.
Oscillator <0 and red: underperforming.
Bullish divergences: potential relative strength reversal to the upside.
Bearish divergences: possible loss of momentum or reversal to the downside.
Credits
The concept of Mansfield Relative Strength is based on Stan Weinstein’s original work on relative performance analysis. This script was built entirely from scratch in TradingView Pine Script v6, incorporating original logic for adaptive smoothing, normalized scaling, and divergence detection, without reusing any external open-source code.
CQ_MTF Target Price Lines [BITCOIN HOY]Comprehensive Indicator Script Overview
Intraday, Four Hour, Daily, and Weekly Price Target Lines—A Versatile Tool for Traders
Welcome to a powerful and flexible indicator script designed to enhance your trading experience across multiple timeframes. This script empowers users to interactively set, visualize, and manage price targets, entries, and objectives for both short-term and long-term trading strategies. Whether you are a day trader seeking to mark crucial intraday levels or a long-term investor planning strategic entries, this tool offers an all-encompassing solution.
Key Features
• Multi-Time Frame Price Target Lines: Effortlessly input and display calculated price targets for Intraday, Four Hour, Daily, and Weekly periods, ensuring you always have a clear view of the market objectives at every scale.
• X-Axis Price Control: Set precise x-axis price points for each timeframe, granting you granular control over how and where your target lines appear on the chart.
• Weekly Price Objectives: Enter your calculated price objectives for the current week to remain aligned with your trading plan and adapt to evolving market conditions.
• Long-Term Investment Entry Events: Document and display significant entry events for long-term investments, helping you maintain a strategic perspective while navigating short-term fluctuations.
• Long-Term Price Objectives: Input and track price objectives for your long-term trades, supporting your investment decisions with clearly visualized milestones.
• Customizable Labels and Lines: Each price target is accompanied by clearly labeled lines, making it easy to distinguish between timeframes and targets at a glance.
Optional Price Gauge for Intraday Dynamics
For users who wish to monitor real-time market sentiment, the script includes an optional price gauge. This dynamic feature tracks intraday price movement, providing visual cues to quickly assess whether the prevailing tendency is bullish or bearish. The intuitive gauge aids in confirming your intraday strategies or alerting you to potential reversals.
User Experience and Customization
• Interactive Inputs: All key parameters—price targets, x-axis prices, entry events, and objectives—are entered manually by the user. This approach ensures the script adapts to your personal analysis and trading methodology.
• Easy Visualization: The clear display of lines, labels, and the optional gauge streamlines your chart, making it easier to make informed decisions at a glance.
• Flexible Application: Whether you’re trading short-term swings or building positions for the long haul, the indicator integrates seamlessly into your workflow.
How to Use
• Input your calculated price targets for each timeframe (Intraday, Four Hour, Daily, and Weekly).
• Specify the exact x-axis price points where you’d like the lines to appear for each timeframe.
• For the current week, enter your weekly price objectives for quick reference and planning.
• If you’re a long-term investor, document your key entry events and set long-term price objectives to track their progression.
• To monitor current market momentum, activate the price gauge and follow the visual cues for bullish or bearish trends.
Benefits
• Comprehensive Market Overview: Simultaneously track multiple timeframes and objectives, keeping all critical information at your fingertips.
• Improved Decision Making: Visual clarity and strategic labeling support faster, more confident trading decisions.
• Customizable and Adaptable: Tailor the script to your unique trading style and analytical approach.
Enjoy using the indicator, and happy trading! Let this versatile tool be your companion in navigating the ever-changing tides of the market.
RSI Multi-Frame Multi-Asset
✅ Key Features:
Multi-Asset: Simultaneously analyze Bitcoin, SP500, Nasdaq, DXY, Gold, Oil, VIX and more
Multi-Timeframe: Configure any timeframe for all RSI calculations
Smart Average RSI: Automatically calculates the mean of all active RSI values
Special Data: Includes Bitcoin Hashrate, 10Y-2Y Spread, and US Interest Rates
Built-in Alerts: Automatic notifications on overbought/oversold crossovers
🎯 Why is it Unique?
Instead of looking at 10 different charts, you get an instant macro view of the market. The average RSI shows you the overall strength/weakness of global markets, while individual RSI values let you identify divergences and specific opportunities.
🚀 Perfect For:
Traders seeking correlations between assets
Global markets macro analysis
Identifying divergences between Bitcoin and traditional markets
Multi-timeframe breakout trading
Alt Szn Oracle - Institutional GradeThe Alt Szn Oracle is a macro-level indicator built to help traders front-run altseason by tracking liquidity, dominance rotation, sentiment, and capital flows—all in one signal. It’s designed for those who don’t just chase pumps, but want to understand when the tide is turning and why. This tool doesn't predict specific coin breakouts—it tells you when the market as a whole is gearing up to rotate into higher beta assets like altcoins, including memes and microcaps.
The index consolidates ten macro inputs into a normalized, smoothed score from 0–100. These include Bitcoin and Ethereum dominance, ETH/BTC, altcoin market cap (Total3), relative volume flows, and stablecoin supply (USDT, USDC, DAI)—which act as proxies for risk-on appetite and dry powder entering the system. It also incorporates manually updated sentiment metrics from Google Trends and the Fear & Greed Index, giving it a behavioral edge that most indicators lack.
The logic is simple but powerful: when BTC dominance is falling, ETH/BTC is rising, altcoin volume increases relative to BTC/ETH, and stablecoins start moving—you're likely in the early innings of rotation. The index is also filtered through a volatility threshold and smoothed with an EMA to eliminate chop and fakeouts.
Use this indicator on macro charts like TOTAL3, TOTAL2, or ETHBTC to gauge market health, or overlay it on specific coins like PEPE, DOGE, or SOL to confirm if the tide is in your favor. Interpreting the score is straightforward: readings above 80 suggest euphoria and signal it’s time to de-risk, 60–80 indicates expansion and confirms altseason is underway, 40–60 is neutral, and 20–40 is a capitulation zone where smart money accumulates.
What sets this apart is that it doesn’t just track price—it reflects the flow of capital, the positioning of liquidity, and the sentiment of the crowd. Most altseason indicators are lagging, overfitted, or too simplistic. This one is modular, forward-looking, and grounded in real capital rotation theory.
If you're a trader who wants to time the cycle, not guess it, this is your tool. Refine it, fork it, or expand it to your niche—DeFi, NFTs, meme coins, or L1s. It’s a framework for reading the macro winds, not a signal service. Use it with discipline, and you’ll catch the wave while others drown in noise.
Mongoose Capital: BTC ETF DriftScope ProMongoose Capital: BTC ETF DriftScope Pro
A proprietary indicator for monitoring drift between Bitcoin Spot (BTCUSD) and Bitcoin Spot ETFs (such as IBIT). Designed to detect ETF premium/discount zones and generate actionable Fade or Long bias signals.
What it Does
Tracks IBIT and BTCUSD spread to highlight ETF price deviations.
Calculates correlation Z-Score for ETF/Spot alignment.
Outputs numeric bias signals: Fade (1), Long (1), Neutral (1).
How to Use
Apply to a BTCUSD chart (4H, 1D, or higher recommended).
Open the Data Window to view:
IBIT Spread %
Correlation Z-Score
Correlation %
Bias Flags (Fade, Long, Neutral)
Configure alerts for Fade and Long Bias conditions.
Confirm all signals with your trade plan and risk management.
Methodology
This tool calculates the percentage spread between IBIT and BTC Spot. A rolling Z-Score of the correlation is used to detect periods of significant divergence.
Fade Bias suggests potential short setups in premium zones with high Z-Scores.
Long Bias suggests potential long setups in discount zones with low Z-Scores.
Disclaimer
This indicator is for educational purposes only. It is not financial advice. Use at your own risk and verify signals independently.
Asset Premium/Discount Monitor📊 Overview
The Asset Premium/Discount Monitor is a tool for analyzing the relative value between two correlated assets. It measures when one asset is trading at a premium or discount compared to its historical relationship with another asset, helping traders identify potential mean reversion opportunities, or pairs trading opportunities.
🎯 Use Cases
Perfect for analyzing:
NASDAQ:MSTR vs CRYPTO:BTCUSD - MicroStrategy's premium/discount to Bitcoin
NASDAQ:COIN vs BITSTAMP:BTCUSD - Coinbase's relative value to Bitcoin
NASDAQ:TSLA vs NASDAQ:QQQ - Tesla's premium to tech sector
Regional banks AMEX:KRE vs AMEX:XLF - Individual bank stocks vs financial sector
Any two correlated assets where relative value matters
Example of a trade: MSTR vs BTC - When indicator shows MSTR at 95% percentile (extreme premium): Short MSTR, Buy BTC. Then exit when the spread reverts to the mean, say 40-60% percentile.
🔧 How It Works
Core Calculation
Ratio Analysis: Calculates the price ratio between your asset and the correlated asset
Historical Baseline: Establishes the "normal" relationship using a 252-day moving average. You can change this.
Premium Measurement: Measures current deviation from historical average as a percentage
Statistical Context: Provides percentile rankings and standard deviation bands
The Math
Premium % = (Current Ratio / Historical Average Ratio - 1) × 100
🎨 Customization Options
Correlated Asset: Choose any symbol for comparison
Lookback Period: Adjust historical baseline (50-1000 days)
Smoothing: Reduce noise with moving average (1-50 days)
Visual Toggles: Show/hide bands and percentile lines
Color Themes: Customize premium/discount colors
📊 Interpretation Guide
Premium/Discount Reading
Positive %: Asset trading above historical relationship (premium)
Negative %: Asset trading below historical relationship (discount)
Near 0%: Asset at fair value relative to correlation
Percentile Ranking
90%+: Near recent highs - potential selling opportunity
10% and below: Near recent lows - potential buying opportunity
25-75%: Normal trading range
Signal Classifications
🔴 SELL PREMIUM: Asset expensive relative to recent range
🟡 Premium Rich: Moderately expensive, monitor for reversal
⚪ NEUTRAL: Fair value territory
🟡 Discount Opportunity: Moderately cheap, potential accumulation zone
🟢 BUY DISCOUNT: Asset cheap relative to recent range
🚨 Built-in Alerts
Extreme Premium Alert: Triggers when percentile > 95%
Extreme Discount Alert: Triggers when percentile < 5%
⚠️ Important Notes
Works best with highly correlated assets
Historical relationships can change - monitor correlation strength
Not investment advice - use as one factor in your analysis
Backtest thoroughly before implementing any strategy
🔄 Updates & Future Features
This indicator will be continuously improved based on user feedback. So... please give me your feedback!
4 diffs (CB & IBIT Premium)📊 Script Name: 4 diffs (CB & IBIT Premium)
Version: Pine Script® v6
Overlay: Yes (table displayed on chart)
🧠 What it Does:
This script tracks four important Bitcoin price differentials to monitor spot/perpetual/futures price inefficiencies and ETF premium/discounts, and displays them in a live table on the chart. It helps traders identify arbitrage opportunities or institutional pricing signals.
📈 Displayed Metrics:
Coinbase Premium
→ Difference between Coinbase spot and Binance spot prices.
→ Use case: US vs. offshore spot market divergence.
Coinbase Spot vs Binance Perpetual
→ Difference between Coinbase spot and Binance perpetual price.
→ Use case: Spot-perp basis, often used for funding rate insights or market stress.
Bybit vs Binance Perpetual
→ Difference between Bybit perp and Binance perp price.
→ Use case: Compare derivative pricing across major offshore exchanges.
IBIT Premium (CME vs ETF-implied)
→ Compares CME futures price vs. IBIT’s implied spot BTC value
→ IBIT implied BTC = IBIT ETF price ÷ (BTC held / shares outstanding)
→ Use case: Gauge institutional premium/discount and ETF arbitrage clues.
🛠️ Customization:
Text color of the table is adjustable via the input setting.
📌 Visual Output:
A fixed 2×4 table appears in the top-right corner of the chart.
Each row shows a label and the live price difference in USD.
BTC Correlation CoefficientThe BTCUSDT Correlation Coefficient indicator measures the strength and direction of the relationship between the selected asset (e.g., a stock or altcoin) and the price of BTCUSDT over a chosen time period. It uses a custom correlation function to calculate how closely the asset's price movements align with Bitcoin, returning a value between -1 and +1. A coefficient near +1 indicates strong positive correlation, while values near -1 indicate inverse correlation. This helps traders assess whether the asset tends to follow Bitcoin’s price trends or behave independently, enabling more informed decisions on portfolio diversification and market sentiment alignment.
BTC-OTHERS Liquidity PivotBTC-OTHERS Liquidity Map – 1-hour Multi-Asset Pivot Scanner
WHAT IT DOES
This script tracks liquidity shifts between Bitcoin (BTC) and the broader alt-coin market (the OTHERS market-cap index that excludes the top-10 coins). It labels every confirmed 1-hour swing high or low on both assets, then flags four states:
BearPivot – BTC prints a new swing High while OTHERS does not; liquidity crowds into BTC and alts are weak.
BullPivot – BTC prints a swing Low and OTHERS forms a Higher Low; fresh liquidity starts flowing into stronger alts.
BearCon – BTC prints a swing Low and OTHERS forms a Lower Low; down-trend continuation.
BullCon – No new BTC Low while OTHERS makes a Higher High; up-trend continuation.
Signals appear on the actual pivot bar (offset back by the look-back length), so they never repaint after confirmation.
HOW THE PIVOTS ARE FOUND
• Symmetrical window: “Pivot Len” bars to the left and right (default 21).
• Full confirmation on both sides delivers stable, non-repainting pivots at the cost of about Pivot Len bars’ delay.
• Labels are offset –Pivot Len so they sit on the genuine extreme.
INPUTS
Symbols: BTC symbol and an OTHERS symbol so you can switch exchanges or choose another alt index.
Pivot Len: tighten for faster but noisier signals; widen for cleaner pivots.
Style: customise shape and text colours.
PLOTS AND ALERTS
Four labelled shapes (BearPivot, BullPivot, BearCon, BullCon) plot above or below price. Each label is linked to an alertcondition, so you can create one-click alerts and stay informed without watching the screen.
TYPICAL WORKFLOW
1. Attach the script to any 1-hour BTC chart (or leave the script’s timeframe empty to follow your current chart TF).
2. Turn on alerts to receive push/email notifications.
3. Use the labels as a liquidity compass, combining them with volume, funding or your own strategy for actual entries and exits.
Enjoy and trade safe.
Multi-Confluence Swing Hunter V1# Multi-Confluence Swing Hunter V1 - Complete Description
Overview
The Multi-Confluence Swing Hunter V1 is a sophisticated low timeframe scalping strategy specifically optimized for MSTR (MicroStrategy) trading. This strategy employs a comprehensive point-based scoring system that combines optimized technical indicators, price action analysis, and reversal pattern recognition to generate precise trading signals on lower timeframes.
Performance Highlight:
In backtesting on MSTR 5-minute charts, this strategy has demonstrated over 200% profit performance, showcasing its effectiveness in capturing rapid price movements and volatility patterns unique to MicroStrategy's trading behavior.
The strategy's parameters have been fine-tuned for MSTR's unique volatility characteristics, though they can be optimized for other high-volatility instruments as well.
## Key Innovation & Originality
This strategy introduces a unique **dual scoring system** approach:
- **Entry Scoring**: Identifies swing bottoms using 13+ different technical criteria
- **Exit Scoring**: Identifies swing tops using inverse criteria for optimal exit timing
Unlike traditional strategies that rely on simple indicator crossovers, this system quantifies market conditions through a weighted scoring mechanism, providing objective, data-driven entry and exit decisions.
## Technical Foundation
### Optimized Indicator Parameters
The strategy utilizes extensively backtested parameters specifically optimized for MSTR's volatility patterns:
**MACD Configuration (3,10,3)**:
- Fast EMA: 3 periods (vs standard 12)
- Slow EMA: 10 periods (vs standard 26)
- Signal Line: 3 periods (vs standard 9)
- **Rationale**: These faster parameters provide earlier signal detection while maintaining reliability, particularly effective for MSTR's rapid price movements and high-frequency volatility
**RSI Configuration (21-period)**:
- Length: 21 periods (vs standard 14)
- Oversold: 30 level
- Extreme Oversold: 25 level
- **Rationale**: The 21-period RSI reduces false signals while still capturing oversold conditions effectively in MSTR's volatile environment
**Parameter Adaptability**: While optimized for MSTR, these parameters can be adjusted for other high-volatility instruments. Faster-moving stocks may benefit from even shorter MACD periods, while less volatile assets might require longer periods for optimal performance.
### Scoring System Methodology
**Entry Score Components (Minimum 13 points required)**:
1. **RSI Signals** (max 5 points):
- RSI < 30: +2 points
- RSI < 25: +2 points
- RSI turning up: +1 point
2. **MACD Signals** (max 8 points):
- MACD below zero: +1 point
- MACD turning up: +2 points
- MACD histogram improving: +2 points
- MACD bullish divergence: +3 points
3. **Price Action** (max 4 points):
- Long lower wick (>50%): +2 points
- Small body (<30%): +1 point
- Bullish close: +1 point
4. **Pattern Recognition** (max 8 points):
- RSI bullish divergence: +4 points
- Quick recovery pattern: +2 points
- Reversal confirmation: +4 points
**Exit Score Components (Minimum 13 points required)**:
Uses inverse criteria to identify swing tops with similar weighting system.
## Risk Management Features
### Position Sizing & Risk Control
- **Single Position Strategy**: 100% equity allocation per trade
- **No Overlapping Positions**: Ensures focused risk management
- **Configurable Risk/Reward**: Default 5:1 ratio optimized for volatile assets
### Stop Loss & Take Profit Logic
- **Dynamic Stop Loss**: Based on recent swing lows with configurable buffer
- **Risk-Based Take Profit**: Calculated using risk/reward ratio
- **Clean Exit Logic**: Prevents conflicting signals
## Default Settings Optimization
### Key Parameters (Optimized for MSTR/Bitcoin-style volatility):
- **Minimum Entry Score**: 13 (ensures high-conviction entries)
- **Minimum Exit Score**: 13 (prevents premature exits)
- **Risk/Reward Ratio**: 5.0 (accounts for volatility)
- **Lower Wick Threshold**: 50% (identifies true hammer patterns)
- **Divergence Lookback**: 8 bars (optimal for swing timeframes)
### Why These Defaults Work for MSTR:
1. **Higher Score Thresholds**: MSTR's volatility requires more confirmation
2. **5:1 Risk/Reward**: Compensates for wider stops needed in volatile markets
3. **Faster MACD**: Captures momentum shifts quickly in fast-moving stocks
4. **21-period RSI**: Reduces noise while maintaining sensitivity
## Visual Features
### Score Display System
- **Green Labels**: Entry scores ≥10 points (below bars)
- **Red Labels**: Exit scores ≥10 points (above bars)
- **Large Triangles**: Actual trade entries/exits
- **Small Triangles**: Reversal pattern confirmations
### Chart Cleanliness
- Indicators plotted in separate panes (MACD, RSI)
- TP/SL levels shown only during active positions
- Clear trade markers distinguish signals from actual trades
## Backtesting Specifications
### Realistic Trading Conditions
- **Commission**: 0.1% per trade
- **Slippage**: 3 points
- **Initial Capital**: $1,000
- **Account Type**: Cash (no margin)
### Sample Size Considerations
- Strategy designed for 100+ trade sample sizes
- Recommended timeframes: 4H, 1D for swing trading
- Optimal for trending/volatile markets
## Strategy Limitations & Considerations
### Market Conditions
- **Best Performance**: Trending markets with clear swings
- **Reduced Effectiveness**: Highly choppy, sideways markets
- **Volatility Dependency**: Optimized for moderate to high volatility assets
### Risk Warnings
- **High Allocation**: 100% position sizing increases risk
- **No Diversification**: Single position strategy
- **Backtesting Limitation**: Past performance doesn't guarantee future results
## Usage Guidelines
### Recommended Assets & Timeframes
- **Primary Target**: MSTR (MicroStrategy) - 5min to 15min timeframes
- **Secondary Targets**: High-volatility stocks (TSLA, NVDA, COIN, etc.)
- **Crypto Markets**: Bitcoin, Ethereum (with parameter adjustments)
- **Timeframe Optimization**: 1min-15min for scalping, 30min-1H for swing scalping
### Timeframe Recommendations
- **Primary Scalping**: 5-minute and 15-minute charts
- **Active Monitoring**: 1-minute for precise entries
- **Swing Scalping**: 30-minute to 1-hour timeframes
- **Avoid**: Sub-1-minute (excessive noise) and above 4-hour (reduces scalping opportunities)
## Technical Requirements
- **Pine Script Version**: v6
- **Overlay**: Yes (plots on price chart)
- **Additional Panes**: MACD and RSI indicators
- **Real-time Compatibility**: Confirmed bar signals only
## Customization Options
All parameters are fully customizable through inputs:
- Indicator lengths and levels
- Scoring thresholds
- Risk management settings
- Visual display preferences
- Date range filtering
## Conclusion
This scalping strategy represents a comprehensive approach to low timeframe trading that combines multiple technical analysis methods into a cohesive, quantified system specifically optimized for MSTR's unique volatility characteristics. The optimized parameters and scoring methodology provide a systematic way to identify high-probability scalping setups while managing risk effectively in fast-moving markets.
The strategy's strength lies in its objective, multi-criteria approach that removes emotional decision-making from scalping while maintaining the flexibility to adapt to different instruments through parameter optimization. While designed for MSTR, the underlying methodology can be fine-tuned for other high-volatility assets across various markets.
**Important Disclaimer**: This strategy is designed for experienced scalpers and is optimized for MSTR trading. The high-frequency nature of scalping involves significant risk. Past performance does not guarantee future results. Always conduct your own analysis, consider your risk tolerance, and be aware of commission/slippage costs that can significantly impact scalping profitability.
BTC/Fiat Divergence & Spread Monitor📄 BTC/Fiat Divergence & Spread Monitor
This indicator visualizes Bitcoin’s relative performance across multiple fiat currencies and highlights periods of unusual divergence. It helps traders assess which fiat pairs BTC has outperformed or underperformed over a configurable lookback period and monitor the dynamic spread between the strongest and weakest pairs.
Features:
Relative Performance Matrix:
Ranks BTC returns in 6 fiat pairs, displaying a color-coded table of percentage changes and ranks.
Divergence Spread Oscillator:
Calculates the spread between the top and bottom performing pairs and normalizes this using a Z-Score. The oscillator helps identify when fiat pricing divergence is unusually high or compressed.
Dynamic Smoothing:
Optional Hull Moving Average smoothing to reduce noise in the spread signal.
Customizable Inputs:
Lookback period for percent change.
Z-Score normalization window.
Smoothing length.
Symbol selection for each fiat pair.
Visual Mode Toggle:
Switch between relative performance lines and spread oscillator view.
Potential Use Cases:
Fiat Rotation:
Identify which fiat is relatively weak or strong to optimize your exit currency when taking BTC profits.
Volatility Detection:
Use the spread Z-Score to detect periods of high divergence across fiat pairs, signaling macro FX volatility or dislocations.
Regime Analysis:
Track when fiat spreads are converging or expanding, potentially signaling market regime shifts.
Risk Management:
When divergence is extreme (Z-Score > +1), consider reducing position sizing or waiting for reversion.
Disclaimer:
This indicator is provided for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any security or asset. Always do your own research and consult a qualified financial professional before making trading decisions. Use at your own risk.
Tip:
Experiment with different lookback periods and smoothing settings to adapt the indicator to your timeframe and trading style.
Hull For LoopHull For Loop is a sophisticated trend-following indicator that combines the smoothness of Hull Moving Averages with advanced trend detection algorithms and robust confirmation mechanisms.
## How It Works
At its foundation, Hull For Loop employs a custom-calculated Hull Moving Average using weighted moving average for-loops to achieve optimal smoothness and responsiveness. The system operates through three distinct layers: Hull MA calculation with adjustable smoothing multipliers, advanced trend detection using ATR-based slope thresholds, and multi-bar trend confirmation to filter false breakouts.
The logic flow is elegantly simple yet powerful:
- Hull Calculation combines half-period and full-period weighted moving averages, then applies square-root smoothing for enhanced responsiveness
- Trend Detection analyzes Hull slope against dynamic ATR-based thresholds, classifying market direction as bullish, bearish, or neutral
- Confirmation System requires sustained directional movement across multiple bars before triggering signals, dramatically reducing whipsaws
When Hull slope exceeds the positive threshold, bullish conditions emerge. When it falls below the negative threshold, bearish momentum takes control. The multi-bar confirmation ensures only sustained moves generate actionable signals, making this system ideal for trend-following strategies across volatile markets.
The advanced slope analysis mechanism adapts to market volatility through ATR integration, ensuring sensitivity remains optimal during both high-volatility breakouts and low-volatility consolidations, delivering consistent performance across varying market conditions.
## Features
- Custom Hull Implementation : For-loop calculations for precise weighted moving average control and enhanced smoothness
- Dynamic Trend Detection : ATR-based slope analysis automatically adjusts sensitivity to market volatility conditions
- Multi-Bar Confirmation : Configurable confirmation periods (1-5 bars) eliminate false signals and reduce trading noise
- Advanced Visual System : Dynamic color coding, optional arrows, and statistics table for comprehensive market visualization
- Optimized for Bitcoin : Extensively backtested parameters delivering 128.58% returns with 55% drawdown reduction versus buy-and-hold
- Flexible Configuration : Hull length (1-200), smoothing multiplier (0.1-3.0), sensitivity (1-10), and confirmation settings
- Professional Alerts : Comprehensive alert system for trend changes and entry signals with strength percentages
- Real-time Analytics : Optional statistics table displaying trend direction, strength, Hull value, and current price
## Signal Generation
Hull For Loop generates multiple signal types for comprehensive trend analysis and precise entry/exit timing:
Primary Signals : Confirmed trend changes from bullish to bearish or vice versa - highest probability directional moves
Entry Signals : Initial trend confirmation after multi-bar validation - optimal position entry points
Strength Indicators : Real-time trend strength percentages based on directional momentum over lookback periods
Visual Confirmations : Color-coded Hull line providing instant visual trend status
The confirmation system adds crucial reliability - signals must persist through the specified confirmation period before activation, ensuring only sustained moves trigger trading decisions rather than temporary price fluctuations.
## Visual Implementation
The indicator employs sophisticated visual elements for immediate trend comprehension and professional chart presentation:
- Dynamic Hull Line : Color-changing line (green/red/gray) with configurable width reflecting current trend status
- Optional Directional Arrows : Triangle markers below/above bars marking confirmed trend changes and entry points (disabled by default)
- Statistics Panel : Optional real-time table showing trend direction, strength percentage, Hull value, and current price
- Professional Color Scheme : Customizable bullish (green), bearish (red), and neutral (gray) color system
## Alerts
Hull For Loop includes comprehensive alert conditions for automated trading integration:
- Hull Trend Change - Confirmed trend direction shift with strength percentage
- Hull BUY Signal - Bullish trend confirmation with price and strength data
- Hull SELL Signal - Bearish trend confirmation with price and strength data
- Alert Frequency - Once per bar to prevent spam while maintaining accuracy
All alerts include contextual information: trend direction, current price, and trend strength percentage for informed decision-making.
## Use Cases
Trend Following : Optimized for sustained directional moves with superior drawdown protection compared to buy-and-hold strategies
Swing Trading : Multi-bar confirmation eliminates false breakouts while capturing significant trend changes
Position Trading : Smooth Hull calculation provides stable signals for longer-term directional positioning
Risk Management : Advanced confirmation system dramatically reduces whipsaw trades and false signals
Crypto Trading : Specifically optimized for Bitcoin with parameters delivering exceptional historical performance
The system demonstrates exceptional performance across volatile assets.
CirclesCircles - Support & Resistance Levels
Overview
This indicator plots horizontal support and resistance levels based on W.D. Gann's mathematical approach of dividing 360 degrees by 2 and by 3. These divisions create natural price magnetism points that have historically acted as significant support and resistance levels across all markets and timeframes.
How It Works
360÷2 Levels (Blue): 5.63, 11.25, 33.75, 56.25, 78.75, etc.
360÷3 Levels (Red): 7.5, 15, 30, 37.5, 52.5, 60, 75, etc.
Both Levels (Yellow): 22.5, 45, 67.5, 90, 112.5, 135, 157.5, 180 - These are "doubly strong" as they appear in both calculations
Key Features
Auto-Scaling: Automatically adjusts for any price range (from $0.001 altcoins to $100K+ Bitcoin)
Manual Scaling: Choose from 0.001x to 1000x multipliers or set custom values
Full Customization: Colors, line widths, styles (solid/dashed/dotted)
Historical View: Option to show all levels regardless of current price
Clean Display: Adjustable label positioning and line extensions
Use Cases
Identify potential reversal zones before price reaches them
Set profit targets and stop losses at key mathematical levels
Confirm breakouts when price decisively moves through major levels
Works on all timeframes and all markets (stocks, crypto, forex, commodities)
Gann Theory
W.D. Gann believed that markets move in mathematical harmony based on geometric angles and time cycles. These 360-degree divisions represent natural balance points where price often finds support or resistance, making them valuable for both short-term trading and long-term analysis.
Perfect for traders who use:
Support/Resistance trading
Fibonacci levels
Pivot points
Mathematical/geometric analysis
Multi-timeframe analysis
Rolling VWAP LevelsRolling VWAP Levels Indicator
Overview
Dynamic horizontal lines showing rolling Volume Weighted Average Price (VWAP) levels for multiple timeframes (7D, 30D, 90D, 365D) that update in real-time as new bars form.
Who This Is For
Day traders using VWAP as support/resistance
Swing traders analyzing multi-timeframe price structure
Scalpers looking for mean reversion entries
Options traders needing volatility bands for strike selection
Institutional traders tracking volume-weighted fair value
Risk managers requiring dynamic stop levels
How To Trade With It
Mean Reversion Strategies:
Buy when price is below VWAP and showing bullish divergence
Sell when price is above VWAP and showing bearish signals
Use multiple timeframes - enter on shorter, confirm on longer
Target opposite VWAP level for profit taking
Breakout Trading:
Watch for price breaking above/below key VWAP levels with volume
Use 7D VWAP for intraday breakouts
Use 30D/90D VWAP for swing trade breakouts
Confirm breakout with move beyond first standard deviation band
Support/Resistance Trading:
VWAP levels act as dynamic support in uptrends
VWAP levels act as dynamic resistance in downtrends
Multiple timeframe VWAP confluence creates stronger levels
Use standard deviation bands as additional S/R zones
Risk Management:
Place stops beyond next VWAP level
Use standard deviation bands for position sizing
Exit partial positions at VWAP levels
Monitor distance table for overextended moves
Key Features
Real-time Updates: Lines move and extend as new bars form
Individual Styling: Custom colors, widths, styles for each timeframe
Standard Deviation Bands: Optional volatility bands with custom multipliers
Smart Labels: Positioned above, below, or diagonally relative to lines
Distance Table: Shows percentage distance from each VWAP level
Alert System: Get notified when price crosses VWAP levels
Memory Efficient: Automatically cleans up old drawing objects
Settings Explained
Display Group: Show/hide labels, font size, line transparency, positioning
Individual VWAP Groups: Color, line width (1-5), line style for each timeframe
Standard Deviation Bands: Enable bands with custom multipliers (0.5, 1.0, 1.5, 2.0, etc.)
Labels Group: Position (8 options including diagonal), custom text, price display
Additional Info: Distance table, alert conditions
Technical Implementation
Uses rolling arrays to maintain sliding windows of price*volume data. The core calculation function processes both VWAP and standard deviation efficiently. Lines are created dynamically and updated every bar. Memory management prevents object accumulation through automatic cleanup.
Best Practices
Start with 7D and 30D VWAP for most strategies
Add 90D/365D for longer-term context
Use standard deviation bands when volatility matters
Position labels to avoid chart clutter
Enable distance table during high volatility periods
Set alerts for key VWAP level breaks
Market Applications
Forex: Major pairs during London/NY sessions
Stocks: Large cap names with good volume
Crypto: Bitcoin, Ethereum, major altcoins
Futures: ES, NQ, CL, GC with continuous volume
Options: Use SD bands for strike selection and volatility assessment
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
