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Correlation Coefficient📊 Correlation Coefficient (CC) This indicator measures the statistical correlation between two selected securities over a defined period, scaled from -100 to +100. It helps you quickly assess whether assets are moving: Together (positive correlation) Opposite (negative correlation) Independently (zero correlation) 🔧 Features: Select any two symbols (default: NIFTY & BANKNIFTY) Adjustable length parameter for short-term or long-term correlation analysis Clean, color-coded plot with horizontal levels to easily identify key correlation zones 📈 Useful For: Pair trading setups Hedging strategies Detecting market regime shifts or intermarket divergences ⚠️ Disclaimer: This is not trading or investment advice. This indicator is intended for informational purposes only and is not recommended for making direct trading decisions.
אינדיקטור Pine Script®
מאת ‎Pro_Quantitative_Trader‎
Ergodic Market Divergence (EMD)Ergodic Market Divergence (EMD) Bridging Statistical Physics and Market Dynamics Through Ensemble Analysis The Revolutionary Concept: When Physics Meets Trading After months of research into ergodic theory—a fundamental principle in statistical mechanics—I've developed a trading system that identifies when markets transition between predictable and unpredictable states. This indicator doesn't just follow price; it analyzes whether current market behavior will persist or revert, giving traders a scientific edge in timing entries and exits. The Core Innovation: Ergodic Theory Applied to Markets What Makes Markets Ergodic or Non-Ergodic? In statistical physics, ergodicity determines whether a system's future resembles its past. Applied to trading: Ergodic Markets (Mean-Reverting) - Time averages equal ensemble averages - Historical patterns repeat reliably - Price oscillates around equilibrium - Traditional indicators work well Non-Ergodic Markets (Trending) - Path dependency dominates - History doesn't predict future - Price creates new equilibrium levels - Momentum strategies excel The Mathematical Framework The Ergodic Score combines three critical divergences: Ergodic Score = (Price Divergence × Market Stress + Return Divergence × 1000 + Volatility Divergence × 50) / 3 Where: Price Divergence: How far current price deviates from market consensus Return Divergence: Momentum differential between instrument and market Volatility Divergence: Volatility regime misalignment Market Stress: Adaptive multiplier based on current conditions The Ensemble Analysis Revolution Beyond Single-Instrument Analysis Traditional indicators analyze one chart in isolation. EMD monitors multiple correlated markets simultaneously (SPY, QQQ, IWM, DIA) to detect systemic regime changes. This ensemble approach: Reveals Hidden Divergences: Individual stocks may diverge from market consensus before major moves Filters False Signals: Requires broader market confirmation Identifies Regime Shifts: Detects when entire market structure changes Provides Context: Shows if moves are isolated or systemic Dynamic Threshold Adaptation Unlike fixed-threshold systems, EMD's boundaries evolve with market conditions: Base Threshold = SMA(Ergodic Score, Lookback × 3) Adaptive Component = StDev(Ergodic Score, Lookback × 2) × Sensitivity Final Threshold = Smoothed(Base + Adaptive) This creates context-aware signals that remain effective across different market environments. The Confidence Engine: Know Your Signal Quality Multi-Factor Confidence Scoring Every signal receives a confidence score based on: Signal Clarity (0-35%): How decisively the ergodic threshold is crossed Momentum Strength (0-25%): Rate of ergodic change Volatility Alignment (0-20%): Whether volatility supports the signal Market Quality (0-20%): Price convergence and path dependency factors Real-Time Confidence Updates The Live Confidence metric continuously updates, showing: - Current opportunity quality - Market state clarity - Historical performance influence - Signal recency boost - Visual Intelligence System Adaptive Ergodic Field Bands Dynamic bands that expand and contract based on market state: Primary Color: Ergodic state (mean-reverting) Danger Color: Non-ergodic state (trending) Band Width: Expected price movement range Squeeze Indicators: Volatility compression warnings Quantum Wave Ribbons Triple EMA system (8, 21, 55) revealing market flow: Compressed Ribbons: Consolidation imminent Expanding Ribbons: Directional move developing Color Coding: Matches current ergodic state Phase Transition Signals Clear entry/exit markers at regime changes: Bull Signals: Ergodic restoration (mean reversion opportunity) Bear Signals: Ergodic break (trend following opportunity) Confidence Labels: Percentage showing signal quality Visual Intensity: Stronger signals = deeper colors Professional Dashboard Suite Main Analytics Panel (Top Right) Market State Monitor - Current regime (Ergodic/Non-Ergodic) - Ergodic score with threshold - Path dependency strength - Quantum coherence percentage Divergence Metrics - Price divergence with severity - Volatility regime classification - Strategy mode recommendation - Signal strength indicator Live Intelligence - Real-time confidence score - Color-coded risk levels - Dynamic strategy suggestions Performance Tracking (Left Panel) Signal Analytics - Total historical signals - Win rate with W/L breakdown - Current streak tracking - Closed trade counter Regime Analysis - Current market behavior - Bars since last signal - Recommended actions - Average confidence trends Strategy Command Center (Bottom Right) Adaptive Recommendations - Active strategy mode - Primary approach (mean reversion/momentum) - Suggested indicators ("weapons") - Entry/exit methodology - Risk management guidance - Comprehensive Input Guide Core Algorithm Parameters Analysis Period (10-100 bars) Scalping (10-15): Ultra-responsive, more signals, higher noise Day Trading (20-30): Balanced sensitivity and stability Swing Trading (40-100): Smooth signals, major moves only Default: 20 - optimal for most timeframes Divergence Threshold (0.5-5.0) Hair Trigger (0.5-1.0): Catches every wiggle, many false signals Balanced (1.5-2.5): Good signal-to-noise ratio Conservative (3.0-5.0): Only extreme divergences Default: 1.5 - best risk/reward balance Path Memory (20-200 bars) Short Memory (20-50): Recent behavior focus, quick adaptation Medium Memory (50-100): Balanced historical context Long Memory (100-200): Emphasizes established patterns Default: 50 - captures sufficient history without lag Signal Spacing (5-50 bars) Aggressive (5-10): Allows rapid-fire signals Normal (15-25): Prevents clustering, maintains flow Conservative (30-50): Major setups only Default: 15 - optimal trade frequency Ensemble Configuration Select markets for consensus analysis: SPY: Broad market sentiment QQQ: Technology leadership IWM: Small-cap risk appetite DIA: Blue-chip stability More instruments = stronger consensus but potentially diluted signals Visual Customization Color Themes (6 professional options): Quantum: Cyan/Pink - Modern trading aesthetic Matrix: Green/Red - Classic terminal look Heat: Blue/Red - Temperature metaphor Neon: Cyan/Magenta - High contrast Ocean: Turquoise/Coral - Calming palette Sunset: Red-orange/Teal - Warm gradients Display Controls: - Toggle each visual component - Adjust transparency levels - Scale dashboard text - Show/hide confidence scores - Trading Strategies by Market State - Ergodic State Strategy (Primary Color Bands) Market Characteristics - Price oscillates predictably - Support/resistance hold - Volume patterns repeat - Mean reversion dominates Optimal Approach Entry: Fade moves at band extremes Target: Middle band (equilibrium) Stop: Just beyond outer bands Size: Full confidence-based position Recommended Tools - RSI for oversold/overbought - Bollinger Bands for extremes - Volume profile for levels - Non-Ergodic State Strategy (Danger Color Bands) Market Characteristics - Price trends persistently - Levels break decisively - Volume confirms direction - Momentum accelerates Optimal Approach Entry: Breakout from bands Target: Trail with expanding bands Stop: Inside opposite band Size: Scale in with trend Recommended Tools - Moving average alignment - ADX for trend strength - MACD for momentum - Advanced Features Explained Quantum Coherence Metric Measures phase alignment between individual and ensemble behavior: 80-100%: Perfect sync - strong mean reversion setup 50-80%: Moderate alignment - mixed signals 0-50%: Decoherence - trending behavior likely Path Dependency Analysis Quantifies how much history influences current price: Low (<30%): Technical patterns reliable Medium (30-50%): Mixed influences High (>50%): Fundamental shift occurring Volatility Regime Classification Contextualizes current volatility: Normal: Standard strategies apply Elevated: Widen stops, reduce size Extreme: Defensive mode required Signal Strength Indicator Real-time opportunity quality: - Distance from threshold - Momentum acceleration - Cross-validation factors Risk Management Framework Position Sizing by Confidence 90%+ confidence = 100% position size 70-90% confidence = 75% position size 50-70% confidence = 50% position size <50% confidence = 25% or skip Dynamic Stop Placement Ergodic State: ATR × 1.0 from entry Non-Ergodic State: ATR × 2.0 from entry Volatility Adjustment: Multiply by current regime Multi-Timeframe Alignment - Check higher timeframe regime - Confirm ensemble consensus - Verify volume participation - Align with major levels What Makes EMD Unique Original Contributions First Ergodic Theory Trading Application: Transforms abstract physics into practical signals Ensemble Market Analysis: Revolutionary multi-market divergence system Adaptive Confidence Engine: Institutional-grade signal quality metrics Quantum Coherence: Novel market alignment measurement Smart Signal Management: Prevents clustering while maintaining responsiveness Technical Innovations Dynamic Threshold Adaptation: Self-adjusting sensitivity Path Memory Integration: Historical dependency weighting Stress-Adjusted Scoring: Market condition normalization Real-Time Performance Tracking: Built-in strategy analytics Optimization Guidelines By Timeframe Scalping (1-5 min) Period: 10-15 Threshold: 0.5-1.0 Memory: 20-30 Spacing: 5-10 Day Trading (5-60 min) Period: 20-30 Threshold: 1.5-2.5 Memory: 40-60 Spacing: 15-20 Swing Trading (1H-1D) Period: 40-60 Threshold: 2.0-3.0 Memory: 80-120 Spacing: 25-35 Position Trading (1D-1W) Period: 60-100 Threshold: 3.0-5.0 Memory: 100-200 Spacing: 40-50 By Market Condition Trending Markets - Increase threshold - Extend memory - Focus on breaks Ranging Markets - Decrease threshold - Shorten memory - Focus on restores Volatile Markets - Increase spacing - Raise confidence requirement - Reduce position size - Integration with Other Analysis - Complementary Indicators For Ergodic States - RSI divergences - Bollinger Band squeezes - Volume profile nodes - Support/resistance levels For Non-Ergodic States - Moving average ribbons - Trend strength indicators - Momentum oscillators - Breakout patterns - Fundamental Alignment - Check economic calendar - Monitor sector rotation - Consider market themes - Evaluate risk sentiment Troubleshooting Guide Too Many Signals: - Increase threshold - Extend signal spacing - Raise confidence minimum Missing Opportunities - Decrease threshold - Reduce signal spacing - Check ensemble settings Poor Win Rate - Verify timeframe alignment - Confirm volume participation - Review risk management Disclaimer This indicator is for educational and informational purposes only. It does not constitute financial advice. Trading involves substantial risk of loss and is not suitable for all investors. Past performance does not guarantee future results. The ergodic framework provides unique market insights but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose. This tool should complement, not replace, comprehensive trading strategies and sound judgment. Markets remain inherently unpredictable despite advanced analysis techniques. Transform market chaos into trading clarity with Ergodic Market Divergence. Created with passion for the TradingView community Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
אינדיקטור Pine Script®
מאת ‎DskyzInvestments‎
7
Profit Guard ProProfitGuard Pro ProfitGuard Pro is a risk management and profit calculation tool that helps traders optimize their trades by handling position sizing, risk management, leverage, and take profit calculations. With support for both cumulative and non-cumulative take profit strategies, this versatile indicator provides the insights you need to maximize your trading strategy. How to Use ProfitGuard Pro: Load the Indicator: Add ProfitGuard Pro to your chart in TradingView. Set Your Entry Position: Input your desired entry price. Define Your Stop Loss: Enter the price at which your trade will exit to minimize losses. Add Take Profit Levels: Input your TP1, TP2, TP3, and TP4 levels, as needed. If you want fewer take profit levels, adjust the number of TPs in the settings menu. You can choose between 1 to 4 take profit levels based on your strategy. Adjust Risk Settings: Specify your account size and risk percentage to calculate position size and leverage. Choose Cumulative or Non-Cumulative Mode: Toggle cumulative profit mode to either recalculate position sizes as each take profit is hit or keep position sizes static for each TP. Once set up, ProfitGuard Pro will automatically calculate your position size, leverage, and potential profits for each take profit level, providing a clear visual on your chart to guide your trading decisions. Key Features: Risk Management: Calculate your risk percentage based on account size and stop loss. Visualize risk in dollar terms and percentage of your account. Position Size & Leverage: Automatically calculate the ideal position size and leverage for your trade based on your entry, stop loss, and risk settings. Ensure you are trading with the appropriate leverage for your account size. Cumulative vs Non-Cumulative Profit Mode: Cumulative Mode: Adjusts position size after each take profit is reached, recalculating for remaining contracts. Non-Cumulative Mode: Treats each take profit as a separate calculation using the full position size. Take Profit Levels: Set up to 4 customizable take profit levels. Adjust percentage values for each TP target, and visualize them on your chart with easy-to-read lines. Profit Calculation: Displays potential profits for each take profit level based on whether cumulative or non-cumulative mode is selected. Calculate your risk-reward ratio dynamically at each TP. Customizable Visuals: Easily customize the table's size, position, and color scheme to fit your chart. Visualize key trade details like leverage, contracts, margin, and profits directly on your chart. Short and Long Position Support: Automatically adjusts calculations based on whether you're trading long or short.
אינדיקטור Pine Script®
מאת ‎svstaats‎
Value at Risk (VaR/CVaR) - Stop Loss ToolThis script calculates Value at Risk (VaR) and Conditional Value at Risk (CVaR) over a configurable T-bar forward horizon, based on historical T-bar log returns. It plots projected price thresholds that reflect the worst X% of historical return outcomes, helping set statistically grounded stop-loss levels. A 95% 5-day VaR of −3% means: “In the worst 5% of all historical 5-day periods, losses were 3% or more.” If you're bullish, and your thesis is correct, price should not behave like one of those worst-case scenarios. So if the market starts trading below that 5-day VaR level, it may indicate that your long bias is invalidated, and a stop-loss near that level can help protect against further downside consistent with tail-risk behavior. How it's different: Unlike ATR or standard deviation-based methods, which measure recent volatility magnitude, VaR/CVaR incorporate both the magnitude and **likelihood** (5% chance for example) of adverse moves. This makes it better suited for risk-aware position sizing and exits grounded in actual historical return distributions. How to use for stop placement: - Set your holding horizon (T) and confidence level (e.g., 95%) in the inputs. - The script plots a price level below which only the worst 5% (or chosen %) of T-bar returns have historically occurred (VaR). - If price approaches or breaches the VaR line, your bullish/bearish thesis may be invalidated. - CVaR gives a deeper threshold: the average loss **if** things go worse than VaR — useful for a secondary or emergency stop. FURTHER NOTES FROM SOURCE CODE: //======================================================================// // If you're bullish (expecting the price to go up), then under normal circumstances, prices should not behave like they do on the worst-case days. // If they are — you're probably wrong, or something unexpected is happening. Basically, returns shouldn't be exhibiting downside tail-like behavior if you're bullish. // VaR(95%, T) gives the threshold below which the price falls only 5% of the time historically, over T days/bars and considering N historical samples. // CVaR tells you the expected/average price level if that adverse move continues // Caveats: // For a variety of reasons, VaR underestimates volatility, despite using historical returns directly rather than making normality assumptions // as is the case with the standard historicalvol/bollinger band/stdev/ATR approaches) // Volatility begets volatility (volatility clustering), and VaR is not a conditional probability on recent volatility so it likely underestimates the true volatility of an adverse event // Regieme shifts occur (bullish phase after prolonged bearish behavior), so upside/short VaR would underestimate the best-case days in the beginning of that move, depending on lookahead horizon/sampling period // News/events happen, and maybe your sampling period doesn't contain enough event-driven returns to form reliable stats // In general of course, this tool assumes past return distributions are reflective of forward risk (not the case in non-stationary time series) // Thus, this tool is not predictive — it shows historical tail risk, not guaranteed outcomes. // Also, when forming log-returns, overlapping windows of returns are used (to get more samples), but this introduces autocorrelation (if it wasn't there already). This means again, the true VaR is underestimated. // Description: // This script calculates and plots both Value at Risk (VaR) and // Conditional Value at Risk (CVaR) for a given confidence level, using // historical log returns. It computes both long-side (left tail) and // short-side (right tail) risk, and converts them into price thresholds (red and green lines respectively). // // Key Concepts: // - VaR: "There is a 95% chance the loss will be less than this value over T days. Represents the 95th-percentile worst empirical returns observed in the sampling period, over T bars. // - CVaR: "Given that the loss exceeds the VaR, the average of those worst 5% losses is this value. (blue line)" Expected tail loss. If the worst case breached, how bad can it get on average // - For shorts, the script computes the mirror (right-tail) equivalents. // - Use T-day log returns if estimating risk over multiple days forward. // - You can see instances where the VaR for time T, was surpassed historically with the "backtest" boolean // // Usage for Stop-Loss: // - LONG POSITIONS: // • 95th percentile means, 5% of the time (1 in 20 times) you'd expect to get a VaR level loss (touch the red line), over the next T bars. // • VaR threshold = minimum price expected with (1 – confidence)% chance. // • CVaR threshold = expected price if that worst-case zone is breached. // → Use as potential stop-loss (VaR) or disaster stop (CVaR). If you're bullish (and you're right), price should not be exhibiting returns consistent with the worst 5% of days/T_bars historically. //======================================================================//
אינדיקטור Pine Script®
מאת ‎scakolli‎
1A Monthly P&L Table - Using Library1A Monthly P&L Table: Track Your Performance Month-by-Month Overview: The 1A Monthly P&L Table is a straightforward yet powerful indicator designed to give you an immediate overview of your asset's (or strategy's) percentage performance on a monthly basis. Displayed conveniently in the bottom-right corner of your chart, this tool helps you quickly assess historical gains and losses, making it easier to analyze trends in performance over time. Key Features: Monthly Performance at a Glance: Clearly see the percentage change for each past month. Cumulative P&L: A running total of the displayed monthly P&L is provided, giving you a quick sum of performance over the selected period. Customizable Display: Months to Display: Choose how many past months you want to see in the table (from 1 to 60 months). Text Size: Adjust the text size (Tiny, Small, Normal, Large, Huge) to fit your viewing preferences. Text Color: Customize the color of the text for better visibility against your chart background. Intraday & Daily Compatibility: The table is optimized to display on daily and intraday timeframes, ensuring it's relevant for various trading styles. (Note: For very long-term analysis on weekly/monthly charts, you might consider other tools, as this focuses on granular monthly P&L.) How It Works: The indicator calculates the percentage change from the close of the previous month to the close of the current month. For the very first month displayed, it calculates the P&L from the opening price of the chart's first bar to the close of that month. This data is then neatly organized into a table, updated on the last bar of the day or session. Ideal For: Traders and investors who want a quick, visual summary of monthly performance. Analyzing seasonal trends or consistent periods of profitability/drawdown. Supplementing backtesting results with a clear month-by-month breakdown. Settings: Text Color: Changes the color of all text within the table. Text Size: Controls the font size of the table content. Months to Display: Determines the number of recent months included in the table.
אינדיקטור Pine Script®
מאת ‎forexfederation‎
MonthlyPnLTableLibrary "MonthlyPnLTable" monthlyPnL(currentClose, initialOpenPrice, monthsToDisplay)   Parameters:      currentClose (float)      initialOpenPrice (float)      monthsToDisplay (int) displayPnLTable(pnls, pnlMonths, pnlYears, textSizeOption, labelColor)   Parameters:      pnls (array)      pnlMonths (array)      pnlYears (array)      textSizeOption (string)      labelColor (color)
ספריית Pine Script®
מאת ‎forexfederation‎
LANZ Strategy 3.0 [Backtest]🔷 LANZ Strategy 3.0 — Asian Range Fibonacci Scalping Strategy LANZ Strategy 3.0 is a precision-engineered backtesting tool tailored for intraday traders who rely on the Asian session range to determine directional bias. This strategy implements dynamic Fibonacci projections and strict time-window validation to simulate a clean and disciplined trading environment. 🧠 Core Components: Asian Range Bias Definition: Direction is established between 01:15–02:15 a.m. NY time based on the candle’s close in relation to the midpoint of the Asian session range (18:00–01:15 NY). Limit Order Execution: Only one trade is placed daily, using a limit order at the Asian range high (for sells) or low (for buys), between 01:15–08:00 a.m. NY. Fibonacci-Based TP/SL: Original Mode: TP = 2.25x range, SL = 0.75x range. Optimized Mode: TP = 1.95x range, SL = 0.65x range. No Trade After 08:00 NY: If the limit order is not executed before 08:00 a.m. NY, it is canceled. Fallback Logic at 02:15 NY: If the market direction misaligns with the setup at 02:15 a.m., the system re-evaluates and can re-issue the order. End-of-Day Closure: All positions are closed at 15:45 NY if still open. 📊 Backtest-Ready Design: Entries and exits are executed using strategy.entry() and strategy.exit() functions. Position size is fixed via capital risk allocation ($100 per trade by default). Only one position can be active at a time, ensuring controlled risk. 📝 Notes: This strategy is ideal for assets sensitive to the Asian/London session overlap, such as Forex pairs and indices. Easily switch between Fibonacci versions using a single dropdown input. Fully deterministic: all entries are based on pre-defined conditions and time constraints. 👤 Credits: Strategy developed by rau_u_lanz using Pine Script v6. Built for traders who favor clean sessions, directional clarity, and consistent execution using time-based logic and Fibonacci projections.
אסטרטגיית Pine Script®
מאת ‎rau_u_lanz‎
Lorentzian Classification - Advanced Trading DashboardLorentzian Classification - Relativistic Market Analysis A Journey from Theory to Trading Reality What began as fascination with Einstein's relativity and Lorentzian geometry has evolved into a practical trading tool that bridges theoretical physics and market dynamics. This indicator represents months of wrestling with complex mathematical concepts, debugging intricate algorithms, and transforming abstract theory into actionable trading signals. The Theoretical Foundation Lorentzian Distance in Market Space Traditional Euclidean distance treats all feature differences equally, but markets don't behave uniformly. Lorentzian distance, borrowed from spacetime geometry, provides a more nuanced similarity measure: d(x,y) = Σ ln(1 + |xi - yi|) This logarithmic formulation naturally handles: Scale invariance: Large price moves don't overwhelm small but significant patterns Outlier robustness: Extreme values are dampened rather than dominating Non-linear relationships: Captures market behavior better than linear metrics K-Nearest Neighbors with Relativistic Weighting The algorithm searches historical market states for patterns similar to current conditions. Each neighbor receives weight inversely proportional to its Lorentzian distance: w = 1 / (1 + distance) This creates a "gravitational" effect where closer patterns have stronger influence on predictions. The Implementation Challenge Creating meaningful market features required extensive experimentation: Price Features: Multi-timeframe momentum (1, 2, 3, 5, 8 bar lookbacks) Volume Features: Relative volume analysis against 20-period average Volatility Features: ATR and Bollinger Band width normalization Momentum Features: RSI deviation from neutral and MACD/price ratio Each feature undergoes min-max normalization to ensure equal weighting in distance calculations. The Prediction Mechanism For each current market state: Feature Vector Construction: 12-dimensional representation of market conditions Historical Search: Scan lookback period for similar patterns using Lorentzian distance Neighbor Selection: Identify K nearest historical matches Outcome Analysis: Examine what happened N bars after each match Weighted Prediction: Combine outcomes using distance-based weights Confidence Calculation: Measure agreement between neighbors Technical Hurdles Overcome Array Management: Complex indexing to prevent look-ahead bias Distance Calculations: Optimizing nested loops for performance Memory Constraints: Balancing lookback depth with computational limits Signal Filtering: Preventing clustering of identical signals Advanced Dashboard System Main Control Panel The primary dashboard provides real-time market intelligence: Signal Status: Current prediction with confidence percentage Neighbor Analysis: How many historical patterns match current conditions Market Regime: Trend strength, volatility, and volume analysis Temporal Context: Real-time updates with timestamp Performance Analytics Comprehensive tracking system monitors: Win Rate: Percentage of successful predictions Signal Count: Total predictions generated Streak Analysis: Current winning/losing sequence Drawdown Monitoring: Maximum equity decline Sharpe Approximation: Risk-adjusted performance estimate Risk Assessment Panel Multi-dimensional risk analysis: RSI Positioning: Overbought/oversold conditions ATR Percentage: Current volatility relative to price Bollinger Position: Price location within volatility bands MACD Alignment: Momentum confirmation Confidence Heatmap Visual representation of prediction reliability: Historical Confidence: Last 10 periods of prediction certainty Strength Analysis: Magnitude of prediction values over time Pattern Recognition: Color-coded confidence levels for quick assessment Input Parameters Deep Dive Core Algorithm Settings K Nearest Neighbors (1-20): More neighbors create smoother but less responsive signals. Optimal range 5-8 for most markets. Historical Lookback (50-500): Deeper history improves pattern recognition but reduces adaptability. 100-200 bars optimal for most timeframes. Feature Window (5-30): Longer windows capture more context but reduce sensitivity. Match to your trading timeframe. Feature Selection Price Changes: Essential for momentum and reversal detection Volume Profile: Critical for institutional activity recognition Volatility Measures: Key for regime change detection Momentum Indicators: Vital for trend confirmation Signal Generation Prediction Horizon (1-20): How far ahead to predict. Shorter horizons for scalping, longer for swing trading. Signal Threshold (0.5-0.9): Confidence required for signal generation. Higher values reduce false signals but may miss opportunities. Smoothing (1-10): EMA applied to raw predictions. More smoothing reduces noise but increases lag. Visual Design Philosophy Color Themes Professional: Corporate blue/red for institutional environments Neon: Cyberpunk cyan/magenta for modern aesthetics Matrix: Green/red hacker-inspired palette Classic: Traditional trading colors Information Hierarchy The dashboard system prioritizes information by importance: Primary Signals: Largest, most prominent display Confidence Metrics: Secondary but clearly visible Supporting Data: Detailed but unobtrusive Historical Context: Available but not distracting Trading Applications Signal Interpretation Long Signals: Prediction > threshold with high confidence Look for volume confirmation - Check trend alignment - Verify support levels Short Signals: Prediction < -threshold with high confidence Confirm with resistance levels - Check for distribution patterns - Verify momentum divergence - Market Regime Adaptation Trending Markets: Higher confidence in directional signals Ranging Markets: Focus on reversal signals at extremes Volatile Markets: Require higher confidence thresholds Low Volume: Reduce position sizes, increase caution Risk Management Integration Confidence-Based Sizing: Larger positions for higher confidence signals Regime-Aware Stops: Wider stops in volatile regimes Multi-Timeframe Confirmation: Align signals across timeframes Volume Confirmation: Require volume support for major signals Originality and Innovation This indicator represents genuine innovation in several areas: Mathematical Approach First application of Lorentzian geometry to market pattern recognition. Unlike Euclidean-based systems, this naturally handles market non-linearities. Feature Engineering Sophisticated multi-dimensional feature space combining price, volume, volatility, and momentum in normalized form. Visualization System Professional-grade dashboard system providing comprehensive market intelligence in intuitive format. Performance Tracking Real-time performance analytics typically found only in institutional trading systems. Development Journey Creating this indicator involved overcoming numerous technical challenges: Mathematical Complexity: Translating theoretical concepts into practical code Performance Optimization: Balancing accuracy with computational efficiency User Interface Design: Making complex data accessible and actionable Signal Quality: Filtering noise while maintaining responsiveness The result is a tool that brings institutional-grade analytics to individual traders while maintaining the theoretical rigor of its mathematical foundation. Best Practices - Parameter Optimization - Start with default settings and adjust based on: Market Characteristics: Volatile vs. stable Trading Timeframe: Scalping vs. swing trading Risk Tolerance: Conservative vs. aggressive Signal Confirmation Never trade on Lorentzian signals alone: Price Action: Confirm with support/resistance Volume: Verify with volume analysis Multiple Timeframes: Check higher timeframe alignment Market Context: Consider overall market conditions Risk Management Position Sizing: Scale with confidence levels Stop Losses: Adapt to market volatility Profit Targets: Based on historical performance Maximum Risk: Never exceed 2-3% per trade Disclaimer This indicator is for educational and research purposes only. It does not constitute financial advice or guarantee profitable trading results. The Lorentzian classification system reveals market patterns but cannot predict future price movements with certainty. Always use proper risk management, conduct your own analysis, and never risk more than you can afford to lose. Market dynamics are inherently uncertain, and past performance does not guarantee future results. This tool should be used as part of a comprehensive trading strategy, not as a standalone solution. Bringing the elegance of relativistic geometry to market analysis through sophisticated pattern recognition and intuitive visualization. Thank you for sharing the idea. You're more than a follower, you're a leader! @vasanthgautham1221 Trade with precision. Trade with insight. — Dskyz , for DAFE Trading Systems
אינדיקטור Pine Script®
מאת ‎DskyzInvestments‎
8
Eigenvector Centrality Drift (ECD) - Market State Network What is Eigenvector Centrality Drift (ECD)? Eigenvector Centrality Drift (ECD) is a groundbreaking indicator that applies concepts from network science to financial markets. Instead of viewing price as a simple series, ECD models the market as a dynamic network of “micro-states”—distinct combinations of price, volatility, and volume. By tracking how the influence of these states changes over time, ECD helps you spot regime shifts and transitions in market character before they become obvious in price. This is not another moving average or momentum oscillator. ECD is inspired by eigenvector centrality—a measure of influence in network theory—and adapts it to the world of price action, volatility, and volume. It’s about understanding which market states are “in control” and when that control is about to change. Theoretical Foundation Network Science: In complex systems, nodes (states) and edges (transitions) form a network. Eigenvector centrality measures how influential a node is, not just by its direct connections, but by the influence of the nodes it connects to. Market Micro-States: Each bar is classified into a “state” based on price change, volatility, and volume. The market transitions between these states, forming a network of possible regimes. Centrality Drift: By tracking the centrality (influence) of the current state, and how it changes (drifts) over time, ECD highlights when the market’s “center of gravity” is shifting—often a precursor to major moves or regime changes. How ECD Works State Classification: Each bar is assigned to one of N market micro-states, based on a weighted combination of normalized price change, volatility, and volume. Transition Matrix: Over a rolling window, ECD tracks how often the market transitions from each state to every other state, forming a transition probability matrix. Centrality Calculation: Using a simplified eigenvector approach, ECD calculates the “influence” score for each state, reflecting how central it is to the network of recent market behavior. Centrality Drift: The indicator tracks the Z-score of the change in centrality for the current state. Rapid increases or decreases, or a shift in the dominant state, signal a potential regime shift. Dominant State: ECD also highlights which state currently has the highest influence, providing insight into the prevailing market character. Inputs: 🌐 Market State Configuration Number of Market States (n_states, default 6): Number of distinct micro-states to track. 3–4: Simple (Up/Down/Sideways) 5–6: Balanced (recommended) 7–9: Complex, more nuanced Price Change Weight (price_weight, default 0.4): How much price movement defines a state. Higher = more directional. Volatility Weight (vol_weight, default 0.3): How much volatility defines a state. Higher = more regime focus. Volume Weight (volume_weight, default 0.3): How much volume defines a state. Higher = more participation focus. 🔗 Network Analysis Transition Matrix Window (transition_window, default 50): Lookback for building the state transition matrix. Shorter: Adapts quickly Longer: More stable Influence Decay Factor (influence_decay, default 0.85): How much influence propagates through the network. Higher: Distant transitions matter more Lower: Only immediate transitions matter Drift Detection Sensitivity (drift_sensitivity, default 1.5): Z-score threshold for significant centrality drift. Lower: More signals Higher: Only major shifts 🎨 Visualization Show Network Visualization (show_network, default true): Background color and effects based on network structure. Show Centrality Score (show_centrality, default true): Plots the current state’s centrality measure. Show Drift Indicator (show_drift, default true): Plots the centrality drift Z-score. Show State Map (show_state_map, default true): Dashboard showing all state centralities and which is dominant. Color Scheme (color_scheme, default "Quantum"): “Quantum”: Cyan/Magenta “Neural”: Green/Blue “Plasma”: Yellow/Pink “Matrix”: Green/Black Color Schemes Dynamic gradients reflect the current state’s centrality and drift, using your chosen color palette. Background network effect: The more central the current state, the more intense the background. Centrality and drift lines: Color-coded for clarity and regime shift detection. Visual Logic Centrality Score Line: Plots the influence of the current state, with glow for emphasis. Drift Indicator: Histogram of centrality drift Z-score, green for positive, red for negative. Threshold Lines: Dotted lines mark the drift sensitivity threshold for regime shift alerts. State Map Dashboard: Top-right panel shows all state centralities, highlights the current and dominant state, and visualizes influence with bars. Information Panel: Bottom-left panel summarizes current state, centrality, dominant state, drift Z-score, and regime shift status. How to Use ECD Centrality Score: High = current state is highly influential; low = state is peripheral. Drift Z-Score: Large positive/negative = rapid change in influence, regime shift likely. Near zero = stable network, no major shift. Dominant State: The state with the highest centrality is “in control” of the market’s transitions. State Map: Use to see which states are rising or falling in influence. Tips: Use fewer states for simple markets, more for nuanced analysis. Watch for drift Z-score crossing the threshold—these are your regime shift signals. Combine with your own system for confirmation. Alerts: ECD Regime Shift: Significant centrality drift detected—potential regime change. ECD State Change: Market state transition occurred. ECD Dominance Shift: Dominant market state has changed. Originality & Usefulness ECD is not a mashup or rehash of standard indicators. It is a novel application of network science and eigenvector centrality to market microstructure, providing a new lens for understanding regime shifts and market transitions. The state network, centrality drift, and dashboard are unique to this script. ECD is designed for anticipation, not confirmation—helping you see the market’s “center of gravity” shift before price action makes it obvious. Chart Info Script Name: Eigenvector Centrality Drift (ECD) – Market State Network Recommended Use: Any asset, any timeframe. Tune parameters to your style. Disclaimer This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results. See the market as a network. Anticipate the shift in influence. — Dskyz , for DAFE Trading Systems
אינדיקטור Pine Script®
מאת ‎DskyzInvestments‎
H4 Swing Grade Checklist English V.1✅ H4 Swing Grade Checklist – Auto Grading for Smart Money Setups This script helps manual traders assess the quality of a Smart Money swing trade setup by checking 7 key criteria. The system assigns a grade (A+, A, A−, or B) based on how many and which checklist items are met. 📋 Checklist Items (7 total): ✅ Sweep occurs within 4 candles ✅ MSS (strong break candle) ✅ Entry is placed outside the wick of the sweep ✅ FVG is fresh (not previously used) ✅ FVG overlaps Fibonacci 0.705 level ✅ FVG lies within Premium or Discount zone ✅ Entry is placed at 0.705 Fibonacci retracement 🏅 Grading Criteria: A+ → All 7 checklist items are satisfied A → Only missing #5 (FVG Overlap with 0.705) A− → Only missing #4 (FVG Fresh) B → Only missing #2 (MSS – clear break of structure) – → Any other combinations / fewer than 6 conditions met ⚙️ Features: Toggle visibility with one click Fixed display in top-right or bottom-right of the chart Color-coded grading logic (Green, Yellow, Orange, Blue) Clear checklist feedback for trade journaling or evaluation 🚀 Ideal For: ICT / Smart Money traders Prop firm evaluations Swing trade quality control
אינדיקטור Pine Script®
מאת ‎weewybravo‎
4
Information Asymmetry Gradient (IAG) What is the Information Asymmetry Gradient (IAG)? The Information Asymmetry Gradient (IAG) is a unique market regime and imbalance detector that quantifies the subtle, directional “information flow” in price and volume. Inspired by information theory and market microstructure, IAG is designed to help traders spot the early buildup of conviction or surprise—the kind of hidden imbalance that often precedes major price moves. Unlike traditional volume or momentum indicators, IAG focuses on the efficiency and directionality of information transfer: how much “informational energy” is being revealed by up-moves versus down-moves, normalized by price movement. It’s not just about net flow, but about the quality and asymmetry of that flow. Theoretical Foundation Information Asymmetry: Markets move when new information is revealed. If one side (buyers or sellers) is consistently more “informationally efficient” per unit of price change, an imbalance is building—even if price hasn’t moved much yet. Gradient: By tracking the rate of change (gradient) between fast and slow information flows, IAG highlights when a subtle imbalance is accelerating. Volatility of Asymmetry: Sudden spikes in the volatility of information asymmetry often signal regime uncertainty or the approach of a “surprise” move. How IAG Works Directional Information Content: For each bar, IAG estimates the “information per unit of price change” for both up-moves and down-moves, using volume and price action. Asymmetry Calculation: Computes the difference (or ratio) between up and down information content, revealing directional bias. Gradient Detection: Calculates both a fast and slow EMA of the asymmetry, then measures their difference (the “gradient”), normalized as a Z-score. Volatility of Asymmetry: Tracks the standard deviation of asymmetry over a rolling window, with Z-score normalization to spot “information shocks.” Flow Strength: Quantifies the conviction of the current information flow on a 0–100 scale. Regime Detection: Flags “extreme” asymmetry, “building” flow, and “high volatility” states. Inputs: 🌌 Core Asymmetry Parameters Fast Information Period (short_len, default 8): EMA period for detecting immediate information flow changes. 5–8: Scalping (1–5min) 8–12: Day trading (15min–1hr) 12–20: Swing trading (4hr+) Slow Information Period (long_len, default 34): EMA period for baseline information context. Should be 3–5x fast period. Default (34): Fibonacci number, stable for most assets. Gradient Smoothing (gradient_smooth, default 3): Smooths the gradient calculation. 1–2: Raw, responsive 3–5: Balanced 6–10: Very smooth 📊 Asymmetry Method Calculation Mode (calc_mode, default "Weighted"): “Simple”: Basic volume split by direction “Weighted”: Volume × price movement (default, most robust) “Logarithmic”: Log-scaled for large moves Use Ratio (show_ratio, default false): “Difference”: UpInfo – DownInfo (additive) “Ratio”: UpInfo / DownInfo (multiplicative, better for comparing volatility regimes) 🌊 Volatility Analysis Volatility Window (stdev_len, default 21): Lookback for measuring asymmetry volatility. Volatility Alert Level (vol_threshold, default 1.5): Z-score threshold for volatility alerts. 🎨 Visual Settings Color Theme (color_theme, default "Starry Night"): Van Gogh-inspired palettes: “Starry Night”: Deep blues and yellows “Sunflowers”: Warm yellows and browns “Café Terrace”: Night blues and warm lights “Wheat Field”: Golden and sky blue Show Swirl Effects (show_swirls, default true): Adds swirling background to visualize information turbulence. Show Signal Stars (show_stars, default true): Star markers at significant asymmetry points. Show Info Dashboard (show_dashboard, default true): Top-right panel with current metrics and market state. Show Flow Visualization (show_flow, default true): Main gradient line with artistic effects. Color Schemes Dynamic color gradients adapt to both the direction and intensity of the information gradient, using Van Gogh-inspired palettes for visual clarity and artistic flair. Glow and aura effects: The main line is layered with glows for depth and to highlight strong signals. Swirl background: Visualizes the “turbulence” of information flow, darker and more intense as flow strength and volatility rise. Visual Logic Main Gradient Line: Plots the normalized information gradient (Z-score), color-coded by direction and intensity. Glow/Aura: Multiple layers for visual depth and to highlight strong signals. Threshold Zones: Dotted lines and filled areas mark “Building” and “Extreme” asymmetry zones. Volatility Ribbon: Area plot of volatility Z-score, highlighting information shocks. Signal Stars: Circular markers at each “Extreme” event, color-coded for bullish/bearish; cross markers for volatility spikes. Dashboard: Top-right panel shows current status (Extreme, Building, High Volatility, Balanced), gradient value, flow strength, information balance, and volatility status. Trading Guide: Bottom-left panel explains all states and how to interpret them. How to Use IAG 🌟 EXTREME: Major information imbalance—potential for explosive move or reversal. 🌙 BUILDING: Asymmetry is forming—watch for a breakout or trend acceleration. 🌪️ HIGH VOLATILITY: Information flow is unstable—expect regime uncertainty or “surprise” moves. ☁️ BALANCED: No clear bias—market is in equilibrium. Positive Gradient: Bullish information flow (buyers have the edge). Negative Gradient: Bearish information flow (sellers have the edge). Flow >66%: Strong conviction—crowd is acting in unison. Volatility Spike: Regime uncertainty—be alert for sudden moves. Tips: - Use lower periods for scalping, higher for swing trading. - “Weighted” mode is most robust for most assets. - Combine with price action or your own system for confirmation. - Works on all assets and timeframes—tune to your style. Alerts IAG Extreme Asymmetry: Extreme information asymmetry detected. IAG Building Flow: Information flow building. IAG High Volatility: Information volatility spike. IAG Bullish/Bearish Extreme: Directional extreme detected. Originality & Usefulness IAG is not a mashup of existing indicators. It is a novel approach to quantifying the “surprise” or “conviction” element in market moves, focusing on the efficiency and directionality of information transfer per unit of price change. The multi-layered color logic, artistic visual effects, and regime dashboard are unique to this script. IAG is designed for anticipation, not confirmation—helping you see subtle imbalances before they become obvious in price. Chart Info Script Name: Information Asymmetry Gradient (IAG) – Starry Night Recommended Use: Any asset, any timeframe. Tune parameters to your style. Disclaimer This script is for research and educational purposes only. It does not provide financial advice or direct buy/sell signals. Always use proper risk management and combine with your own strategy. Past performance is not indicative of future results. Trade with insight. Trade with anticipation. — Dskyz , for DAFE Trading Systems
אינדיקטור Pine Script®
מאת ‎DskyzInvestments‎
3
multi-tf standard devs [keypoems]Multi-Timeframe Standard Deviations Levels A visual map of “how far is too far” across any three higher time-frames. 1. What it does This script plots dynamic price “rails” built from standard deviation (StDev)—the same math that underpins the bell curve—on up to three higher-time-frames (HTFs) at once. • It measures the volatility of intraday open-to-close increments, reaching back as far as 5000 bars (≈ 20 years on daily data). • Each HTF can be extended to the next session or truncated at session close for tidy dashboards. • Lines can be mirrored so you see symmetric positive/negative bands, and optional background fills shade the “probability cone.” Because ≈ 68 % of moves live inside ±1 StDev, ≈ 95 % inside ±2, and ≈ 99.7 % inside ±3, the plot instantly shows when price is statistically stretched or compressed. 3. Key settings Higher Time-Frame #1-3 Turn each HTF on/off, pick the interval (anything from 1 min to 1 year), and decide whether lines should extend into the next period. Show levels for last X days Keep your chart clean by limiting how many historical sessions are displayed (1-50). Based on last X periods Length of the StDev sample. Long look-backs (e.g. 5 000) iron-out day-to-day noise; short look-backs make the bands flex with recent volatility. Fib Settings Toggle each multiple, line thickness/style/colour, label size, whether to print the numeric level, the live price, the HTF label, and whether to tint the background (choose your own opacity). 4. Under-the-hood notes StDev is calculated on (close – open) / open rather than absolute prices, making the band width scale-agnostic. Watch for tests of ±1: Momentum traders ride the breakout with a target at the next band. Mean-reversion traders wait for the first stall candle and trade back to zero line or VWAP. Bottom line: Multi-Timeframe Standard-Deviations turns raw volatility math into an intuitive “price terrain map,” helping you instantly judge whether a move is ordinary, stretched, or extreme—across the time-frames that matter to you. Original code by fadizeidan and stats by NQStats's ProbableChris.
אינדיקטור Pine Script®
מאת ‎keypoems‎
10
Bullish Volume AnomalyAnomaly is designed to spot hidden bullish accumulation before price actually breaks out, by blending a trend-aware volume measure with a volatility-adjusted price channel. Here’s how it works: First, it runs a simple ATR-based zigzag to identify the current swing direction. Volume is then signed (+ for up-trends, – for down-trends) and cumulatively summed. By converting that cumulative signed volume into a z-score over the past 480 bars, we get a sense of when buying or selling pressure is unusually strong relative to its own history. At the same time, price itself is normalized into a z-score over the same 480-bar window, and its change over that period is also tracked. These two measures—volume z-score (s) and price z-score (p)—are compared, and the indicator looks for moments when s outpaces p by at least two standard deviations (s – p > 2), while price momentum change remains low (c < 1) and the net volume is positive (s > 0). That combination flags instances where heavy buying is taking place but price hasn’t yet reacted. To define a dynamic trading zone, it plots a 288-bar EMA of price as the middle band (t2), and builds upper and lower bands around it using the average close-to-open range multiplied by a user-set factor. The lower band (t1) sits beneath the EMA by that volatility-based margin. A signal fires only when the bar’s high stays below t1—meaning price is still “sleeping” under the lower volatility boundary even as bullish volume builds up. Together, these filters home in on anomalies: strong, trend-aligned volume surges that outstrip price movement, occurring while price sits below its lower volatility band. In practice, that often marks early accumulation before a breakout. You can tweak the ATR length and multiplier for the zigzag, as well as the channel period and range factor, to suit different markets or timeframes.
אינדיקטור Pine Script®
מאת ‎UnknownUnicorn13336802‎
Normalized DXY+Custom USD Index (DXY+) – Normalized Dollar Strength with Bitcoin, Gold, and Yuan. This custom USD strength index replicates the structure of the official U.S. Dollar Index (DXY), while expanding it to include modern financial assets such as Bitcoin (BTC), Ethereum (ETH), gold (XAU), and the Chinese yuan (CNY). Weights for the core fiat currencies (EUR, JPY, GBP, CAD, SEK, CHF) follow the official ICE DXY methodology. Additional components are weighted proportionally based on their estimated global economic influence. The index is normalized from its initial valid data point, meaning it starts at 100 on the first day all asset inputs are available. From that point forward, it tracks the relative strength of the U.S. dollar against this expanded basket. This provides a more comprehensive and modernized view of the dollar's strength—not only against traditional fiat currencies, but also in the context of rising decentralized assets and non-Western trade power.
אינדיקטור Pine Script®
מאת ‎travisreeee‎
HGDA Hany Ghazy Digital Analytics area zone'sIndicator Name: HGDA Hany Ghazy Digital Analytics area zones Description: This indicator plots several key price zones based on the highest high and lowest low over a user-defined lookback period. The plotted zones represent dynamic support and resistance levels calculated using specific ratios of the price range (High - Low), as follows: - Zone 1 (Light Red): Represents an upper resistance zone. - Zone 2 (Medium Green): Represents a medium support zone. - Zone 3 (Dark Red): Represents a lower resistance zone. - Zone 4 (Dark Green): Represents a strong support zone. Additionally, the indicator plots a yellow "Zero" line representing the midpoint price of the selected period, serving as a balance point for price action. This indicator is ideal for identifying the overall market trend, as prices typically move from the upper resistance zones (light red) downwards to the end of the wave in the lower zones (dark green). This helps traders better understand wave nature and direction. Usage: - The colored zones assist in identifying potential reversal or continuation areas. - These zones can be used to plan entries, exits, and risk management. - Default lookback period is 20 bars, adjustable in the settings to suit the timeframe. Notes: - This indicator relies on historical price data and does not guarantee market predictions. - It is recommended to combine it with other indicators and analytical tools for improved trading decisions. --- Developed by Hany Ghazy Digital Analytics (HGDA).
אינדיקטור Pine Script®
מאת ‎Hany_Elghazy‎
Custom USD IndexThis is a modernized, expanded version of the U.S. Dollar Index (DXY), designed to provide a more accurate representation of the dollar’s global strength in today’s diversified economy. Unlike the traditional DXY, which excludes major players like China and entirely omits real-world stores of value, this custom index (DXY+) includes: Fiat Currencies (78.3% total weight): EUR, JPY, GBP, CAD, AUD, CHF, and CNY — equally weighted to reflect the global currency landscape. Gold (17.5%): Gold (XAUUSD) is included as a traditional reserve asset and inflation hedge, acknowledging its continued monetary relevance. Cryptocurrencies (2.8% total weight): Bitcoin (BTC) and Ethereum (ETH) represent the emerging digital monetary layer. The index rises when the U.S. dollar strengthens relative to this blended basket, and falls when the dollar weakens against it. This is ideal for traders, economists, and macro analysts seeking a more inclusive and up-to-date measure of dollar performance.
אינדיקטור Pine Script®
מאת ‎travisreeee‎
Float, Daily % Change & Short %This TradingView Pine Script displays a compact table on your chart showing four key metrics for any stock: 📊 What It Shows: Float – Number of publicly available shares, formatted in K/M/B. Daily % Change – Price change from yesterday’s close to the current price. Intraday % Change – Price change from today’s open to the current price. Short Volume % – Estimated short volume as a percentage of total daily volume. ⚙️ How to Use: Add the script to your TradingView chart. Choose table size and screen position from the settings panel. The values update in real-time on the latest candle only, so they stay out of the way but always visible. Ideal for momentum traders, short float hunters, and day traders who need quick access to real-time float, price action, and short volume stats.
אינדיקטור Pine Script®
מאת ‎Daniel_Vin‎
6
SOFR Spread (proxy: FEDFUNDS - US03MY)📊 SOFR Spread (Proxy: FEDFUNDS - US03MY) – Monitoring USD Money Market Liquidity In 2008, the spread exhibits a sharp vertical spike, signaling a severe liquidity dislocation: investors rushed into short-term U.S. Treasuries, pushing their yields down dramatically, while the FEDFUNDS rate remained relatively high. This behavior indicates extreme systemic stress in the interbank lending market, preceding massive Federal Reserve interventions such as rate cuts, emergency liquidity operations, and the launch of quantitative easing (QE). Description: This indicator plots the spread between the Effective Federal Funds Rate (FEDFUNDS) and the 3-Month US Treasury Bill yield (US03MY), used here as a proxy for the SOFR spread. It serves as a simple yet powerful tool to detect liquidity dislocations and stress signals in the US short-term funding markets. Interpretation: 🔴 Spread > 0.20% → Possible liquidity stress: elevated repo rates, cash shortage, interbank distrust. 🟡 Spread ≈ 0% → Normal market conditions, balanced liquidity. 🟢 Spread < 0% → Excess liquidity: strong demand for T-Bills, “flight to safety”, or distortion due to expansionary monetary policy. Ideal for: Monitoring Fed policy impact Anticipating market-wide liquidity squeezes Correlation with DXY, SPX, VIX, MOVE Index, and risk sentiment 🧠 Note: As SOFR is not directly available on TradingView, FEDFUNDS is used as a reliable proxy, closely tracking the same trends in most macro conditions.
אינדיקטור Pine Script®
מאת ‎bordimichele00‎
LANZ Strategy 2.0 [Backtest]🔷 LANZ Strategy 2.0 — Structural Breakout Logic with Dynamic Swing Protection LANZ Strategy 2.0 is a precision-focused backtesting system built for intraday traders who rely on structural confirmations before the London session to guide directional bias. This tool uses smart swing detection, risk-defined position sizing, and strict time-based execution to simulate real trading conditions with clarity and control. 🧠 Core Components: Structural Confirmation (Trend & BoS): Detects trend direction and break of structure (BoS) using a three-swing logic, aligning trade entries with valid structural movement. Time-Based Execution: Trades are triggered exclusively at 02:00 a.m. New York time, ensuring disciplined and repeatable intraday testing. Swing-Based SL Models: Traders can select between three stop-loss protection types: First Swing: Most recent structural level Second Swing: Prior level Full Coverage: All recent swing levels + configurable pip buffer Dynamic TP Calculation: Take-Profit is projected as a risk-based multiple (RR), fully adjustable via input. Capital-Based Risk Management: Risk is defined as a percentage of a fixed account size (e.g., $100 per trade from $10,000), and lot size is automatically calculated based on SL distance. Fallback Entry Logic: If structural breakout is present but trend is not confirmed, a secondary entry is triggered. End-of-Session Management: Any open trades are automatically closed at 11:45 a.m. NY time, with optional manual labeling or review. 📊 Visual Features (Optional in Indicator Version): (Note: Visuals apply to the indicator version of LANZ 2.0, not this backtest script) Swing level labels (1st, 2nd) and dynamic SL/TP lines. Real-time session coloring for clarity: Pre-London, Entry Window, and NY Close. Outcome labels: +RR, -RR, or net % at close. Auto-cleanup of previous drawings for a clean chart per session. ⚙️ How It Works: Detects last trend and BoS using swing logic before 02:00 a.m. NY. At 02:00 a.m., evaluates directional bias and executes BUY or SELL if confirmed. Applies selected SL logic (1st, 2nd, or full swing protection). Sets TP based on the RR multiplier. Closes the trade either on SL, TP, or at 11:45 a.m. NY manually. 🔔 Alerts: Time-of-day alert at 02:00 a.m. NY to monitor execution. Can be extended to cover SL/TP triggers or new BoS events. 📝 Notes: Designed for backtesting precision and discretionary decision-making. Ideal for Forex pairs, indices, or assets active during the London session. Fully customizable: session timing, swing logic, SL buffer, and RR. 👤 Credits: Strategy built by @rau_u_lanz using Pine Script v6, combining structural logic, capital-based risk control, and London-session timing in a backtest-ready framework for traders who demand accuracy and structure.
אסטרטגיית Pine Script®
מאת ‎rau_u_lanz‎
Statistical Pairs Trading IndicatorZ-Score Stat Trading — Statistical Pairs Trading Indicator 📊🔗 --- What is it? Z-Score Stat Trading is a powerful indicator for statistical pairs trading and quantitative analysis of two correlated assets. It calculates the Z-Score of the log-price spread between any two symbols you choose, providing both long-term and short-term Z-Score signals. You’ll also see real-time correlation, volatility, spread, and the number of long/short signals in a handy on-chart table! --- How to Use 🛠️ 1. Add the indicator to your chart. 2. Select two assets (symbols) to analyze in the settings. 3. Watch the Z-Score plots (blue and orange lines) and threshold levels (+2, -2 by default). 4. Check the info table for: - Correlation - Volatility - Spread - Number of long (NL) and short (NS) signals in the last 1000 bars 5. Set up alerts for signal generation or threshold crossings if you want to be notified automatically. --- Trading Strategy 💡 - This indicator is designed for statistical arbitrage (mean reversion) strategies. - Long Signal (🟢): When both Z-Scores drop below the negative threshold (e.g., -2), a long signal is generated. → Buy Symbol A, Sell Symbol B, expecting the spread to revert to the mean. - Short Signal (🔴): When both Z-Scores rise above the positive threshold (e.g., +2), a short signal is generated. → Sell Symbol A, Buy Symbol B, again expecting mean reversion. - The info table helps you quickly assess the frequency of signals and the current statistical relationship between your chosen assets. --- Best Practices & Warnings 🚦 - Avoid high leverage! Pairs trading can be risky, especially during periods of divergence. Use conservative position sizing. - Check for cointegration: Before using this indicator, make sure both assets are cointegrated or have a strong historical relationship. This increases the reliability of mean reversion signals. - Check correlation: Only use asset pairs with a high correlation (preferably 0.8–0.9 or higher) for best results. The correlation value is shown in the info table. - Scale in and out gradually: When entering or exiting positions, consider doing so in parts rather than all at once. This helps manage slippage and risk, especially in volatile markets. --- ⚠️ Note on Performance: This indicator may work a bit slowly, especially on large timeframes or long chart histories, because the calculation of NL and NS (number of long/short signals) is computationally intensive. --- Disclaimer ⚠️ This script is provided for educational and informational purposes only . It is not financial advice or a recommendation to buy or sell any asset. Use at your own risk. The author assumes no responsibility for any trading decisions or losses.
אינדיקטור Pine Script®
מאת ‎bratan2‎
4
Fibo Normalized RSI & RSI RibbonPlots both standard and Z-score normalized RSI ribbons using Fibonacci-based periods. Supports adjustable normalization, optional 0–100 scaling, and multi-line visualizations for momentum and deviation analysis. This tool is designed for traders who want to go beyond standard RSI by adding: Statistical normalization (Z-score) Multi-period analysis (Fibonacci structure) Advanced divergence and exhaustion detection It gives you both classical momentum context and mathematically rigorous deviation insight, making it ideal for: Swing traders Quant-inclined discretionary traders Multi-timeframe analysts Trend Confirmation When both RSI and normalized RSI across short and long periods are stacked in the same direction (e.g., above 50 or with high Z-scores), the trend is likely strong. Disagreement between the two ribbons (e.g., RSI high but normalized RSI flat) may indicate late-stage trend or false strength. Mean Reversion Trades Look for normalized RSI values > +2 or < -2 (i.e., ~2 standard deviations). Cross-check with standard RSI to see if the move aligns with a traditional overbought/oversold level. Great for fade/reversal setups when Z-score RSI is extreme but classic RSI is just beginning to turn. Divergence Detection Compare the slope of RSI vs. normalized RSI over same period: If RSI is rising but normalized RSI is falling → momentum is fading despite apparent strength. Excellent for early warnings before reversals. Multi-Timeframe Confluence Use short-period ribbons (e.g., 3–13) for tactical entries/exits. Use long-period ribbons (e.g., 55–233) for macro trend bias. Alignment across both = high-confidence zone.
אינדיקטור Pine Script®
מאת ‎SCJedi‎
Risk Calculator PRO — manual lot size + auto lot-suggestionWhy risk management? 90 % of traders blow up because they size positions emotionally. This tool forces Risk-First Thinking: choose the amount you’re willing to lose, and the script reverse-engineers everything else. Key features 1. Manual or Market Entry – click “Use current price” or type a custom entry. 2. Setup-based ₹-Risk – four presets (A/B/C/D). Edit to your workflow. 3. Lot-Size Input + Auto Lot Suggestion – you tell the contract size ⇒ script tells you how many lots. 4. Auto-SL (optional) – tick to push stop-loss to exactly 1-lot risk. 5. Instant Targets – 1 : 2, 1 : 3, 1 : 4, 1 : 5 plotted and alert-ready. 6. P&L Preview – table shows potential profit at each R-multiple plus real ₹ at SL. 7. Margin Column – enter per-lot margin once; script totals it for any size. 8. Clean Table UI – dark/light friendly; updates every 5 bars. 9. Alert Pack – SL, each target, plus copy-paste journal line on the chart. How to use 1. Add to chart > “Format”. 2. Type the lot size for the symbol (e.g., 1250 for Natural Gas, 1 for cash equity). 3. Pick Side (Buy / Sell) & Setup grade. 4. ✅ If you want the script to place SL for you, tick Auto-SL (risk = 1 lot). 5. Otherwise type your own Stop-loss. 6. Read the table: • Suggested lots = how many to trade so risk ≤ setup ₹. • Risk (currency) = real money lost if SL hits. 7. Set TradingView alerts on the built-in conditions (T1_2, SL_hit, etc.) if you’d like push / email. 8. Copy the orange CSV label to Excel / Sheets for journalling. Best practices • Never raise risk to “fit” a trade. Lower size instead. • Review win-rate vs. R multiple monthly; adjust setups A–D accordingly. • Test Auto-SL in replay before going live. Disclaimer This script is educational. Past performance ≠ future results. The author isn’t responsible for trading losses.
אינדיקטור Pine Script®
מאת ‎luvrohit1010‎