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Momentum ChecklistMomentum Checklist - Visual Trading Dashboard A clean, easy-to-read dashboard that displays key momentum indicators in one convenient table. This indicator helps traders quickly determine the directional bias of price action by combining ADX, Directional Movement Index (DMI), and Money Flow Index (MFI). What It Shows: ADX (Average Directional Index): Measures trend strength. Green checkmark appears when ADX ≥ 20, indicating a strong trending market DI+ (Positive Directional Indicator): Tracks upward price movement DI- (Negative Directional Indicator): Tracks downward price movement MFI (Money Flow Index): Volume-weighted momentum indicator. When > 50 indicates bullish money flow Bias: Automatically calculates directional bias: LONG: When DI+ > 25 and DI- < 20 SHORT: When DI- > 25 and DI+ < 20 NEUTRAL: When conditions are mixed Trading Strategy: This indicator helps determine the bias of price movement in a certain direction. When coupled with Bollinger Bands, it becomes a very powerful combination to catch those big explosive moves up or down. The momentum confirmation from this checklist combined with Bollinger Band squeezes or breakouts can significantly improve entry timing. Recommended Usage: Timeframes: 5-minute to 15-minute charts for optimal performance Best Assets: US30, XAUUSD (Gold), BTCUSD, and most major indices Works exceptionally well on volatile instruments with strong directional moves Features: Color-coded cells for instant visual confirmation Customizable position (Top Right, Top Left, Bottom Right, Bottom Left) Adjustable text size (Tiny, Small, Normal) Configurable ADX, DMI, and MFI period settings Perfect for day traders and scalpers looking for quick momentum confirmation before entering trades! Feel free to adjust any part of this description to match your style! 🎯
Pine Script®指標
由krishnaperi95提供
CRR EMAS HH LLCRR HH LL EMAs — Market Structure & EMA Levels (Educational) CRR HH LL EMAs is an educational chart overlay designed to help traders visualize market structure and key EMA price levels in a clean and objective way. This indicator combines two core concepts: Market Structure Higher Highs (HH) Lower Lows (LL) Recent swing highs and lows as visual references EMA-Based Price Levels EMA 20 EMA 50 EMA 100 EMA 200 Each EMA is displayed as a dynamic price level to help identify trend alignment, support, and resistance zones. The script is intended to improve price context awareness, not decision automation. What this script is USED FOR This tool helps traders to: Visually identify bullish and bearish structure Understand where price is trading relative to key EMAs Spot potential support and resistance zones Analyze trend strength and pullbacks Improve discretionary market reading It is especially useful for: Market structure analysis Trend-following context Educational chart studies Multi-timeframe observation What this script IS NOT This script is NOT a trading strategy. It does NOT generate buy or sell signals. It does NOT predict future price movements. It does NOT provide financial or investment advice. It does NOT guarantee profitability. All drawings and levels are visual references only. Important Notes This indicator is non-repainting All levels are based on confirmed price data The script is designed for manual and discretionary analysis Use it as a context tool, not as a signal generator
Pine Script®指標
由rivero8894提供
DafePatternsLibDafePatternLib: The Adaptive Pattern Recognition Engine DafePatternLib is not a static pattern library. It is an adaptive recognition engine. It doesn't just find patterns; it tracks, weights, and filters them based on their performance in the live market. █ CHAPTER 1: THE PHILOSOPHY — BEYOND STATIC RULES, INTO DYNAMIC LEARNING For decades, chart pattern analysis has been trapped in a rigid paradigm. An indicator coded to find a "Bullish Engulfing" will signal that pattern with the same confidence every time, regardless of whether it has been failing consistently for weeks. It has no memory and no ability to adapt. DafePatternLib was created to change this. It is built on a performance-based reinforcement framework. This library is not just a collection of detection functions; it is a self-weighting logic system. It tracks outcomes. It remembers what works. Over time, it amplifies the signals of high-probability patterns and filters out those that are failing in the current market regime. This is not a black box. It is an open-source, observable learning system. It strengthens and weakens its own internal weights based on positive and negative feedback, evolving into a tool adapted to the specific asset you are trading. █ CHAPTER 2: CORE INNOVATIONS This library introduces several advanced concepts for algorithmic analysis: Reinforcement Learning Engine: The core of the system. Every high-confidence pattern is logged into "Active Memory." The library tracks the outcome against projected stops and targets. If successful, the weight for that pattern category is strengthened. If it fails, the weight is reduced. This creates a continuous feedback loop. Adaptation Rate (Plasticity): You have direct control over the engine's "plasticity"—its ability to learn. High plasticity allows fast adaptation to new conditions; lower plasticity creates a stable, long-term model. Dynamic Volatility Scaling (DVS): Markets breathe. DVS is a proprietary function that calculates a real-time volatility scalar by comparing current ATR to historical averages. This scalar automatically adjusts lookback periods and sensitivities. In high volatility, engines look for larger structures; in low volatility, they tighten focus. Smart Confidence Score: The output is not a simple "true/false." Every pattern includes two scores: • Raw Confidence: Static confidence based on the pattern's textbook definition. • Net Confidence: The adaptive score (Raw Confidence × Learned Bias). A performing pattern sees its confidence boosted; a failing pattern gets penalized. Intelligent Filtering: If the learned bias for a category (e.g., "Candle") drops below a threshold (e.g., 0.8), the library automatically filters those signals, treating them as low-probability noise until performance improves. █ CHAPTER 3: ANATOMY OF THE LOGIC — HOW IT THINKS The LogicWeights (The Core) The central data structure holding the system's "memory." It stores a floating-point weight or "bias" for each of the five major categories (Candle, Harmonic, Structure, Geometry, VSA). Initialized at 1.0 (neutral). update_core() (The Learning Process) The heart of the reinforcement loop. When a pattern resolves (win/loss), this function applies a positive or negative adjustment to the corresponding category weight. Weights are constrained between 0.5 (distrust) and 2.0 (trust). manage_memory() (Short-Term Memory) Maintains an array of active signals. On every bar, it checks if targets or stops have been hit. Resolved patterns trigger update_core(). Unresolved patterns eventually expire, applying a minor penalty to discourage stagnation. scan_pattern_universe() (Master Controller) The main exported function. On every bar, it: Calculates the Dynamic Volatility Scalar (DVS). Runs all pattern detection engines (VSA, Geometry, Candles, etc.) adapted to DVS. Identifies the single best pattern based on raw confidence. Passes it to memory for tracking. Applies the learned bias to calculate Net Confidence. Returns the final, adaptively weighted PatternResult. █ CHAPTER 4: DEVELOPER INTEGRATION GUIDE Designed for simplicity and power. 1. Import the Library: import DskyzInvestments/DafePatternLib/1 as pattern 2. Call the Scanner: The library handles DVS, scanning, memory, and learning internally. pattern.PatternResult signal = pattern.scan_pattern_universe() 3. Use the Result: if signal.is_active label.new(bar_index, signal.entry, "Conf: " + str.tostring(signal.net_confidence, "#") + "%") With just these lines, you integrate a self-weighting, multi-pattern recognition engine. █ INPUTS TEMPLATE (COPY INTO YOUR SCRIPT) // ═══════════════════════════════════════════════════════════ // INPUT GROUPS // ═══════════════════════════════════════════════════════════ string G_AI_ENGINE = "══════════ 🧠 LOGIC ENGINE ══════════" string G_AI_PATTERNS = "══════════ 🔬 PATTERN SELECTION ══════════" string G_AI_VISUALS = "══════════ 🎨 VISUALS & SIGNALS ══════════" string G_AI_DASH = "══════════ 📋 LOGIC STATE DASHBOARD ══════════" string G_AI_ALERTS = "══════════ 🔔 ALERTS ══════════" // ═══════════════════════════════════════════════════════════ // LOGIC ENGINE CONTROLS // ═══════════════════════════════════════════════════════════ bool i_enable_ai = input.bool(true, "✨ Enable Adaptive Engine", group = G_AI_ENGINE, tooltip="Master switch to enable the pattern recognition and learning system.") float i_plasticity = input.float(0.03, "Adaptation Rate", minval=0.01, maxval=0.1, step=0.01, group = G_AI_ENGINE, tooltip="Controls adaptation speed. • Low (0.01-0.02): Stable learning. • Medium (0.03-0.05): Balanced. • High (0.06+): Fast adaptation.") float i_filter_threshold = input.float(0.8, "Adaptive Filter Threshold", minval=0.5, maxval=1.0, step=0.05, group = G_AI_ENGINE, tooltip="Hide signals from categories with a learned bias below this value.") // ═══════════════════════════════════════════════════════════ // PATTERN SELECTION // ═══════════════════════════════════════════════════════════ bool i_scan_candles = input.bool(true, "🕯️ Candlestick Patterns", group = G_AI_PATTERNS, inline="row1") bool i_scan_vsa = input.bool(true, "📦 Volume Spread Analysis", group = G_AI_PATTERNS, inline="row1") bool i_scan_geometry = input.bool(true, "📐 Geometric Patterns", group = G_AI_PATTERNS, inline="row2") bool i_scan_structure = input.bool(true, "📈 Market Structure (SMC)", group = G_AI_PATTERNS, inline="row2") bool i_scan_harmonic = input.bool(false, "🦋 Harmonic Setups", group = G_AI_PATTERNS, inline="row3") // ═══════════════════════════════════════════════════════════ // VISUALS & DASHBOARD // ═══════════════════════════════════════════════════════════ bool i_show_signals = input.bool(true, "Show Signals", group = G_AI_VISUALS) bool i_show_dashboard = input.bool(true, "Show Logic Dashboard", group = G_AI_DASH) █ DEVELOPMENT PHILOSOPHY DafePatternLib was born from a vision to bring dynamic logic to technical analysis. We believe an indicator should not be a static tool, but an intelligent partner that adapts. This library is an open-source framework empowering developers to build the next generation of smart indicators. █ DISCLAIMER • LIBRARY FOR DEVELOPERS: This script produces no visual output on its own. It is an engine for developers. • ADAPTIVE, NOT PREDICTIVE: Reinforcement learning optimizes based on recent history. It is a statistical edge, not a crystal ball. • RISK WARNING: Patterns and confidence scores are for informational purposes. "The key to trading success is emotional discipline. If intelligence were the key, there would be a lot more people making money trading." — Victor Sperandeo Create with DAFE.
Pine Script®腳本庫
由DskyzInvestments提供
WickPressureLibWickPressureLib: The Regime Dynamics Engine DESCRIPTION: WickPressureLib/b] is not a standard candlestick pattern library. It is an advanced analytical engine designed to deconstruct the internal dynamics of price action. It provides a definitive toolkit for analyzing candle microstructure and quantifying order flow pressure through statistical modeling. █ CHAPTER 1: THE PHILOSOPHY — BEYOND PATTERNS, INTO DYNAMICS A candlestick wick represents a specific market event: a rejection of price. Traditional analysis often labels these simply as "bullish" or "bearish." This library aims to go deeper by treating each candle as a dataset of opposing forces. The WickPressureLib translates static price action into dynamic metrics. It deconstructs the candle into core components and subjects them to multi-layered analysis. It calculates Kinetic Force , estimates institutional Delta , tracks the Siege Decay of key levels, and uses Thompson Sampling (a Bayesian probability algorithm) to assess the statistical weight of each formation. This library does not just identify patterns; it quantifies the forces that create them. It is designed for developers who need quantitative, data-driven metrics rather than subjective interpretation. █ CHAPTER 2: THE ANALYTICAL PIPELINE — SIX LAYERS OF LOGIC The engine's capabilities come from a six-stage processing pipeline. Each layer builds upon the last to create a comprehensive data object. LAYER 1 — DELTA ESTIMATION: Uses a proprietary model to approximate order flow (Delta) within a single candle based on the relationship between wicks, body, and total range. LAYER 2 — SIEGE ANALYSIS: A concept for measuring structural integrity. Every time a price level is tested by a wick, its "Siege Decay" score is updated. Repeated tests without a breakout result in a decayed score, indicating weakening support/resistance. LAYER 3 — MAGNETISM ENGINE: Calculates the probability of a wick being "filled" (mean reversion) based on trend strength and volume profile. Distinguishes between rejection wicks and exhaustion wicks. LAYER 4 — REGIME DETECTION: Context-aware analysis using statistical tools— Shannon Entropy (disorder), DFA (trend vs. mean-reversion), and Hurst Exponent (persistence)—to classify the market state (e.g., "Bull Trend," "Bear Range," "Choppy"). LAYER 5 — ADAPTIVE LEARNING (THOMPSON SAMPLING): Uses a Bayesian Multi-Armed Bandit algorithm to track performance. It maintains a set of "Agents," each tracking a different wick pattern type. Based on historical outcomes, the system updates the probability score for each pattern in real-time. LAYER 6 — CONTEXTUAL ROUTING: The final layer of logic. The engine analyzes the wick, determines its pattern type, and routes it to the appropriate Agent for probability assessment, weighted by the current market regime. █ CHAPTER 3: CORE FUNCTIONS analyze_wick() — The Master Analyzer The primary function. Accepts a bar index and returns a WickAnalysis object containing over 15 distinct metrics: • Anomaly Score: Z-Score indicating how statistically rare the wick's size is. • Kinetic Force: Metric combining range and relative volume to quantify impact. • Estimated Delta: Approximation of net buying/selling pressure. • Siege Decay: Structural integrity of the tested level. • Magnet Score: Probability of the wick being filled. • Win Probability: Adaptive success rate based on the Thompson Sampling engine. scan_clusters() — Liquidity Zone Detection Scans recent price history to identify "Pressure Clusters"—zones where multiple high-pressure wicks have overlapped. Useful for finding high-probability supply and demand zones. detect_regime() — Context Engine Uses statistical methods to determine the market's current personality (Trending, Ranging, or Volatile). This output allows the analysis to adapt dynamically to changing conditions. █ CHAPTER 4: DEVELOPER INTEGRATION GUIDE This library is a low-level engine for building sophisticated indicators. 1. Import the Library: import DskyzInvestments/DafeWickLib/1 as wpk 2. Initialize the Agents: var agents = wpk.create_learning_agents() 3. Analyze the Market: regime = wpk.detect_regime(100) wick_data = wpk.analyze_wick(0, regime, agents) prob = wpk.get_probability(wick_data, regime) 4. Update Learning (Feedback Loop): agent_id = wpk.get_agent_by_pattern(wick_data) agents := wpk.update_learning_agent(agents, agent_id, 1.0) // +1 win, -1 loss █ CHAPTER 5: THE DEVELOPER'S FRAMEWORK — INTEGRATION GUIDE This library serves as a professional integration framework. This guide provides instructions and templates required to connect the DAFE components into a unified custom Pine Script indicator. PART I: THE INPUTS TEMPLATE (CONTROL PANEL) To provide users full control over the system, include the input templates from all connected libraries. This section details the bridge-specific controls. // ╔═════════════════════════════════════════════════════════╗ // ║ BRIDGE INPUTS TEMPLATE (COPY INTO YOUR SCRIPT) ║ // ╚═════════════════════════════════════════════════════════╝ // INPUT GROUPS string G_BRIDGE_MAIN = "════════════ 🌉 BRIDGE CONFIG ════════════" string G_BRIDGE_EXT = "════════════ 🌐 EXTERNAL DATA ════════════" // BRIDGE MAIN CONFIG float i_bridge_min_conf = input.float(0.55, "Min Confidence to Trade", minval=0.4, maxval=0.8, step=0.01, group=G_BRIDGE_MAIN, tooltip="Minimum blended confidence required for a trade signal.") int i_bridge_warmup = input.int(100, "System Warmup Bars", minval=50, maxval=500, group=G_BRIDGE_MAIN, tooltip="Bars required for data gathering before signals begin.") // EXTERNAL DATA SOCKETS bool i_ext_enable = input.bool(true, "🌐 Enable External Data Sockets", group=G_BRIDGE_EXT, tooltip="Enables analysis of external market data (e.g., VIX, DXY).") // Example for one external socket string i_ext1_name = input.string("VIX", "Socket 1: Name", group=G_BRIDGE_EXT, inline="ext1") string i_ext1_sym = input.symbol("TVC:VIX", "Symbol", group=G_BRIDGE_EXT, inline="ext1") string i_ext1_type = input.string("volatility", "Data Type", options= , group=G_BRIDGE_EXT, inline="ext1") float i_ext1_weight = input.float(1.0, "Weight", minval=0.1, maxval=2.0, step=0.1, group=G_BRIDGE_EXT, inline="ext1") PART II: IMPLEMENTATION LOGIC (THE CORE LOOP) This boilerplate code demonstrates the complete, unified pipeline structure. // ╔════════════════════════════════════════════════════════╗ // ║ USAGE EXAMPLE (ADAPT TO YOUR SCRIPT) ║ // ╚════════════════════════════════════════════════════════╝ // 1. INITIALIZE ENGINES (First bar only) var rl.RLAgent agent = rl.init(...) var spa.SPAEngine spa_engine = spa.init(...) var bridge.BridgeState bridge_state = bridge.init_bridge(i_spa_num_arms, i_rl_num_actions, i_bridge_min_conf, i_bridge_warmup) // 2. CONNECT SOCKETS (First bar only) if barstate.isfirst // Connect internal sockets agent := rl.connect_socket(agent, "rsi", ...) // Register external sockets if i_ext_enable ext_socket_1 = bridge.create_ext_socket(i_ext1_name, i_ext1_sym, i_ext1_type, i_ext1_weight) bridge_state := bridge.register_ext_socket(bridge_state, ext_socket_1) // 3. MAIN LOOP (Every bar) // --- A. UPDATE EXTERNAL DATA --- if i_ext_enable = request.security(i_ext1_sym, timeframe.period, ) bridge_state := bridge.update_ext_by_name(bridge_state, i_ext1_name, ext1_c, ext1_h, ext1_l) bridge_state := bridge.aggregate_ext_sockets(bridge_state) // --- B. RL/ML PROPOSES --- rl.RLState ml_state = rl.build_state(agent) = rl.select_action(agent, ml_state) agent := updated_agent // --- C. BRIDGE TRANSLATES --- array arm_signals = bridge.generate_arm_signals(ml_action.action, ml_action.confidence, i_spa_num_arms, i_rl_num_actions, 0) // --- D. SPA DISPOSES --- spa_engine := spa.feed_signals(spa_engine, arm_signals, close) = spa.select(spa_engine) spa_engine := updated_spa string arm_name = spa.get_name(spa_engine, selected_arm) // --- E. RECONCILE REGIME & COMPUTE RISK --- bridge_state := bridge.reconcile_regime(bridge_state, ml_regime_id, ml_regime_name, ml_conf, spa_regime_id, spa_conf, ...) float risk = bridge.compute_risk(bridge_state, ml_action.confidence, spa_conf, ...) // --- F. MAKE FINAL DECISION --- bridge_state := bridge.make_decision(bridge_state, ml_action.action, ml_action.confidence, selected_arm, arm_name, final_spa_signal, spa_conf, risk, 0.25) bridge.UnifiedDecision final_decision = bridge_state.decision // --- G. EXECUTE --- if final_decision.should_trade // Plot signals, manage positions based on final_decision.direction // --- H. LEARN (FEEDBACK LOOP) --- if (trade_is_closed) bridge_state := bridge.compute_reward(bridge_state, selected_arm, ...) agent := rl.learn(agent, ..., bridge_state.reward.shaped_reward, ...) // --- I. PERFORMANCE & DIAGNOSTICS --- bridge_state := bridge.update_performance(bridge_state, actual_market_direction) if barstate.islast label.new(bar_index, high, bridge.bridge_diagnostics(bridge_state), textalign=text.align_left) █ DEVELOPMENT PHILOSOPHY DafeMLSPABridge represents a hierarchical design philosophy. We believe robust systems rely not on a single algorithm, but on the intelligent integration of specialized subsystems. A complete trading logic requires tactical precision (ML), strategic selection (SPA), and environmental awareness (External Sockets). This library provides the infrastructure for these components to communicate and coordinate. █ DISCLAIMER & IMPORTANT NOTES • LIBRARY FOR DEVELOPERS: This script is an integration tool and produces no output on its own. It requires implementation of DafeRLMLLib and DafeSPALib. • COMPUTATION: Full bridged systems are computationally intensive. • RISK: All automated decisions are based on statistical probabilities from historical data. They do not predict future market movements with certainty. "The whole is greater than the sum of its parts." — Aristotle Create with DAFE.
Pine Script®腳本庫
由DskyzInvestments提供
Borna StructureBorna Structure Borna Structure is a clean market structure indicator that plots key swing levels on the chart and marks Break of Structure (BOS) and Change of Character (CHoCH) events based on close-confirmed breaks. The indicator uses horizontal levels to represent structural highs and lows and prints BOS or CHoCH only when price breaks and closes beyond a valid level, avoiding repeated signals on continuation candles. This makes it suitable for manual analysis and backtesting, especially on intraday timeframes. Borna Structure does not provide buy or sell signals and is intended to be used as a market structure reference tool, commonly combined with session levels or price action confirmation.
Pine Script®指標
由Borna_trading提供
Adaptive BSP v6The Adaptive Buying and Selling Pressure (ABSP) indicator is the "engine" of your system. Unlike standard volume oscillators that just look at total quantity, this logic dissects the internal price action of every candle to determine who is actually in control. 1. The Core Calculation (Intra-Bar Delta) Instead of just looking at the candle color, the ABSP logic calculates pressure based on where the price closes relative to the high and low of the bar: • Buying Pressure (BP): Measured as the distance from the candle's Low to its Close. BP = Close - min(Low, Close) • Selling Pressure (SP): Measured as the distance from the candle's High to its Close. SP = max(High, Close) - Close 2. The Adaptive Lookback (The "Pulse") Standard indicators use a "static" period (like 14 or 20). The ABSP is different; it uses the Market Pulse to change its own length: • It tracks the number of bars since the last significant structural pivot. • If the market is moving fast with frequent pivots, the lookback shortens (more sensitive). • If the market is trending smoothly without pivots, the lookback lengthens (more stable). 3. Statistical Normalization (Z-Score) To make the data readable across different assets (like Crypto vs. Forex), we apply a Z-Score calculation. This measures how many standard deviations the current pressure is away from the mean: • Neutral: Z = approx 0 (Balanced market). • High Intensity: Z > 2.0 (Significant buying surge). • Extreme Exhaustion: Z > 3.0 (Potential blow-off top/bottom). 4. Key Logic Points Feature | Function | Trading Benefit ============================= Net Delta | Subtracts SP from BP. | Instant view of which side is winning the tug-of-war. ---------------------------------------------------------------------------- EMA Smoothing | Uses a Series EMA on the raw values. | Filters out "noise" while remaining responsive to price. ---------------------------------------------------------------------------- Divergence Logic | Compares Price Highs to Pressure Highs. | Flags when a trend is losing "gas" before price actually drops. ---------------------------------------------------------------------------- Z-Intensity Filter | Only flags "PRO" signals at extremes. | Ensures you aren't entering during "retail chop." How it drives the "Fusion" System: In your current setup, the ABSP acts as the ultimate filter. A "Wave" is just a zig-zag on the chart, but the ABSP tells the script: "This wave is legitimate because the Z-Score is at 2.1 and Buying Pressure is exponentially higher than Selling Pressure." Would you like me to add a specific "Exhaustion" alert to the ABSP logic that pings you when the Z-Score hits an extreme level (>3.0), even if a new wave hasn't formed yet?
Pine Script®指標
由kimlombard提供
5, 8, 21, 200 EMA Daily 200 SMA Daily VWAPMulti-timeframe EMA stack with Daily VWAP & 200 SMA This clean overlay indicator combines popular exponential moving averages (5, 8, 21, 200 EMA on current timeframe) with a higher-timeframe Daily 200 SMA and session-resetting Daily VWAP — perfect for trend following, dynamic support/resistance, and intraday bias on stocks, forex, crypto, or futures. Key Features: • 5 EMA (very fast) – quick momentum & scalping filter (default lime) • 8 EMA (fast) – short-term trend & pullback entries (default blue) • 21 EMA (medium) – intermediate trend & confluence zone (default orange) • 200 EMA (long) – major trend direction & big-picture support/resistance (default purple) • Daily 200 SMA – smooth higher-timeframe trend line that stays constant on lower TFs (default teal, thicker line) • Daily VWAP – volume-weighted average price that resets each trading day (default yellow) All lines feature right-edge labels that auto-refresh daily and follow price action (toggleable + size adjustable). Common uses: - Trend alignment: Trade in direction of higher EMAs + Daily 200 SMA - Pullbacks: Enter near 5/8/21 EMA when aligned with 200s - Intraday mean reversion: Use Daily VWAP as fair value anchor - Dynamic S/R: Watch reactions at these levels Fully customizable colors, lengths, and label visibility. Clean code, no repainting issues on historical bars. Happy trading!
Pine Script®指標
由Cag100提供
Fusion Elite: Smart-Alert + ADR [v6]🔱 The Fusion Elite Trading Manifesto Version 1.0 — Execution Strategy & Rules I. The Three Pillars of Confluence Every high-probability trade must be a "meeting of the minds" between three distinct market forces: 1. Market Structure (The Wave): A structural pivot must be confirmed. We don't guess bottoms or tops; we wait for the pivot to print. 2. Internal Pressure (The ABSP): The wave must be backed by net buying or selling pressure. A bullish wave with negative net pressure is a "Fakeout." 3. Momentum (Auto-Lens MACD): The move must have the "wind at its back." We look for the histogram to be in sync with our entry direction. II. Signal Hierarchy Not all labels are created equal. Use this hierarchy to manage your risk: III. The "Gas Tank" (ADR) Rule The Average Daily Range is your most important filter for trend longevity. • Fuel to Burn (>50\% ADR Room): Aggressive entries allowed. The trend has room to expand into a "runner." • Running on Fumes (<20\% ADR Room): No new trend entries. Focus on trailing stops. • Tank Empty (<10\% ADR Room): Look for SESS HUNT 🎯 reversal signals. The market is overextended and likely to "snap back" to the mean. IV. The Trend Shutter (Macro Bias) The 1-Hour background shadow is your "North Star." • Emerald Shadow: Long-bias only. Ignore bearish waves; only take PRO BUY and ADD+ signals. • Crimson Shadow: Short-bias only. Ignore bullish waves; only take PRO SELL and ADD- signals. V. Defensive Procedures (The Warnings) • !! DIV WARNING !!: If the dashboard flashes a divergence warning, the current move is "weak." Move Stop Loss to break-even or take 50\% profit immediately. • Sync Divergence: If the 15s and 5m timeframes are "CHOP" (disagreeing), stay flat. We only strike when the Confluence Meter shows dominance (>75\%). VI. The Professional Mindset "I do not trade price; I trade the confluence of structural pivots, institutional liquidity hunts, and statistical pressure extremes." 1. Verify the Shadow (1H Bias). 2. Check the Gas Tank (ADR Room). 3. Wait for the Confluence (Triple Threat / PRO Signal). 4. Manage the Trade (Trust the ATR-based SL/TP).
Pine Script®指標
由kimlombard提供
Sessions Gold Sniper MGC1!Overview The MGC1! Sniper Time Zones is a specialized intraday precision tool designed for Gold futures traders (MGC/GC). It visually segments the trading day into four critical high-volatility windows based on ICT/SMC Killzones and Market Profile auction logic. Core Functionality The script automatically highlights specific time blocks on the chart to identify where "Smart Money" is likely to inject liquidity. It assists the trader in avoiding "chop" (low volatility periods) and focusing execution only during high-probability hours. Highlighted Sessions London Open (06:00 – 10:00): Captures the initial trend setting and European liquidity raids. Pre-NY Lunch (12:00 – 13:00): Monitors mid-day rebalancing or potential position squaring before the NY open. NY Open (14:00 – 16:00): The primary volatility window for ICT/SMC setups (Silver Bullet & Judat Swing). NY PM Session (16:30 – 18:00): Focuses on the afternoon expansion or daily close reversals. Key Features Dynamic Labels: Clear, top-aligned text labels identify each session, ensuring you never lose track of the current market context across any timeframe (M1 to H1). Customizable Aesthetics: Fully adjustable color palette via the settings menu to match any dark or light chart theme. Visual Scannability: Uses transparent background fills (bgcolor) to allow price action and candlesticks to remain the primary focus while providing structural time-context. Technical Setup Platform: TradingView (Pine Script v5). Timezone: Set to UTC+1 (Central European Time) by default to align with the MGC1! Sniper methodology.
Pine Script®指標
由caktrading提供
DkS Morning Start PRO 3.0DkS Morning Start PRO — FX Live Guide (Auto Entry / SL / TP + Asia Range) DkS Morning Start PRO is a professional trading tool designed for Forex and intraday traders who want precise, rule-based entries using the Asian session breakout, with fully automated Entry, Stop Loss, and Take Profit levels. The script automatically detects the Asian session range, monitors breakout conditions during the morning session, and generates a complete trading plan with clean, continuous visual levels directly on the chart. Key Features • Automatic Asian Range (Daily High & Low) Draws the current day’s Asian High and Low and automatically removes previous levels, keeping your chart clean and focused. • Automatic Entry, Stop Loss, and Take Profit Calculated using professional logic based on: Asian range breakout Optional retest confirmation Configurable risk management Custom Risk/Reward ratio • Clean and Professional Visual Display Includes: Continuous Entry, SL, and TP lines Professional labels (Entry / SL / TP) Real-time informational panel Clear and minimal chart design • Live Trading Plan (Before Confirmation) Displays potential Entry, SL, and TP levels in advance, allowing traders to prepare before the signal confirms. • Professional Confirmation Filters Built-in filters for higher-probability setups: Fast and Slow EMA trend filter RSI confirmation filter One trade per day option (ideal for FTMO and prop firms) • Designed for Forex Intraday and Scalping Highly effective on: EURUSD GBPUSD AUDUSD XAUUSD Recommended timeframes: M5 M15 M30 Advantages • Eliminates emotional decision-making • Provides clear, rule-based entries • Improves consistency and discipline • Ideal for FTMO and prop firm trading • Clean, professional interface • Non-repainting logic How It Works Detects the Asian session range Waits for breakout during morning session Confirms retest (optional) Calculates Entry, Stop Loss, and Take Profit Displays full trading plan automatically
Pine Script®指標
由dksniewieders提供
Damodaran_EV_EBITLibrary "Damodaran_EV_EBIT" sector_sigma(sector)   Parameters:      sector (string) ev_ebit_base(industry)   Parameters:      industry (string) ev_ebit_band(industry, sector)   Parameters:      industry (string)      sector (string) ev_ebit_low(industry, sector)   Parameters:      industry (string)      sector (string) ev_ebit_high(industry, sector)   Parameters:      industry (string)      sector (string)
Pine Script®腳本庫
由himynameisbuzz提供
AURORA PRIME Alerts (Indicator)/@version=6 indicator("AURORA PRIME Alerts (Indicator)", overlay=true) // --- inputs and logic copied from your strategy (only the parts needed for signals) --- tfHTF = input.timeframe("60", "HTF for Structure") // ... copy any inputs you want exposed ... // Example: assume longEntry, shortEntry, canAdd are computed exactly as in your strategy // (paste the same computations here or import them) // For demonstration, placeholder signals (replace with your real conditions) longEntry = false // <-- replace with your strategy's longEntry expression shortEntry = false // <-- replace with your strategy's shortEntry expression canAdd = false // <-- replace with your strategy's canAdd expression inPosLong = false // <-- replace with your strategy's inPosLong expression inPosShort = false // <-- replace with your strategy's inPosShort expression // Alert conditions exposed to TradingView UI alertcondition(longEntry, title="AURORA PRIME Long Entry", message="AURORA PRIME Long Entry") alertcondition(shortEntry, title="AURORA PRIME Short Entry", message="AURORA PRIME Short Entry") alertcondition(canAdd and inPosLong, title="AURORA PRIME Long Add", message="AURORA PRIME Long Add") alertcondition(canAdd and inPosShort, title="AURORA PRIME Short Add", message="AURORA PRIME Short Add") // Optional visuals to match strategy plotshape(longEntry, title="Long", style=shape.triangleup, color=color.new(color.lime, 0), size=size.small, location=location.belowbar) plotshape(shortEntry, title="Short", style=shape.triangledown, color=color.new(color.red, 0), size=size.small, location=location.abovebar)
Pine Script®指標
由bettencourt37提供