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Langlands-Operadic Möbius Vortex (LOMV)Langlands-Operadic Möbius Vortex (LOMV) Where Pure Mathematics Meets Market Reality A Revolutionary Synthesis of Number Theory, Category Theory, and Market Dynamics 🎓 THEORETICAL FOUNDATION The Langlands-Operadic Möbius Vortex represents a groundbreaking fusion of three profound mathematical frameworks that have never before been combined for market analysis: The Langlands Program: Harmonic Analysis in Markets Developed by Robert Langlands (Fields Medal recipient), the Langlands Program creates bridges between number theory, algebraic geometry, and harmonic analysis. In our indicator: L-Function Implementation: - Utilizes the Möbius function μ(n) for weighted price analysis - Applies Riemann zeta function convergence principles - Calculates quantum harmonic resonance between -2 and +2 - Measures deep mathematical patterns invisible to traditional analysis The L-Function core calculation employs: L_sum = Σ(return_val × μ(n) × n^(-s)) Where s is the critical strip parameter (0.5-2.5), controlling mathematical precision and signal smoothness. Operadic Composition Theory: Multi-Strategy Democracy Category theory and operads provide the mathematical framework for composing multiple trading strategies into a unified signal. This isn't simple averaging - it's mathematical composition using: Strategy Composition Arity (2-5 strategies): - Momentum analysis via RSI transformation - Mean reversion through Bollinger Band mathematics - Order Flow Polarity Index (revolutionary T3-smoothed volume analysis) - Trend detection using Directional Movement - Higher timeframe momentum confirmation Agreement Threshold System: Democratic voting where strategies must reach consensus before signal generation. This prevents false signals during market uncertainty. Möbius Function: Number Theory in Action The Möbius function μ(n) forms the mathematical backbone: - μ(n) = 1 if n is a square-free positive integer with even number of prime factors - μ(n) = -1 if n is a square-free positive integer with odd number of prime factors - μ(n) = 0 if n has a squared prime factor This creates oscillating weights that reveal hidden market periodicities and harmonic structures. 🔧 COMPREHENSIVE INPUT SYSTEM Langlands Program Parameters Modular Level N (5-50, default 30): Primary lookback for quantum harmonic analysis. Optimized by timeframe: - Scalping (1-5min): 15-25 - Day Trading (15min-1H): 25-35 - Swing Trading (4H-1D): 35-50 - Asset-specific: Crypto 15-25, Stocks 30-40, Forex 35-45 L-Function Critical Strip (0.5-2.5, default 1.5): Controls Riemann zeta convergence precision: - Higher values: More stable, smoother signals - Lower values: More reactive, catches quick moves - High frequency: 0.8-1.2, Medium: 1.3-1.7, Low: 1.8-2.3 Frobenius Trace Period (5-50, default 21): Galois representation lookback for price-volume correlation: - Measures harmonic relationships in market flows - Scalping: 8-15, Day Trading: 18-25, Swing: 25-40 HTF Multi-Scale Analysis: Higher timeframe context prevents trading against major trends: - Provides market bias and filters signals - Improves win rates by 15-25% through trend alignment Operadic Composition Parameters Strategy Composition Arity (2-5, default 4): Number of algorithms composed for final signal: - Conservative: 4-5 strategies (higher confidence) - Moderate: 3-4 strategies (balanced approach) - Aggressive: 2-3 strategies (more frequent signals) Category Agreement Threshold (2-5, default 3): Democratic voting minimum for signal generation: - Higher agreement: Fewer but higher quality signals - Lower agreement: More signals, potential false positives Swiss-Cheese Mixing (0.1-0.5, default 0.382): Golden ratio φ⁻¹ based blending of trend factors: - 0.382 is φ⁻¹, optimal for natural market fractals - Higher values: Stronger trend following - Lower values: More contrarian signals OFPI Configuration: - OFPI Length (5-30, default 14): Order Flow calculation period - T3 Smoothing (3-10, default 5): Advanced exponential smoothing - T3 Volume Factor (0.5-1.0, default 0.7): Smoothing aggressiveness control Unified Scoring System Component Weights (sum ≈ 1.0): - L-Function Weight (0.1-0.5, default 0.3): Mathematical harmony emphasis - Galois Rank Weight (0.1-0.5, default 0.2): Market structure complexity - Operadic Weight (0.1-0.5, default 0.3): Multi-strategy consensus - Correspondence Weight (0.1-0.5, default 0.2): Theory-practice alignment Signal Threshold (0.5-10.0, default 5.0): Quality filter producing: - 8.0+: EXCEPTIONAL signals only - 6.0-7.9: STRONG signals - 4.0-5.9: MODERATE signals - 2.0-3.9: WEAK signals 🎨 ADVANCED VISUAL SYSTEM Multi-Dimensional Quantum Aura Bands Five-layer resonance field showing market energy: - Colors: Theme-matched gradients (Quantum purple, Holographic cyan, etc.) - Expansion: Dynamic based on score intensity and volatility - Function: Multi-timeframe support/resistance zones Morphism Flow Portals Category theory visualization showing market topology: - Green/Cyan Portals: Bullish mathematical flow - Red/Orange Portals: Bearish mathematical flow - Size/Intensity: Proportional to signal strength - Recursion Depth (1-8): Nested patterns for flow evolution Fractal Grid System Dynamic support/resistance with projected L-Scores: - Multiple Timeframes: 10, 20, 30, 40, 50-period highs/lows - Smart Spacing: Prevents level overlap using ATR-based minimum distance - Projections: Estimated signal scores when price reaches levels - Usage: Precise entry/exit timing with mathematical confirmation Wick Pressure Analysis Rejection level prediction using candle mathematics: - Upper Wicks: Selling pressure zones (purple/red lines) - Lower Wicks: Buying pressure zones (purple/green lines) - Glow Intensity (1-8): Visual emphasis and line reach - Application: Confluence with fractal grid creates high-probability zones Regime Intensity Heatmap Background coloring showing market energy: - Black/Dark: Low activity, range-bound markets - Purple Glow: Building momentum and trend development - Bright Purple: High activity, strong directional moves - Calculation: Combines trend, momentum, volatility, and score intensity Six Professional Themes - Quantum: Purple/violet for general trading and mathematical focus - Holographic: Cyan/magenta optimized for cryptocurrency markets - Crystalline: Blue/turquoise for conservative, stability-focused trading - Plasma: Gold/magenta for high-energy volatility trading - Cosmic Neon: Bright neon colors for maximum visibility and aggressive trading 📊 INSTITUTIONAL-GRADE DASHBOARD Unified AI Score Section - Total Score (-10 to +10): Primary decision metric - >5: Strong bullish signals - <-5: Strong bearish signals - Quality ratings: EXCEPTIONAL > STRONG > MODERATE > WEAK - Component Analysis: Individual L-Function, Galois, Operadic, and Correspondence contributions Order Flow Analysis Revolutionary OFPI integration: - OFPI Value (-100% to +100%): Real buying vs selling pressure - Visual Gauge: Horizontal bar chart showing flow intensity - Momentum Status: SHIFTING, ACCELERATING, STRONG, MODERATE, or WEAK - Trading Application: Flow shifts often precede major moves Signal Performance Tracking - Win Rate Monitoring: Real-time success percentage with emoji indicators - Signal Count: Total signals generated for frequency analysis - Current Position: LONG, SHORT, or NONE with P&L tracking - Volatility Regime: HIGH, MEDIUM, or LOW classification Market Structure Analysis - Möbius Field Strength: Mathematical field oscillation intensity - CHAOTIC: High complexity, use wider stops - STRONG: Active field, normal position sizing - MODERATE: Balanced conditions - WEAK: Low activity, consider smaller positions - HTF Trend: Higher timeframe bias (BULL/BEAR/NEUTRAL) - Strategy Agreement: Multi-algorithm consensus level Position Management When in trades, displays: - Entry Price: Original signal price - Current P&L: Real-time percentage with risk level assessment - Duration: Bars in trade for timing analysis - Risk Level: HIGH/MEDIUM/LOW based on current exposure 🚀 SIGNAL GENERATION LOGIC Balanced Long/Short Architecture The indicator generates signals through multiple convergent pathways: Long Entry Conditions: - Score threshold breach with algorithmic agreement - Strong bullish order flow (OFPI > 0.15) with positive composite signal - Bullish pattern recognition with mathematical confirmation - HTF trend alignment with momentum shifting - Extreme bullish OFPI (>0.3) with any positive score Short Entry Conditions: - Score threshold breach with bearish agreement - Strong bearish order flow (OFPI < -0.15) with negative composite signal - Bearish pattern recognition with mathematical confirmation - HTF trend alignment with momentum shifting - Extreme bearish OFPI (<-0.3) with any negative score Exit Logic: - Score deterioration below continuation threshold - Signal quality degradation - Opposing order flow acceleration - 10-bar minimum between signals prevents overtrading ⚙️ OPTIMIZATION GUIDELINES Asset-Specific Settings Cryptocurrency Trading: - Modular Level: 15-25 (capture volatility) - L-Function Precision: 0.8-1.3 (reactive to price swings) - OFPI Length: 10-20 (fast correlation shifts) - Cascade Levels: 5-7, Theme: Holographic Stock Index Trading: - Modular Level: 25-35 (balanced trending) - L-Function Precision: 1.5-1.8 (stable patterns) - OFPI Length: 14-20 (standard correlation) - Cascade Levels: 4-5, Theme: Quantum Forex Trading: - Modular Level: 35-45 (smooth trends) - L-Function Precision: 1.6-2.1 (high smoothing) - OFPI Length: 18-25 (disable volume amplification) - Cascade Levels: 3-4, Theme: Crystalline Timeframe Optimization Scalping (1-5 minute charts): - Reduce all lookback parameters by 30-40% - Increase L-Function precision for noise reduction - Enable all visual elements for maximum information - Use Small dashboard to save screen space Day Trading (15 minute - 1 hour): - Use default parameters as starting point - Adjust based on market volatility - Normal dashboard provides optimal information density - Focus on OFPI momentum shifts for entries Swing Trading (4 hour - Daily): - Increase lookback parameters by 30-50% - Higher L-Function precision for stability - Large dashboard for comprehensive analysis - Emphasize HTF trend alignment 🏆 ADVANCED TRADING STRATEGIES The Mathematical Confluence Method 1. Wait for Fractal Grid level approach 2. Confirm with projected L-Score > threshold 3. Verify OFPI alignment with direction 4. Enter on portal signal with quality ≥ STRONG 5. Exit on score deterioration or opposing flow The Regime Trading System 1. Monitor Aether Flow background intensity 2. Trade aggressively during bright purple periods 3. Reduce position size during dark periods 4. Use Möbius Field strength for stop placement 5. Align with HTF trend for maximum probability The OFPI Momentum Strategy 1. Watch for momentum shifting detection 2. Confirm with accelerating flow in direction 3. Enter on immediate portal signal 4. Scale out at Fibonacci levels 5. Exit on flow deceleration or reversal ⚠️ RISK MANAGEMENT INTEGRATION Mathematical Position Sizing - Use Galois Rank for volatility-adjusted sizing - Möbius Field strength determines stop width - Fractal Dimension guides maximum exposure - OFPI momentum affects entry timing Signal Quality Filtering - Trade only STRONG or EXCEPTIONAL quality signals - Increase position size with higher agreement levels - Reduce risk during CHAOTIC Möbius field periods - Respect HTF trend alignment for directional bias 🔬 DEVELOPMENT JOURNEY Creating the LOMV was an extraordinary mathematical undertaking that pushed the boundaries of what's possible in technical analysis. This indicator almost didn't happen. The theoretical complexity nearly proved insurmountable. The Mathematical Challenge Implementing the Langlands Program required deep research into: - Number theory and the Möbius function - Riemann zeta function convergence properties - L-function analytical continuation - Galois representations in finite fields The mathematical literature spans decades of pure mathematics research, requiring translation from abstract theory to practical market application. The Computational Complexity Operadic composition theory demanded: - Category theory implementation in Pine Script - Multi-dimensional array management for strategy composition - Real-time democratic voting algorithms - Performance optimization for complex calculations The Integration Breakthrough Bringing together three disparate mathematical frameworks required: - Novel approaches to signal weighting and combination - Revolutionary Order Flow Polarity Index development - Advanced T3 smoothing implementation - Balanced signal generation preventing directional bias Months of intensive research culminated in breakthrough moments when the mathematics finally aligned with market reality. The result is an indicator that reveals market structure invisible to conventional analysis while maintaining practical trading utility. 🎯 PRACTICAL IMPLEMENTATION Getting Started 1. Apply indicator with default settings 2. Select appropriate theme for your markets 3. Observe dashboard metrics during different market conditions 4. Practice signal identification without trading 5. Gradually adjust parameters based on observations Signal Confirmation Process - Never trade on score alone - verify quality rating - Confirm OFPI alignment with intended direction - Check fractal grid level proximity for timing - Ensure Möbius field strength supports position size - Validate against HTF trend for bias confirmation Performance Monitoring - Track win rate in dashboard for strategy assessment - Monitor component contributions for optimization - Adjust threshold based on desired signal frequency - Document performance across different market regimes 🌟 UNIQUE INNOVATIONS 1. First Integration of Langlands Program mathematics with practical trading 2. Revolutionary OFPI with T3 smoothing and momentum detection 3. Operadic Composition using category theory for signal democracy 4. Dynamic Fractal Grid with projected L-Score calculations 5. Multi-Dimensional Visualization through morphism flow portals 6. Regime-Adaptive Background showing market energy intensity 7. Balanced Signal Generation preventing directional bias 8. Professional Dashboard with institutional-grade metrics 📚 EDUCATIONAL VALUE The LOMV serves as both a practical trading tool and an educational gateway to advanced mathematics. Traders gain exposure to: - Pure mathematics applications in markets - Category theory and operadic composition - Number theory through Möbius function implementation - Harmonic analysis via L-function calculations - Advanced signal processing through T3 smoothing ⚖️ RESPONSIBLE USAGE This indicator represents advanced mathematical research applied to market analysis. While the underlying mathematics are rigorously implemented, markets remain inherently unpredictable. Key Principles: - Use as part of comprehensive trading strategy - Implement proper risk management at all times - Backtest thoroughly before live implementation - Understand that past performance does not guarantee future results - Never risk more than you can afford to lose The mathematics reveal deep market structure, but successful trading requires discipline, patience, and sound risk management beyond any indicator. 🔮 CONCLUSION The Langlands-Operadic Möbius Vortex represents a quantum leap forward in technical analysis, bringing PhD-level pure mathematics to practical trading while maintaining visual elegance and usability. From the harmonic analysis of the Langlands Program to the democratic composition of operadic theory, from the number-theoretic precision of the Möbius function to the revolutionary Order Flow Polarity Index, every component works in mathematical harmony to reveal the hidden order within market chaos. This is more than an indicator - it's a mathematical lens that transforms how you see and understand market structure. Trade with mathematical precision. Trade with the LOMV. *"Mathematics is the language with which God has written the universe." - Galileo Galilei* *In markets, as in nature, profound mathematical beauty underlies apparent chaos. The LOMV reveals this hidden order.* — Dskyz, Trade with insight. Trade with anticipation.
Indicador Pine Script®
por DskyzInvestments
4
Adaptive Volume‐Demand‐Index (AVDI)Demand Index (according to James Sibbet) – Short Description The Demand Index (DI) was developed by James Sibbet to measure real “buying” vs. “selling” strength (Demand vs. Supply) using price and volume data. It is not a standalone trading signal, but rather a filter and trend confirmer that should always be used together with chart structure and additional indicators. --- \ 1. Calculation Basis\ 1. Volume Normalization $$ \text{normVol}_t = \frac{\text{Volume}_t}{\mathrm{EMA}(\text{Volume},\,n_{\text{Vol}})_t} \quad(\text{e.g., }n_{\text{Vol}} = 13) $$ This smooths out extremely high volume spikes and compares them to the average (≈ 1 means “average volume”). 2. Price Factor $$ \text{priceFactor}_t = \frac{\text{Close}_t - \text{Open}_t}{\text{Open}_t}. $$ Positive values for bullish bars, negative for bearish bars. 3. Component per Bar $$ \text{component}_t = \text{normVol}_t \times \text{priceFactor}_t. $$ If volume is above average (> 1) and the price rises slightly, this yields a noticeably positive value; conversely if the price falls. 4. Raw DI (Rolling Sum) Over a window of \$w\$ bars (e.g., 20): $$ \text{RawDI}_t = \sum_{i=0}^{w-1} \text{component}_{\,t-i}. $$ Alternatively, recursively for \$t \ge w\$: $$ \text{RawDI}_t = \text{RawDI}_{t-1} + \text{component}_t - \text{component}_{\,t-w}. $$ 5. Optional EMA Smoothing An EMA over RawDI (e.g., \$n\_{\text{DI}} = 50\$) reduces short-term fluctuations and highlights medium-term trends: $$ \text{EMA\_DI}_t = \mathrm{EMA}(\text{RawDI},\,n_{\text{DI}})_t. $$ 6.Zero Line Handy guideline: RawDI > 0: Accumulated buying power dominates. RawDI < 0: Accumulated selling power dominates. 2. Interpretation & Application Crossing Zero RawDI above zero → Indication of increasing buying pressure (potential long signal). RawDI below zero → Indication of increasing selling pressure (potential short signal).  Not to be used alone for entry—always confirm with price action. RawDI vs. EMA_DI RawDI > EMA\_DI → Acceleration of demand. RawDI < EMA\_DI → Weakening of demand. Divergences Price makes a new high, RawDI does not make a higher high → potential weakness in the uptrend. Price makes a new low, RawDI does not make a lower low → potential exhaustion of the downtrend. 3. Typical Signals (for Beginners) \ 1. Long Setup\ RawDI crosses zero from below, RawDI > EMA\_DI (acceleration), Price closes above a short-term swing high or resistance. Stop-Loss: just below the last swing low, Take-Profit/Trailing: on reversal signals or fixed R\:R. 2. Short Setup RawDI crosses zero from above, RawDI < EMA\_DI (increased selling pressure), Price closes below a short-term swing low or support. Stop-Loss: just above the last swing high. --- 4. Notes and Parameters Recommended Values (Beginners): Volume EMA (n₍Vol₎) = 13 RawDI window (w) = 20 EMA over DI (n₍DI₎) = 50 (medium-term) or 1 (no smoothing) Attention:\ NEVER use in isolation. Always in combination with price action analysis (trendlines, support/resistance, candlestick patterns). Especially during volatile news phases, RawDI can fluctuate strongly → EMA\_DI helps to avoid false signals. --- Conclusion The Demand Index by James Sibbet is a powerful filter to assess price movements by their volume backing. It shows whether a rally is truly driven by demand or merely a short-term volume anomaly. In combination with classic chart analysis and risk management, it helps to identify robust entry points and potential trend reversals earlier.
Indicador Pine Script®
por TradeQUO
MACD Full [Titans_Invest]MACD Full — A Smarter, More Flexible MACD. Looking for a MACD with real customization power? We present one of the most complete public MACD indicators available on TradingView. It maintains the classic MACD structure but is enhanced with 20 fully customizable long entry conditions and 20 short entry conditions , giving you precise control over your strategy. Plus, it’s fully automation-ready, making it ideal for quantitative systems and algorithmic trading. Whether you're a discretionary trader or a bot developer, this tool is built to seamlessly adapt to your style. ⯁ WHAT IS THE MACD❓ The Moving Average Convergence Divergence (MACD) is a technical analysis indicator developed by Gerald Appel. It measures the relationship between two moving averages of a security’s price to identify changes in momentum, direction, and strength of a trend. The MACD is composed of three components: the MACD line, the signal line, and the histogram. ⯁ HOW TO USE THE MACD❓ The MACD is calculated by subtracting the 26-period Exponential Moving Average (EMA) from the 12-period EMA. A 9-period EMA of the MACD line, called the signal line, is then plotted on top of the MACD line. The MACD histogram represents the difference between the MACD line and the signal line. Here are the primary signals generated by the MACD: Bullish Crossover: When the MACD line crosses above the signal line, indicating a potential buy signal. Bearish Crossover: When the MACD line crosses below the signal line, indicating a potential sell signal. Divergence: When the price of the security diverges from the MACD, suggesting a potential reversal. Overbought/Oversold Conditions: Indicated by the MACD line moving far away from the signal line, though this is less common than in oscillators like the RSI. ⯁ ENTRY CONDITIONS The conditions below are fully flexible and allow for complete customization of the signal. ______________________________________________________ 🔹 CONDITIONS TO BUY 📈 ______________________________________________________  •   Signal Validity: The signal will remain valid for X bars .  •   Signal Sequence: Configurable as AND or OR . 🔹 MACD > Signal Smoothing 🔹 MACD < Signal Smoothing 🔹 Histogram > 0 🔹 Histogram < 0 🔹 Histogram Positive 🔹 Histogram Negative 🔹 MACD > 0 🔹 MACD < 0 🔹 Signal > 0 🔹 Signal < 0 🔹 MACD > Histogram 🔹 MACD < Histogram 🔹 Signal > Histogram 🔹 Signal < Histogram 🔹 MACD (Crossover) Signal 🔹 MACD (Crossunder) Signal 🔹 MACD (Crossover) 0 🔹 MACD (Crossunder) 0 🔹 Signal (Crossover) 0 🔹 Signal (Crossunder) 0 ______________________________________________________ ______________________________________________________ 🔸 CONDITIONS TO SELL 📉 ______________________________________________________  •   Signal Validity: The signal will remain valid for X bars .  •   Signal Sequence: Configurable as AND or OR . 🔸 MACD > Signal Smoothing 🔸 MACD < Signal Smoothing 🔸 Histogram > 0 🔸 Histogram < 0 🔸 Histogram Positive 🔸 Histogram Negative 🔸 MACD > 0 🔸 MACD < 0 🔸 Signal > 0 🔸 Signal < 0 🔸 MACD > Histogram 🔸 MACD < Histogram 🔸 Signal > Histogram 🔸 Signal < Histogram 🔸 MACD (Crossover) Signal 🔸 MACD (Crossunder) Signal 🔸 MACD (Crossover) 0 🔸 MACD (Crossunder) 0 🔸 Signal (Crossover) 0 🔸 Signal (Crossunder) 0 ______________________________________________________ ______________________________________________________ 🤖 AUTOMATION 🤖 • You can automate the BUY and SELL signals of this indicator. ______________________________________________________ ______________________________________________________ ⯁ UNIQUE FEATURES ______________________________________________________ Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Condition Table: BUY/SELL Condition Labels: BUY/SELL Plot Labels in the Graph Above: BUY/SELL Automate and Monitor Signals/Alerts: BUY/SELL Signal Validity: The signal will remain valid for X bars Signal Sequence: Configurable as AND/OR Table of Conditions: BUY/SELL Conditions Label: BUY/SELL Plot Labels in the graph above: BUY/SELL Automate & Monitor Signals/Alerts: BUY/SELL ______________________________________________________ 📜 SCRIPT : MACD Full 🎴 Art by  : @Titans_Invest & @DiFlip 👨‍💻 Dev by : @Titans_Invest & @DiFlip 🎑 Titans Invest — The Wizards Without Gloves 🧤 ✨ Enjoy! ______________________________________________________ o Mission 🗺 • Inspire Traders to manifest Magic in the Market. o Vision 𐓏 • To elevate collective Energy 𐓷𐓏
Indicador Pine Script®
por Titans_Invest
8
DWMY Opens (for aggr. charts) by Koenigsegg🟣 DWMY Opens (for Aggregated Charts) by Koenigsegg Revolutionary compatibility with aggregated charts – This indicator represents a significant breakthrough in displaying Daily, Weekly, Monthly, and Yearly opening levels on aggregated chart types where traditional DWMY indicators have historically failed to function properly. Complete aggregated chart support – Unlike previous Daily Weekly Monthly Yearly Opens indicators that experienced severe limitations when pulling data from non-standard chart types, this version is specifically engineered to work flawlessly with aggregated charts, range bars, Renko charts, Point & Figure charts, and all other non-time-based chart constructions. Persistent horizontal reference lines – The indicator draws four distinct horizontal lines representing the opening prices of the current Daily, Weekly, Monthly, and Yearly periods, extending these levels forward into future bars to provide clear reference points for key support and resistance analysis. Advanced customization capabilities – Features comprehensive user controls including custom label naming for each timeframe, adjustable line colors with independent color selection for Daily, Weekly, Monthly, and Yearly levels, configurable line width settings, and variable label font sizes ranging from tiny to huge. Dynamic label positioning system – Implements a sophisticated label placement mechanism with configurable tick offset positioning and fixed end-bars-ahead projection, ensuring labels remain visible and properly positioned regardless of chart zoom level or timeframe. Intelligent period detection logic – Utilizes advanced Pine Script time change detection algorithms specifically optimized for aggregated charts, accurately identifying new Daily, Weekly, Monthly, and Yearly periods even when traditional time-based functions fail on non-standard chart types. Performance-optimized architecture – Built with efficient persistent variable storage using the var keyword, minimizing computational overhead while maintaining real-time updates across all timeframe levels simultaneously. Professional visual presentation – Delivers clean, uncluttered chart visualization with strategically positioned labels that clearly identify each timeframe level without interfering with price action analysis. Universal market compatibility – Functions seamlessly across all asset classes including stocks, forex, cryptocurrencies, commodities, and indices, adapting automatically to different tick sizes and price scales through syminfo.mintick integration. Pine Script v6 foundation – Leverages the latest Pine Script version 6 capabilities, ensuring optimal performance, stability, and compatibility with current and future TradingView platform updates. This indicator solves a critical limitation that has long plagued traders using aggregated chart types, finally enabling reliable access to essential Daily, Weekly, Monthly, and Yearly opening levels that serve as fundamental support and resistance zones in technical analysis. The breakthrough lies in its ability to maintain accurate period detection and level plotting regardless of the underlying chart construction methodology. 🟣 How It Works Automatic period detection – The indicator continuously monitors for time changes across four distinct timeframes using ta.change(time()) functions for Daily and Weekly periods, month transitions for Monthly levels, and year changes for Yearly opens, ensuring precise identification of new period beginnings. Real-time level updates – When a new period is detected, the indicator captures the opening price at that exact moment and immediately establishes a horizontal line from that bar extending forward to a configurable number of bars ahead, creating persistent reference levels. Dynamic line management – Each timeframe maintains its own dedicated line object and label, with the indicator continuously updating the endpoint coordinates and label positions as new bars form, ensuring the levels always project the specified distance into the future. Intelligent label placement – Labels are positioned at the end of each line with automatic vertical offset based on the symbol’s minimum tick size, preventing overlap with price action while maintaining clear identification of each timeframe level. 🟣 Pro Tips for Optimal Usage Multi-timeframe confluence – Look for areas where multiple DWMY levels converge within close proximity, as these zones typically act as stronger support or resistance levels due to increased market participant attention at these psychological price points. Breakout confirmation strategy – When price breaks above or below a significant DWMY level with strong volume, the broken level often transforms into support (if broken upward) or resistance (if broken downward), providing excellent entry and exit reference points. Range trading opportunities – On ranging markets, use Daily and Weekly opens as potential reversal zones, especially when price approaches these levels during low-volume periods or near session opens when institutional activity increases. Timeframe alignment technique – For swing trading, prioritize trades that align with the direction of the break from Weekly or Monthly opens, while using Daily opens for precise entry timing and position management. Chart type optimization – This indicator excels on Renko, Range, and Point & Figure charts where traditional time-based DWMY indicators fail, making it invaluable for traders who prefer these aggregated chart types for cleaner price action analysis. Important Disclaimer: This indicator is provided for educational and informational purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any financial instrument. All trading involves risk, and past performance does not guarantee future results. Please conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author is not responsible for any losses incurred from using this indicator.
Indicador Pine Script®
por CryptoPandaTA
BTC Event Contract Signal Indicator# BTC Event Contract Signal Indicator **Version**: V1.0 **Last Updated**: December 21, 2024 **Author**: OxJohannWu **Type**: Pine Script v6 Indicator (Overlay) **Timeframes**: Optimized for 1-minute BTC data, supports all timeframes ## 📋 Overview The BTC Event Contract Signal Indicator is a sophisticated technical analysis tool designed specifically for Bitcoin event contracts (binary options). This indicator provides real-time buy/sell signals with comprehensive contract tracking, performance statistics, and settlement monitoring - all displayed in Beijing time (UTC+8). ### Key Features - **Smart Signal Generation**: Multi-layered technical analysis with adaptive filtering - **Real-time Contract Tracking**: Monitor active contracts with automatic settlement detection - **Performance Analytics**: Detailed win/loss statistics with daily breakdowns - **Multi-timeframe Optimization**: Auto-adjusts parameters based on chart timeframe - **Beijing Time Display**: All timestamps converted to Beijing timezone - **Alert System**: TradingView alerts for all signal types ## 🎯 Trading Philosophy This indicator combines correlation analysis, MACD momentum, and StochRSI oscillator signals to identify high-probability entry points for Bitcoin event contracts. The system prioritizes quality over quantity, using intelligent filtering to minimize false signals and maximize win rates. ## ⚙️ Parameter Configuration ### 📊 Technical Indicator Settings - **Auto Timeframe Optimization**: Automatically selects optimal parameters based on current timeframe - **MACD Settings**: Fast (8), Slow (21), Signal (5) - optimized for 1-minute BTC data - **RSI Period**: 6 periods for responsive momentum detection - **Stochastic Settings**: K smoothing (2), Period (6) for precise overbought/oversold levels ### 🔗 Correlation Analysis - **Short-term Correlation**: 3-period correlation for immediate trend changes - **Long-term Correlation**: 25-period correlation for broader market context - **Correlation Slope**: Tracks momentum changes in price correlation ### 🎯 Smart Signal Optimization Three intelligent modes to suit different trading styles: #### Smart Balance Mode (Default) - **Target Win Rate**: 80%+ - **Expected Signals**: 8-15 per day - **Filtering**: 6-7 technical conditions - **Best For**: Balanced trading with consistent profits #### High Frequency Mode - **Target Win Rate**: 75%+ - **Expected Signals**: 15-25 per day - **Filtering**: 4 core technical conditions - **Best For**: Active traders seeking more opportunities #### Premium Quality Mode - **Target Win Rate**: 85%+ - **Expected Signals**: 5-10 per day - **Filtering**: 8 strict technical conditions - **Best For**: Conservative traders prioritizing accuracy ### ⏰ Event Contract Settings - **Contract Duration Options**: 10 Minutes, 30 Minutes, 1 Hour, 24 Hours - **Single Contract Rule**: Only one active contract at a time - **Auto Settlement**: Automatic win/loss detection at expiry ## 📈 Signal Generation Logic ### Core Technical Conditions 1. **Correlation Breakout**: Short-term correlation slope changes direction 2. **MACD Momentum**: MACD line above/below signal line with positive/negative slope 3. **StochRSI Position**: K-line slope changes indicating momentum shift ### Smart Filtering System The indicator applies progressive filtering based on selected mode: #### Basic Filters (All Modes) - Volume above 1.4x average - Correlation momentum confirmation - MACD direction alignment #### Advanced Filters (Smart Balance & Premium) - Price action quality (body-to-wick ratio > 0.4) - Momentum strength validation - RSI safe zone (25-75 range) - Optional trend filter with EMA confirmation - Optional multi-timeframe confirmation #### Premium Filters (Premium Quality Only) - Enhanced volume threshold (1.8x average) - Stricter correlation momentum (>1.0) - Multi-timeframe EMA alignment - Advanced momentum validation ### Signal Strength Classification - **Normal Signals**: Basic technical alignment (small arrows) - **Strong Signals**: Enhanced momentum + volume confirmation (large arrows) ## 🎨 Visual Display System ### Signal Arrows - **🔼 Green Triangle Up**: Call signal (buy/long) - **🔽 Red Triangle Down**: Put signal (sell/short) - **💪 Enhanced Arrows**: Strong signals with special emoji indicators ### Settlement Results - **🎉 WIN**: Profitable contracts (green) - **💸 LOSS**: Losing contracts (red) - **Automatic Display**: Shows results immediately upon contract expiry ### Information Labels Each signal displays: - Signal type (Call/Put, Normal/Strong) - Selected mode and timeframe - Contract duration - Settlement results with win/loss indication ## 📊 Statistics Dashboard ### Real-time Performance Table Located in the top-right corner, displaying: #### Summary Statistics - **Total Contracts**: Overall contract count - **Overall Win Rate**: Percentage with color coding (Green: 80%+, Orange: 60-79%, Red: <60%) - **Today's Performance**: Daily statistics with separate tracking - **Win/Loss Breakdown**: Detailed count of profitable vs losing trades #### Directional Analysis - **Call Performance**: Success rate for bullish contracts - **Put Performance**: Success rate for bearish contracts - **Balanced Tracking**: Identifies directional bias in performance #### System Status - **Filter Mode**: Current smart filter status (Smart✓/Basic✗) - **Contract Duration**: Selected timeframe - **Beijing Time**: Real-time timestamp display - **Current Price**: Live BTC/USDT price - **Contract Status**: Active contract indicator (🔄 Active/✅ Ready) ## 💡 Usage Guidelines ### Optimal Setup 1. **Recommended Timeframe**: 1-minute for maximum signal frequency 2. **Symbol**: BTCUSDT or BTCUSD perpetual futures 3. **Mode Selection**: Start with "Smart Balance" for consistent performance 4. **Contract Duration**: Begin with 10-minute contracts for faster feedback ### Best Practices - **Pre-market Analysis**: Check overall market conditions before trading - **Risk Management**: Never risk more than 2-3% of capital per contract - **Session Timing**: Best performance during high-volume trading sessions - **Signal Confirmation**: Wait for arrow + label confirmation before entry - **Performance Monitoring**: Regularly review win rate statistics ### Trading Sessions - **Asian Session**: 00:00-08:00 Beijing Time (moderate volatility) - **European Session**: 15:00-23:00 Beijing Time (high volatility) - **US Session**: 21:00-05:00 Beijing Time (peak volatility) ## 🚨 Alert Configuration ### Available Alerts 1. **BTC Call Signal**: Basic bullish signal alerts 2. **BTC Put Signal**: Basic bearish signal alerts 3. **BTC Strong Call Signal**: High-quality bullish signals 4. **BTC Strong Put Signal**: High-quality bearish signals ### Alert Setup ``` Alert Condition: Select from dropdown Frequency: Once Per Bar Close Expiration: No expiration (for continuous monitoring) Webhook: Optional for automated trading systems ``` ### Alert Message Format ``` 🚀 BTC Event Contract Call Signal ⏰ Time: 💰 Price: $ ``` ## 🔧 Advanced Configuration ### Parameter Optimization - **Auto-Optimization Enabled**: Uses predefined optimized parameters - **Manual Override**: Disable auto-optimization for custom parameter testing - **Timeframe Adaptation**: Parameters automatically adjust for 1-min, 3-min, and higher timeframes ### Filter Customization - **Volume Filter**: Adjustable multiplier (1.1-2.5x) - **Trend Filter**: Optional EMA trend confirmation - **Advanced Confirmation**: Multi-timeframe validation - **Smart Filter**: Toggle for intelligent filtering system ## 📈 Performance Expectations ### Historical Backtesting Results Based on extensive BTCUSDT 1-minute data testing: #### Smart Balance Mode - **Average Win Rate**: 78-82% - **Daily Signals**: 10-15 - **Best Sessions**: European/US overlap - **Recommended For**: Most traders #### High Frequency Mode - **Average Win Rate**: 73-77% - **Daily Signals**: 18-25 - **Best Sessions**: High volatility periods - **Recommended For**: Active scalpers #### Premium Quality Mode - **Average Win Rate**: 83-87% - **Daily Signals**: 6-10 - **Best Sessions**: Trending market conditions - **Recommended For**: Conservative traders ## ⚠️ Risk Warnings ### Important Disclaimers - **High-Risk Trading**: Event contracts involve significant risk of loss - **Market Volatility**: Cryptocurrency markets are highly volatile and unpredictable - **No Guarantee**: Past performance does not guarantee future results - **Capital Risk**: Only trade with funds you can afford to lose completely ### Risk Management Guidelines - **Position Sizing**: Never risk more than 1-2% per trade - **Daily Limits**: Set maximum daily loss limits - **Emotional Control**: Avoid revenge trading after losses - **Market Conditions**: Adjust exposure based on volatility - **Continuous Monitoring**: Regularly assess indicator performance ## 🔄 Version History ### V1.0 (December 21, 2024) - Initial English release - Complete translation from Chinese version - Optimized for international users - Enhanced documentation with detailed explanations - Maintained all original functionality and performance characteristics ## 🛠️ Technical Specifications ### Pine Script Details - **Version**: Pine Script v6 - **Type**: Indicator with overlay=true - **Max Objects**: 500 boxes, 500 labels - **Memory Optimization**: Efficient array and map usage - **Performance**: Optimized for real-time execution ### System Requirements - **Platform**: TradingView Pro, Pro+, or Premium - **Browser**: Modern browser with JavaScript enabled - **Connection**: Stable internet for real-time data - **Display**: Minimum 1080p resolution recommended ## 📞 Support & Updates ### Getting Help - **Documentation**: Refer to this comprehensive guide - **Common Issues**: Check parameter settings and timeframe compatibility - **Performance**: Verify market conditions and volatility levels ### Update Policy - **Regular Updates**: Continuous optimization based on market conditions - **Version Tracking**: All changes documented with version numbers - **Backward Compatibility**: Settings preserved across updates --- **Disclaimer**: This indicator is for educational and analysis purposes only. Trading cryptocurrencies and event contracts involves substantial risk. Always conduct your own research and consider your risk tolerance before trading. The authors are not responsible for any trading losses incurred through the use of this indicator.
Indicador Pine Script®
por OxJohannWu
Bilateral Filter For Loop [BackQuant]Bilateral Filter For Loop The Bilateral Filter For Loop is an advanced technical indicator designed to filter out market noise and smooth out price data, thus improving the identification of underlying market trends. It employs a bilateral filter, which is a sophisticated non-linear filter commonly used in image processing and price time series analysis. By considering both spatial and range differences between price points, this filter is highly effective at preserving significant trends while reducing random fluctuations, ultimately making it suitable for dynamic trend-following strategies. Please take the time to read the following: Key Features 1. Bilateral Filter Calculation: The bilateral filter is the core of this indicator and works by applying a weight to each data point based on two factors: spatial distance and price range difference. This dual weighting process allows the filter to preserve important price movements while reducing the impact of less relevant fluctuations. The filter uses two primary parameters: Spatial Sigma (σ_d): This parameter adjusts the weight applied based on the distance of each price point from the current price. A larger spatial sigma means more smoothing, as further away values will contribute more heavily to the result. Range Sigma (σ_r): This parameter controls how much weight is applied based on the difference in price values. Larger price differences result in smaller weights, while similar price values result in larger weights, thereby preserving the trend while filtering out noise. The output of this filter is a smoothed version of the original price series, which eliminates short-term fluctuations, helping traders focus on longer-term trends. The bilateral filter is applied over a rolling window, adjusting the level of smoothing dynamically based on both the distance between values and their relative price movements. 2. For Loop Calculation for Trend Scoring: A for-loop is used to calculate the trend score based on the filtered price data. The loop compares the current value to previous values within the specified window, scoring the trend as follows: +1 for upward movement (when the filtered value is greater than the previous value). -1 for downward movement (when the filtered value is less than the previous value). The cumulative result of this loop gives a continuous trend score, which serves as a directional indicator for the market's momentum. By summing the scores over the window period, the loop provides an aggregate value that reflects the overall trend strength. This score helps determine whether the market is experiencing a strong uptrend, downtrend, or sideways movement. 3. Long and Short Conditions: Once the trend score has been calculated, it is compared against predefined threshold levels: A long signal is generated when the trend score exceeds the upper threshold, indicating that the market is in a strong uptrend. A short signal is generated when the trend score crosses below the lower threshold, signaling a potential downtrend or trend reversal. These conditions provide clear signals for potential entry points, and the color-coding helps traders quickly identify market direction: Long signals are displayed in green. Short signals are displayed in red. These signals are designed to provide high-confidence entries for trend-following strategies, helping traders capture profitable movements in the market. 4. Trend Background and Bar Coloring: The script offers customizable visual settings to enhance the clarity of the trend signals. Traders can choose to: Color the bars based on the trend direction: Bars are colored green for long signals and red for short signals. Change the background color to provide additional context: The background will be shaded green for a bullish trend and red for a bearish trend. This visual feedback helps traders to stay aligned with the prevailing market sentiment. These features offer a quick visual reference for understanding the market's direction, making it easier for traders to identify when to enter or exit positions. 5. Threshold Lines for Visual Feedback: Threshold lines are plotted on the chart to represent the predefined long and short levels. These lines act as clear markers for when the market reaches a critical threshold, triggering a potential buy (long) or sell (short) signal. By showing these threshold lines on the chart, traders can quickly gauge the strength of the market and assess whether the trend is strong enough to warrant action. These thresholds can be adjusted based on the trader's preferences, allowing them to fine-tune the indicator for different market conditions or asset behaviors. 6. Customizable Parameters for Flexibility: The indicator offers several parameters that can be adjusted to suit individual trading preferences: Window Period (Bilateral Filter): The window size determines how many past price values are used to calculate the bilateral filter. A larger window increases smoothing, while a smaller window results in more responsive, but noisier, data. Spatial Sigma (σ_d) and Range Sigma (σ_r): These values control how sensitive the filter is to price changes and the distance between data points. Fine-tuning these parameters allows traders to adjust the degree of noise reduction applied to the price series. Threshold Levels: The upper and lower thresholds determine when the trend score crosses into long or short territory. These levels can be customized to better match the trader's risk tolerance or asset characteristics. Visual Settings: Traders can customize the appearance of the chart, including the line width of trend signals, bar colors, and background shading, to make the indicator more readable and aligned with their charting style. 7. Alerts for Trend Reversals: The indicator includes alert conditions for real-time notifications when the market crosses the defined thresholds. Traders can set alerts to be notified when: The trend score crosses the long threshold, signaling an uptrend. The trend score crosses the short threshold, signaling a downtrend. These alerts provide timely information, allowing traders to take immediate action when the market shows a significant change in direction. Final Thoughts The Bilateral Filter For Loop indicator is a robust tool for trend-following traders who wish to reduce market noise and focus on the underlying trend. By applying the bilateral filter and calculating trend scores, this indicator helps traders identify strong uptrends and downtrends, providing reliable entry signals with minimal market noise. The customizable parameters, visual feedback, and alerting system make it a versatile tool for traders seeking to improve their timing and capture profitable market movements. Thus following all of the key points here are some sample backtests on the 1D Chart Disclaimer: Backtests are based off past results, and are not indicative of the future. INDEX:BTCUSD INDEX:ETHUSD CRYPTO:SOLUSD
Indicador Pine Script®
por BackQuant
GER40 BIAS Forecast [ML-Based]🎯 Purpose: This indicator provides a daily directional bias (LONG / SHORT / FLAT) for the German DAX40 index (GER40) using a statistically optimized scoring model, developed with 6 years of historical data and verified through machine learning analysis. 🧠 How the Score Works (ML-derived): Each trading day receives a bias score (0–3) for both long and short setups, based on these 3 factors from the daily candle: Condition Long Score Logic Short Score Logic 1. Candle Direction Close > Open → +1 Close < Open → +1 2. VWAP Slope VWAP > VWAP → +1 VWAP < VWAP → +1 3. Volatility Strength Range > SMA(20) → +1 Close < Yesterday's Low → +1 (Rejection) ➡️ A score of 2 or more triggers a Long or Short Bias for the day. These scoring rules are derived from a machine learning model trained on 6 years of DAX data, identifying the most predictive features for directional follow-through. 📘 Bias Interpretation: Score Result Daily Bias Background Color Long Score ≥ 2 LONG Green Short Score ≥ 2 SHORT Red Both < 2 FLAT Gray 📍 Indicator Features: 🎨 Background coloring to visualize daily bias directly on intraday charts 🔢 Optional score labels (e.g. “Long: 2 | Short: 1”) per calendar day 📈 VWAP line plotted for additional intraday context ❌ Entry signals removed – this version focuses solely on forecasting directional bias 💡 Use Case: Morning planning aid Filtering for high-probability intraday setups Combining with session-based entry systems
Indicador Pine Script®
por Precious_Life
Volume Point of Control with Fib Based Profile🍀Description: This indicator is a comprehensive volume profile analysis tool designed to identify key price levels based on trading activity within user-defined timeframes. It plots the Point of Control (POC), Value Area High (VAH), and Value Area Low (VAL), along with dynamically calculated Fibonacci levels derived from the developing period's range. It offers extensive customization for both historical and developing levels. 🍀Core Features: Volume Profiling (POC, VAH, VAL): Calculates and plots the POC (price level with the highest volume), VAH, and VAL for a selected timeframe (e.g., Daily, Weekly). The Value Area percentage is configurable. 70% is common on normal volume profiles, but this script allows you to configure multiple % levels via the fib levels. I recommend using 2 versions of this indicator on a chart, one has Value Area at 1 (100% - high and low of lookback) and the second is a specified VA area (i.e. 70%) like in the chart snapshot above. See examples at the bottom. Historical Levels: Plots POC, VAH, and VAL from previous completed periods. Optionally displays only "Unbroken" levels – historical levels that price has not yet revisited, which can act as stronger magnets or resistance/support. The user can manage the number of historical lines displayed to prevent chart clutter. Developing Levels: Shows the POC, VAH, and VAL as they form in real-time during the current, incomplete period. This provides insight into intraday/intra-period value migration. Dynamic Fibonacci Levels: Calculates and plots Fibonacci retracement/extension levels based dynamically on the range between the developing POC and the developing VAH/VAL. Offers 8 configurable % levels above and below POC that can be toggled on/off. Visual Customization: Extensive options for colors, line styles, and widths for all plotted levels. Optional gradient fill for the Value Area that visualizes current price distance from POC - option to invert the colors as well. Labels for developing levels and Fibonacci levels for easy identification. 🍀Characteristics: Volume-Driven: Levels are derived from actual trading volume, reflecting areas of high participation and price agreement/disagreement. Timeframe Specific: The results are entirely dependent on the chosen profile timeframe. Dynamic & Static Elements: Developing levels and Fibs update live, while historical levels remain fixed once their period closes. Lagging (Historical) & Potentially Leading: Historical levels are based on the past, but are often respected by future price action. Developing levels show current dynamics. 🍀How to Use It: Identifying Support & Resistance: Historical and developing POCs, VAHs, and VALs are often key areas where price may react. Unbroken levels are particularly noteworthy. Market Context & Sentiment: Trading above the POC suggests bullish strength/acceptance of higher prices, while trading below suggests bearishness/acceptance of lower prices. Entry/Exit Zones: Interactions with these levels (rejections, breakouts, tests) can provide potential entry or exit signals, especially when confirming with other analysis methods. Dynamic Targets: The Fibonacci levels calculated from the developing POC-VA range offer potential intraday/intra-period price targets or areas of interest. Understanding Value Migration: Observing the movement of the developing POC/VAH/VAL throughout the period reveals where value is currently being established. 🍀Potential Drawbacks: Input Sensitivity: The choice of timeframe, Value Area percentage, and volume resolution heavily influences the generated levels. Experimentation is needed for optimal settings per instrument/market. (I've found that Range Charts can provide very accurate volume levels on TV since the time element is removed. This helps to refine the accuracy of price levels with high volume.) Volume Data Dependency: Requires accurate volume data. May be less reliable on instruments with sparse or questionable volume reporting. Chart Clutter: Enabling all features simultaneously can make the chart busy. Utilize the line management inputs and toggle features as needed. Not a Standalone Strategy: This indicator provides context and key levels. It should be used alongside other technical analysis tools and price action reading for robust decision-making. Developing Level Fluctuation: Developing POC/VA/Fib levels can shift considerably, especially early in a new period, before settling down as more volume accumulates and time passes. 🍀Recommendations/Examples: I recommend have this indicator on your chart twice, one has the VA set at 1 (100%) and has the fib levels plotted. The second has the VA set to 0.7 (70%) to highlight the defined VA. Here is an example with 3 on a chart. VA of 100%, VA of 80%, and VA of 20%
Indicador Pine Script®
por ShamrockShane
2
GEEKSDOBYTE IFVG w/ Buy/Sell Signals1. Inputs & Configuration Swing Lookback (swingLen) Controls how many bars on each side are checked to mark a swing high or swing low (default = 5). Booleans to Toggle Plotting showSwings – Show small triangle markers at swing highs/lows showFVG – Show Fair Value Gap zones showSignals – Show “BUY”/“SELL” labels when price inverts an FVG showDDLine – Show a yellow “DD” line at the close of the inversion bar showCE – Show an orange dashed “CE” line at the midpoint of the gap area 2. Swing High / Low Detection isSwingHigh = ta.pivothigh(high, swingLen, swingLen) Marks a bar as a swing high if its high is higher than the highs of the previous swingLen bars and the next swingLen bars. isSwingLow = ta.pivotlow(low, swingLen, swingLen) Marks a bar as a swing low if its low is lower than the lows of the previous and next swingLen bars. Plotting If showSwings is true, small red downward triangles appear above swing highs, and green upward triangles below swing lows. 3. Fair Value Gap (3‐Bar) Identification A Fair Value Gap (FVG) is defined here using a simple three‐bar logic (sometimes called an “inefficiency” in price): Bullish FVG (bullFVG) Checks if, two bars ago, the low of that bar (low ) is strictly greater than the current bar’s high (high). In other words: bullFVG = low > high Bearish FVG (bearFVG) Checks if, two bars ago, the high of that bar (high ) is strictly less than the current bar’s low (low). In other words: bearFVG = high < low When either condition is true, it identifies a three‐bar “gap” or unfilled imbalance in the market. 4. Drawing FVG Zones If showFVG is enabled, each time a bullish or bearish FVG is detected: Bullish FVG Zone Draws a semi‐transparent green box from the bar two bars ago (where the gap began) at low up to the current bar’s high. Bearish FVG Zone Draws a semi‐transparent red box from the bar two bars ago at high down to the current bar’s low. These colored boxes visually highlight the “fair value imbalance” area on the chart. 5. Inversion (Fill) Detection & Entry Signals An inversion is defined as the price “closing through” that previously drawn FVG: Bullish Inversion (bullInversion) Occurs when a bullish FVG was identified on bar-2 (bullFVG), and on the current bar the close is greater than that old bar-2 low: bullInversion = bullFVG and close > low Bearish Inversion (bearInversion) Occurs when a bearish FVG was identified on bar-2 (bearFVG), and on the current bar the close is lower than that old bar-2 high: bearInversion = bearFVG and close < high When an inversion is true, the indicator optionally draws two lines and a label (depending on input toggles): Draw “DD” Line (yellow, solid) Plots a horizontal yellow line from the current bar’s close price extending five bars forward (bar_index + 5). This is often referred to as a “Demand/Daily Demand” line, marking where price inverted the gap. Draw “CE” Line (orange, dashed) Calculates the midpoint (ce) of the original FVG zone. For a bullish inversion: ce = (low + high) / 2 For a bearish inversion: ce = (high + low) / 2 Plots a horizontal dashed orange line at that midpoint for five bars forward. Plot Label (“BUY” / “SELL”) If showSignals is true, a green “BUY” label is placed at the low of the current bar when a bullish inversion occurs. Likewise, a red “SELL” label at the high of the current bar when a bearish inversion happens. 6. Putting It All Together Swing Markers (Optional): Visually confirm recent swing highs and swing lows with small triangles. FVG Zones (Optional): Highlight areas where price left a 3-bar gap (bullish in green, bearish in red). Inversion Confirmation: Wait for price to close beyond the old FVG boundary. Once that happens, draw the yellow “DD” line at the close, the orange dashed “CE” line at the zone’s midpoint, and place a “BUY” or “SELL” label exactly on that bar. User Controls: All of the above elements can be individually toggled on/off (showSwings, showFVG, showSignals, showDDLine, showCE). In Practice A bullish FVG forms whenever a strong drop leaves a gap in liquidity (three bars ago low > current high). When price later “fills” that gap by closing above the old low, the script signals a potential long entry (BUY), draws a demand line at the closing price, and marks the midpoint of that gap. Conversely, a bearish FVG marks a potential short zone (three bars ago high < current low). When price closes below that gap’s high, it signals a SELL, with similar lines drawn. By combining these elements, the indicator helps users visually identify inefficiencies (FVGs), confirm when price inverts/fills them, and place straightforward buy/sell labels alongside reference lines for trade management.
Indicador Pine Script®
por RayenGeeksdoByte
Levels Of Interest------------------------------------------------------------------------------------ LEVELS OF INTEREST (LOI) TRADING INDICATOR GUIDE ------------------------------------------------------------------------------------ Table of Contents: 1. Indicator Overview & Core Functionality 2. VWAP Foundation & Historical Context 3. Multi-Timeframe VWAP Analysis 4. Moving Average Integration System 5. Trend Direction Signal Detection 6. Visual Design & Display Features 7. Custom Level Integration 8. Repaint Protection Technology 9. Practical Trading Applications 10. Setup & Configuration Recommendations ------------------------------------------------------------------------------------ 1. INDICATOR OVERVIEW & CORE FUNCTIONALITY ------------------------------------------------------------------------------------ The LOI indicator combines multiple VWAP calculations with moving averages across different timeframes. It's designed to show where institutional money is flowing and help identify key support and resistance levels that actually matter in today's markets. Primary Functions: - Multi-timeframe VWAP analysis (Daily, Weekly, Monthly, Yearly) - Advanced moving average integration (EMA, SMA, HMA) - Real-time trend direction detection - Institutional flow analysis - Dynamic support/resistance identification Target Users: Day traders, swing traders, position traders, and institutional analysts seeking comprehensive market structure analysis. ------------------------------------------------------------------------------------ 2. VWAP FOUNDATION & HISTORICAL CONTEXT ------------------------------------------------------------------------------------ Historical Development: VWAP started in the 1980s when big institutional traders needed a way to measure if they were getting good fills on their massive orders. Unlike regular price averages, VWAP weighs each price by the volume traded at that level. This makes it incredibly useful because it shows you where most of the real money changed hands. Mathematical Foundation: The basic math is simple: you take each price, multiply it by the volume at that price, add them all up, then divide by total volume. What you get is the true "average" price that reflects actual trading activity, not just random price movements. Formula: VWAP = Σ(Price × Volume) / Σ(Volume) Where typical price = (High + Low + Close) / 3 Institutional Behavior Patterns: - When price trades above VWAP, institutions often look to sell - When it's below, they're usually buying - Creates natural support and resistance that you can actually trade against - Serves as benchmark for execution quality assessment ------------------------------------------------------------------------------------ 3. MULTI-TIMEFRAME VWAP ANALYSIS ------------------------------------------------------------------------------------ Core Innovation: Here's where LOI gets interesting. Instead of just showing daily VWAP like most indicators, it displays four different timeframes simultaneously: **Daily VWAP Implementation**: - Resets every morning at market open - Provides clearest picture of intraday institutional sentiment - Primary tool for day trading strategies - Most responsive to immediate market conditions **Weekly VWAP System**: - Resets each Monday (or first trading day) - Smooths out daily noise and volatility - Perfect for swing trades lasting several days to weeks - Captures weekly institutional positioning **Monthly VWAP Analysis**: - Resets at beginning of each calendar month - Captures bigger institutional rebalancing at month-end - Fund managers often operate on monthly mandates - Significant weight in intermediate-term analysis **Yearly VWAP Perspective**: - Resets annually for full-year institutional view - Shows long-term institutional positioning - Where pension funds and sovereign wealth funds operate - Critical for major trend identification Confluence Zone Theory: The magic happens when multiple VWAP levels cluster together. These confluence zones often become major turning points because different types of institutional money all see value at the same price. ------------------------------------------------------------------------------------ 4. MOVING AVERAGE INTEGRATION SYSTEM ------------------------------------------------------------------------------------ Multi-Type Implementation: The indicator includes three types of moving averages, each with its own personality and application: **Exponential Moving Averages (EMAs)**: - React quickly to recent price changes - Displayed as solid lines for easy identification - Optimal performance in trending market conditions - Higher sensitivity to current price action **Simple Moving Averages (SMAs)**: - Treat all historical data points equally - Appear as dashed lines in visual display - Slower response but more reliable in choppy conditions - Traditional approach favored by institutional traders **Hull Moving Averages (HMAs)**: - Newest addition to the system (dotted line display) - Created by Alan Hull in 2005 - Solves classic moving average dilemma: speed vs. accuracy - Manages to be both responsive and smooth simultaneously Technical Innovation: Alan Hull's solution addresses the fundamental problem where moving averages are either too slow (missing moves) or too fast (generating false signals). HMAs achieve optimal balance through weighted calculation methodology. Period Configuration: - 5-period: Short-term momentum assessment - 50-period: Intermediate trend identification - 200-period: Long-term directional confirmation ------------------------------------------------------------------------------------ 5. TREND DIRECTION SIGNAL DETECTION ------------------------------------------------------------------------------------ Real-Time Momentum Analysis: One of LOI's best features is its real-time trend detection system. Next to each moving average, visual symbols provide immediate trend assessment: Symbol System: - ▲ Rising average (bullish momentum confirmation) - ▼ Falling average (bearish momentum indication) - ► Flat average (consolidation or indecision period) Update Frequency: These signals update in real-time with each new price tick and function across all configured timeframes. Traders can quickly scan daily and weekly trends to assess alignment or conflicting signals. Multi-Timeframe Trend Analysis: - Simultaneous daily and weekly trend comparison - Immediate identification of trend alignment - Early warning system for potential reversals - Momentum confirmation for entry decisions ------------------------------------------------------------------------------------ 6. VISUAL DESIGN & DISPLAY FEATURES ------------------------------------------------------------------------------------ Color Psychology Framework: The color scheme isn't random but based on psychological associations and trading conventions: - **Blue Tones**: Institutional neutrality (VWAP levels) - **Green Spectrum**: Growth and stability (weekly timeframes) - **Purple Range**: Longer-term sophistication (monthly analysis) - **Orange Hues**: Importance and attention (yearly perspective) - **Red Tones**: User-defined significance (custom levels) Adaptive Display Technology: The indicator automatically adjusts decimal places based on the instrument you're trading. High-priced stocks show 2 decimals, while penny stocks might show 8. This keeps the display incredibly clean regardless of what you're analyzing - no cluttered charts or overwhelming information overload. Smart Labeling System: Advanced positioning algorithm automatically spaces all elements to prevent overlap, even during extreme zoom levels or multiple timeframe analysis. Every level stays clearly readable without any visual chaos disrupting your analysis. ------------------------------------------------------------------------------------ 7. CUSTOM LEVEL INTEGRATION ------------------------------------------------------------------------------------ User-Defined Level System: Beyond the calculated VWAP and moving average levels, traders can add custom horizontal lines at any price point for personalized analysis. Strategic Applications: - **Psychological Levels**: Round numbers, previous significant highs/lows - **Technical Levels**: Fibonacci retracements, pivot points - **Fundamental Targets**: Analyst price targets, earnings estimates - **Risk Management**: Stop-loss and take-profit zones Integration Features: - Seamless incorporation with smart labeling system - Custom color selection for visual organization - Extension capabilities across all chart timeframes - Maintains display clarity with existing indicators ------------------------------------------------------------------------------------ 8. REPAINT PROTECTION TECHNOLOGY ------------------------------------------------------------------------------------ Critical Trading Feature: This addresses one of the most significant issues in live trading applications. Most multi-timeframe indicators "repaint," meaning they display different signals when viewing historical data versus real-time analysis. Protection Benefits: - Ensures every displayed signal could have been traded when it appeared - Eliminates discrepancies between historical and live analysis - Provides realistic performance expectations - Maintains signal integrity across chart refreshes Configuration Options: - **Protection Enabled**: Default setting for live trading - **Protection Disabled**: Available for backtesting analysis - User-selectable toggle based on analysis requirements - Applies to all multi-timeframe calculations Implementation Note: With protection enabled, signals may appear one bar later than without protection, but this ensures all signals represent actionable opportunities that could have been executed in real-time market conditions. ------------------------------------------------------------------------------------ 9. PRACTICAL TRADING APPLICATIONS ------------------------------------------------------------------------------------ **Day Trading Strategy**: Focus on daily VWAP with 5-period moving averages. Look for bounces off VWAP or breaks through it with volume. Short-term momentum signals provide entry and exit timing. **Swing Trading Approach**: Weekly VWAP becomes your primary anchor point, with 50-period averages showing intermediate trends. Position sizing based on weekly VWAP distance. **Position Trading Method**: Monthly and yearly VWAP provide broad market context, while 200-period averages confirm long-term directional bias. Suitable for multi-week to multi-month holdings. **Multi-Timeframe Confluence Strategy**: The highest-probability setups occur when daily, weekly, and monthly VWAPs cluster together, especially when multiple moving averages confirm the same direction. These represent institutional consensus zones. Risk Management Integration: - VWAP levels serve as dynamic stop-loss references - Multiple timeframe confirmation reduces false signals - Institutional flow analysis improves position sizing decisions - Trend direction signals optimize entry and exit timing ------------------------------------------------------------------------------------ 10. SETUP & CONFIGURATION RECOMMENDATIONS ------------------------------------------------------------------------------------ Initial Configuration: Start with default settings and adjust based on individual trading style and market focus. Short-term traders should emphasize daily and weekly timeframes, while longer-term investors benefit from monthly and yearly level analysis. Transparency Optimization: The transparency settings allow clear price action visibility while maintaining level reference points. Most traders find 70-80% transparency optimal - it provides a clean, unobstructed view of price movement while maintaining all critical reference levels needed for analysis. Integration Strategy: Remember that no indicator functions effectively in isolation. LOI provides excellent context for institutional flow and trend direction analysis, but should be combined with complementary analysis tools for optimal results. Performance Considerations: - Multiple timeframe calculations may impact chart loading speed - Adjust displayed timeframes based on trading frequency - Customize color schemes for different market sessions - Regular review and adjustment of custom levels ------------------------------------------------------------------------------------ FINAL ANALYSIS ------------------------------------------------------------------------------------ Competitive Advantage: What makes LOI different is its focus on where real money actually trades. By combining volume-weighted calculations with multiple timeframes and trend detection, it cuts through market noise to show you what institutions are really doing. Key Success Factor: Understanding that different timeframes serve different purposes is essential. Use them together to build a complete picture of market structure, then execute trades accordingly. The integration of institutional flow analysis with technical trend detection creates a comprehensive trading tool that addresses both short-term tactical decisions and longer-term strategic positioning. ------------------------------------------------------------------------------------ END OF DOCUMENTATION ------------------------------------------------------------------------------------
Indicador Pine Script®
por meddymarkusvanhala
2
HoLo (Highest Open Lowest Open)HoLo (Highest Open Lowest Open) Method Overview HoLo stands for "Highest Open Lowest Open" – a forex trading strategy. Core Concept Definition of HoLo: Highest Open (HO): The highest opening price among all H1 candles of the current trading day Lowest Open (LO): The lowest opening price among all H1 candles of the current trading day Trading Day: Starts at Asia Open Session Strategy Setup Step 1: Mark Key Levels Current day's High/Low Highest Open and Lowest Open (from H1 candles) Step 2: Define the Area of Interest Sell Zone: Between the Highest Open and the current day's High Buy Zone: Between the Lowest Open and the current day's Low Trade Entry Rules Sell Trade: Price goes above the Highest Open Trigger candle (M5, M15, or M30) closes above the Highest Open Enter a sell when price revisits the Highest Open level (Sell Stop Order) Buy Trade: Price drops below the Lowest Open Trigger candle closes below the Lowest Open Enter a buy when price revisits the Lowest Open level (Buy Stop Order) Trigger Timeframe: Choose M1, M5, or M15 based on: Your screen time availability Personal trading style Risk and Profit Management Stop Loss: For sell: Set SL at the day’s High + spread For buy: Set SL at the day’s Low + spread Take Profit (TP) Basic Rule: You should open 2 positions: When profit reaches 1R: Take partial profit + move SL to BE (Break Even) Let the remaining position run using partial TP or trailing stop Money Management: Never risk more than 1% per trade Recommended: 0.5% risk due to multiple opportunities daily Prioritize major pairs. The Indicator How to read data For Day Traders Monitor the sell zone (red area) for potential short entries near resistance Watch the buy zone (blue area) for potential long entries near support Use cross signals for entry/exit points Pay attention to timing markers for key market hours Alert HO (Highest Open) level changes LO (Lowest Close) level changes Price crossing key levels Timing notifications
Indicador Pine Script®
por dangtunglam14
Heikin-Ashi Mean Reversion Oscillator [Alpha Extract]The Heikin-Ashi Mean Reversion Oscillator combines the smoothing characteristics of Heikin-Ashi candlesticks with mean reversion analysis to create a powerful momentum oscillator. This indicator applies Heikin-Ashi transformation twice - first to price data and then to the oscillator itself - resulting in smoother signals while maintaining sensitivity to trend changes and potential reversal points. 🔶 CALCULATION Heikin-Ashi Transformation: Converts regular OHLC data to smoothed Heikin-Ashi values Component Analysis: Calculates trend strength, body deviation, and price deviation from mean Oscillator Construction: Combines components with weighted formula (40% trend strength, 30% body deviation, 30% price deviation) Double Smoothing: Applies EMA smoothing and second Heikin-Ashi transformation to oscillator values Signal Generation: Identifies trend changes and crossover points with overbought/oversold levels Formula: HA Close = (Open + High + Low + Close) / 4 HA Open = (Previous HA Open + Previous HA Close) / 2 Trend Strength = Normalized consecutive HA candle direction Body Deviation = (HA Body - Mean Body) / Mean Body * 100 Price Deviation = ((HA Close - Price Mean) / Price Mean * 100) / Standard Deviation * 25 Raw Oscillator = (Trend Strength * 0.4) + (Body Deviation * 0.3) + (Price Deviation * 0.3) Final Oscillator = 50 + (EMA(Raw Oscillator) / 2) 🔶 DETAILS Visual Features: Heikin-Ashi Candlesticks: Smoothed oscillator representation using HA transformation with vibrant teal/red coloring Overbought/Oversold Zones: Horizontal lines at customizable levels (default 70/30) with background highlighting in extreme zones Moving Averages: Optional fast and slow EMA overlays for additional trend confirmation Signal Dashboard: Real-time table showing current oscillator status (Overbought/Oversold/Bullish/Bearish) and buy/sell signals Reference Lines: Middle line at 50 (neutral), with 0 and 100 boundaries for range visualization Interpretation: Above 70: Overbought conditions, potential selling opportunity Below 30: Oversold conditions, potential buying opportunity Bullish HA Candles: Green/teal candles indicate upward momentum Bearish HA Candles: Red candles indicate downward momentum MA Crossovers: Fast EMA above slow EMA suggests bullish momentum, below suggests bearish momentum Zone Exits: Price moving out of extreme zones (above 70 or below 30) often signals trend continuation 🔶 EXAMPLES Mean Reversion Signals: When the oscillator reaches extreme levels (above 70 or below 30), it identifies potential reversal points where price may revert to the mean. Example: Oscillator reaching 80+ levels during strong uptrends often precedes short-term pullbacks, providing profit-taking opportunities. Trend Change Detection: The double Heikin-Ashi smoothing helps identify genuine trend changes while filtering out market noise. Example: When oscillator HA candles change from red to teal after oversold readings, this confirms potential trend reversal from bearish to bullish. Moving Average Confirmation: Fast and slow EMA crossovers on the oscillator provide additional confirmation of momentum shifts. Example: Fast EMA crossing above slow EMA while oscillator is rising from oversold levels provides strong bullish confirmation signal. Dashboard Signal Integration: The real-time dashboard combines oscillator status with directional signals for quick decision-making. Example: Dashboard showing "Oversold" status with "BUY" signal when HA candles turn bullish provides clear entry timing. 🔶 SETTINGS Customization Options: Calculation: Oscillator period (default 14), smoothing factor (1-50, default 2) Levels: Overbought threshold (50-100, default 70), oversold threshold (0-50, default 30) Moving Averages: Toggle display, fast EMA length (default 9), slow EMA length (default 21) Visual Enhancements: Show/hide signal dashboard, customizable table position Alert Conditions: Oversold bounce, overbought reversal, bullish/bearish MA crossovers The Heikin-Ashi Mean Reversion Oscillator provides traders with a sophisticated momentum tool that combines the smoothing benefits of Heikin-Ashi analysis with mean reversion principles. The double transformation process creates cleaner signals while the integrated dashboard and multiple confirmation methods help traders identify high-probability entry and exit points during both trending and ranging market conditions.
Indicador Pine Script®
por AlphaExtract
Risk-Adjusted Momentum Oscillator# Risk-Adjusted Momentum Oscillator (RAMO): Momentum Analysis with Integrated Risk Assessment ## 1. Introduction Momentum indicators have been fundamental tools in technical analysis since the pioneering work of Wilder (1978) and continue to play crucial roles in systematic trading strategies (Jegadeesh & Titman, 1993). However, traditional momentum oscillators suffer from a critical limitation: they fail to account for the risk context in which momentum signals occur. This oversight can lead to significant drawdowns during periods of market stress, as documented extensively in the behavioral finance literature (Kahneman & Tversky, 1979; Shefrin & Statman, 1985). The Risk-Adjusted Momentum Oscillator addresses this gap by incorporating real-time drawdown metrics into momentum calculations, creating a self-regulating system that automatically adjusts signal sensitivity based on current risk conditions. This approach aligns with modern portfolio theory's emphasis on risk-adjusted returns (Markowitz, 1952) and reflects the sophisticated risk management practices employed by institutional investors (Ang, 2014). ## 2. Theoretical Foundation ### 2.1 Momentum Theory and Market Anomalies The momentum effect, first systematically documented by Jegadeesh & Titman (1993), represents one of the most robust anomalies in financial markets. Subsequent research has confirmed momentum's persistence across various asset classes, time horizons, and geographic markets (Fama & French, 1996; Asness, Moskowitz & Pedersen, 2013). However, momentum strategies are characterized by significant time-varying risk, with particularly severe drawdowns during market reversals (Barroso & Santa-Clara, 2015). ### 2.2 Drawdown Analysis and Risk Management Maximum drawdown, defined as the peak-to-trough decline in portfolio value, serves as a critical risk metric in professional portfolio management (Calmar, 1991). Research by Chekhlov, Uryasev & Zabarankin (2005) demonstrates that drawdown-based risk measures provide superior downside protection compared to traditional volatility metrics. The integration of drawdown analysis into momentum calculations represents a natural evolution toward more sophisticated risk-aware indicators. ### 2.3 Adaptive Smoothing and Market Regimes The concept of adaptive smoothing in technical analysis draws from the broader literature on regime-switching models in finance (Hamilton, 1989). Perry Kaufman's Adaptive Moving Average (1995) pioneered the application of efficiency ratios to adjust indicator responsiveness based on market conditions. RAMO extends this concept by incorporating volatility-based adaptive smoothing, allowing the indicator to respond more quickly during high-volatility periods while maintaining stability during quiet markets. ## 3. Methodology ### 3.1 Core Algorithm Design The RAMO algorithm consists of several interconnected components: #### 3.1.1 Risk-Adjusted Momentum Calculation The fundamental innovation of RAMO lies in its risk adjustment mechanism: Risk_Factor = 1 - (Current_Drawdown / Maximum_Drawdown × Scaling_Factor) Risk_Adjusted_Momentum = Raw_Momentum × max(Risk_Factor, 0.05) This formulation ensures that momentum signals are dampened during periods of high drawdown relative to historical maximums, implementing an automatic risk management overlay as advocated by modern portfolio theory (Markowitz, 1952). #### 3.1.2 Multi-Algorithm Momentum Framework RAMO supports three distinct momentum calculation methods: 1. Rate of Change: Traditional percentage-based momentum (Pring, 2002) 2. Price Momentum: Absolute price differences 3. Log Returns: Logarithmic returns preferred for volatile assets (Campbell, Lo & MacKinlay, 1997) This multi-algorithm approach accommodates different asset characteristics and volatility profiles, addressing the heterogeneity documented in cross-sectional momentum studies (Asness et al., 2013). ### 3.2 Leading Indicator Components #### 3.2.1 Momentum Acceleration Analysis The momentum acceleration component calculates the second derivative of momentum, providing early signals of trend changes: Momentum_Acceleration = EMA(Momentum_t - Momentum_{t-n}, n) This approach draws from the physics concept of acceleration and has been applied successfully in financial time series analysis (Treadway, 1969). #### 3.2.2 Linear Regression Prediction RAMO incorporates linear regression-based prediction to project momentum values forward: Predicted_Momentum = LinReg_Value + (LinReg_Slope × Forward_Offset) This predictive component aligns with the literature on technical analysis forecasting (Lo, Mamaysky & Wang, 2000) and provides leading signals for trend changes. #### 3.2.3 Volume-Based Exhaustion Detection The exhaustion detection algorithm identifies potential reversal points by analyzing the relationship between momentum extremes and volume patterns: Exhaustion = |Momentum| > Threshold AND Volume < SMA(Volume, 20) This approach reflects the established principle that sustainable price movements require volume confirmation (Granville, 1963; Arms, 1989). ### 3.3 Statistical Normalization and Robustness RAMO employs Z-score normalization with outlier protection to ensure statistical robustness: Z_Score = (Value - Mean) / Standard_Deviation Normalized_Value = max(-3.5, min(3.5, Z_Score)) This normalization approach follows best practices in quantitative finance for handling extreme observations (Taleb, 2007) and ensures consistent signal interpretation across different market conditions. ### 3.4 Adaptive Threshold Calculation Dynamic thresholds are calculated using Bollinger Band methodology (Bollinger, 1992): Upper_Threshold = Mean + (Multiplier × Standard_Deviation) Lower_Threshold = Mean - (Multiplier × Standard_Deviation) This adaptive approach ensures that signal thresholds adjust to changing market volatility, addressing the critique of fixed thresholds in technical analysis (Taylor & Allen, 1992). ## 4. Implementation Details ### 4.1 Adaptive Smoothing Algorithm The adaptive smoothing mechanism adjusts the exponential moving average alpha parameter based on market volatility: Volatility_Percentile = Percentrank(Volatility, 100) Adaptive_Alpha = Min_Alpha + ((Max_Alpha - Min_Alpha) × Volatility_Percentile / 100) This approach ensures faster response during volatile periods while maintaining smoothness during stable conditions, implementing the adaptive efficiency concept pioneered by Kaufman (1995). ### 4.2 Risk Environment Classification RAMO classifies market conditions into three risk environments: - Low Risk: Current_DD < 30% × Max_DD - Medium Risk: 30% × Max_DD ≤ Current_DD < 70% × Max_DD - High Risk: Current_DD ≥ 70% × Max_DD This classification system enables conditional signal generation, with long signals filtered during high-risk periods—a approach consistent with institutional risk management practices (Ang, 2014). ## 5. Signal Generation and Interpretation ### 5.1 Entry Signal Logic RAMO generates enhanced entry signals through multiple confirmation layers: 1. Primary Signal: Crossover between indicator and signal line 2. Risk Filter: Confirmation of favorable risk environment for long positions 3. Leading Component: Early warning signals via acceleration analysis 4. Exhaustion Filter: Volume-based reversal detection This multi-layered approach addresses the false signal problem common in traditional technical indicators (Brock, Lakonishok & LeBaron, 1992). ### 5.2 Divergence Analysis RAMO incorporates both traditional and leading divergence detection: - Traditional Divergence: Price and indicator divergence over 3-5 periods - Slope Divergence: Momentum slope versus price direction - Acceleration Divergence: Changes in momentum acceleration This comprehensive divergence analysis framework draws from Elliott Wave theory (Prechter & Frost, 1978) and momentum divergence literature (Murphy, 1999). ## 6. Empirical Advantages and Applications ### 6.1 Risk-Adjusted Performance The risk adjustment mechanism addresses the fundamental criticism of momentum strategies: their tendency to experience severe drawdowns during market reversals (Daniel & Moskowitz, 2016). By automatically reducing position sizing during high-drawdown periods, RAMO implements a form of dynamic hedging consistent with portfolio insurance concepts (Leland, 1980). ### 6.2 Regime Awareness RAMO's adaptive components enable regime-aware signal generation, addressing the regime-switching behavior documented in financial markets (Hamilton, 1989; Guidolin, 2011). The indicator automatically adjusts its parameters based on market volatility and risk conditions, providing more reliable signals across different market environments. ### 6.3 Institutional Applications The sophisticated risk management overlay makes RAMO particularly suitable for institutional applications where drawdown control is paramount. The indicator's design philosophy aligns with the risk budgeting approaches used by hedge funds and institutional investors (Roncalli, 2013). ## 7. Limitations and Future Research ### 7.1 Parameter Sensitivity Like all technical indicators, RAMO's performance depends on parameter selection. While default parameters are optimized for broad market applications, asset-specific calibration may enhance performance. Future research should examine optimal parameter selection across different asset classes and market conditions. ### 7.2 Market Microstructure Considerations RAMO's effectiveness may vary across different market microstructure environments. High-frequency trading and algorithmic market making have fundamentally altered market dynamics (Aldridge, 2013), potentially affecting momentum indicator performance. ### 7.3 Transaction Cost Integration Future enhancements could incorporate transaction cost analysis to provide net-return-based signals, addressing the implementation shortfall documented in practical momentum strategy applications (Korajczyk & Sadka, 2004). ## References Aldridge, I. (2013). *High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems*. 2nd ed. Hoboken, NJ: John Wiley & Sons. Ang, A. (2014). *Asset Management: A Systematic Approach to Factor Investing*. New York: Oxford University Press. Arms, R. W. (1989). *The Arms Index (TRIN): An Introduction to the Volume Analysis of Stock and Bond Markets*. Homewood, IL: Dow Jones-Irwin. Asness, C. S., Moskowitz, T. J., & Pedersen, L. H. (2013). Value and momentum everywhere. *Journal of Finance*, 68(3), 929-985. Barroso, P., & Santa-Clara, P. (2015). Momentum has its moments. *Journal of Financial Economics*, 116(1), 111-120. Bollinger, J. (1992). *Bollinger on Bollinger Bands*. New York: McGraw-Hill. Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple technical trading rules and the stochastic properties of stock returns. *Journal of Finance*, 47(5), 1731-1764. Calmar, T. (1991). The Calmar ratio: A smoother tool. *Futures*, 20(1), 40. Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). *The Econometrics of Financial Markets*. Princeton, NJ: Princeton University Press. Chekhlov, A., Uryasev, S., & Zabarankin, M. (2005). Drawdown measure in portfolio optimization. *International Journal of Theoretical and Applied Finance*, 8(1), 13-58. Daniel, K., & Moskowitz, T. J. (2016). Momentum crashes. *Journal of Financial Economics*, 122(2), 221-247. Fama, E. F., & French, K. R. (1996). Multifactor explanations of asset pricing anomalies. *Journal of Finance*, 51(1), 55-84. Granville, J. E. (1963). *Granville's New Key to Stock Market Profits*. Englewood Cliffs, NJ: Prentice-Hall. Guidolin, M. (2011). Markov switching models in empirical finance. In D. N. Drukker (Ed.), *Missing Data Methods: Time-Series Methods and Applications* (pp. 1-86). Bingley: Emerald Group Publishing. Hamilton, J. D. (1989). A new approach to the economic analysis of nonstationary time series and the business cycle. *Econometrica*, 57(2), 357-384. Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. *Journal of Finance*, 48(1), 65-91. Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. *Econometrica*, 47(2), 263-291. Kaufman, P. J. (1995). *Smarter Trading: Improving Performance in Changing Markets*. New York: McGraw-Hill. Korajczyk, R. A., & Sadka, R. (2004). Are momentum profits robust to trading costs? *Journal of Finance*, 59(3), 1039-1082. Leland, H. E. (1980). Who should buy portfolio insurance? *Journal of Finance*, 35(2), 581-594. Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of technical analysis: Computational algorithms, statistical inference, and empirical implementation. *Journal of Finance*, 55(4), 1705-1765. Markowitz, H. (1952). Portfolio selection. *Journal of Finance*, 7(1), 77-91. Murphy, J. J. (1999). *Technical Analysis of the Financial Markets: A Comprehensive Guide to Trading Methods and Applications*. New York: New York Institute of Finance. Prechter, R. R., & Frost, A. J. (1978). *Elliott Wave Principle: Key to Market Behavior*. Gainesville, GA: New Classics Library. Pring, M. J. (2002). *Technical Analysis Explained: The Successful Investor's Guide to Spotting Investment Trends and Turning Points*. 4th ed. New York: McGraw-Hill. Roncalli, T. (2013). *Introduction to Risk Parity and Budgeting*. Boca Raton, FL: CRC Press. Shefrin, H., & Statman, M. (1985). The disposition to sell winners too early and ride losers too long: Theory and evidence. *Journal of Finance*, 40(3), 777-790. Taleb, N. N. (2007). *The Black Swan: The Impact of the Highly Improbable*. New York: Random House. Taylor, M. P., & Allen, H. (1992). The use of technical analysis in the foreign exchange market. *Journal of International Money and Finance*, 11(3), 304-314. Treadway, A. B. (1969). On rational entrepreneurial behavior and the demand for investment. *Review of Economic Studies*, 36(2), 227-239. Wilder, J. W. (1978). *New Concepts in Technical Trading Systems*. Greensboro, NC: Trend Research.
Indicador Pine Script®
por EdgeTools
Cumulative Intraday Volume with Long/Short LabelsThis indicator calculates a running total of volume for each trading day, then shows on the price chart when that total crosses levels you choose. Every day at 6:00 PM Eastern Time, the total goes back to zero so it always reflects only the current day’s activity. From that moment on, each time a new candle appears the indicator looks at whether the candle closed higher than it opened or lower. If it closed higher, the candle’s volume is added to the running total; if it closed lower, the same volume amount is subtracted. As a result, the total becomes positive when buyers have dominated so far today and negative when sellers have dominated. Because futures markets close at 6 PM ET, the running total resets exactly then, mirroring the way most intraday traders think in terms of a single session. Throughout the day, you will see this running total move up or down according to whether more volume is happening on green or red candles. Once the total goes above a number you specify (for example, one hundred thousand contracts), the indicator will place a small “Long” label at that candle on the main price chart to let you know buying pressure has reached that level. Similarly, once the total goes below a negative number you choose (for example, minus one hundred thousand), a “Short” label will appear at that candle to signal that selling pressure has reached your chosen threshold. You can set these threshold numbers to whatever makes sense for your trading style or the market you follow. Because raw volume alone never turns negative, this design uses candle direction as a sign. Green candles (where the close is higher than the open) add volume, and red candles (where the close is lower than the open) subtract volume. Summing those signed volume values tells you in a single number whether buying or selling has been stronger so far today. That number resets every evening, so it does not carry over any buying or selling from previous sessions. Once you have this indicator on your chart, you simply watch the “summed volume” line as it moves throughout the day. If it climbs past your long threshold, you know buyers are firmly in control and a long entry might make sense. If it falls past your short threshold, you know sellers are firmly in control and a short entry might make sense. In quieter markets or times of low volume, you might use a smaller threshold so that even modest buying or selling pressure will trigger a label. During very active periods, a larger threshold will prevent too many signals when volume spikes frequently. This approach is straightforward but can be surprisingly powerful. It does not rely on complex formulas or hidden statistical measures. Instead, it simply adds and subtracts daily volume based on candle color, then alerts you when that total reaches levels you care about. Over several years of historical testing, this formula has shown an ability to highlight moments when intraday sentiment shifts decisively from buyers to sellers or vice versa. Because the indicator resets every day at 6 PM, it always reflects only today’s sentiment and remains easy to interpret without carrying over past data. You can use it on any intraday timeframe, but it works especially well on five-minute or fifteen-minute charts for futures contracts. If you want a clear gauge of whether buyers or sellers are dominating in real time, and you prefer a rule-based method rather than a complex model, this indicator gives you exactly that. It shows net buying or selling pressure at a glance, resets each session like most intraday traders do, and marks the moments when that pressure crosses the levels you decide are important. By combining a daily reset with signed volume, you get a single number that tells you precisely what the crowd is doing at any given moment, without any of the guesswork or hidden calculations that more complicated indicators often carry.
Indicador Pine Script®
por QuantByBoji
Buysell Martingale Signal - CustomBuysell Martingale Signal - Custom Indicator Introduction: This indicator provides a dynamic buy and sell signal system incorporating an adaptive Martingale logic. Built upon the signalLib_yashgode9/2 library, it is designed for use across various markets and timeframes. Key Features: Primary Buy & Sell Signals: Identifies initial buy and sell opportunities based on directional changes derived from the signalLib. Martingale Signals: For Short (Sell) Positions: A Martingale Sell signal is triggered when the price moves against the existing short position by a specified stepPercent from the last entry price, indicating a potential opportunity to average down or increase position size. For Long (Buy) Positions: Similarly, a Martingale Buy signal is triggered when the price moves against the existing long position by a stepPercent from the last entry price. On-Chart Labels: Displays clear, customizable labels on the chart for primary Buy, Sell, Martingale Buy, and Martingale Sell signals. Customizable Colors: Allows users to set distinct colors for primary signals and Martingale signals for better visual distinction. Adjustable Sensitivity: Features configurable parameters (DEPTH_ENGINE, DEVIATION_ENGINE, BACKSTEP_ENGINE) to fine-tune the sensitivity of the underlying signal generation. Webhook Support (Static Message Alerts): This indicator provides alerts with static messages for both primary and Martingale buy/sell signals. These alerts can be leveraged for automation by external systems (such as trading bots or exchange-provided Webhook Signal Trading services). Important Note: When using these alerts for automation, an external system is required to handle the complex Martingale logic and position management (e.g., tracking steps, PnL calculation, hedging, dynamic quantity sizing), as this indicator solely focuses on signal generation and sending predefined messages. How to Use: Add the indicator to your desired chart. Adjust the input parameters in the indicator's settings to match your specific trading symbol and timeframe. For automation, you can set up TradingView alerts for the Buy Signal (Main/Martingale) and Sell Signal (Main/Martingale) conditions, pointing them to your preferred Webhook URL. Configurable Parameters: DEPTH_ENGINE: (e.g., 30) Controls the depth of analysis for the signal algorithm. DEVIATION_ENGINE: (e.g., 5) Defines the allowable deviation for signal generation. BACKSTEP_ENGINE: (e.g., 5) Specifies the number of historical bars to look back. Martingale Step Percent: (e.g., 0.5) The percentage price movement against the current position that triggers a Martingale signal. Labels Transparency: Adjusts the transparency of the on-chart signal labels. Buy-Color / Sell-Color: Sets the color for primary Buy and Sell signal labels. Martingale Buy-Color / Martingale Sell-Color: Sets the color for Martingale Buy and Sell signal labels. Label size: Controls the visual size of the labels. Label Offset: Adjusts the vertical offset of the labels from the candlesticks. Risk Warning: Financial trading inherently carries significant risk. Martingale strategies are particularly high-risk and can lead to substantial losses or even complete liquidation of capital if the market moves strongly and persistently against your position. Always backtest thoroughly and practice with a demo account, fully understanding the associated risks, before engaging with real capital.
Indicador Pine Script®
por NADER_CY
5
Codigo Trading 1.0📌Codigo Trading 1.0 This indicator strategically combines SuperTrend, multiple Exponential Moving Averages (EMAs), the Relative Strength Index (RSI), and the Average True Range (ATR) to offer clear entry and exit signals, as well as an in-depth view of market trends. Ideal for traders looking to optimize their operations with an all-in-one tool. 🔩How the Indicator Works: This indicator relies on the interaction and confirmation of several key components to generate signals: SuperTrend: Determines the primary trend direction. An uptrend SuperTrend signal (green line) indicates an upward trend, while a downtrend (red line) signals a downward trend. It also serves as a guide for setting Stop Loss and Take Profit levels. EMAs: Includes EMAs of 10, 20, 55, 100, 200, and 325 periods. The relationship between the EMA 10 and EMA 20 is fundamental for confirming the strength and direction of movements. An EMA 10 above the EMA 20 suggests an uptrend, and vice versa. Longer EMAs act as dynamic support and resistance levels, offering a broader view of the market structure. RSI: Used to identify overbought (RSI > 70/80) and oversold (RSI < 30/20) conditions, generating "Take Profit" alerts for potential trade closures. ATR: Monitors market volatility to help you manage exits. ATR exit signals are triggered when volatility changes direction, indicating a possible exhaustion of the movement. 🗒️Entry and Exit Signals: I designed specific alerts based on all the indicators I use in conjunction: Long Entries: When SuperTrend is bullish and EMA 10 crosses above EMA 20. Short Entries: When SuperTrend is bearish and EMA 10 crosses below EMA 20. RSI Exits (Take Profit): Indicated by "TP" labels on the chart, when the RSI reaches extreme levels (overbought for longs, oversold for shorts). EMA 20 Exits: When the price closes below EMA 20 (for longs) or above EMA 20 (for shorts). ATR Exits: When the ATR changes direction, signaling a possible decrease in momentum. 📌Key Benefits: Clarity in Trend: Quickly identifies market direction with SuperTrend and EMA alignment. Strategic Entry and Exit Signals: Receive timely alerts to optimize your entry and exit points. Assisted Trade Management: RSI and ATR help you consider when to take profits or exit a position. Intuitive Visualization: Arrows, labels, and colored lines make analysis easy to interpret. Disclaimer: Trading in financial markets carries significant risks. This indicator is an analysis tool and should not be considered financial advice. Always conduct your own research and trade at your own risk.
Indicador Pine Script®
por Codigo_Trading
Profits Framework 25.6The Profits Framework 25.6 is a multi-timeframe, EMA-based trading system designed for futures traders seeking clean, high-conviction entries. This script uses: EMAs (12, 50, 200) for structure 30-minute confluence with the current chart A 4-factor entry scoring system (bias, stack, pullback, candle confirmation) Fixed 100-tick target/stop Real-time BUY/SELL labels with entry prices Scoreboard showing win/loss outcomes for both directions Best suited for NQ futures traders using the 15-minute chart for entries. Test and adapt to your style before live trading.
Indicador Pine Script®
por dpratt
OA - SMESSmart Money Entry Signals (SMES) The SMES indicator is developed to identify potential turning points in market behavior by analyzing internal price dynamics, rather than relying on external volume or sentiment data. It leverages normalized price movement, directional volatility, and smoothing algorithms to detect potential areas of accumulation or distribution by market participants. Core Concepts Smart Money Flow calculation based on normalized price positioning Directional VHF (Vertical Horizontal Filter) used to enhance signal directionality Overbought and Oversold regions defined with optional glow visualization Entry and Exit signals based on dynamic crossovers Highly customizable input parameters for precision control Key Inputs Smart Money Flow Period Smoothing Period Price Analysis Length Fibonacci Lookback Length Visual toggle options (zones, glow effects, signal display) Usage This tool plots the smoothed smart money flow as a standalone oscillator, designed to help traders identify potential momentum shifts or extremes in market sentiment. Entry signals are generated through crossover logic, while optional filters based on price behavior can refine those signals. Exit signals are shown when the smart money line exits extreme regions. Important Notes This indicator does not repaint Works on all timeframes and instruments Best used as a confirmation tool with other technical frameworks All calculations are based strictly on price data Disclaimer This script is intended for educational purposes only. It does not provide financial advice or guarantee performance. Please do your own research and apply appropriate risk management before making any trading decisions.
Indicador Pine Script®
por onurag
4
CNN Statistical Trading System [PhenLabs]📌 DESCRIPTION An advanced pattern recognition system utilizing Convolutional Neural Network (CNN) principles to identify statistically significant market patterns and generate high-probability trading signals. CNN Statistical Trading System transforms traditional technical analysis by applying machine learning concepts directly to price action. Through six specialized convolution kernels, it detects momentum shifts, reversal patterns, consolidation phases, and breakout setups simultaneously. The system combines these pattern detections using adaptive weighting based on market volatility and trend strength, creating a sophisticated composite score that provides both directional bias and signal confidence on a normalized -1 to +1 scale. 🚀 CONCEPTS • Built on Convolutional Neural Network pattern recognition methodology adapted for financial markets • Six specialized kernels detect distinct price patterns: upward/downward momentum, peak/trough formations, consolidation, and breakout setups • Activation functions create non-linear responses with tanh-like behavior, mimicking neural network layers • Adaptive weighting system adjusts pattern importance based on current market regime (volatility < 2% and trend strength) • Multi-confirmation signals require CNN threshold breach (±0.65), RSI boundaries, and volume confirmation above 120% of 20-period average 🔧 FEATURES Six-Kernel Pattern Detection: Simultaneous analysis of upward momentum, downward momentum, peak/resistance, trough/support, consolidation, and breakout patterns using mathematically optimized convolution kernels. Adaptive Neural Architecture: Dynamic weight adjustment based on market volatility (ATR/Price) and trend strength (EMA differential), ensuring optimal performance across different market conditions. Professional Visual Themes: Four sophisticated color palettes (Professional, Ocean, Sunset, Monochrome) with cohesive design language. Default Monochrome theme provides clean, distraction-free analysis. Confidence Band System: Upper and lower confidence zones at 150% of threshold values (±0.975) help identify high-probability signal areas and potential exhaustion zones. Real-Time Information Panel: Live display of CNN score, market state with emoji indicators, net momentum, confidence percentage, and RSI confirmation with dynamic color coding based on signal strength. Individual Feature Analysis: Optional display of all six kernel outputs with distinct visual styles (step lines, circles, crosses, area fills) for advanced pattern component analysis. User Guide • Monitor CNN Score crossing above +0.65 for long signals or below -0.65 for short signals with volume confirmation • Use confidence bands to identify optimal entry zones - signals within confidence bands carry higher probability • Background intensity reflects signal strength - darker backgrounds indicate stronger conviction • Enter long positions when blue circles appear above oscillator with RSI < 75 and volume > 120% average • Enter short positions when dark circles appear below oscillator with RSI > 25 and volume confirmation • Information panel provides real-time confidence percentage and momentum direction for position sizing decisions • Individual feature plots allow granular analysis of specific pattern components for strategy refinement 💡Conclusion CNN Statistical Trading System represents the evolution of technical analysis, combining institutional-grade pattern recognition with retail accessibility. The six-kernel architecture provides comprehensive market pattern coverage while adaptive weighting ensures relevance across all market conditions. Whether you’re seeking systematic entry signals or advanced pattern confirmation, this indicator delivers mathematically rigorous analysis with intuitive visual presentation.
Indicador Pine Script®
por PhenLabs
1
Congestion Indicator - Oscillator by saurabh maggoCore Functionality Market State Detection: Congestion: Identifies periods of low volatility (price consolidation) where the price range is tight relative to the Average True Range (ATR). Visualized with a blue background in the oscillator panel. Breakout Up: Detects upward breakouts from congestion zones, requiring conditions like price movement above the congestion high, volume spikes, and volatility increases. Visualized with a green background. Breakdown (Breakout Down): Detects downward breakouts from congestion zones, with similar conditions as Breakout Up but for downward movement. Visualized with a red background. Post-Congestion: Identifies the period after a congestion zone ends but before a breakout occurs (if extend_until_breakout is disabled). Visualized with a yellow background. Pullback: Detects pullbacks after breakouts or breakdowns, useful for identifying potential entry points (if use_pullback_entry is enabled). Visualized with a purple background. Visualization: Oscillator Panel: Displays the market state in a separate panel below the chart. Background Color: The panel’s background color changes to reflect the current state (e.g., blue for Congestion, green for Breakout Up). Histogram Plot: Optionally plots the state value as a histogram (e.g., 1 for Congestion, 2 for Breakout Up), toggleable via TradingView’s "Style" tab ("Market State"). The histogram provides a numerical representation of the state: Congestion: 1.0 Breakout Up: 2.0 Breakdown: -2.0 Post-Congestion: 0.5 Pullback: 1.5 None: 0.0 Alerts: Generates alerts for state changes (Congestion, Breakout Up, Breakdown). Supports enhanced alerts (if use_enhanced_alerts is enabled), including additional context like breakout level, volatility state, and trend direction. Includes an alert cooldown period (if use_alert_cooldown is enabled) to prevent excessive alerts. Key Features and Filters Customizable Parameters: Lookback Period: Adjusts the number of bars used to calculate the price range for congestion detection. Range Threshold: Sets the maximum price range (as a percentage of ATR) for a congestion zone. Dynamic Threshold: Optionally uses a percentile-based dynamic threshold for more adaptive congestion detection. Minimum Congestion Bars: Requires a minimum number of bars for a congestion zone to be confirmed. Volume Filter: Optionally requires low volume during congestion zones. Volume Breakout Filter: Requires a volume spike for breakouts/breakdowns. Volatility Breakout Filter: Requires an ATR spike for breakouts/breakdowns. Minimum Price Movement: Optionally requires a minimum price movement for breakouts/breakdowns. RSI Filter: Optionally requires RSI to be in a neutral range during congestion. Max Price Range Filter: Limits the absolute price range for congestion zones. Trend Filter: Optionally filters breakouts/breakdowns based on a higher timeframe trend (using a moving average). Momentum Filter: Optionally requires MACD momentum confirmation for breakouts/breakdowns. Pullback Detection: Optionally detects pullbacks after breakouts/breakdowns for entry opportunities. Timeframe Adjustment: Adjusts parameters based on the chart’s timeframe. Auto-Settings: Automatically adjusts parameters based on market volatility. Show Current Day Only: Optionally limits the indicator’s display to the current trading day (NSE session). Presets: Offers predefined configurations (Default, Aggressive, Conservative) for quick setup. Session Support: Operates within the NSE session (9:15 AM–3:30 PM IST) by default, ensuring relevance for Indian markets. Visual Output The oscillator panel uses color-coded backgrounds to indicate the market state: Blue: Congestion Green: Breakout Up Red: Breakdown Yellow: Post-Congestion Purple: Pullback Transparent (None): No state detected The histogram plot (optional) provides a numerical representation of the state, which can be toggled on/off in TradingView’s settings. Alerts Alerts are triggered for significant state changes (Congestion, Breakout Up, Breakdown). Enhanced alerts include additional details like price levels, volatility, and trend direction, making them more informative for traders. Step 2: Craft the Description for Publishing Based on the analysis, here’s a concise, user-friendly description you can use when publishing the indicator on TradingView: Congestion Indicator - Oscillator by Saurabh Maggo This indicator identifies market congestion zones, breakouts, breakdowns, post-congestion periods, and pullbacks in a separate oscillator panel below your chart. Designed for traders, it helps you spot key market states and potential trading opportunities with clear visual cues and customizable alerts. Key Features: Market States: Detects Congestion (Blue), Breakout Up (Green), Breakdown (Red), Post-Congestion (Yellow), and Pullbacks (Purple). Visual Display: Shows market states using background colors in an oscillator panel, with an optional histogram plot (toggleable in settings). Alerts: Generates alerts for state changes, with enhanced options to include price levels, volatility, and trend context. Customizable Filters: Includes volume, volatility, RSI, trend, momentum, and price movement filters to refine signals. Adaptable Settings: Supports dynamic thresholds, timeframe adjustments, auto-settings based on volatility, and predefined presets (Default, Aggressive, Conservative). NSE Session: Optimized for Indian markets with a default session time of 9:15 AM–3:30 PM IST. How can Grok help?
Indicador Pine Script®
por srbhmaggo