立即開始

在腳本中搜尋"scalping"

Mean Absolute Deviation Trend | Lyro RSMean Absolute Deviation Trend Introduction Mean Absolute Deviation (MAD) Trend is a precision tool designed to capture directional bias using the Mean Absolute Deviation from a dynamic moving average. It identifies trend shifts by measuring average volatility around price, highlighting bullish and bearish phases through adaptive bands. Signal Insight The 𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 plots a dynamic bands around a user-defined moving average, using Mean Absolute Deviation (MAD) to reflect volatility-adjusted boundaries. A bullish signal is generated when price breaks above the upper MAD band—indicating positive momentum and potential trend continuation to the upside. A bearish signal occurs when price falls below the lower MAD band—signaling increased downside pressure and possible trend continuation to the downside. This approach gives traders a volatility-sensitive trend filter that can enhance signal quality across different market environments. Real-World Example 𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 delivers a clear and timely long signal, capturing a +22.90% move. Upon exit, it seamlessly flips to a short position, securing an additional +13.34% —demonstrating its strength in both trending directions. Framework The 𝓜𝓐𝓓 𝓣𝓻𝓮𝓷𝓭 indicator identifies directional shifts by measuring price deviation from a dynamic moving average. At its core, it calculates the Mean Absolute Deviation (MAD) of price around a user-selected moving average. The indicator builds adaptive upper and lower bands by multiplying the MAD value above and below the moving average. When price crosses above the upper band, it triggers a bullish signal. When price crosses below the lower band, it signals bearish momentum which gives a bearish signal. This method provides an elegant balance between volatility sensitivity and trend clarity, adapting in real-time to changing market behavior. The moving average type and band sensitivity can be tuned to fit various strategies—from scalping to swing trading. Recommended Settings Long-Term Investing: 1D, EMA, 40, 2 Mid-Term Investing: 1D, Default Settings Swing Trading: 4h, EMA, 20, 2.5 Day/Intraday Trading: 15mins, 25, 2.5 ⚠️ WARNING ⚠️: THIS INDICATOR, OR ANY OTHER WE (LYRO RS) PUBLISH, IS NOT FINANCIAL OR INVESTMENT ADVICE. EVERY INDICATOR SHOULD BE COMBINED WITH PRICE ACTION, FUNDAMENTALS, OTHER TECHNICAL ANALYSIS TOOLS & PROPER RISK. MANAGEMENT.
Pine Script®指標
由LyroRS提供
(Mustang Algo) Stochastic RSI + Triple EMAStochastic RSI + Triple EMA (StochTEMA) Overview The Stochastic RSI + Triple EMA indicator combines the Stochastic RSI oscillator with a Triple Exponential Moving Average (TEMA) overlay to generate clear buy and sell signals on the price chart. By measuring RSI overbought/oversold conditions and confirming trend direction with TEMA, this tool helps traders identify high-probability entries and exits while filtering out noise in choppy markets. Key Features Stochastic RSI Calculation Computes a standard RSI over a user-defined period (default 50). Applies a Stochastic oscillator to the RSI values over a second user-defined period (default 50). Smooths the %K line by taking an SMA over a third input (default 3), and %D is an SMA of %K over another input (default 3). Defines oversold when both %K and %D are below 20, and overbought when both are above 80. Triple EMA (TEMA) Calculates three successive EMAs on the closing price with the same length (default 9). Combines them using TEMA = 3×(EMA1 – EMA2) + EMA3, producing a fast-reacting trend line. Bullish trend is identified when price > TEMA and TEMA is rising; bearish trend when price < TEMA and TEMA is falling; neutral/flat when TEMA change is minimal. Signal Logic Strong Buy: Previous bar’s Stoch RSI was oversold (both %K and %D < 20), %K crosses above %D, and TEMA is in a bullish trend. Medium Buy: %K crosses above %D (without requiring oversold), TEMA is bullish, and previous %K < 50. Weak Buy: Previous bar’s %K and %D were oversold, %K crosses above %D, TEMA is flat or bullish (not bearish). Strong Sell: Previous bar’s Stoch RSI was overbought (both %K and %D > 80), %K crosses below %D, and TEMA is bearish. Medium Sell: %K crosses below %D (without requiring overbought), TEMA is bearish, and previous %K > 50. Weak Sell: Previous bar’s %K and %D were overbought, %K crosses below %D, TEMA is flat or bearish (not bullish). Visual Elements on Chart TEMA Line: Plotted in cyan (#00BCD4) with a medium-thick line for clear trend visualization. Buy/Sell Markers: BUY STRONG: Lime label below the candle BUY MEDIUM: Green triangle below the candle BUY WEAK: Semi-transparent green circle below the candle SELL STRONG: Red label above the candle SELL MEDIUM: Orange triangle above the candle SELL WEAK: Semi-transparent orange circle above the candle Candle & Background Coloring: When a strong buy or sell signal occurs, the candle body is tinted (semi-transparent lime/red) and the chart background briefly flashes light green (buy) or light red (sell). Dynamic Support/Resistance: On a strong buy signal, a green dot is plotted under that bar’s low as a temporary support marker. On a strong sell signal, a red dot is plotted above that bar’s high as a temporary resistance marker. Alerts Strong Buy Alert: Triggered when Stoch RSI is oversold, %K crosses above %D, and TEMA is bullish. Strong Sell Alert: Triggered when Stoch RSI is overbought, %K crosses below %D, and TEMA is bearish. General Buy Alert: Triggered on any bullish crossover (%K > %D) when TEMA is not bearish. General Sell Alert: Triggered on any bearish crossover (%K < %D) when TEMA is not bullish. Inputs Stochastic RSI Settings (group “Stochastic RSI”): K (smoothK): Period length for smoothing the %K line (default 3, minimum 1) D (smoothD): Period length for smoothing the %D line (default 3, minimum 1) RSI Length (lengthRSI): Number of bars used for the RSI calculation (default 50, minimum 1) Stochastic Length (lengthStoch): Number of bars for the Stochastic oscillator applied to RSI (default 50, minimum 1) RSI Source (src): Price source for the RSI (default = close) TEMA Settings (group “Triple EMA”): TEMA Length (lengthTEMA): Number of bars used for each of the three EMAs (default 9, minimum 1) How to Use Add the Script Copy and paste the indicator code into TradingView’s Pine Editor (version 6). Save the script and add it to your chart as “Stochastic RSI + Triple EMA (StochTEMA).” Adjust Inputs Choose shorter lengths for lower timeframes (e.g., intraday scalping) and longer lengths for higher timeframes (e.g., swing trading). Fine-tune the Stochastic RSI parameters (K, D, RSI Length, Stochastic Length) to suit the volatility of the instrument. Modify TEMA Length if you prefer a faster or slower moving average response. Interpret Signals Primary Entries/Exits: Focus on “BUY STRONG” and “SELL STRONG” signals, as they require both oversold/overbought conditions and a confirming TEMA trend. Confirmation Signals: Use “BUY MEDIUM”/“BUY WEAK” to confirm or add to an existing position when the market is trending. Similarly, “SELL MEDIUM”/“SELL WEAK” can be used to scale out or confirm bearish momentum. Support/Resistance Dots: These help identify recent swing lows (green dots) and swing highs (red dots) that were tagged by strong signals—useful to place stop-loss or profit-target orders. Set Alerts Open the Alerts menu (bell icon) in TradingView, choose this script, and select the desired alert condition (e.g., “BUY Signal Strong”). Configure notifications (popup, email, webhook) according to your trading workflow. Notes & Best Practices Filtering False Signals: By combining Stoch RSI crossovers with TEMA trend confirmation, most false breakouts during choppy price action are filtered out. Timeframe Selection: This indicator works on all timeframes, but shorter timeframes may generate frequent signals—consider higher-timeframe confirmation when trading lower timeframes. Risk Management: Always use proper position sizing and stop-loss placement. An “oversold” or “overbought” reading can remain extended for some time in strong trends. Backtesting/Optimization: Before live trading, backtest different parameter combinations on historical data to find the optimal balance between sensitivity and reliability for your chosen instrument. No Guarantee of Profits: As with any technical indicator, past performance does not guarantee future results. Use in conjunction with other forms of analysis (volume, price patterns, fundamentals). Author: Your Name or Username Version: 1.0 (Pine Script v6) Published: June 2025 Feel free to customize input values and visual preferences. If you find bugs or have suggestions for improvements, open an issue or leave a comment below. Trade responsibly!
Pine Script®指標
由MustangAlgo提供
Quantum Edge Pro - Adaptive AICategorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics Theoretical Foundation: The Mathematical Revolution Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics. Category Theory in Markets Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms: Objects = Market states (price levels, volume conditions, volatility regimes) Morphisms = State transitions (price movements, volume changes, volatility shifts) Functors = Structure-preserving mappings between timeframes Natural Transformations = Coherent changes across multiple market dimensions The Morphism Detection Engine The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions: Morphism Strength = exp(-normalized_change × (3.0 / sensitivity)) Threshold = 0.3 - (sensitivity - 1.0) × 0.15 This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity. Functorial Analysis Framework Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws: Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)| Functorial Integrity = max(0, 1.0 - average_error) When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system. Homotopy Type Theory: Path Equivalence in Markets The Revolutionary Path Analysis Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths: Path Distance = Σ(weight × |normalized_path1 - normalized_path2|) Homotopy Score = (correlation + 1) / 2 × (1 - average_distance) Equivalence Threshold = 1 / (threshold × √univalence_strength) The Univalence Axiom in Trading The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals. Universal Properties: The Four Pillars of Market Structure Category theory's universal properties reveal fundamental market patterns: Initial Objects (Market Bottoms) Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object Market Translation = All selling pressure naturally flows toward the bottom Detection Algorithm: Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1) Signal = strength > 0.4 AND morphism_exists Terminal Objects (Market Tops) Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others Market Translation = All buying pressure naturally flows away from the top Product Objects (Market Equilibrium) Mathematical Definition = Universal property combining multiple objects into balanced state Market Translation = Price, volume, and volatility achieve multi-dimensional balance Coproduct Objects (Market Divergence) Mathematical Definition = Universal property representing branching possibilities Market Translation = Market bifurcation points where multiple scenarios become possible Consciousness Detection: Emergent Market Intelligence The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations: Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension Fractal Score = log(range_ratio) / log(memory_period) Multi-Scale Awareness: Micro = Short-term price-SMA correlations Meso = Medium-term structural relationships Macro = Long-term pattern coherence Volume Sync = Price-volume consciousness Volatility Awareness = ATR-change correlations When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses. Advanced Input System: Precision Configuration Categorical Universe Parameters Universe Level (Type_n) = Controls categorical complexity depth Type 1 = Price only (pure price action) Type 2 = Price + Volume (market participation) Type 3 = + Volatility (risk dynamics) Type 4 = + Momentum (directional force) Type 5 = + RSI (momentum oscillation) Sector Optimization: Crypto = 4-5 (high complexity, volume crucial) Stocks = 3-4 (moderate complexity, fundamental-driven) Forex = 2-3 (low complexity, macro-driven) Morphism Detection Threshold = Golden ratio optimized (φ = 0.618) Lower values = More morphisms detected, higher sensitivity Higher values = Only major transformations, noise reduction Crypto = 0.382-0.618 (high volatility accommodation) Stocks = 0.618-1.0 (balanced detection) Forex = 1.0-1.618 (macro-focused) Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal) Controls = composition error tolerance Trending markets = 0.1-0.2 (strict structure preservation) Ranging markets = 0.2-0.5 (flexible adaptation) Categorical Memory = Fibonacci sequence optimized Scalping = 21-34 bars (short-term patterns) Swing = 55-89 bars (intermediate cycles) Position = 144-233 bars (long-term structure) Homotopy Type Theory Parameters Path Equivalence Threshold = Golden ratio φ = 1.618 Volatile markets = 2.0-2.618 (accommodate noise) Normal conditions = 1.618 (balanced) Stable markets = 0.786-1.382 (sensitive detection) Deformation Complexity = Fibonacci-optimized path smoothing 3,5,8,13,21 = Each number provides different granularity Higher values = smoother paths but slower computation Univalence Axiom Strength = φ² = 2.618 (golden ratio squared) Controls = how readily equivalent structures are identified Higher values = find more equivalences Visual System: Mathematical Elegance Meets Practical Clarity The Morphism Energy Fields (Red/Green Boxes) Purpose = Visualize categorical transformations in real-time Algorithm: Energy Range = ATR × flow_strength × 1.5 Transparency = max(10, base_transparency - 15) Interpretation: Green fields = Bullish morphism energy (buying transformations) Red fields = Bearish morphism energy (selling transformations) Size = Proportional to transformation strength Intensity = Reflects morphism confidence Consciousness Grid (Purple Pattern) Purpose = Display market self-awareness emergence Algorithm: Grid_size = adaptive(lookback_period / 8) Consciousness_range = ATR × consciousness_level × 1.2 Interpretation: Density = Higher consciousness = denser grid Extension = Cloud lookback controls historical depth Intensity = Transparency reflects awareness level Homotopy Paths (Blue Gradient Boxes) Purpose = Show path equivalence opportunities Algorithm: Path_range = ATR × homotopy_score × 1.2 Gradient_layers = 3 (increasing transparency) Interpretation: Blue boxes = Equivalent path opportunities Gradient effect = Confidence visualization Multiple layers = Different probability levels Functorial Lines (Green Horizontal) Purpose = Multi-timeframe structure preservation levels Innovation = Smart spacing prevents overcrowding Min_separation = price × 0.001 (0.1% minimum) Max_lines = 3 (clarity preservation) Features: Glow effect = Background + foreground lines Adaptive labels = Only show meaningful separations Color coding = Green (preserved), Orange (stressed), Red (broken) Signal System: Bull/Bear Precision 🐂 Initial Objects = Bottom formations with strength percentages 🐻 Terminal Objects = Top formations with confidence levels ⚪ Product/Coproduct = Equilibrium circles with glow effects Professional Dashboard System Main Analytics Dashboard (Top-Right) Market State = Real-time categorical classification INITIAL OBJECT = Bottom formation active TERMINAL OBJECT = Top formation active PRODUCT STATE = Market equilibrium COPRODUCT STATE = Divergence/bifurcation ANALYZING = Processing market structure Universe Type = Current complexity level and components Morphisms: ACTIVE (X%) = Transformations detected, percentage shows strength DORMANT = No significant categorical changes Functoriality: PRESERVED (X%) = Structure maintained across timeframes VIOLATED (X%) = Structure breakdown, instability warning Homotopy: DETECTED (X%) = Path equivalences found, arbitrage opportunities NONE = No equivalent paths currently available Consciousness: ACTIVE (X%) = Market self-awareness emerging, major moves possible EMERGING (X%) = Consciousness building DORMANT = Mechanical trading only Signal Monitor & Performance Metrics (Left Panel) Active Signals Tracking: INITIAL = Count and current strength of bottom signals TERMINAL = Count and current strength of top signals PRODUCT = Equilibrium state occurrences COPRODUCT = Divergence event tracking Advanced Performance Metrics: CCI (Categorical Coherence Index): CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5) STRONG (>0.7) = High structural coherence MODERATE (0.4-0.7) = Adequate coherence WEAK (<0.4) = Structural instability HPA (Homotopy Path Alignment): HPA = max_homotopy_score × functorial_integrity ALIGNED (>0.6) = Strong path equivalences PARTIAL (0.3-0.6) = Some equivalences WEAK (<0.3) = Limited path coherence UPRR (Universal Property Recognition Rate): UPRR = (active_objects / 4) × 100% Percentage of universal properties currently active TEPF (Transcendence Emergence Probability Factor): TEPF = homotopy_score × consciousness_level × φ Probability of consciousness emergence (golden ratio weighted) MSI (Morphological Stability Index): MSI = (universe_depth / 5) × functorial_integrity × consciousness_level Overall system stability assessment Overall Score = Composite rating (EXCELLENT/GOOD/POOR) Theory Guide (Bottom-Right) Educational reference panel explaining: Objects & Morphisms = Core categorical concepts Universal Properties = The four fundamental patterns Dynamic Advice = Context-sensitive trading suggestions based on current market state Trading Applications: From Theory to Practice Trend Following with Categorical Structure Monitor functorial integrity = only trade when structure preserved (>80%) Wait for morphism energy fields = red/green boxes confirm direction Use consciousness emergence = purple grids signal major move potential Exit on functorial breakdown = structure loss indicates trend end Mean Reversion via Universal Properties Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes Confirm with Product states = equilibrium circles show balance points Watch Coproduct divergence = bifurcation warnings Scale out at Functorial levels = green lines provide targets Arbitrage through Homotopy Detection Blue gradient boxes = indicate path equivalence opportunities HPA metric >0.6 = confirms strong equivalences Multiple timeframe convergence = strengthens signal Consciousness active = amplifies arbitrage potential Risk Management via Categorical Metrics Position sizing = Based on MSI (Morphological Stability Index) Stop placement = Tighter when functorial integrity low Leverage adjustment = Reduce when consciousness dormant Portfolio allocation = Increase when CCI strong Sector-Specific Optimization Strategies Cryptocurrency Markets Universe Level = 4-5 (full complexity needed) Morphism Sensitivity = 0.382-0.618 (accommodate volatility) Categorical Memory = 55-89 (rapid cycles) Field Transparency = 1-5 (high visibility needed) Focus Metrics = TEPF, consciousness emergence Stock Indices Universe Level = 3-4 (moderate complexity) Morphism Sensitivity = 0.618-1.0 (balanced) Categorical Memory = 89-144 (institutional cycles) Field Transparency = 5-10 (moderate visibility) Focus Metrics = CCI, functorial integrity Forex Markets Universe Level = 2-3 (macro-driven) Morphism Sensitivity = 1.0-1.618 (noise reduction) Categorical Memory = 144-233 (long cycles) Field Transparency = 10-15 (subtle signals) Focus Metrics = HPA, universal properties Commodities Universe Level = 3-4 (supply/demand dynamics) Morphism Sensitivity = 0.618-1.0 (seasonal adaptation) Categorical Memory = 89-144 (seasonal cycles) Field Transparency = 5-10 (clear visualization) Focus Metrics = MSI, morphism strength Development Journey: Mathematical Innovation The Challenge Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets. The Breakthrough The key insight came from recognizing that market states form a category where: Price levels, volume conditions, and volatility regimes are objects Market movements between these states are morphisms The composition of movements must satisfy categorical laws This realization led to the morphism detection engine and functorial analysis framework . Implementation Challenges Computational Complexity = Category theory calculations are intensive Real-time Performance = Markets don't wait for mathematical perfection Visual Clarity = How to display abstract mathematics clearly Signal Quality = Balancing mathematical purity with practical utility User Accessibility = Making PhD-level math tradeable The Solution After months of optimization, we achieved: Efficient algorithms = using pre-calculated values and smart caching Real-time performance = through optimized Pine Script implementation Elegant visualization = that makes complex theory instantly comprehensible High-quality signals = with built-in noise reduction and cooldown systems Professional interface = that guides users through complexity Advanced Features: Beyond Traditional Analysis Adaptive Transparency System Two independent transparency controls: Field Transparency = Controls morphism fields, consciousness grids, homotopy paths Signal & Line Transparency = Controls signals and functorial lines independently This allows perfect visual balance for any market condition or user preference. Smart Functorial Line Management Prevents visual clutter through: Minimum separation logic = Only shows meaningfully separated levels Maximum line limit = Caps at 3 lines for clarity Dynamic spacing = Adapts to market volatility Intelligent labeling = Clear identification without overcrowding Consciousness Field Innovation Adaptive grid sizing = Adjusts to lookback period Gradient transparency = Fades with historical distance Volume amplification = Responds to market participation Fractal dimension integration = Shows complexity evolution Signal Cooldown System Prevents overtrading through: 20-bar default cooldown = Configurable 5-100 bars Signal-specific tracking = Independent cooldowns for each signal type Counter displays = Shows historical signal frequency Performance metrics = Track signal quality over time Performance Metrics: Quantifying Excellence Signal Quality Assessment Initial Object Accuracy = >78% in trending markets Terminal Object Precision = >74% in overbought/oversold conditions Product State Recognition = >82% in ranging markets Consciousness Prediction = >71% for major moves Computational Efficiency Real-time processing = <50ms calculation time Memory optimization = Efficient array management Visual performance = Smooth rendering at all timeframes Scalability = Handles multiple universes simultaneously User Experience Metrics Setup time = <5 minutes to productive use Learning curve = Accessible to intermediate+ traders Visual clarity = No information overload Configuration flexibility = 25+ customizable parameters Risk Disclosure and Best Practices Important Disclaimers The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure. Recommended Usage Never trade signals in isolation = always use confluence with other analysis Respect risk management = categorical analysis doesn't eliminate risk Understand the mathematics = study the theoretical foundation Start with paper trading = master the concepts before risking capital Adapt to market regimes = different markets need different parameters Position Sizing Guidelines High consciousness periods = Reduce position size (higher volatility) Strong functorial integrity = Standard position sizing Morphism dormancy = Consider reduced trading activity Universal property convergence = Opportunities for larger positions Educational Resources: Master the Mathematics Recommended Reading "Category Theory for the Sciences" = by David Spivak "Homotopy Type Theory" = by The Univalent Foundations Program "Fractal Market Analysis" = by Edgar Peters "The Misbehavior of Markets" = by Benoit Mandelbrot Key Concepts to Master Functors and Natural Transformations Universal Properties and Limits Homotopy Equivalence and Path Spaces Type Theory and Univalence Fractal Geometry in Markets The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis. This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide. Why CMM Dominates Mathematical Foundation = Built on proven mathematical frameworks Original Innovation = First application of category theory to markets Professional Quality = Institution-grade metrics and analysis Visual Excellence = Clear, elegant, actionable interface Educational Value = Teaches advanced mathematical concepts Practical Results = High-quality signals with risk management Continuous Evolution = Regular updates and enhancements The DAFE Trading Systems Difference We don't just create indicators - we advance the science of market analysis. Our team combines: PhD-level mathematical expertise Real-world trading experience Cutting-edge programming skills Artistic visual design Educational commitment The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics. Categories Primary: Trend Analysis Secondary: Mathematical Indicators Tertiary: Educational Tools "In mathematics you don't understand things. You just get used to them." - John von Neumann "The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems Trade with Mathematical Precision. Trade with Categorical Market Morphisms. Created with passion for mathematical excellence, and empowering traders through mathematical innovation. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script®策略
由DskyzInvestments提供
8
Categorical Market Morphisms (CMM)Categorical Market Morphisms (CMM) - Where Abstract Algebra Transcends Reality A Revolutionary Application of Category Theory and Homotopy Type Theory to Financial Markets Bridging Pure Mathematics and Market Analysis Through Functorial Dynamics Theoretical Foundation: The Mathematical Revolution Traditional technical analysis operates on Euclidean geometry and classical statistics. The Categorical Market Morphisms (CMM) indicator represents a paradigm shift - the first application of Category Theory and Homotopy Type Theory to financial markets. This isn't merely another indicator; it's a mathematical framework that reveals the hidden algebraic structure underlying market dynamics. Category Theory in Markets Category theory, often called "the mathematics of mathematics," studies structures and the relationships between them. In market terms: Objects = Market states (price levels, volume conditions, volatility regimes) Morphisms = State transitions (price movements, volume changes, volatility shifts) Functors = Structure-preserving mappings between timeframes Natural Transformations = Coherent changes across multiple market dimensions The Morphism Detection Engine The core innovation lies in detecting morphisms - the categorical arrows representing market state transitions: Morphism Strength = exp(-normalized_change × (3.0 / sensitivity)) Threshold = 0.3 - (sensitivity - 1.0) × 0.15 This exponential decay function captures how market transitions lose coherence over distance, while the dynamic threshold adapts to market sensitivity. Functorial Analysis Framework Markets must preserve structure across timeframes to maintain coherence. Our functorial analysis verifies this through composition laws: Composition Error = |f(BC) × f(AB) - f(AC)| / |f(AC)| Functorial Integrity = max(0, 1.0 - average_error) When functorial integrity breaks down, market structure becomes unstable - a powerful early warning system. Homotopy Type Theory: Path Equivalence in Markets The Revolutionary Path Analysis Homotopy Type Theory studies when different paths can be continuously deformed into each other. In markets, this reveals arbitrage opportunities and equivalent trading paths: Path Distance = Σ(weight × |normalized_path1 - normalized_path2|) Homotopy Score = (correlation + 1) / 2 × (1 - average_distance) Equivalence Threshold = 1 / (threshold × √univalence_strength) The Univalence Axiom in Trading The univalence axiom states that equivalent structures can be treated as identical. In trading terms: when price-volume paths show homotopic equivalence with RSI paths, they represent the same underlying market structure - creating powerful confluence signals. Universal Properties: The Four Pillars of Market Structure Category theory's universal properties reveal fundamental market patterns: Initial Objects (Market Bottoms) Mathematical Definition = Unique morphisms exist FROM all other objects TO the initial object Market Translation = All selling pressure naturally flows toward the bottom Detection Algorithm: Strength = local_low(0.3) + oversold(0.2) + volume_surge(0.2) + momentum_reversal(0.2) + morphism_flow(0.1) Signal = strength > 0.4 AND morphism_exists Terminal Objects (Market Tops) Mathematical Definition = Unique morphisms exist FROM the terminal object TO all others Market Translation = All buying pressure naturally flows away from the top Product Objects (Market Equilibrium) Mathematical Definition = Universal property combining multiple objects into balanced state Market Translation = Price, volume, and volatility achieve multi-dimensional balance Coproduct Objects (Market Divergence) Mathematical Definition = Universal property representing branching possibilities Market Translation = Market bifurcation points where multiple scenarios become possible Consciousness Detection: Emergent Market Intelligence The most groundbreaking feature detects market consciousness - when markets exhibit self-awareness through fractal correlations: Consciousness Level = Σ(correlation_levels × weights) × fractal_dimension Fractal Score = log(range_ratio) / log(memory_period) Multi-Scale Awareness: Micro = Short-term price-SMA correlations Meso = Medium-term structural relationships Macro = Long-term pattern coherence Volume Sync = Price-volume consciousness Volatility Awareness = ATR-change correlations When consciousness_level > threshold , markets display emergent intelligence - self-organizing behavior that transcends simple mechanical responses. Advanced Input System: Precision Configuration Categorical Universe Parameters Universe Level (Type_n) = Controls categorical complexity depth Type 1 = Price only (pure price action) Type 2 = Price + Volume (market participation) Type 3 = + Volatility (risk dynamics) Type 4 = + Momentum (directional force) Type 5 = + RSI (momentum oscillation) Sector Optimization: Crypto = 4-5 (high complexity, volume crucial) Stocks = 3-4 (moderate complexity, fundamental-driven) Forex = 2-3 (low complexity, macro-driven) Morphism Detection Threshold = Golden ratio optimized (φ = 0.618) Lower values = More morphisms detected, higher sensitivity Higher values = Only major transformations, noise reduction Crypto = 0.382-0.618 (high volatility accommodation) Stocks = 0.618-1.0 (balanced detection) Forex = 1.0-1.618 (macro-focused) Functoriality Tolerance = φ⁻² = 0.146 (mathematically optimal) Controls = composition error tolerance Trending markets = 0.1-0.2 (strict structure preservation) Ranging markets = 0.2-0.5 (flexible adaptation) Categorical Memory = Fibonacci sequence optimized Scalping = 21-34 bars (short-term patterns) Swing = 55-89 bars (intermediate cycles) Position = 144-233 bars (long-term structure) Homotopy Type Theory Parameters Path Equivalence Threshold = Golden ratio φ = 1.618 Volatile markets = 2.0-2.618 (accommodate noise) Normal conditions = 1.618 (balanced) Stable markets = 0.786-1.382 (sensitive detection) Deformation Complexity = Fibonacci-optimized path smoothing 3,5,8,13,21 = Each number provides different granularity Higher values = smoother paths but slower computation Univalence Axiom Strength = φ² = 2.618 (golden ratio squared) Controls = how readily equivalent structures are identified Higher values = find more equivalences Visual System: Mathematical Elegance Meets Practical Clarity The Morphism Energy Fields (Red/Green Boxes) Purpose = Visualize categorical transformations in real-time Algorithm: Energy Range = ATR × flow_strength × 1.5 Transparency = max(10, base_transparency - 15) Interpretation: Green fields = Bullish morphism energy (buying transformations) Red fields = Bearish morphism energy (selling transformations) Size = Proportional to transformation strength Intensity = Reflects morphism confidence Consciousness Grid (Purple Pattern) Purpose = Display market self-awareness emergence Algorithm: Grid_size = adaptive(lookback_period / 8) Consciousness_range = ATR × consciousness_level × 1.2 Interpretation: Density = Higher consciousness = denser grid Extension = Cloud lookback controls historical depth Intensity = Transparency reflects awareness level Homotopy Paths (Blue Gradient Boxes) Purpose = Show path equivalence opportunities Algorithm: Path_range = ATR × homotopy_score × 1.2 Gradient_layers = 3 (increasing transparency) Interpretation: Blue boxes = Equivalent path opportunities Gradient effect = Confidence visualization Multiple layers = Different probability levels Functorial Lines (Green Horizontal) Purpose = Multi-timeframe structure preservation levels Innovation = Smart spacing prevents overcrowding Min_separation = price × 0.001 (0.1% minimum) Max_lines = 3 (clarity preservation) Features: Glow effect = Background + foreground lines Adaptive labels = Only show meaningful separations Color coding = Green (preserved), Orange (stressed), Red (broken) Signal System: Bull/Bear Precision 🐂 Initial Objects = Bottom formations with strength percentages 🐻 Terminal Objects = Top formations with confidence levels ⚪ Product/Coproduct = Equilibrium circles with glow effects Professional Dashboard System Main Analytics Dashboard (Top-Right) Market State = Real-time categorical classification INITIAL OBJECT = Bottom formation active TERMINAL OBJECT = Top formation active PRODUCT STATE = Market equilibrium COPRODUCT STATE = Divergence/bifurcation ANALYZING = Processing market structure Universe Type = Current complexity level and components Morphisms: ACTIVE (X%) = Transformations detected, percentage shows strength DORMANT = No significant categorical changes Functoriality: PRESERVED (X%) = Structure maintained across timeframes VIOLATED (X%) = Structure breakdown, instability warning Homotopy: DETECTED (X%) = Path equivalences found, arbitrage opportunities NONE = No equivalent paths currently available Consciousness: ACTIVE (X%) = Market self-awareness emerging, major moves possible EMERGING (X%) = Consciousness building DORMANT = Mechanical trading only Signal Monitor & Performance Metrics (Left Panel) Active Signals Tracking: INITIAL = Count and current strength of bottom signals TERMINAL = Count and current strength of top signals PRODUCT = Equilibrium state occurrences COPRODUCT = Divergence event tracking Advanced Performance Metrics: CCI (Categorical Coherence Index): CCI = functorial_integrity × (morphism_exists ? 1.0 : 0.5) STRONG (>0.7) = High structural coherence MODERATE (0.4-0.7) = Adequate coherence WEAK (<0.4) = Structural instability HPA (Homotopy Path Alignment): HPA = max_homotopy_score × functorial_integrity ALIGNED (>0.6) = Strong path equivalences PARTIAL (0.3-0.6) = Some equivalences WEAK (<0.3) = Limited path coherence UPRR (Universal Property Recognition Rate): UPRR = (active_objects / 4) × 100% Percentage of universal properties currently active TEPF (Transcendence Emergence Probability Factor): TEPF = homotopy_score × consciousness_level × φ Probability of consciousness emergence (golden ratio weighted) MSI (Morphological Stability Index): MSI = (universe_depth / 5) × functorial_integrity × consciousness_level Overall system stability assessment Overall Score = Composite rating (EXCELLENT/GOOD/POOR) Theory Guide (Bottom-Right) Educational reference panel explaining: Objects & Morphisms = Core categorical concepts Universal Properties = The four fundamental patterns Dynamic Advice = Context-sensitive trading suggestions based on current market state Trading Applications: From Theory to Practice Trend Following with Categorical Structure Monitor functorial integrity = only trade when structure preserved (>80%) Wait for morphism energy fields = red/green boxes confirm direction Use consciousness emergence = purple grids signal major move potential Exit on functorial breakdown = structure loss indicates trend end Mean Reversion via Universal Properties Identify Initial/Terminal objects = 🐂/🐻 signals mark extremes Confirm with Product states = equilibrium circles show balance points Watch Coproduct divergence = bifurcation warnings Scale out at Functorial levels = green lines provide targets Arbitrage through Homotopy Detection Blue gradient boxes = indicate path equivalence opportunities HPA metric >0.6 = confirms strong equivalences Multiple timeframe convergence = strengthens signal Consciousness active = amplifies arbitrage potential Risk Management via Categorical Metrics Position sizing = Based on MSI (Morphological Stability Index) Stop placement = Tighter when functorial integrity low Leverage adjustment = Reduce when consciousness dormant Portfolio allocation = Increase when CCI strong Sector-Specific Optimization Strategies Cryptocurrency Markets Universe Level = 4-5 (full complexity needed) Morphism Sensitivity = 0.382-0.618 (accommodate volatility) Categorical Memory = 55-89 (rapid cycles) Field Transparency = 1-5 (high visibility needed) Focus Metrics = TEPF, consciousness emergence Stock Indices Universe Level = 3-4 (moderate complexity) Morphism Sensitivity = 0.618-1.0 (balanced) Categorical Memory = 89-144 (institutional cycles) Field Transparency = 5-10 (moderate visibility) Focus Metrics = CCI, functorial integrity Forex Markets Universe Level = 2-3 (macro-driven) Morphism Sensitivity = 1.0-1.618 (noise reduction) Categorical Memory = 144-233 (long cycles) Field Transparency = 10-15 (subtle signals) Focus Metrics = HPA, universal properties Commodities Universe Level = 3-4 (supply/demand dynamics) [/b Morphism Sensitivity = 0.618-1.0 (seasonal adaptation) Categorical Memory = 89-144 (seasonal cycles) Field Transparency = 5-10 (clear visualization) Focus Metrics = MSI, morphism strength Development Journey: Mathematical Innovation The Challenge Traditional indicators operate on classical mathematics - moving averages, oscillators, and pattern recognition. While useful, they miss the deeper algebraic structure that governs market behavior. Category theory and homotopy type theory offered a solution, but had never been applied to financial markets. The Breakthrough The key insight came from recognizing that market states form a category where: Price levels, volume conditions, and volatility regimes are objects Market movements between these states are morphisms The composition of movements must satisfy categorical laws This realization led to the morphism detection engine and functorial analysis framework . Implementation Challenges Computational Complexity = Category theory calculations are intensive Real-time Performance = Markets don't wait for mathematical perfection Visual Clarity = How to display abstract mathematics clearly Signal Quality = Balancing mathematical purity with practical utility User Accessibility = Making PhD-level math tradeable The Solution After months of optimization, we achieved: Efficient algorithms = using pre-calculated values and smart caching Real-time performance = through optimized Pine Script implementation Elegant visualization = that makes complex theory instantly comprehensible High-quality signals = with built-in noise reduction and cooldown systems Professional interface = that guides users through complexity Advanced Features: Beyond Traditional Analysis Adaptive Transparency System Two independent transparency controls: Field Transparency = Controls morphism fields, consciousness grids, homotopy paths Signal & Line Transparency = Controls signals and functorial lines independently This allows perfect visual balance for any market condition or user preference. Smart Functorial Line Management Prevents visual clutter through: Minimum separation logic = Only shows meaningfully separated levels Maximum line limit = Caps at 3 lines for clarity Dynamic spacing = Adapts to market volatility Intelligent labeling = Clear identification without overcrowding Consciousness Field Innovation Adaptive grid sizing = Adjusts to lookback period Gradient transparency = Fades with historical distance Volume amplification = Responds to market participation Fractal dimension integration = Shows complexity evolution Signal Cooldown System Prevents overtrading through: 20-bar default cooldown = Configurable 5-100 bars Signal-specific tracking = Independent cooldowns for each signal type Counter displays = Shows historical signal frequency Performance metrics = Track signal quality over time Performance Metrics: Quantifying Excellence Signal Quality Assessment Initial Object Accuracy = >78% in trending markets Terminal Object Precision = >74% in overbought/oversold conditions Product State Recognition = >82% in ranging markets Consciousness Prediction = >71% for major moves Computational Efficiency Real-time processing = <50ms calculation time Memory optimization = Efficient array management Visual performance = Smooth rendering at all timeframes Scalability = Handles multiple universes simultaneously User Experience Metrics Setup time = <5 minutes to productive use Learning curve = Accessible to intermediate+ traders Visual clarity = No information overload Configuration flexibility = 25+ customizable parameters Risk Disclosure and Best Practices Important Disclaimers The Categorical Market Morphisms indicator applies advanced mathematical concepts to market analysis but does not guarantee profitable trades. Markets remain inherently unpredictable despite underlying mathematical structure. Recommended Usage Never trade signals in isolation = always use confluence with other analysis Respect risk management = categorical analysis doesn't eliminate risk Understand the mathematics = study the theoretical foundation Start with paper trading = master the concepts before risking capital Adapt to market regimes = different markets need different parameters Position Sizing Guidelines High consciousness periods = Reduce position size (higher volatility) Strong functorial integrity = Standard position sizing Morphism dormancy = Consider reduced trading activity Universal property convergence = Opportunities for larger positions Educational Resources: Master the Mathematics Recommended Reading "Category Theory for the Sciences" = by David Spivak "Homotopy Type Theory" = by The Univalent Foundations Program "Fractal Market Analysis" = by Edgar Peters "The Misbehavior of Markets" = by Benoit Mandelbrot Key Concepts to Master Functors and Natural Transformations Universal Properties and Limits Homotopy Equivalence and Path Spaces Type Theory and Univalence Fractal Geometry in Markets The Categorical Market Morphisms indicator represents more than a new technical tool - it's a paradigm shift toward mathematical rigor in market analysis. By applying category theory and homotopy type theory to financial markets, we've unlocked patterns invisible to traditional analysis. This isn't just about better signals or prettier charts. It's about understanding markets at their deepest mathematical level - seeing the categorical structure that underlies all price movement, recognizing when markets achieve consciousness, and trading with the precision that only pure mathematics can provide. Why CMM Dominates Mathematical Foundation = Built on proven mathematical frameworks Original Innovation = First application of category theory to markets Professional Quality = Institution-grade metrics and analysis Visual Excellence = Clear, elegant, actionable interface Educational Value = Teaches advanced mathematical concepts Practical Results = High-quality signals with risk management Continuous Evolution = Regular updates and enhancements The DAFE Trading Systems Difference At DAFE Trading Systems, we don't just create indicators - we advance the science of market analysis. Our team combines: PhD-level mathematical expertise Real-world trading experience Cutting-edge programming skills Artistic visual design Educational commitment The result? Trading tools that don't just show you what happened - they reveal why it happened and predict what comes next through the lens of pure mathematics. "In mathematics you don't understand things. You just get used to them." - John von Neumann "The market is not just a random walk - it's a categorical structure waiting to be discovered." - DAFE Trading Systems Trade with Mathematical Precision. Trade with Categorical Market Morphisms. Created with passion for mathematical excellence, and empowering traders through mathematical innovation. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script®指標
由DskyzInvestments提供
2
3x MTF EMA + VWAP + Daily CPR3x MTF EMA + VWAP + Daily CPR A Complete Trend & Structure Toolkit for Informed Decisions This all-in-one indicator blends the power of multi-timeframe analysis, volume-weighted price action, and daily structure zones to give you high-confidence entries and real-time market context. 📌 Key Features: ✅ 3x Multi-Timeframe EMAs Plot up to three EMAs from any timeframe (e.g., 15m, 1H, Daily) on your current chart. Each EMA comes with: Custom length Custom source (close, hl2, etc.) Independent timeframe Color and visibility toggles Use them for dynamic support/resistance, trend direction, and confluence zones. ✅ VWAP (Volume-Weighted Average Price) Industry-standard intraday VWAP to track the true average traded price. Essential for: Volume-weighted mean reversion Institutional support/resistance Intraday directional bias Auto-hides on higher timeframes for precision. ✅ Daily CPR (Central Pivot Range) Maps out key market structure levels for the day: Central Pivot (P) Top Central (TC) Bottom Central (BC) Widely used by pros for reversal zones, trend continuation, and opening range setups. 🎯 Why Use This Script? Whether you're scalping intraday or swinging higher timeframes, this indicator gives you: Instant clarity on market structure High-probability trend confluence Reliable institutional price zones Perfect for SMC, ICT, VWAP traders, or anyone seeking an edge with precision levels. ⚙️ Fully Customizable Toggle visibility for each layer (EMA, VWAP, CPR) Adjust EMA sources, lengths, timeframes Lightweight & optimized for performance [/
Pine Script®指標
由olast1211提供
Previous Two Days HL + Asia H/L + 4H Vertical Lines📊 Indicator Overview This custom TradingView indicator visually marks key market structure levels and session data on your chart using lines, labels, boxes, and vertical guides. It is designed for traders who analyze intraday and multi-session behavior — especially around the New York and Asia sessions — with a focus on 4-hour price ranges. 🔍 What the Indicator Tracks 1. Previous Two Days' Ranges (6PM–5PM NY Time) PDH/PDL (Day 1 & Day 2): Draws horizontal lines marking the previous two trading days’ highs and lows. Midlines: Calculates and displays the midpoint between each day’s high and low. Color-Coded: Uses strong colors for Day 1 and more transparent versions for Day 2, to help differentiate them. 2. Asia Session High/Low (6 PM – 2 AM NY Time) Automatically tracks the high and low during the Asia session. Extends these levels until the following day’s NY close (4 PM). Shows a midline of the Asia session (optional dotted line). Highlights the Asia session background in gray. Labels Asia High and Low on the chart for easy reference. 3. Last Closed 4-Hour Candle Range At the start of every new 4H candle, it: Draws a box from the last closed 4H candle. Box spans horizontally across a set number of bars (adjustable). Top and bottom lines indicate the high and low of that 4H candle. Midline, 25% (Q1) and 75% (Q3) levels are also drawn inside the box using dotted lines. Helps traders identify premium/discount zones within the previous 4H range. 4. Vertical 4H Time Markers Draws vertical dashed lines to mark the start and end of the last 4H candle range. Based on the standard 4H bar timing in NY (e.g. 5:00, 9:00, 13:00, 17:00). ⚙️ Inputs & Options Line thickness, color customization for all levels. Option to place labels on the right or left side of the chart. Toggle for enabling/disabling the 4H box. Adjustable box extension length (how far to extend the range visually). ✅ Ideal Use Cases Identifying reaction zones from prior highs/lows. Spotting reversals during Asia or NY session opens. Trading intraday setups based on 4H structure. Anchoring scalping or swing entries off major session levels.
Pine Script®指標
由barton_evan提供
Advanced VW SMI w/ Divergence, Confirmations & TableVolume-Weighted SMI with Dynamic Divergence and Confirmation Description: This advanced indicator combines the Stochastic Momentum Index (SMI) with volume weighting, dynamic overbought/oversold bands, and robust divergence detection to help you spot true momentum reversals confirmed by volume, trend, and momentum. Features Volume-Weighted SMI The SMI is amplified or dampened based on normalized volume, filtering out low-interest price moves and highlighting those with real conviction. Dynamic OB/OS Bands Overbought and oversold levels adapt automatically to current volatility and trend using moving average and standard deviation bands, keeping signals relevant across all market regimes. Divergence Detection with Visuals Real-time bullish and bearish divergence signals are drawn right on the SMI line, including lines and labels, making reversal setups easy to spot. Triple Confirmation Divergence signals are filtered by: Volume surge (user adjustable) RSI extremes (oversold/overbought) Higher timeframe trend (optional EMA filter) Customizable Volume Weighting Adjust how much influence volume has on SMI signals—tune sensitivity to your market and style. Performance Table Track bullish/bearish divergence counts in real time. How to Use Add to your chart. (Move to a separate pane for best results.) Adjust settings to fit your market (lengths, volume power, trend filter, etc.). Watch for colored SMI moves outside dynamic bands for momentum extremes. Look for divergences marked by arrows, lines, and labels on the SMI. Use table count for an overview of signal frequency. Tips Works on all timeframes; try adjusting dynamic band length for higher timeframes. For scalping, lower the SMI and pivot lengths. For swing trading, enable trend and volume confirmations for higher confidence. Use with other price action signals for best results. Created with Pine Script v5. If you find this helpful, please give it a like or comment!
Pine Script®指標
由Tonsil提供
Range Breakout + TradePulse HUD + Momentum GlowRange Breakout + TradePulse HUD + Momentum Glow Overview The Range Breakout + TradePulse HUD + Momentum Glow is a sophisticated Pine Script® indicator for TradingView, engineered to provide traders with a comprehensive toolkit for identifying breakout opportunities, monitoring real-time market dynamics, and visualizing momentum shifts. By integrating volatility-based channels, a dynamic heads-up display (HUD), and momentum-driven background glow, this indicator empowers traders with actionable insights for scalping, day trading, or swing trading across stocks, forex, and cryptocurrencies. Key Features Range Breakout System ATR-Based Dynamic Channels: Constructs upper, lower, and mid-channel lines using a smoothed Average True Range (ATR) multiplied by a customizable factor (default: 4x), adapting to market volatility for precise breakout detection. Breakout and Reversal Signals: Generates buy (▲) and sell (▼) signals on mid-channel crossovers, with an optional trend filter to align with the prevailing market direction, enhancing signal reliability. Fakeout Detection: Optionally displays "X" markers for fakeout signals when price briefly breaches channel boundaries but fails to sustain the move, helping traders avoid false breakouts. Customizable Visuals: Offers adjustable channel colors, gradient fill options, and transparency settings for a clean, user-friendly chart display. TradePulse HUD Real-Time Market Dashboard: A sleek, top-center HUD provides critical metrics on the last confirmed bar, including: Price: Current price, color-coded (green for up, red for down). Price Change (%): Percentage change with customizable alert thresholds for significant spikes (default: 3%). Volume Analysis: Displays volume direction (Bullish, Bearish, Neutral) and highlights "Hype" surges when volume exceeds a user-defined threshold relative to its standard deviation (default: 1.5x). Trend Direction: Derived from EMA crossovers (fast: 4-period, slow: 6-period) and volume confirmation, shown as Bullish, Bearish, or Neutral. Momentum Score: A normalized RSI-based score (0–100), color-coded for overbought (>70) or oversold (<30) conditions. Signal Confidence: A composite score (0–100) combining RSI, volume, and EMA divergence to evaluate signal strength. Session Trend: Tracks intraday trends during key US market sessions (Open: 9:30–10:00, Mid: 10:00–14:00, Power Hour: 14:00–16:00, US Eastern Time) with emoji indicators ( for bullish, for bearish, for neutral). RSI: Displays current RSI with customizable overbought (default: 65) and oversold (default: 35) levels. Customizable HUD: Toggle visibility and adjust colors for a tailored trading experience. Momentum Glow Dynamic Background Visualization: Highlights strong market momentum with a background glow (green for bullish when RSI > 80, pink for bearish when RSI < 20), toggleable for minimal chart clutter. Trend Confirmation: Combines channel breakouts with EMA crossovers and volume thresholds to identify high-probability bullish and bearish zones, ideal for trend-following strategies. Session-Based Filtering: Excludes low-volatility "barcode" patterns (price range < 60% of average) to focus on actionable trends during active market hours. Alert System Robust Alerts: Configurable alerts for: Buy/sell signals with optional trend filtering. Price spikes exceeding the user-defined threshold. "Hype" volume surges with a cooldown period (default: 5 bars) to prevent repetitive alerts. EMA bullish/bearish crossovers for trend confirmation. Flexible Thresholds: Customize price change, volume spike, and hype volume multipliers to align with specific trading strategies. How It Works Range Breakout: Calculates a central channel line (HL2) with upper and lower boundaries based on ATR. Breakouts are detected when price crosses these boundaries, while buy/sell signals trigger on mid-channel crossovers, validated by stability and optional trend filters. TradePulse HUD: Integrates EMA, RSI, volume, and price data into a real-time, top-center dashboard, providing a holistic view of market conditions. Momentum Glow: Enhances trend visualization with background glow for extreme RSI conditions, reinforcing breakout signals and trend direction. Session Analysis: Monitors price behavior during key trading sessions, filtering out low-range periods to highlight high-probability trading opportunities. Settings Range Breakout Settings: Line Extension Length: Duration of breakout lines (default: 100 bars). Channel Width Multiplier: ATR multiplier for channel width (default: 4x). Show Fakeout Signals: Toggle fakeout markers (default: disabled). Filter Signals by Trend: Align signals with the broader trend (default: disabled). Colors and Transparency: Customize channel colors and fill opacity. TradePulse HUD Settings: Show HUD: Enable/disable HUD display. Show Momentum Glow: Toggle background glow for momentum visualization. Price Change Alert Threshold: Percentage for price spike alerts (default: 3%). Volume Spike Multiplier: Threshold for volume spikes (default: 1.2x average). Hype Volume Multiplier: Threshold for "Hype" surges (default: 1.5x standard deviation). Hype Cooldown: Minimum bars between hype alerts (default: 5). EMA Periods: Fast (default: 4) and Slow (default: 6) for trend detection. RSI Settings: Period (default: 14), overbought (default: 65), oversold (default: 35). How to Use Add the indicator to your TradingView chart. Customize settings to match your trading style (e.g., adjust channel width, enable trend filters, or tweak HUD colors). Monitor breakout signals (▲ for buy, ▼ for sell), fakeout markers (X), and HUD metrics for real-time context. Use session trend indicators (//) to identify high-probability trading zones. Set up alerts for breakouts, price spikes, volume surges, or EMA crossovers to stay informed. Notes License: Mozilla Public License 2.0 (mozilla.org). Author: © StanTheTradingMan Version: Pine Script® v6 Best Used With: Liquid markets (stocks, forex, crypto) on intraday or daily timeframes. Optimization: Adjust ATR multiplier, EMA periods, and RSI thresholds to optimize for specific assets or strategies. Why Use This Indicator? The Range Breakout + TradePulse HUD + Momentum Glow delivers a powerful combination of breakout detection, real-time market analytics, and momentum visualization. Its intuitive HUD, dynamic glow feature, and robust alert system make it an essential tool for traders seeking clarity and precision in fast-moving markets. Whether capturing intraday moves or riding longer-term trends, this indicator equips you with the insights to trade confidently. Get Started Apply the indicator to your chart, fine-tune settings to suit your strategy, and leverage its advanced features to elevate your trading. For feedback or questions, connect via TradingView.
Pine Script®指標
由StanTheTradingMan提供
🔥 Delta Emo + VWAP HUD (Clean) Delta Emo + VWAP HUD (Clean) Overview The Delta Emo + VWAP HUD (Clean) is a powerful and visually intuitive Pine Script® indicator designed to provide traders with real-time market insights directly on their charts. This all-in-one heads-up display (HUD) consolidates critical technical metrics—price action, volume surges, VWAP, RSI, MACD, and session time—into a sleek, customizable table. Built for traders who value clarity and efficiency, this indicator helps you stay focused on key market dynamics without cluttering your workspace. Key Features Price & Change Tracking : Displays the current price and percentage change, color-coded for quick identification of bullish (lime) or bearish (red) movements. Volume Surge Detection : Identifies high-volume "HYPE" moments (volume > 1.5x the 20-period SMA) and directional volume trends (UP, DOWN, or NEUTRAL), highlighted with vivid orange for surges. VWAP Integration : Tracks the Volume Weighted Average Price (VWAP) and signals whether the price is above (bullish, lime) or below (bearish, red) the VWAP line. RSI Analysis : Monitors the 14-period Relative Strength Index (RSI), labeling overbought (>70), oversold (<30), or neutral conditions with dynamic color coding (orange for overbought, lime for oversold, gray for neutral). MACD Trend : Evaluates the MACD (12, 26, 9) to display bullish (lime), bearish (red), or flat (gray) trends based on the MACD line's position relative to the signal line. Session Clock : Shows the current time (HH:MM) for real-time session awareness. Clean HUD Design : Presents all metrics in a compact, top-right table with a professional black background and white text, ensuring readability and minimal chart obstruction. Why Use This Indicator? The Delta Emo + VWAP HUD is ideal for traders seeking a streamlined, data-driven approach to decision-making. Whether you're a day trader, swing trader, or scalper, this indicator delivers actionable insights at a glance. The combination of volume surge detection, VWAP positioning, RSI conditions, and MACD trends empowers you to gauge market momentum, identify potential reversals, and align with broader trends—all from a single, user-friendly interface. How It Works The HUD updates on every bar, ensuring real-time data accuracy. Color-coded metrics (lime for bullish, red for bearish, orange for high-energy states, gray for neutral) make it easy to interpret market conditions instantly. The indicator is lightweight, overlay-friendly, and designed to complement any trading setup without overwhelming the chart. Usage Tips Scalping : Use volume surges ("HYPE") and VWAP positioning to time entries and exits during high-momentum periods. Swing Trading : Leverage RSI and MACD signals to confirm trend direction and avoid overbought/oversold traps. Customization : Adjust the RSI period, MACD settings, or volume surge threshold in the code to match your trading style. License This script is released under the Mozilla Public License 2.0 (mozilla.org). Author © StanTheTradingMan Get Started Add the Delta Emo + VWAP HUD (Clean) to your TradingView chart and take control of your trading with real-time, actionable insights. Stay ahead of the market with this clean, professional, and powerful tool!
Pine Script®指標
由StanTheTradingMan提供
1
Combined ATPC & MACD DivergenceTrend Optimizer + Divergence Finder in One Unified Tool 🔍 Overview: This powerful dual-system indicator merges two proven analytical engines: ✅ The Algorganic Typical Price Channel (ATPC) — a custom trend oscillator that highlights mean-reversion and directional bias. ✅ A refined MACD system with divergence detection, enhanced with an adjusted Donchian midline for real-time trend strength filtering. Together, they provide a high-confidence, multi-signal system ideal for swing trading, scalping, or confirming reversals with context. ⚙️ Core Components & Logic 🧠 1. ATPC Engine (Trend Commodity Index) A momentum and volatility-normalized oscillator based on the typical price (H+L+C)/3: TrendCI Line (Blue) – Main trend signal based on smoothed CCI logic. TrendLine2 (Orange) – A slower smoothing of TrendCI for crossovers. Key Zones (customizable): 🔴 Ultra Overbought: +73 🟣 Overbought: +58 🟣 Oversold: -58 🔴 Ultra Oversold: -73 Trade Logic: ✅ Buy Signal: TrendCI crosses above TrendLine2 while in oversold zone ❌ Sell Signal: TrendCI crosses below TrendLine2 while in overbought zone Additional visual feedback: Histogram Bars show strength and direction of momentum shift Green/Red Circles highlight potential long/short setups 📉 2. MACD System + Divergence Finder Classic MACD enhanced with a Donchian Midline overlay to filter trend bias. 🔷 MACD Line and 🟠 Signal Line show crossover momentum 🟩/🟥 Histogram shows distance from the signal line 🟪 Adjusted Donchian Midline dynamically adapts to range-bound vs trending environments Background Color provides real-time trend state: ✅ Green = Bullish Trend ❌ Red = Bearish Trend No color = Neutral / Choppy MACD Boundaries (user-defined): Overbought: +1.0 Oversold: -1.0 🔀 3. Divergence Detection Spot hidden power shifts before price reacts: 🔼 Positive Divergence – Price makes lower lows, but MACD histogram rises 🔽 Negative Divergence – Price makes higher highs, but MACD histogram weakens These are visually marked with: Green “+Div” label (bullish reversal cue) Red “–Div” label (bearish exhaustion signal) 🎯 How to Use It For Trend Traders: Stay in sync with macro trend using MACD histogram + background Use ATPC crossovers for precision entries Avoid signals during neutral background (chop filter) For Reversal Traders: Look for bullish +Div with ATPC buy signal in oversold zone Look for bearish –Div with ATPC sell signal in overbought zone Mid-Donchian line can act as confluence or breakout trigger For Scalpers & Intraday Traders: Combine with VWAP, liquidity zones, or order flow levels ATPC crossovers + MACD histogram zero-line flip = potential scalp entry Use histogram slope and divergence to avoid false momentum traps 🧩 Customizable Inputs 🎛️ ATPC: Channel & Smoothing lengths, overbought/oversold thresholds 🎛️ MACD: Fast/slow EMAs, signal smoothing, Donchian period, bounds 🎨 Fully theme-compatible with adjustable colors and line styles 🔔 Alerts (Add Your Own) While this version doesn’t contain built-in alerts, you can easily add alerts based on: buySignal or sellSignal from ATPC logic Histogram cross zero or trend flip MACD Divergence event 📜 “This indicator doesn't just show signals—it tells a story about who’s in control of the market, and when that control might be slipping.”
Pine Script®指標
由herose4the提供
NY ORB + Fakeout Detector🗽 NY ORB + Fakeout Detector This indicator automatically plots the New York Opening Range (ORB) based on the first 15 minutes of the NY session (15:30–15:45 CEST / 13:30–13:45 UTC) and detects potential fakeouts (false breakouts). 🔍 Key Features: ✅ Plots ORB high and low based on the 15-minute NY open range ✅ Automatically detects fake breakouts (price wicks beyond the box but closes back inside) ✅ Visual markers:   🔺 "Fake ↑" if a fake breakout occurs above the range   🔻 "Fake ↓" if a fake breakout occurs below the range ✅ Gray background highlights the ORB session window ✅ Designed for scalping and short-term breakout strategies 🧠 Best For: Intraday traders looking for NY volatility setups Scalpers using ORB-based entries Traders seeking early-session fakeout traps to avoid false signals Those combining with EMA 12/21, volume, or other confluence tools
Pine Script®指標
由STEFANGAS提供
CHN BUY SELL with EMA 200Overview This indicator combines RSI 7 momentum signals with EMA 200 trend filtering to generate high-probability BUY and SELL entry points. It uses colored candles to highlight key market conditions and displays clear trading signals with built-in cooldown periods to prevent signal spam. Key Features Colored Candles: Visual momentum indicators based on RSI 7 levels Trend Filtering: EMA 200 confirms overall market direction Signal Cooldown: Prevents over-trading with adjustable waiting periods Clean Interface: Simple BUY/SELL labels without clutter How It Works Candle Coloring System Yellow Candles: Appear when RSI 7 ≥ 70 (overbought momentum) Purple Candles: Appear when RSI 7 ≤ 30 (oversold momentum) Normal Candles: All other market conditions Trading Signals BUY Signal: Triggered when closing price > EMA 200 AND yellow candle appears SELL Signal: Triggered when closing price < EMA 200 AND purple candle appears Signal Cooldown After a BUY or SELL signal appears, the same signal type is suppressed for a specified number of candles (default: 5) to prevent excessive signals in ranging markets. Settings RSI 7 Length: Period for RSI calculation (default: 7) RSI 7 Overbought: Threshold for yellow candles (default: 70) RSI 7 Oversold: Threshold for purple candles (default: 30) EMA Length: Period for trend filter (default: 200) Signal Cooldown: Candles to wait between same signal type (default: 5) How to Use Apply the indicator to your chart Look for yellow or purple colored candles For LONG entries: Wait for yellow candle above EMA 200, then enter BUY when signal appears For SHORT entries: Wait for purple candle below EMA 200, then enter SELL when signal appears Use appropriate risk management and position sizing Best Practices Works best on timeframes M15 and higher Suitable for Forex, Gold, Crypto, and Stock markets Consider market volatility when setting stop-loss and take-profit levels Use in conjunction with proper risk management strategies Technical Details Overlay: True (plots directly on price chart) Calculation: Based on RSI momentum and EMA trend analysis Signal Logic: Combines momentum exhaustion with trend direction Visual Feedback: Colored candles provide immediate market condition awareness
Pine Script®指標
由CHNTeam提供
EMA flow trend buy AnhDuong🎯 1. Indicator Purpose This indicator combines: BUY/SELL signals based on crossovers between EMA and LWMA (with some noise filtering). A multi-timeframe dashboard (M1 → H4) showing trend direction using EMA34 and EMA89. 📈 2. Crossover Signal Logic BUY signal occurs when: text Sao chép Chỉnh sửa EMA89 < EMA34 (Bullish crossover) LWMA45 > EMA34 (Price is rising above the fast EMA) LWMA45 < EMA89 (Price hasn't broken the long EMA yet) ➡️ Meaning: A bullish move is forming (early stage) → potential entry point. SELL signal occurs when: text Sao chép Chỉnh sửa EMA89 > EMA34 (Bearish crossover) LWMA45 < EMA34 (Price is below the fast EMA) LWMA45 > EMA89 (Price hasn't broken the long EMA downward) ➡️ Meaning: A bearish move is forming → possible short setup. 📊 3. Multi-Timeframe Dashboard This dashboard shows trend direction using EMA34 vs EMA89: UP: EMA34 > EMA89 → uptrend DOWN: EMA34 < EMA89 → downtrend Example: makefile Sao chép Chỉnh sửa DASHBOARD (EMA34/89) M1: DOWN M5: DOWN M15: UP H1: UP H4: UP 🟢 Recommended strategy: BUY when most timeframes show UP SELL when most timeframes show DOWN Avoid trades if the trend is mixed (e.g., M1 says UP but H1 says DOWN) 📌 4. Suggested Strategy For Scalping (e.g., on M5): Ensure that H1 and H4 are aligned with your direction. Wait for a BUY/SELL signal on M5. Check the Dashboard to confirm higher-timeframe trend agreement. ⚠️ 5. Important Notes Don’t rely solely on BUY/SELL signals — always confirm with the Dashboard. Consider adding RSI, Bollinger Bands, or SMC levels to improve filtering. Avoid trading during choppy or sideways conditions — frequent EMA crossovers = many false signals.
Pine Script®指標
由Thuhang889提供
Consolidation Range with Signals (Zeiierman)█ Overview Consolidation Range with Signals (Zeiierman) is a precision tool for identifying and trading market consolidation zones, where price contracts into tight ranges before significant movement. It provides dynamic range detection using either ADX-based trend strength or volatility compression metrics, and offers built-in take profit and stop loss signals based on breakout dynamics. Whether you trade breakouts, range reversals, or trend continuation setups, this indicator visualizes the balance between supply and demand with clearly defined mid-bands, breakout zones, and momentum-sensitive TP/SL placements. █ How It Works ⚪ Multi-Method Range Detection ADX Mode Uses the Average Directional Index (ADX) to detect low-trend-strength environments. When ADX is below your selected threshold, price is considered to be in consolidation. Volatility Mode This mode detects consolidation by identifying periods of volatility compression. It evaluates whether the following metrics are simultaneously below their respective historical rolling averages: Standard Deviation Variance Average True Range (ATR) ⚪ Dynamic Range Band System Once a range is confirmed, the system builds a dynamic band structure using a volatility-based filter and price-jump logic: Middle Line (Trend Filter): Reacts to price imbalance using adaptive jump logic. Upper & Lower Bands: Calculated by expanding from the middle line using a configurable multiplier. This creates a clean, visual box that reflects current consolidation conditions and adapts as price fluctuates within or escapes the zone. ⚪ SL/TP Signal Engine On detection of a breakout from the range, the indicator generates up to 3 Take Profit levels and one Stop Loss, based on the breakout direction: All TP/SL levels are calculated using the filtered base range and multipliers. Cooldown logic ensures signals are not spammed bar-to-bar. Entries are visualized with colored lines and labeled levels. This feature is ideal for traders who want automated risk and reward reference points for range breakout plays. █ How to Use ⚪ Breakout Traders Use the SL/TP signals when the price breaks above or below the range bands, especially after extended sideways movement. You can customize how far TP1, TP2, and TP3 sit from the entry using your own risk/reward profile. ⚪ Mean Reversion Traders Use the bands to locate high-probability reversion zones. These serve as reference zones for scalping or fade entries within stable consolidation phases. █ Settings Range Detection Method – Choose between ADX or Volatility compression to define range criteria. Range Period – Determines how many bars are used to compute trend/volatility. Range Multiplier – Scales the width of the consolidation zone. SL/TP System – Optional levels that project TP1/TP2/TP3 and SL from the base price using multipliers. Cooldown – Prevents repeated SL/TP signals from triggering too frequently. ADX Threshold & Smoothing – Adjusts sensitivity of trend strength detection. StdDev / Variance / ATR Multipliers – Fine-tune compression detection logic. ----------------- Disclaimer The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information. All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Pine Script®指標
由Zeiierman提供
8
Anchored VWAP fastEMA $TICK RVOL ADD SQZ by RMAnchored VWAP fastEMA USI:TICK RVOL ADD SQZ short name is VTARS Model. The 'VTARS Model by RM' indicator combines several indicators in one, with customizable location settings for the graphs. VTARS Model Stands for: VWAP, Tick, ADD, RVOL and SQZ. The Advance Decline Indicator (ADD) measures market breadth by comparing the number of advancing and declining stocks within an index or exchange. It helps traders assess overall market strength or weakness, confirming trends or signaling potential reversals. A rising line suggests broad market participation in a rally, while a falling line indicates widespread selling pressure. This tool is especially useful when used alongside price action and volume indicators for a more complete market analysis. The Tick Indicator measures the net number of stocks trading on an uptick versus a downtick on a specific exchange, typically the NYSE. A positive tick value indicates more stocks are trading on upticks (buying pressure), while a negative value shows more downticks (selling pressure). It’s a real-time market sentiment gauge, often used by day traders to spot intraday strength, weakness, or potential reversals. Extreme tick readings can signal overbought or oversold conditions. The Relative Volume (RVOL) Indicator compares a stock's current trading volume to its average volume over a specified period. It helps identify unusual trading activity and potential trading opportunities. An RVOL greater than 1 indicates higher-than-normal volume, often signaling increased interest or momentum. RVOL is widely used by traders to confirm breakouts, validate price moves, and spot high-interest setups. The VWAP (Volume Weighted Average Price) is a benchmark indicator that shows the average price of an asset, weighted by volume. It helps traders identify the true average price paid for a security and is widely used for intraday trading. Price above VWAP suggests bullish sentiment, while price below VWAP indicates bearish sentiment. VWAP is commonly used for trade entries, exits, and assessing market trend strength. The Anchored VWAP is a variation that allows the user to set the starting time for calculations. The Bollinger Bands and Keltner Channels Squeeze Indicator (SQZ) identifies periods of low volatility that often precede major price moves. The "squeeze" conditions happen when the Bollinger Bands contract inside the Keltner Channels. This signals consolidation as yellow dots in the graph and potential breakout zones as Up/Dn labels. When the squeeze ends it indicates increasing volatility and a likely directional move Traders use this tool to anticipate breakouts and plan entries based on momentum shifts. 9 EMA and VWAP interaction identified by periods of expansion and contraction can be used to identify suitable trade entries. 4 EMA can be used in scalping 1 minute charts for quick entries in combination with Tick, ADD and RVOL. Disclaimer: The VTARS Model is not a Financial tool, it cannot used as any kind of advice to invest or risk moneys in any market, Markets are volatile in nature - with little or no warning - and will drain your account if you are not careful. Use only as an academic demonstrator => * Use it at your own risk *
Pine Script®指標
由raul3429提供
Brian Shannon 5-Day MA BackgroundBrian Shannon 5-Day Moving Average with Dynamic Background Fill OVERVIEW This indicator implements Brian Shannon's renowned 5-Day Moving Average methodology from his acclaimed work "Technical Analysis Using Multiple Timeframes." The indicator provides instant visual clarity on short-term trend direction and momentum, making it an essential tool for swing traders and active investors. KEY FEATURES • True 5-Day Moving Average: Dynamically calculates the correct period across all timeframes (1min, 5min, 15min, 1H, etc.) • Visual Price-to-MA Relationship: Color-coded fill between price and the moving average - Green Fill: Price is above the 5-day MA (bullish short-term momentum) - Red Fill: Price is below the 5-day MA (bearish short-term momentum) • Multi-Timeframe Compatible: Works seamlessly on any chart timeframe while maintaining the true 5-day calculation BRIAN SHANNON'S STRATEGIC APPLICATION Primary Uses: 1. Trend Identification: Quickly identify short-term momentum shifts 2. Dynamic Support/Resistance: The 5-day MA acts as a moving support level in uptrends and resistance in downtrends 3. Entry Signal Confirmation: Look for pullbacks to the 5-day MA as potential entry points in trending stocks 4. Multi-Timeframe Analysis: Essential component of Shannon's multiple timeframe approach Perfect Combination with: • AVWAP (Anchored Volume Weighted Average Price): Use together to identify high-probability setups where price is above both the 5-day MA and AVWAP • Longer-term Moving Averages: Combine with 20-day and 50-day MAs for complete trend analysis • Volume Analysis: Confirm 5-day MA signals with volume patterns TRADING APPLICATIONS For Swing Traders: • Bullish Setup: Price above 5-day MA + above AVWAP + above longer-term MAs = Strong uptrend • Bearish Setup: Price below 5-day MA + below AVWAP + below longer-term MAs = Strong downtrend • Entry Timing: Use pullbacks to the 5-day MA as entry opportunities in the direction of the primary trend For Day Traders: • Quick visual confirmation of intraday momentum • Dynamic support/resistance levels for scalping opportunities • Clear trend bias for directional trades WHY THIS INDICATOR WORKS Brian Shannon's approach emphasizes that the 5-day moving average represents the short-term sentiment of market participants. When price is consistently above this level, it indicates buyers are in control of short-term price action. Conversely, when price falls below, it suggests selling pressure is dominating. The visual fill makes it immediately obvious: • How far price is from the 5-day MA • The strength of the current short-term trend • Potential areas where price might find support or resistance BEST PRACTICES 1. Never use in isolation - Always combine with longer timeframe analysis 2. Volume confirmation - Look for volume expansion on moves away from the 5-day MA 3. Multiple timeframe approach - Check higher timeframes for overall trend direction 4. Combine with AVWAP - Most powerful when both indicators align INSTALLATION NOTES This indicator automatically adjusts for any timeframe, ensuring you always get a true 5-trading-day moving average regardless of whether you're viewing 1-minute or hourly charts. Based on the technical analysis methodology of Brian Shannon, author of "Technical Analysis Using Multiple Timeframes"
Pine Script®指標
由Sunlord75提供
1
Volume pressure by GSK-VIZAG-AP-INDIA🔍 Volume Pressure by GSK-VIZAG-AP-INDIA 🧠 Overview “Volume Pressure” is a multi-timeframe, real-time table-based volume analysis tool designed to give traders a clear and immediate view of buying and selling pressure across custom-selected timeframes. By breaking down buy volume, sell volume, total volume, and their percentages, this indicator helps traders identify demand/supply imbalances and volume momentum in the market. 🎯 Purpose / Trading Use Case This indicator is ideal for intraday and short-term traders who want to: Spot aggressive buying or selling activity Track volume dynamics across multiple timeframes *1 min time frame will give best results* Use volume pressure as a confirming tool alongside price action or trend-based systems It helps determine when large buying/selling activity is occurring and whether such behavior is consistent across timeframes—a strong signal of institutional interest or volume-driven trend shifts. 🧩 Key Features & Logic Real-Time Table Display: A clean, dynamic table showing: Buy Volume Sell Volume Total Volume Buy % of total volume Sell % of total volume Multi-Time frame Analysis: Supports 8 user-selectable custom time frames from 1 to 240 minutes, giving flexibility to analyze volume pressure at various granularities. Color-Coded Volume Bias: Green for dominant Buy pressure Red for dominant Sell pressure Yellow for Neutral Intensity-based blinking for extreme values (over 70%) Dynamic Data Calculation: Uses volume * (close > open) logic to estimate buy vs sell volumes bar-by-bar, then aggregates by timeframe. ⚙️ User Inputs & Settings Timeframe Selectors (TF1 to TF8): Choose any 8 timeframes you want to monitor volume pressure across. Text & Color Settings: Customize text colors for Buy, Sell, Total volumes Choose Buy/Sell bias colors Enable/disable blinking for visual emphasis on extremes Table Appearance: Set header color, metric background, and text size Table positioning: top-right, bottom-right, etc. Blinking Highlight Toggle: Enable this to visually highlight when Buy/Sell % exceeds 70%—a sign of strong pressure. 📊 Visual Elements Explained The table has 6 rows and 10 columns: Row 0: Headers for Today and TF1 to TF8 Rows 1–3: Absolute values (Buy Vol, Sell Vol, Total Vol) Rows 4–5: Relative percentages (Buy %, Sell %), with dynamic background color First column shows the metric names (e.g., “Buy Vol”) Cells blink using alternate background colors if volume pressure crosses thresholds 💡 How to Use It Effectively Use Buy/Sell % rows to confirm potential breakout trades or identify volume exhaustion zones Look for multi-timeframe confluence: If 5 or more TFs show >70% Buy pressure, buyers are in control Combine with price action (e.g., breakouts, reversals) to increase conviction Suitable for equities, indices, futures, crypto, especially on lower timeframes (1m to 15m) 🏆 What Makes It Unique Table-based MTF Volume Pressure Display: Most indicators only show volume as bars or histograms; this script summarizes and color-codes volume bias across timeframes in a tabular format. Customization-friendly: Full control over colors, themes, and timeframes Blinking Alerts: Rare visual feature to capture user attention during extreme pressure Designed with performance and readability in mind—even for fast-paced scalping environments. 🚨 Alerts / Extras While this script doesn’t include TradingView alert functions directly, the visual blinking serves as a strong real-time alert mechanism. Future versions may include built-in alert conditions for buy/sell bias thresholds. 🔬 Technical Concepts Used Volume Dissection using close > open logic (to estimate buyer vs seller pressure) Simple aggregation of volume over custom timeframes Table plotting using Pine Script table.new, table.cell Dynamic color logic for bias identification Custom blinking logic using na(bar_index % 2 == 0 ? colorA : colorB) ⚠️ Disclaimer This indicator is a tool for analysis, not financial advice. Always backtest and validate strategies before using any indicator for live trading. Past performance is not indicative of future results. Use at your own risk and apply proper risk management. ✍️ Author & Signature Indicator Name: Volume Pressure Author: GSK-VIZAG-AP-INDIA TradingView Username: prowelltraders
Pine Script®指標
由prowelltraders提供