Inizia

Indicatori e strategie

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.
Strategia Pine Script®
di DskyzInvestments
9
Darren - Engulfing + MACD CrossDarren – Engulfing + MACD Cross Overall Behavior Identify an engulfing candle (bullish or bearish). Wait up to windowBars bars for the corresponding MACD crossover (bullish engulfing → MACD cross up; bearish engulfing → MACD cross down). If the crossover occurs within that window, trigger an entry (long or short) and close any opposite open trade. Inputs • macdFast (default 12): length of MACD fast EMA • macdSlow (default 26): length of MACD slow EMA • macdSignal (default 9): length of MACD signal line • windowBars (default 3): maximum bars allowed between an engulfing candle and a MACD crossover Indicators • macdLine and signalLine are calculated using ta.macd(close, macdFast, macdSlow, macdSignal) • macdHist = macdLine – signalLine, plotted as columns (green when ≥ 0, red when < 0) Engulfing Pattern Detection • Bullish engulfing (bullEngulfing) is true when the previous candle is bearish (close < open ), the current candle is bullish (close > open), and the current body fully engulfs the previous body (open < close and close > open ). • Bearish engulfing (bearEngulfing) is the inverse: previous candle bullish, current candle bearish, and current body fully engulfs the prior body. MACD Crossover Detection • macdCrossUp is true when macdLine crosses above signalLine. • macdCrossDown is true when macdLine crosses below signalLine. Timing Logic • barsSinceBull = ta.barssince(bullEngulfing) returns number of bars since the last bullish engulfing. • barsSinceBear = ta.barssince(bearEngulfing) returns number of bars since the last bearish engulfing. • longCondition occurs if a MACD cross up happens within windowBars bars of a bullish engulfing (barsSinceBull ≤ windowBars and macdCrossUp). • shortCondition occurs if a MACD cross down happens within windowBars bars of a bearish engulfing (barsSinceBear ≤ windowBars and macdCrossDown). Chart Markers • “Bull” label below bar whenever bullEngulfing is true. • “Bear” label above bar whenever bearEngulfing is true. • Small “Up” ▲ below bar when macdCrossUp is true. • Small “Down” ▼ above bar when macdCrossDown is true. • Triangle ▲ below bar for Long Entry (longCondition). • Triangle ▼ above bar for Short Entry (shortCondition). Entry & Exit Rules • On longCondition: enter “Long”, and close any existing “Short” position. • On shortCondition: enter “Short”, and close any existing “Long” position.
Strategia Pine Script®
di OEM_redartgnidoc
EMA 12/21 Crossover with ATR-based SL/TPRecommended ATR Lenght: 7 ATR multiplier for stop loss: 1.5 ATR multiplier for take profit: 2 Recalculate- aftter order is filled: Make sure you put this on if using these settings. Using standard OHLC: put on. Theses settings make you 50% win rate with 1.5 profit factor 📈 Ultimate Scalper v2 Strategy Type: Trend-Pullback Scalping Indicators Used: EMA (12/21), MACD Histogram, ADX, ATR Platform: TradingView (Pine Script v5) Author: robinunga16 🎯 Strategy Overview The Ultimate Scalper v2 is a scalping strategy that catches pullbacks within short-term trends using a dynamic combination of 12/21 EMA bands, MACD Histogram crossovers, and ADX for trend confirmation. It uses ATR-based stop-loss and take-profit levels, making it suitable for volatility-sensitive environments. 🧠 Logic Breakdown 🔍 Trend Detection Uses the 12 EMA and 21 EMA to identify the short-term trend: Uptrend: EMA 12 > EMA 21 and ADX > threshold Downtrend: EMA 12 < EMA 21 and ADX > threshold The ADX (default: 25) filters out low-momentum environments. 📉 Pullback Identification Once a trend is detected: A pullback is flagged when the MACD Histogram moves against the trend (below 0 in uptrend, above 0 in downtrend). An entry signal is triggered when the histogram crosses back through zero (indicating momentum is resuming in the trend direction). 🟢 Entry Conditions Long Entry: EMA 12 > EMA 21 ADX > threshold MACD Histogram was below 0 and crosses above 0 Short Entry: EMA 12 < EMA 21 ADX > threshold MACD Histogram was above 0 and crosses below 0 ❌ Exit Logic (ATR-based) The strategy calculates stop-loss and take-profit levels using ATR at the time of entry: Stop-Loss: Entry Price −/+ ATR × Multiplier Take-Profit: Entry Price ± ATR × 2 × Multiplier Default ATR Multiplier: 1.0 ⚙️ Customizable Inputs ADX Threshold: Minimum trend strength for trades (default: 25) ATR Multiplier: Controls SL/TP distance (default: 1.0) 📊 Visuals EMA 12 and EMA 21 band can be added manually for visual reference. Entry and exit signals are plotted via TradingView’s built-in backtesting engine. ⚠️ Disclaimer This is a backtesting strategy, not financial advice. Performance varies across markets and timeframes. Always combine with additional confluence or risk management when going live.
Strategia Pine Script®
di RUmbro16
EMA 12/21 Crossover with ATR-based SL/TP📈 Ultimate Scalper v2 Strategy Type: Trend-Pullback Scalping Indicators Used: EMA (12/21), MACD Histogram, ADX, ATR Platform: TradingView (Pine Script v5) Author: 🎯 Strategy Overview The Ultimate Scalper v2 is a scalping strategy that catches pullbacks within short-term trends using a dynamic combination of 12/21 EMA bands, MACD Histogram crossovers, and ADX for trend confirmation. It uses ATR-based stop-loss and take-profit levels, making it suitable for volatility-sensitive environments. 🧠 Logic Breakdown 🔍 Trend Detection Uses the 12 EMA and 21 EMA to identify the short-term trend: Uptrend: EMA 12 > EMA 21 and ADX > threshold Downtrend: EMA 12 < EMA 21 and ADX > threshold The ADX (default: 25) filters out low-momentum environments. 📉 Pullback Identification Once a trend is detected: A pullback is flagged when the MACD Histogram moves against the trend (below 0 in uptrend, above 0 in downtrend). An entry signal is triggered when the histogram crosses back through zero (indicating momentum is resuming in the trend direction). 🟢 Entry Conditions Long Entry: EMA 12 > EMA 21 ADX > threshold MACD Histogram was below 0 and crosses above 0 Short Entry: EMA 12 < EMA 21 ADX > threshold MACD Histogram was above 0 and crosses below 0 ❌ Exit Logic (ATR-based) The strategy calculates stop-loss and take-profit levels using ATR at the time of entry: Stop-Loss: Entry Price −/+ ATR × Multiplier Take-Profit: Entry Price ± ATR × 2 × Multiplier Default ATR Multiplier: 1.0 ⚙️ Customizable Inputs ADX Threshold: Minimum trend strength for trades (default: 25) ATR Multiplier: Controls SL/TP distance (default: 1.0) 📊 Visuals EMA 12 and EMA 21 band can be added manually for visual reference. Entry and exit signals are plotted via TradingView’s built-in backtesting engine. ⚠️ Disclaimer This is a backtesting strategy, not financial advice. Performance varies across markets and timeframes. Always combine with additional confluence or risk management when going live.
Strategia Pine Script®
di RUmbro16
EU Session Only StrategyThe name of the strategy is the EU session only, but you choose which time is important for you to follow, it can also be the beginning of the US session, a few hours after the news (2 hours after the US open level) or based on the daily open level. 📌 Indicator Description: "EU Session Only Strategy" This TradingView indicator, written in Pine Script version 6, represents a simple yet effective intraday trading strategy focused exclusively on the European trading session. 🎯 Purpose and Use The goal of this strategy is to: Automatically identify the European session open price for the current trading day. Trade only during a defined intraday time window (e.g., between 08:00 and 18:00 UTC). Enter a trade only if the price moves a certain distance (in pips) away from the EU open level. Limit the number of trades per day to avoid overtrading. Automatically close all open positions at the end of the day to minimize overnight risk. ⚙️ How It Works 🔹 1. EU Open Level When the European session opens (e.g., 09:00 UTC), the strategy records the opening price at that moment (eu_open_price). This level is displayed as a red horizontal line on the chart. 🔹 2. Entry Conditions The strategy checks if the current price: Is above the EU open level by at least a defined number of pips → Buy signal. Is below the EU open level by at least a defined number of pips → Sell signal. Trading is allowed only within the specified time range (e.g., 08:00 to 18:00 UTC). A maximum number of trades per day is enforced (e.g., 2 trades max). 🔹 3. Exit Conditions If an opposite signal appears during the day, the strategy automatically closes the current position. At the start of each new day, all open positions are closed, regardless of direction or profit. ✅ Advantages A clear and efficient system based on price reaction around a key daily level. Suitable for automated backtesting and optimization on TradingView. Reduces risk with daily trade limits and end-of-day auto-closing. Ideal for forex pairs that show volatility during the European session (e.g.,GOLD, EUR/USD, GBP/USD, etc.).
Strategia Pine Script®
di Aleksin_Aleksandar
Zero Lag Trend Strategy (MTF) [AlgoAlpha]# Zero Lag Trend Strategy (MTF) - Complete Guide ## Overview The Zero Lag Trend Strategy is a sophisticated trading system that combines zero-lag exponential moving averages with volatility bands and EMA-based entry/exit filtering. This strategy is designed to capture trending movements while minimizing false signals through multiple confirmation layers. ## Core Components ### 1. Zero Lag EMA (ZLEMA) - **Purpose**: Primary trend identification with reduced lag - **Calculation**: Uses a modified EMA that compensates for inherent lag by incorporating price momentum - **Formula**: `EMA(price + (price - price ), length)` where lag = (length-1)/2 - **Default Length**: 70 periods (adjustable) ### 2. Volatility Bands - **Purpose**: Define trend strength and entry/exit zones - **Calculation**: Based on ATR (Average True Range) multiplied by a user-defined multiplier - **Upper Band**: ZLEMA + (ATR * multiplier) - **Lower Band**: ZLEMA - (ATR * multiplier) - **Default Multiplier**: 1.2 (adjustable) ### 3. EMA Filter/Exit System - **Purpose**: Entry filtering and exit signal generation - **Default Length**: 9 periods (fully customizable) - **Color**: Blue line on chart - **Function**: Prevents counter-trend entries and provides clean exit signals ## Entry Logic ### Long Entry Conditions 1. **Primary Signal**: Price crosses above the upper volatility band (strong bullish momentum) 2. **Additional Entries**: Price crosses above ZLEMA while already in an uptrend (if enabled) 3. **EMA Filter**: Price must be above the EMA filter line 4. **Confirmation**: All conditions must align simultaneously ### Short Entry Conditions 1. **Primary Signal**: Price crosses below the lower volatility band (strong bearish momentum) 2. **Additional Entries**: Price crosses below ZLEMA while already in a downtrend (if enabled) 3. **EMA Filter**: Price must be below the EMA filter line 4. **Confirmation**: All conditions must align simultaneously ## Exit Logic **Simple and Clean**: Positions are closed when price crosses the EMA filter line in the opposite direction: - **Long Exit**: Price crosses below the EMA filter - **Short Exit**: Price crosses above the EMA filter ## Multi-Timeframe Analysis The strategy includes a real-time table showing trend direction across 5 different timeframes: - Default timeframes: 5m, 15m, 1h, 4h, 1D (all customizable) - Color-coded signals: Green for bullish, Red for bearish - Helps confirm overall market direction before taking trades ## Key Parameters ### Main Calculations - **Length (70)**: Zero-lag EMA calculation period - **Band Multiplier (1.2)**: Controls volatility band width ### Strategy Settings - **Enable Additional Trend Entries**: Allow multiple entries during strong trends - **EMA Exit Length (9)**: Period for the entry filter and exit EMA ### Timeframes - **5 customizable timeframes** for multi-timeframe trend analysis ### Appearance - **Bullish Color**: Default green (#00ffbb) - **Bearish Color**: Default red (#ff1100) ## Visual Elements ### Chart Display - **ZLEMA Line**: Color-coded trend line (green/red based on trend direction) - **Volatility Bands**: Dynamic upper/lower bands that appear based on trend - **EMA Filter**: Blue line for entry filtering and exits - **Entry Signals**: - Large arrows (▲▼) for primary trend signals - Small arrows for additional trend entries - Tiny letters (L/S) for actual strategy entries ### Information Table - **Position**: Top-right corner - **Content**: Real-time trend status across all configured timeframes - **Updates**: Continuously updated with current market conditions ## Strategy Advantages ### Trend Following Excellence - Captures strong trending moves with reduced whipsaws - Multiple confirmation layers prevent false entries - Dynamic bands adapt to market volatility ### Risk Management - Clear, objective exit rules - EMA filter prevents counter-trend trades - Multi-timeframe confirmation reduces bad trades ### Flexibility - Fully customizable parameters - Works across different timeframes and instruments - Optional additional trend entries for maximum profit potential ### Visual Clarity - Clean, professional chart display - Easy-to-read signals and trends - Comprehensive multi-timeframe overview ## Best Practices ### Parameter Optimization - **Length**: Higher values (50-100) for longer-term trends, lower values (20-50) for shorter-term - **Band Multiplier**: Higher values (1.5-2.0) reduce signals but increase quality - **EMA Length**: Shorter periods (5-13) for quick exits, longer periods (20-50) for trend riding ### Market Conditions - **Trending Markets**: Enable additional trend entries for maximum profit - **Choppy Markets**: Use higher band multiplier and longer EMA for fewer, higher-quality signals - **Different Timeframes**: Adjust all parameters proportionally when changing chart timeframes ### Multi-Timeframe Usage - Align trades with higher timeframe trends - Use lower timeframes for precise entry timing - Avoid trades when timeframes show conflicting signals ## Risk Considerations - Like all trend-following strategies, may struggle in ranging/choppy markets - EMA exit system prioritizes trend continuation over quick profit-taking - Multiple timeframe analysis requires careful interpretation - Backtesting recommended before live trading with any parameter changes ## Conclusion The Zero Lag Trend Strategy provides a comprehensive approach to trend trading with built-in risk management and multi-timeframe analysis. Its combination of advanced technical indicators, clear entry/exit rules, and customizable parameters makes it suitable for both novice and experienced traders seeking to capture trending market movements.
Strategia Pine Script®
di M4ndoo
System 0530 - Stoch RSI Strategy v13 SL-Priority TP-ReversalStrategy Overview: System 0530 - Stochastic RSI Multi-Timeframe This TradingView Pine Script outlines a strategy primarily based on the Stochastic RSI (Stoch RSI) indicator, employing a multi-timeframe approach for signal generation and confirmation. It is designed to operate on a 5-minute chart, referencing 15-minute data for higher-level context. Core Mechanics: Primary Indicator: Stochastic RSI, used to identify overbought/oversold conditions and potential momentum shifts. Timeframes: 5-minute chart: For initial signal triggers and primary execution. 15-minute chart: For signal confirmation and certain take-profit conditions. Entry Logic: Bullish Market Bias Adjustment: Reflecting an overall bullish market trend, this strategy is intended to be applied with more tolerance or lower requirements for triggering long positions compared to short positions. This can be achieved by adjusting the input parameters accordingly (e.g., setting a higher stoch_5min_k_long_trigger threshold, allowing longs to trigger when less oversold, or a higher stoch_15min_long_entry_level, requiring less deep confirmation for longs). 5-Minute Initial Trigger: Long: 5-minute Stoch RSI K-line crosses above its D-line, AND the K-value at the time of the cross is below a specified stoch_5min_k_long_trigger level. Short: 5-minute Stoch RSI K-line crosses below its D-line, AND the K-value at the time of the cross is above a specified stoch_5min_k_short_trigger level. 15-Minute Confirmation: After a 5-minute trigger, the strategy waits for a configurable number of 5-minute bars (wait_window_5min_bars) for confirmation from the 15-minute timeframe. Long Confirmation: 15-minute Stoch RSI K-line must be strictly greater than its D-line, AND the 15-minute K-value must be below stoch_15min_long_entry_level. Short Confirmation: 15-minute Stoch RSI K-line must be strictly less than its D-line, AND the 15-minute K-value must be above stoch_15min_short_entry_level. Position Lock: No new entry signals are generated if the strategy already holds an open position. Duplicate Signal Filter: A cooldown period, defined by min_bars_between_signals, must pass before another signal in the same direction can be considered. Exit Logic: Stop-Loss (SL): The SL is set based on the low (for longs) or high (for shorts) of the 5-minute bar on which the trade was entered. The position is closed if a subsequent 5-minute bar's closing price moves beyond this SL level. SL checks are prioritized over Take-Profit checks. Take-Profit (TP) - Two-Stage Mechanism: TP1 (Closes 50% of the position): Priority A (Extreme K Levels): If the 5-minute Stoch K OR 15-minute Stoch K value exceeds extreme_long_tp_level (for longs) or drops below extreme_short_tp_level (for shorts). Priority B (Conditional 5-min Cross + 15-min K-Reversal): If Extreme K conditions are not met, TP1 is triggered if: A 5-minute Stoch RSI K/D crossover occurs (K crosses below D for longs; K crosses above D for shorts - using strict ta.crossunder/ta.crossover). AND this 5-minute crossover is confirmed by a 15-minute Stoch K-value "reversal" (current 15m K < previous 15m K for longs; current 15m K > previous 15m K for shorts). TP2 (Closes remaining 50% of the position): This stage is active only after TP1 has been taken. If the 5-minute Stoch K OR 15-minute Stoch K value reaches the same extreme_long_tp_level or extreme_short_tp_level again, a waiting period begins, defined by tp2_extreme_k_wait_bars (number of 5-minute bars). If the extreme K condition persists after this waiting period, TP2 is executed. If the extreme K condition disappears during the waiting period, the TP2 attempt for that instance is cancelled. If tp2_extreme_k_wait_bars is set to 0, TP2 will trigger immediately upon the extreme K condition being met after TP1. Note on Fine-Tuning (as per user context): This strategy has been specifically fine-tuned for SPY. As with any trading system, its performance can vary across different instruments and market conditions. The user notes that to potentially maximize profits, especially in trending scenarios where the current "Extreme K" based TP2 might exit prematurely, it is advisable to explore and integrate other indicators or alternative take-profit methodologies. Dynamic approaches like ATR (Average True Range) trailing stops or trend-following exit signals could be considered for managing the second portion of the position.
Strategia Pine Script®
di Archertoria
DB - Range Filter heikenashi Strategy DB - Range Filter Heikenashi Strategy Smart Filtering Meets Heiken-Ashi Precision for Adaptive Trend Breakouts This is not your average range filter strategy. Built from the ground up with adaptive signal logic and hybrid candle interpretation, this script merges range-based volatility filtering with Heiken-Ashi smoothing to isolate meaningful breakouts—while filtering out noise with surgical precision. 🔍 Key Innovations: • Dynamic Range Filtering Engine: Combines smoothed average range with directional bias to create high-confidence entries. • Candle Type Toggle: Choose between standard candles or Heiken-Ashi to shape your signals to your trading style. • Dual-Layer Trend Confirmation: Upward and downward movement counters ensure trend commitment before triggering entries. • Time-Filtered Backtesting: Easily isolate strategy performance within precise historical windows. • Optional Smart Stops: Add stop loss & take profit rules without changing the core logic—perfect for risk-managed deployment. 📈 Visual & Practical Features: • Multi-color bar analysis to identify strength, weakness, and transition zones. • Upper and lower dynamic bands for visualizing profit targets and range boundaries. • Buy/Sell signal labels with direction-aware logic to avoid choppy conditions. • Ideal for high-volatility assets (e.g., BTC) on short timeframes, but fully tunable for any market. Built for traders who value clarity over chaos, this strategy aims to reduce false signals and offer a cleaner execution framework for trend followers and breakout scalpers alike. > Make volatility your ally, not your enemy.
Strategia Pine Script®
di DefiBanked
1
GStrategy XRP 4hRSI + Smart Money Trading Strategy This strategy combines RSI (Relative Strength Index) with Smart Money detection to identify high-probability reversal trades in trending markets. It uses strict entry/exit rules with a 10% hard stop-loss to manage risk. Strategy Logic 1. Entry Conditions Long Entry (Buy): RSI < 30 (Oversold condition) Smart Money Confirmation: Bullish candle (close > open) Volume > 35-period SMA (unusual buying pressure) Price hits a 5-bar low (potential reversal level) Short Entry (Sell): RSI > 70 (Overbought condition) Smart Money Confirmation: Bearish candle (close < open) Volume > 20-period SMA (unusual selling pressure) Price hits a 5-bar high (potential rejection level) 2. Exit Conditions Long Exit: RSI ≥ 70 (Take profit at overbought) Short Exit: RSI ≤ 40 (Take profit at mid-level) Stop-Loss: Hard 10% stop on all trades 3. Position Management No overlapping trades (only 1 position at a time). Stop-loss visualized on the chart (red line). Key Features ✅ RSI Filter: Avoids false reversals by requiring extreme RSI levels. ✅ Smart Money Detection: Confirms institutional activity via volume + price action. ✅ Asymmetric Exits: Longs exit at RSI 70 (full overbought). Shorts exit earlier at RSI 40 (conservative profit-taking). ✅ Strict Risk Control: 10% stop-loss prevents large drawdowns. Indicators Used RSI (14-period) Volume SMA (20 for shorts, 35 for longs) 5-bar High/Low for price extremes.
Strategia Pine Script®
di Graali
Kaufman Trend Strategy# ✅ Kaufman Trend Strategy – Full Description (Script Publishing Version) **Kaufman Trend Strategy** is a dynamic trend-following strategy based on Kaufman Filter theory. It detects real-time trend momentum, reduces noise, and aims to enhance entry accuracy while optimizing risk. ⚠️ _For educational and research purposes only. Past performance does not guarantee future results._ --- ## 🎯 Strategy Objective - Smooth price noise using Kaufman Filter smoothing - Detect the strength and direction of trends with a normalized oscillator - Manage profits using multi-stage take-profits and adaptive ATR stop-loss logic --- ## ✨ Key Features - **Kaufman Filter Trend Detection** Extracts directional signal using a state space model. - **Multi-Stage Profit-Taking** Automatically takes partial profits based on color changes and zero-cross events. - **ATR-Based Volatility Stops** Stops adjust based on swing highs/lows and current market volatility. --- ## 📊 Entry & Exit Logic **Long Entry** - `trend_strength ≥ 60` - Green trend signal - Price above the Kaufman average **Short Entry** - `trend_strength ≤ -60` - Red trend signal - Price below the Kaufman average **Exit (Long/Short)** - Blue trend color → TP1 (50%) - Oscillator crosses 0 → TP2 (25%) - Trend weakens → Final exit (25%) - ATR + swing-based stop loss --- ## 💰 Risk Management - Initial capital: `$3,000` - Order size: `$100` per trade (realistic, low-risk sizing) - Commission: `0.002%` - Slippage: `2 ticks` - Pyramiding: `1` max position - Estimated risk/trade: `~0.1–0.5%` of equity > ⚠️ _No trade risks more than 5% of equity. This strategy follows TradingView script publishing rules._ --- ## ⚙️ Default Parameters - **1st Take Profit**: 50% - **2nd Take Profit**: 25% - **Final Exit**: 25% - **ATR Period**: 14 - **Swing Lookback**: 10 - **Entry Threshold**: ±60 - **Exit Threshold**: ±40 --- ## 📅 Backtest Summary - **Symbol**: USD/JPY - **Timeframe**: 1H - **Date Range**: Jan 3, 2022 – Jun 4, 2025 - **Trades**: 924 - **Win Rate**: 41.67% - **Profit Factor**: 1.108 - **Net Profit**: +$1,659.29 (+54.56%) - **Max Drawdown**: -$1,419.73 (-31.87%) --- ## ✅ Summary This strategy uses Kaufman filtering to detect market direction with reduced lag and increased smoothness. It’s built with visual clarity and strong trade management, making it practical for both beginners and advanced users. --- ## 📌 Disclaimer This script is for educational and informational purposes only and should not be considered financial advice. Use with proper risk controls and always test in a demo environment before live trading.
Strategia Pine Script®
di PakunFX