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ADR TableTrack volatility and session momentum in real-time with customizable precision. Key Features: Average Daily Range (ADR): Configurable length (default 5 days), based on previous daily high–low ranges. Session Anchor Options: Choose anchor at 4 am NY, 6 pm NY, 9:30 am NY, 8:30 am NY, Previous Day Close, or Current Bar. Session Range & %ADR: Displays the real-time range from the chosen anchor, plus what percentage of ADR has been covered. High / Low Target Levels: Calculates ADR targets based on anchor: anchor ± ADR. Optional Target Lines: Draw horizontal lines for high and low targets across the session; customize color and width. Dynamic Table Display: User-selectable table size and text size (Tiny to Huge) for optimal readability. Robust Anchor Logic: Uses the first bar at-or-after anchor time each NY day, ensuring stability even on irregular intraday timeframes. How to Use Choose your anchor in settings. View ADR, session range (with %ADR), and target price levels in the top-right pane.Toggle High/Low lines to overlay targets on the chart. Adjust table and text size to match your workspace. Why It Matters Quickly assess where price stands relative to typical volatility. Easily identify intraday price exhaustion or breakout zones. Anchor flexibility enables use for both futures and equities, aligning with your trading session. Clean, professional display—no clutter, no guesswork.
Pine Script® indicator
by OliverC-H
Daily Price LevelsTrack daily price action like a pro with instant visibility of key levels, percentages, and P&L values - all in one clean view." Bullet points: • Shows Daily Open, High, Low & Median levels • Dynamic color-coding: green above open, red below • Real-time price labels with: Exact price levels % distance between levels Point values Dollar values per contract • Auto-repaints on timeframe changes • 30min alerts for median crosses
Pine Script® indicator
by zer0123456
MSB BOS Market Structure [FTB]Track Market Structure Breaks (MSB) and Breaks of Structure (BOS) on your charts. This indicator does exactly that without clutter and with easy-to-spot. 🔑 Features: MSB (Market Structure Break): Shows when price flips and breaks the previous high/low — possible start of a new trend. BOS (Break of Structure): Highlights key structural breakouts in line with the existing trend. ✅ Pivot-Based Analysis (Body Focused) Uses candle body-based pivot highs and lows to find clean market structure points (no wicks confusion here!). Adjustable pivot strength — control how many candles you want on either side to define a swing. ✅ Clean Visual Markings MSB and BOS lines with optional labels so you see exactly where breaks happen. Customizable line style (Solid, Dashed, Dotted) to match your chart aesthetic. Optional pivot markers to show minor swing highs/lows. ✅ Alerts Ready Set alerts for any MSB or BOS, or filter to specific bullish/bearish breaks — never miss a key level again 💡 How to Use This Indicator: Identify Trend Shifts: Use MSB to spot early trend reversals — when a previous structure breaks against the trend. Catch Continuations: Watch for BOS to confirm trend continuation — great for riding the trend! ⚙️ Settings You Can Adjust: Pivot Strength: How many candles to look back and forward for swing points (default: 3). Show Pivots: Optional — highlight swing highs and lows for extra clarity.
Pine Script® indicator
by FunkyTown_Bytes
2
Altcoin PortfolioTrack your altcoin portfolio balance in Fiat currency. Make sure to open the data window to the right of your charts, it makes everything alot easier to read at a glance. To learn more about customizing this script to fit your portfolio, watch the video here: youtu.be To get more cool scripts and up-to-date information about Autoview, join us in slack slack.with.pink As per the usual, we hope this script helps with your trading venture. Good luck, and happy trading.
Pine Script® indicator
by CryptoRox
WoAlgo Premium v3.0 WoAlgo Premium v3.0 - Smart Money Analysis Overview ** WoAlgo Premium v3.0 ** is an advanced technical analysis indicator designed for educational purposes. This tool combines Smart Money Concepts with multi-factor confluence analysis to help traders identify potential market opportunities across multiple timeframes. The indicator integrates market structure analysis, order flow concepts, and technical momentum indicators into a comprehensive dashboard system. It is designed to assist traders in understanding institutional trading patterns and market dynamics through visual analysis tools. ### What It Does This indicator provides: **1. Smart Money Concepts Analysis** - Market structure identification (Break of Structure and Change of Character patterns) - Order block detection with volume confirmation - Fair value gap recognition - Liquidity zone mapping (equal highs and lows) - Premium and discount zone calculations **2. Multi-Factor Confluence Scoring** The indicator calculates a proprietary confluence score (0-100) based on five key components: - Price action analysis (30% weight) - Volume confirmation (20% weight) - Momentum indicators (25% weight) - Trend strength measurement (15% weight) - Money flow analysis (10% weight) **3. Multi-Timeframe Analysis** - Scans 5 different timeframes (5M, 15M, 1H, 4H, Daily) - Calculates alignment percentage across timeframes - Displays trend and structure status for each period **4. Visual Dashboard System** - Comprehensive main dashboard with 13 metrics - Real-time screener table with 10 data columns - Multi-timeframe scanner - Performance tracking panel ### How It Works **Market Structure Detection** The indicator identifies key structural changes in price action: - **BOS (Break of Structure)**: Indicates trend continuation when price breaks previous swing points - **CHoCH (Change of Character)**: Signals potential trend reversal when market structure shifts **Order Block Identification** Order blocks are detected when: - Significant volume appears at swing points - Price shows strong directional movement from these levels - Enhanced detection with extreme volume confirmation (OB++ markers) **Fair Value Gap Recognition** Gaps between candles are identified when: - Price leaves inefficiencies in the market - Three consecutive candles create a gap pattern - Gap size exceeds minimum threshold based on ATR **Confluence Calculation** The system evaluates multiple technical factors: 1. **Price Position**: Relative to moving averages (EMA 20, 50, 200) 2. **Volume Analysis**: Standard deviation-based volume spikes 3. **Momentum**: RSI, MACD, Stochastic indicators 4. **Trend Strength**: ADX measurements 5. **Money Flow**: MFI indicator readings Each factor contributes weighted points to create an overall confluence score that helps assess signal strength. ### Signal Types **Confirmation Signals (▲ / ▼)** Generated when: - EMA crossovers occur (20/50 cross) - Volume confirmation is present - RSI is in appropriate zone - Confluence score exceeds 50% **Strong Signals (▲+ / ▼+)** Higher-confidence signals requiring: - Confluence score above 70% - Extreme volume confirmation - Alignment with 200 EMA trend - MACD confirmation - Bullish or bearish market structure **Contrarian Signals (⚡)** Reversal indicators appearing when: - RSI reaches extreme levels (<30 or >70) - Stochastic shows oversold/overbought conditions - Price touches Bollinger Band extremes - Potential divergence patterns emerge **Reversal Zones** Visual boxes highlighting areas where: - Market structure conflicts with momentum - High probability of directional change - Key support/resistance levels interact **Smart Trail** Dynamic stop-loss indicator that: - Adjusts based on ATR (Average True Range) - Follows trend direction - Updates automatically as price moves - Provides risk management reference points ### Dashboard Components **Main Dashboard (13 Metrics)** 1. **Confluence Score**: Current bull/bear percentage (0-100) 2. **Market Regime**: Trend classification (Strong Up/Down, Range, Squeeze) 3. **Signal Status**: Active buy/sell signal indication 4. **Structure State**: Current market structure (Bullish/Bearish/Neutral) 5. **Trend Strength**: ADX-based measurement 6. **RSI Level**: Momentum indicator with overbought/oversold zones 7. **MACD Direction**: Trend momentum confirmation 8. **Money Flow Index**: Smart money sentiment 9. **Volume Status**: Current volume relative to average 10. **Volatility Rating**: ATR percentage measurement 11. **ATR Value**: Average true range for position sizing 12. **MTF Alignment**: Multi-timeframe agreement percentage **Screener Table (10 Columns)** - Current symbol and timeframe - Real-time price and percentage change - Quality rating (star system) - Active signal type - Smart trail status - Market structure state - MACD direction - Trend strength percentage - Bollinger Band squeeze detection **MTF Scanner (5 Timeframes)** Displays for each timeframe: - Trend direction indicator - Market structure classification - Visual confirmation with color coding **Performance Metrics** - Win rate percentage (simplified calculation) - Total signals generated - Current confluence score - MTF alignment status - Volatility level ### Settings and Customization **Preset Styles** Choose from predefined configurations: - **Conservative**: Fewer, higher-quality signals - **Moderate**: Balanced approach (recommended) - **Aggressive**: More frequent signals - **Scalper**: Short-term focused - **Swing**: Longer-term oriented - **Custom**: Full manual control **Smart Money Concepts Controls** - Toggle each feature independently - Adjust swing length (3-50 periods) - Enable/disable internal structure - Control order block display - Manage breaker block visibility - Show/hide fair value gaps - Display liquidity zones - Premium/discount zone visualization **Signal Configuration** - Enable/disable confirmation signals - Toggle strong signal markers - Control contrarian signal display - Show/hide reversal zones - Smart trail activation - Sensitivity adjustment (5-50) **Visual Customization** - Moving average display options - MA period adjustments (Fast: 20, Slow: 50, Trend: 200) - Support/resistance line toggle - Dynamic S/R lookback period - Candle coloring based on trend - Color scheme customization - Dashboard size options (Small/Normal/Large) - Position placement (4 corners) ### How to Use **Step 1: Initial Setup** 1. Add indicator to chart 2. Select appropriate preset or use Custom 3. Adjust timeframe to match trading style 4. Configure dashboard visibility preferences **Step 2: Analysis Workflow** 1. Check MTF Scanner for timeframe alignment 2. Review Main Dashboard confluence score 3. Observe Market Regime classification 4. Identify active signals on chart 5. Confirm with Smart Money Concepts (order blocks, FVG, structure) **Step 3: Trade Consideration** Strong signals (▲+ / ▼+) require: - Confluence score >70% - MTF alignment >60% - Confirmation from multiple dashboard metrics - Support from Smart Money Concepts - Appropriate volume levels **Step 4: Risk Management** - Use Smart Trail as dynamic stop-loss reference - Consider ATR for position sizing - Monitor volatility rating - Respect support/resistance levels - Combine with personal risk parameters ### Best Practices **For Scalping (1M-5M timeframes)** - Use Scalper preset - Reduce swing length to 5-7 - Focus on strong signals only - Monitor MTF alignment closely - Quick entries near order blocks **For Intraday Trading (15M-1H timeframes)** - Use Moderate preset (recommended) - Default swing length (10) - Combine confirmation and strong signals - Check MTF scanner before entry - Use fair value gaps for entries **For Swing Trading (4H-D timeframes)** - Use Swing preset - Increase swing length to 15-20 - Focus on strong signals - Require high MTF alignment - Patient approach with major structure levels ### Technical Specifications **Indicators Used** - Exponential Moving Averages (20, 50, 200) - Hull Moving Average - Relative Strength Index (14) - MACD (12, 26, 9) - Money Flow Index (14) - Stochastic Oscillator (14, 3) - ADX / DMI (14) - Bollinger Bands (20, 2) - ATR (14) - Volume Analysis (SMA 20 with standard deviation) **Calculation Methods** - Swing detection using pivot high/low functions - Volume confirmation via statistical analysis - Multi-factor scoring with weighted components - Dynamic support/resistance using highest/lowest functions - Real-time MTF data via security() function ### Limitations and Considerations **Important Notes** 1. This indicator is designed for educational and analytical purposes only 2. Historical performance does not guarantee future results 3. Signals should be confirmed with additional analysis 4. Market conditions vary and affect indicator performance 5. Not all signals will be profitable 6. Risk management is essential for all trading **Known Limitations** - Confluence scoring is algorithmic and not predictive - MTF analysis requires sufficient historical data - Effectiveness varies across different market conditions - Sideways markets may produce conflicting signals - High volatility can affect signal reliability - Backtesting results shown are simplified calculations **Not Suitable For** - Automated trading without human oversight - Sole basis for trading decisions - Guaranteed profit expectations - Inexperienced traders without proper education - Trading without risk management plans ### Market Applicability **Effective On** - Trending markets (any direction) - Clear structure formation periods - Liquid instruments with consistent volume - Multiple asset classes (forex, stocks, crypto, commodities) - Various timeframes with appropriate settings **Less Effective During** - Extended ranging/choppy conditions - Extremely low volume periods - Major news events causing gaps - Early market open with high spread - Illiquid instruments with erratic price action ### Risk Disclaimer **⚠️ IMPORTANT NOTICE** This indicator is provided for **educational and informational purposes only**. It does not constitute financial advice, investment recommendations, or trading signals. **Key Risk Factors:** - Trading financial instruments involves substantial risk of loss - Past performance does not indicate future results - No indicator can predict market movements with certainty - Users should conduct independent research and analysis - Professional financial advice should be sought when appropriate - Risk management and position sizing are critical to successful trading - Users are solely responsible for their trading decisions **Responsible Usage:** - Combine with comprehensive market analysis - Use appropriate stop-loss orders - Never risk more than you can afford to lose - Maintain realistic expectations - Continue education on technical analysis principles - Test thoroughly on demo accounts before live trading - Understand all indicator features before using ### Educational Resources **Understanding Smart Money Concepts** Smart Money Concepts analyze how institutional traders and large market participants operate. Key principles include: - Institutional order flow patterns - Market structure changes - Liquidity manipulation - Supply and demand imbalances - Order block formations **Multi-Timeframe Analysis Theory** Analyzing multiple timeframes helps: - Identify overall market direction - Improve entry timing - Confirm trend strength - Recognize consolidation periods - Reduce conflicting signals **Confluence Trading Approach** Using multiple confirming factors: - Increases signal reliability - Reduces false signals - Provides conviction for trades - Helps with position sizing - Improves risk-reward ratios ### Version History **v3.0 (Current)** - Multi-factor confluence scoring system - Complete Smart Money Concepts implementation - Real-time multi-timeframe analysis - Four professional dashboard panels - Enhanced order block detection - Breaker block identification - Premium/discount zone calculations - Smart trail stop-loss system - Customizable preset configurations - Performance tracking metrics **Development Philosophy** This indicator was developed with focus on: - Educational value for traders - Transparent methodology - Comprehensive feature set - User-friendly interface - Flexible customization options ### Technical Support **For Questions About:** - Indicator functionality - Parameter optimization - Signal interpretation - Dashboard metrics - Best practice recommendations Please use TradingView's comment section below. The developer monitors comments and provides assistance to users learning to use the indicator effectively. ### Acknowledgments This indicator implements concepts from: - Smart Money Concepts trading methodology - Multi-timeframe analysis techniques - Technical indicator theory - Market structure analysis principles - Institutional order flow concepts All implementations are original code and calculations based on established technical analysis principles. --- ## ADDITIONAL INFORMATION SECTION **Category**: Indicators **Type**: Market Structure / Multi-Timeframe Analysis **Complexity**: Intermediate to Advanced **Open Source**: Code visible for transparency and education **Pine Script Version**: v6 **Chart Overlay**: Yes **Maximum Objects**: 500 boxes, 500 lines, 500 labels
Pine Script® indicator
by ionmarpie
Premium Money Flow Oscillator [NeuraAlgo]Premium Money Flow Oscillator (PMFO) — NeuraAlgo The Premium Money Flow Oscillator (PMFO) is an advanced volume-weighted momentum engine designed to reveal true capital flow, not just price movement. It combines multi-layer smoothing, zero-lag correction, and dynamic normalization to deliver a clean, responsive, and noise-resistant money flow signal suitable for both scalping and swing trading. Unlike traditional oscillators, PMFO focuses on pressure behind price — showing when smart money accumulation or distribution is actively occurring. 🔹 Core Features Volume-Weighted Money Flow Measures real buying and selling pressure using price displacement × volume. Filters out weak price moves with low participation. Multi-Layer Smoothing Engine EMA + SMA hybrid base smoothing Gaussian noise reduction Zero-Lag correction Deep & Super smoothing layers → Result: ultra-smooth yet fast reaction to momentum shifts. Dynamic Normalization Automatically adapts to volatility. Keeps signals consistent across all markets and timeframes. 🔹 Smart Zones & Visual Intelligence Dynamic Overbought / Oversold Zones Zones strengthen visually as momentum increases. Strong zones highlight extreme institutional pressure. Adaptive Gradient Coloring Color intensity reflects money flow strength. Instantly see dominance without reading numbers. Background Pulse Subtle market bias feedback (bullish / bearish pressure). 🔹 Multi-Timeframe Confirmation Optional Higher Timeframe Money Flow Confirmation Align lower-timeframe entries with higher-timeframe capital direction. Ideal for trend validation and false-signal reduction. 🔹 Professional Dashboard Live Money Flow Value Market Flow State Strength Percentage MTF Trend Bias Institutional-style status readout designed for quick decision making. 🔹 Best Use Cases ✔ Trend confirmation ✔ Momentum continuation entries ✔ Reversal exhaustion detection ✔ Divergence analysis ✔ Smart money flow tracking ⚠️ Notes PMFO works best when combined with price structure, support/resistance, or trend context. Extreme readings indicate pressure, not immediate reversal — always wait for confirmation. Designed for traders who want clarity, not clutter. Built for precision, not lag.
Pine Script® indicator
by NeuraAlgo
Enigma UnlockedENIGMA Indicator: A Comprehensive Market Bias & Success Tracker The ENIGMA Indicator is a powerful tool designed for traders who aim to identify market bias, track price movements, and evaluate trade performance using multiple timeframes. It combines multiple indicators and advanced logic to provide real-time insights into market trends, helping traders make more informed decisions. Key Features 1. Multi-Timeframe Bias Calculation: The ENIGMA Indicator tracks the market bias across multiple timeframes—Daily (D), 4-Hour (H4), 1-Hour (H1), 30-Minute (30M), 15-Minute (15M), 5-Minute (5M), and 1-Minute (1M). How the Bias is Created: The Bias is a key feature of the ENIGMA Indicator and is determined by comparing the current price with previous price levels for each timeframe. - Bullish Bias (1): The market is considered **bullish** if the **current closing price** is higher than the **previous timeframe’s high**. This suggests that the market is trending upwards, and buyers are in control. - Bearish Bias (-1): The market is considered **bearish** if the **current closing price** is lower than the **previous timeframe’s low**. This suggests that the market is trending downwards, and sellers are in control. - Neutral Bias (0): The market is considered **neutral** if the price is between the **previous high** and **previous low**, indicating indecision or a range-bound market. This bias calculation is performed independently for each timeframe. The **Bias** for each timeframe is then displayed in the **Bias Table** on your chart, providing a clear view of market direction across multiple timeframes. 2. **Customizable Table Display:** - The indicator provides a table that displays the bias for each selected timeframe, clearly marking whether the market is **Bullish**, **Bearish**, or **Neutral**. - Users can choose where to place the table on the chart: top-left, top-right, bottom-left, bottom-right, or center positions, allowing for easy and personalized chart management. 3. **Win/Loss Tracker:** - The table also tracks the **success rate** of **buy** and **sell** trades based on price retests of key bias levels. - For each period (Day, Week, Month), it tracks how often the price has moved in the direction of the initial bias, counting **Buy Wins**, **Sell Wins**, **Buy Losses**, and **Sell Losses**. - This helps traders assess the effectiveness of the market bias over time and adjust their strategies accordingly. #### **How the Success Calculation Determines the Success Rate:** The **Success Calculation** is designed to track how often the price follows the direction of the market bias. It does this by evaluating how the price retests key levels associated with the identified market bias: 1. **Buy Success Calculation**: - The success of a **Buy Trade** is determined when the price breaks above the **previous high** after a **bullish bias** has been identified. - If the price continues to move higher (i.e., makes a new high) after breaking the previous high, the **buy trade is considered successful**. - The indicator tracks how many times this condition is met and counts it as a **Buy Win**. 2. **Sell Success Calculation**: - The success of a **Sell Trade** is determined when the price breaks below the **previous low** after a **bearish bias** has been identified. - If the price continues to move lower (i.e., makes a new low) after breaking the previous low, the **sell trade is considered successful**. - The indicator tracks how many times this condition is met and counts it as a **Sell Win**. 3. **Failure Calculations**: - If the price does not move as expected (i.e., it does not continue in the direction of the identified bias), the trade is considered a **loss** and is tracked as **Buy Loss** or **Sell Loss**, depending on whether it was a bullish or bearish trade. The ENIGMA Indicator keeps a running tally of **Buy Wins**, **Sell Wins**, **Buy Losses**, and **Sell Losses** over a set period (which can be customized to Days, Weeks, or Months). These statistics are updated dynamically in the **Bias Table**, allowing you to track your success rate in real-time and gain insights into the effectiveness of the market bias. #### **Customizable Period Tracking:** - The ENIGMA Indicator allows you to set custom tracking periods (e.g., 30 days, 2 weeks, etc.). The performance metrics reset after each tracking period, helping you monitor your success in different market conditions. 5. **Interactive Settings:** - **Lookback Period**: Define how many bars the indicator should consider for bias calculations. - **Success Tracking**: Set the number of candles to track for calculating the win/loss performance. - **Time Threshold**: Set a time threshold to help define the period during which price retests are considered valid. - **Info Tooltip**: You can enable the information tool in the settings to view detailed explanations of how wins and losses are calculated, ensuring you understand how the indicator works and how the results are derived. #### **How to Use the ENIGMA Indicator:** 1. **Install the Indicator**: - Add the ENIGMA Indicator to your chart. It will automatically calculate and display the bias for multiple timeframes. 2. **Interpret the Bias Table**: - The bias table will show whether the market is **Bullish**, **Bearish**, or **Neutral** across different timeframes. - Look for alignment between the timeframes—when multiple timeframes show the same bias, it may indicate a stronger trend. 3. **Use the Win/Loss Tracker**: - Track how well your trades align with the bias using the **Win/Loss Tracker**. This helps you refine your strategy by understanding which timeframes and biases lead to higher success rates. - For example, if you see a high number of **Buy Wins** and a low number of **Sell Wins**, you may decide to focus more on buying during bullish trends and avoid selling during bearish retracements. 4. **Track Your Period Performance**: - The indicator will automatically track your performance over the set period (Days, Weeks, Months). Use this data to adjust your approach and evaluate the effectiveness of your trading strategy. 5. **Position the Table**: - Customize the placement of the table on your chart based on your preferences. You can choose from options like **Top Left**, **Top Right**, **Bottom Left**, **Bottom Right**, or **Center** to keep the chart uncluttered. 6. **Adjust Settings**: - Modify the indicator settings according to your trading style. You can adjust the **Lookback Period**, **Number of Candles to Track**, and **Time Threshold** to match the pace of your trading. 7. **Use the Info Tooltip**: - Enable the **Info Tool** in the settings to understand how the Buy/Sell Wins and Losses are calculated. The tooltip provides a breakdown of how the indicator tracks price movements and calculates the success rate. **Conclusion:** The **ENIGMA Indicator** is designed to help traders make informed decisions by providing a clear view of the market bias and performance data. With the ability to track bias across multiple timeframes and evaluate your trading success, it can be a powerful tool for refining your trading strategies. Whether you're looking to focus on a single timeframe or analyze multiple timeframes for a stronger bias, the ENIGMA Indicator adapts to your needs, providing both real-time market insights and performance feedback.
Pine Script® indicator
by Niko-picasso369
2
Adaptive Market Wave TheoryAdaptive Market Wave Theory 🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation. The Wave Analysis Problem: Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses: 1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition. 2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw. 3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management. 4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024. 5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve. The AMWT Solution: AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning: • Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed. • Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated. • No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3." • Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time. • No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance. The Core Insight: "Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'" 🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS Why Hidden Markov Models? Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables. This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations. HMM Components: 1. Hidden States (S) : The unobservable market conditions 2. Observations (O) : What we can measure (price, volume, indicators) 3. Transition Matrix (A) : Probability of moving between states 4. Emission Matrix (B) : Probability of observations given each state 5. Initial Distribution (π) : Starting state probabilities AMWT's Six Market States: State 0: IMPULSE_UP • Definition: Strong bullish momentum with high participation • Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising • Typical Duration: 5-20 bars depending on timeframe • What It Means: Institutional buying pressure, trend acceleration phase State 1: IMPULSE_DN • Definition: Strong bearish momentum with high participation • Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling • Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster) • What It Means: Institutional selling pressure, panic or distribution acceleration State 2: CORRECTION • Definition: Counter-trend consolidation with declining momentum • Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing • Typical Duration: 8-30 bars • What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg State 3: ACCUMULATION • Definition: Base-building near lows where informed participants absorb supply • Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range • Typical Duration: 15-50 bars • What It Means: Smart money buying from weak hands, preparing for markup phase State 4: DISTRIBUTION • Definition: Top-forming near highs where informed participants distribute holdings • Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range • Typical Duration: 15-50 bars • What It Means: Smart money selling to late buyers, preparing for markdown phase State 5: TRANSITION • Definition: Regime change period with mixed signals and elevated uncertainty • Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction • Typical Duration: 5-15 bars • What It Means: Market deciding next direction, dangerous for directional trades The Transition Matrix: The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online: From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02 IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02 CORR 0.15 0.15 0.50 0.10 0.10 0.00 ACCUM 0.30 0.05 0.15 0.40 0.05 0.05 DIST 0.05 0.30 0.15 0.05 0.40 0.05 TRANS 0.20 0.20 0.20 0.15 0.15 0.10 Key Insights from Transition Probabilities: • Impulse states are sticky (70% self-transition): Once trending, markets tend to continue • Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain • Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies • Distribution strongly favors IMP_DN transition (30%): Topping leads to declines The Viterbi Algorithm: Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space. Mathematical Formulation: δ_t(j) = max_i × B_j(O_t) Where: δ_t(j) = probability of most likely path ending in state j at time t A_ij = transition probability from state i to state j B_j(O_t) = emission probability of observation O_t given state j AMWT Implementation: AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting: • Current state estimate • State confidence (probability of current state vs alternatives) • State sequence for pattern detection Online Learning (Baum-Welch Adaptation): Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior: f_onlineUpdateHMM(prev_state, curr_state, observation, decay) => // Update transition matrix A *= decay A += (1.0 - decay) // Renormalize row // Update emission matrix B *= decay B += (1.0 - decay) // Renormalize row The decay parameter (default 0.85) controls adaptation speed: • Higher decay (0.95): Slower adaptation, more stable, better for consistent markets • Lower decay (0.80): Faster adaptation, more reactive, better for regime changes Why This Matters for Trading: Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment : "There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION." This enables: • Position sizing by confidence : 90% confidence = full size; 60% confidence = half size • Risk management by transition probability : High correction probability = tighten stops • Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in 🎰 THE 3-BANDIT CONSENSUS SYSTEM The Multi-Agent Philosophy: No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets. AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions. Agent 1: TREND AGENT Philosophy : Markets trend. Follow the trend until it ends. Analytical Components: • EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish) • MACD Histogram: Direction and rate of change • Price Momentum: Close relative to ATR-normalized movement • VWAP Position: Price above/below volume-weighted average price Signal Generation: Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP → Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4 Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1 → Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3 Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP → Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4 Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1 → Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3 When Trend Agent Excels: • Trend days (IB extension >1.5x) • Post-breakout continuation • Institutional accumulation/distribution phases When Trend Agent Fails: • Range-bound markets (ADX <20) • Chop zones after volatility spikes • Reversal days at major levels Agent 2: REVERSION AGENT Philosophy: Markets revert to mean. Extreme readings reverse. Analytical Components: • Bollinger Band Position: Distance from bands, percent B • RSI Extremes: Overbought (>70) and oversold (<30) • Stochastic: %K/%D crossovers at extremes • Band Squeeze: Bollinger Band width contraction Signal Generation: Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25 → Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01 Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75 → Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01 Squeeze Fire Bull: Band squeeze ending AND close > upper band → Signal: +1 (Long), Confidence: 0.65 Squeeze Fire Bear: Band squeeze ending AND close < lower band → Signal: -1 (Short), Confidence: 0.65 When Reversion Agent Excels: • Rotation days (price stays within IB) • Range-bound consolidation • After extended moves without pullback When Reversion Agent Fails: • Strong trend days (RSI can stay overbought for days) • Breakout moves • News-driven directional moves Agent 3: STRUCTURE AGENT Philosophy: Market structure reveals institutional intent. Follow the smart money. Analytical Components: • Break of Structure (BOS): Price breaks prior swing high/low • Change of Character (CHOCH): First break against prevailing trend • Higher Highs/Higher Lows: Bullish structure • Lower Highs/Lower Lows: Bearish structure • Liquidity Sweeps: Stop runs that reverse Signal Generation: BOS Bull: Price breaks above prior swing high with momentum → Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2 CHOCH Bull: First higher low after downtrend, breaking structure → Signal: +1 (Long), Confidence: 0.75 BOS Bear: Price breaks below prior swing low with momentum → Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2 CHOCH Bear: First lower high after uptrend, breaking structure → Signal: -1 (Short), Confidence: 0.75 Liquidity Sweep Long: Price sweeps below swing low then reverses strongly → Signal: +1 (Long), Confidence: 0.80 Liquidity Sweep Short: Price sweeps above swing high then reverses strongly → Signal: -1 (Short), Confidence: 0.80 When Structure Agent Excels: • After liquidity grabs (stop runs) • At major swing points • During institutional accumulation/distribution When Structure Agent Fails: • Choppy, structureless markets • During news events (structure becomes noise) • Very low timeframes (noise overwhelms structure) Thompson Sampling: The Bandit Algorithm With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives). Thompson Sampling Solution: Each agent maintains a Beta distribution representing its success/failure history: Agent success rate modeled as Beta(α, β) Where: α = number of successful signals + 1 β = number of failed signals + 1 On Each Bar: 1. Sample from each agent's Beta distribution 2. Weight agent signals by sampled probabilities 3. Combine weighted signals into consensus 4. Update α/β based on trade outcomes Mathematical Implementation: // Beta sampling via Gamma ratio method f_beta_sample(alpha, beta) => g1 = f_gamma_sample(alpha) g2 = f_gamma_sample(beta) g1 / (g1 + g2) // Thompson Sampling selection for each agent: sampled_prob = f_beta_sample(agent.alpha, agent.beta) weight = sampled_prob / sum(all_sampled_probs) consensus += agent.signal × agent.confidence × weight Why Thompson Sampling? • Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution) • Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff • Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation • Self-Correcting : Poor performers naturally get lower weights over time Example Evolution: Day 1 (Initial): Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty) Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty) Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty) After 50 Signals: Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence) Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming) Structure Agent: Beta(32,19) → samples ~0.63 (outperforming) Result: Structure Agent now receives highest weight in consensus Consensus Requirements by Mode: Aggressive Mode: • Minimum 1/3 agents agreeing • Consensus threshold: 45% • Use case: More signals, higher risk tolerance Balanced Mode: • Minimum 2/3 agents agreeing • Consensus threshold: 55% • Use case: Standard trading Conservative Mode: • Minimum 2/3 agents agreeing • Consensus threshold: 65% • Use case: Higher quality, fewer signals Institutional Mode: • Minimum 2/3 agents agreeing • Consensus threshold: 75% • Additional: Session quality >0.65, mode adjustment +0.10 • Use case: Highest quality signals only 🌀 INTELLIGENT CHOP DETECTION ENGINE The Chop Problem: Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike. AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades. Five-Factor Chop Analysis: Factor 1: ADX Component (25% weight) ADX (Average Directional Index) measures trend strength regardless of direction. ADX < 15: Very weak trend (high chop score) ADX 15-20: Weak trend (moderate chop score) ADX 20-25: Developing trend (low chop score) ADX > 25: Strong trend (minimal chop score) adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100 Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop. Factor 2: Choppiness Index (25% weight) The Choppiness Index measures price efficiency using the ratio of ATR sum to price range: CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n) CI > 61.8: Choppy (range-bound, inefficient movement) CI < 38.2: Trending (directional, efficient movement) CI 38.2-61.8: Transitional chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100 Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range). Factor 3: Range Compression (20% weight) Compares recent range to longer-term range, detecting volatility squeezes: recent_range = Highest(20) - Lowest(20) longer_range = Highest(50) - Lowest(50) compression = 1 - (recent_range / longer_range) compression > 0.5: Strong squeeze (potential breakout imminent) compression < 0.2: No compression (normal volatility) range_compression_score = compression × 100 Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet. Factor 4: Channel Position (15% weight) Tracks price position within the macro channel: channel_position = (close - channel_low) / (channel_high - channel_low) position 0.4-0.6: Center of channel (indecision zone) position <0.2 or >0.8: Near extremes (potential reversal or breakout) channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability. Factor 5: Volume Quality (15% weight) Assesses volume relative to average: vol_ratio = volume / SMA(volume, 20) vol_ratio < 0.7: Low volume (lack of conviction) vol_ratio 0.7-1.3: Normal volume vol_ratio > 1.3: High volume (conviction present) volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0 Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall. Combined Chop Intensity: chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) + (range_compression_score × 0.20) + (channel_chop × 0.15) + (volume_chop × i_volumeChopWeight × 0.15) Regime Classifications: Based on chop intensity and component analysis: • Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively • Trending (20-35%): ADX >20, moderate directional bias, trade normally • Transitioning (35-50%): Mixed signals, regime change possible, reduce size • Mid-Range (50-60%): Price trapped in channel center, avoid new positions • Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only • Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout • Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely Signal Suppression: When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification. Chop Box Visualization: When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions. 💧 LIQUIDITY ANCHORING SYSTEM The Liquidity Concept: Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing. AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence. Liquidity Event Types: Type 1: Volume Spikes Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x) Interpretation: Sudden volume surge indicates institutional activity • Near swing low + reversal: Likely accumulation • Near swing high + reversal: Likely distribution • With continuation: Institutional conviction in direction Type 2: Stop Runs (Liquidity Sweeps) Definition: Price briefly exceeds swing high/low then reverses within N bars Detection: • Price breaks above recent swing high (triggering buy stops) • Then closes back below that high within 3 bars • Signal: Bullish stop run complete, reversal likely Or inverse for bearish: • Price breaks below recent swing low (triggering sell stops) • Then closes back above that low within 3 bars • Signal: Bearish stop run complete, reversal likely Type 3: Absorption Events Definition: High volume with small candle body Detection: • Volume > 2x average • Candle body < 30% of candle range • Interpretation: Large orders being filled without moving price • Implication: Accumulation (at lows) or distribution (at highs) Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity) BSL (Buy-Side Liquidity): • Cluster of swing highs within ATR proximity • Stop losses from shorts sit above these highs • Breaking BSL triggers short covering (fuel for rally) SSL (Sell-Side Liquidity): • Cluster of swing lows within ATR proximity • Stop losses from longs sit below these lows • Breaking SSL triggers long liquidation (fuel for decline) Liquidity Pool Mapping: AMWT continuously scans for and maps liquidity pools: // Detect swing highs/lows using pivot function swing_high = ta.pivothigh(high, 5, 5) swing_low = ta.pivotlow(low, 5, 5) // Track recent swing points if not na(swing_high) bsl_levels.push(swing_high) if not na(swing_low) ssl_levels.push(swing_low) // Display on chart with labels Confluence Scoring Integration: When signals fire near identified liquidity events, confluence scoring increases: • Signal near volume spike: +10% confidence • Signal after liquidity sweep: +15% confidence • Signal at BSL/SSL pool: +10% confidence • Signal aligned with absorption zone: +10% confidence Why Liquidity Anchoring Matters: Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst. 📊 SIGNAL GRADING SYSTEM The Quality Problem: Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence. Confluence Components (100 points total): 1. Bandit Consensus Strength (25 points) consensus_str = weighted average of agent confidences score = consensus_str × 25 Example: Trend Agent: +1 signal, 0.80 confidence, 0.35 weight Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight Structure Agent: +1 signal, 0.75 confidence, 0.40 weight Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77 Score = 0.77 × 25 = 19.25 points 2. HMM State Confidence (15 points) score = hmm_confidence × 15 Example: HMM reports 82% probability of IMPULSE_UP Score = 0.82 × 15 = 12.3 points 3. Session Quality (15 points) Session quality varies by time: • London/NY Overlap: 1.0 (15 points) • New York Session: 0.95 (14.25 points) • London Session: 0.70 (10.5 points) • Asian Session: 0.40 (6 points) • Off-Hours: 0.30 (4.5 points) • Weekend: 0.10 (1.5 points) 4. Energy/Participation (10 points) energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25 score = min(energy, 1.0) × 10 5. Volume Confirmation (10 points) if volume > SMA(volume, 20) × 1.5: score = 10 else if volume > SMA(volume, 20): score = 5 else: score = 0 6. Structure Alignment (10 points) For long signals: • Bullish structure (HH + HL): 10 points • Higher low only: 6 points • Neutral structure: 3 points • Bearish structure: 0 points Inverse for short signals 7. Trend Alignment (10 points) For long signals: • Price > EMA21 > EMA50: 10 points • Price > EMA21: 6 points • Neutral: 3 points • Against trend: 0 points 8. Entry Trigger Quality (5 points) • Strong trigger (multiple confirmations): 5 points • Moderate trigger (single confirmation): 3 points • Weak trigger (marginal): 1 point Grade Scale: Total Score → Grade 85-100 → A+ (Exceptional—all factors aligned) 70-84 → A (Strong—high probability) 55-69 → B (Acceptable—proceed with caution) Below 55 → C (Marginal—filtered by default) Grade-Based Signal Brightness: Signal arrows on the chart have transparency based on grade: • A+: Full brightness (alpha = 0) • A: Slight fade (alpha = 15) • B: Moderate fade (alpha = 35) • C: Significant fade (alpha = 55) This visual hierarchy helps traders instantly identify signal quality. Minimum Grade Filter: Configurable filter (default: C) sets the minimum grade for signal display: • Set to "A" for only highest-quality signals • Set to "B" for moderate selectivity • Set to "C" for all signals (maximum quantity) 🕐 SESSION INTELLIGENCE Why Sessions Matter: Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality. Session Definitions: Asian Session (18:00-03:00 ET) • Characteristics: Lower volatility, range-bound tendency, fewer institutional participants • Quality Score: 0.40 (40% of peak quality) • Strategy Implications: Fade extremes, expect ranges, smaller position sizes • Best For: Mean-reversion setups, accumulation/distribution identification London Session (03:00-12:00 ET) • Characteristics: European institutional activity, volatility pickup, trend initiation • Quality Score: 0.70 (70% of peak quality) • Strategy Implications: Watch for trend development, breakouts more reliable • Best For: Initial trend identification, structure breaks New York Session (08:00-17:00 ET) • Characteristics: Highest liquidity, US institutional activity, major moves • Quality Score: 0.95 (95% of peak quality) • Strategy Implications: Best environment for directional trades • Best For: Trend continuation, momentum plays London/NY Overlap (08:00-12:00 ET) • Characteristics: Peak liquidity, both European and US participants active • Quality Score: 1.0 (100%—maximum quality) • Strategy Implications: Highest probability for successful breakouts and trends • Best For: All signal types—this is prime time Off-Hours • Characteristics: Thin liquidity, erratic price action, gaps possible • Quality Score: 0.30 (30% of peak quality) • Strategy Implications: Avoid new positions, wider stops if holding • Best For: Waiting Smart Weekend Detection: AMWT properly handles the Sunday evening futures open: // Traditional (broken): isWeekend = dayofweek == saturday OR dayofweek == sunday // AMWT (correct): anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime) isWeekend = calendarWeekend AND NOT anySessionActive This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend." Session Transition Boosts: Certain session transitions create trading opportunities: • Asian → London transition: +15% confidence boost (volatility expansion likely) • London → Overlap transition: +20% confidence boost (peak liquidity approaching) • Overlap → NY-only transition: -10% confidence adjustment (liquidity declining) • Any → Off-Hours transition: Signal suppression recommended 📈 TRADE MANAGEMENT SYSTEM The Signal Spam Problem: Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance. Trade Lock Mechanism: Once a signal fires, the system enters a "trade lock" state: Trade Lock Duration: Configurable (default 30 bars) Early Exit Conditions: • TP3 hit (full target reached) • Stop Loss hit (trade failed) • Lock expiration (time-based exit) During lock: • No new signals of same type displayed • Opposite signals can override (reversal) • Trade status tracked in dashboard Target Levels: Each signal generates three profit targets based on ATR: TP1 (Conservative Target) • Default: 1.0 × ATR • Purpose: Quick partial profit, reduce risk • Action: Take 30-40% off position, move stop to breakeven TP2 (Standard Target) • Default: 2.5 × ATR • Purpose: Main profit target • Action: Take 40-50% off position, trail stop TP3 (Extended Target) • Default: 5.0 × ATR • Purpose: Runner target for trend days • Action: Close remaining position or continue trailing Stop Loss: • Default: 1.9 × ATR from entry • Purpose: Define maximum risk • Placement: Below recent swing low (longs) or above recent swing high (shorts) Invalidation Level: Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies: invalidation = entry - (ATR × INVALIDATION_MULT × 1.5) If price reaches invalidation, the current market interpretation is wrong—not just the trade. Visual Trade Management: During active trades, AMWT displays: • Entry arrow with grade label (▲A+, ▼B, etc.) • TP1, TP2, TP3 horizontal lines in green • Stop Loss line in red • Invalidation line in orange (dashed) • Progress indicator in dashboard Persistent Execution Markers: When targets or stops are hit, permanent markers appear: • TP hit: Green dot with "TP1"/"TP2"/"TP3" label • SL hit: Red dot with "SL" label These persist on the chart for review and statistics. 💰 PERFORMANCE TRACKING & STATISTICS Tracked Metrics: • Total Trades: Count of all signals that entered trade lock • Winning Trades: Signals where at least TP1 was reached before SL • Losing Trades: Signals where SL was hit before any TP • Win Rate: Winning / Total × 100% • Total R Profit: Sum of R-multiples from winning trades • Total R Loss: Sum of R-multiples from losing trades • Net R: Total R Profit - Total R Loss Currency Conversion System: AMWT can display P&L in multiple formats: R-Multiple (Default) • Shows risk-normalized returns • "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades • Best for comparing across different position sizes Currency Conversion (USD/EUR/GBP/JPY/INR) • Converts R-multiples to currency based on: - Dollar Risk Per Trade (user input) - Tick Value (user input) - Selected currency Example Configuration: Dollar Risk Per Trade: $100 Display Currency: USD If Net R = +4.2R Display: Net P&L: +$420.00 | 78 trades Ticks • For futures traders who think in ticks • Converts based on tick value input Statistics Reset: Two reset methods: 1. Toggle Reset • Turn "Reset Statistics" toggle ON then OFF • Clears all statistics immediately 2. Date-Based Reset • Set "Reset After Date" (YYYY-MM-DD format) • Only trades after this date are counted • Useful for isolating recent performance 🎨 VISUAL FEATURES Macro Channel: Dynamic regression-based channel showing market boundaries: • Upper/lower bounds calculated from swing pivot linear regression • Adapts to current market structure • Shows overall trend direction and potential reversal zones Chop Boxes: Semi-transparent overlay during high-chop periods: • Purple/orange coloring indicates dangerous conditions • Visual reminder to avoid new positions Confluence Heat Zones: Background shading indicating setup quality: • Darker shading = higher confluence • Lighter shading = lower confluence • Helps identify optimal entry timing EMA Ribbon: Trend visualization via moving average fill: • EMA 8/21/50 with gradient fill between • Green fill when bullish aligned • Red fill when bearish aligned • Gray when neutral Absorption Zone Boxes: Marks potential accumulation/distribution areas: • High volume + small body = absorption • Boxes drawn at these levels • Often act as support/resistance Liquidity Pool Lines: BSL/SSL levels with labels: • Dashed lines at liquidity clusters • "BSL" label above swing high clusters • "SSL" label below swing low clusters Six Professional Themes: • Quantum: Deep purples and cyans (default) • Cyberpunk: Neon pinks and blues • Professional: Muted grays and greens • Ocean: Blues and teals • Matrix: Greens and blacks • Ember: Oranges and reds 🎓 PROFESSIONAL USAGE PROTOCOL Phase 1: Learning the System (Week 1) Goal: Understand AMWT concepts and dashboard interpretation Setup: • Signal Mode: Balanced • Display: All features enabled • Grade Filter: C (see all signals) Actions: • Paper trade ONLY—no real money • Observe HMM state transitions throughout the day • Note when agents agree vs disagree • Watch chop detection engage and disengage • Track which grades produce winners vs losers Key Learning Questions: • How often do A+ signals win vs B signals? (Should see clear difference) • Which agent tends to be right in current market? (Check dashboard) • When does chop detection save you from bad trades? • How do signals near liquidity events perform vs signals in vacuum? Phase 2: Parameter Optimization (Week 2) Goal: Tune system to your instrument and timeframe Signal Mode Testing: • Run 5 days on Aggressive mode (more signals) • Run 5 days on Conservative mode (fewer signals) • Compare: Which produces better risk-adjusted returns? Grade Filter Testing: • Track A+ only for 20 signals • Track A and above for 20 signals • Track B and above for 20 signals • Compare win rates and expectancy Chop Threshold Testing: • Default (80%): Standard filtering • Try 70%: More aggressive filtering • Try 90%: Less filtering • Which produces best results for your instrument? Phase 3: Strategy Development (Weeks 3-4) Goal: Develop personal trading rules based on system signals Position Sizing by Grade: • A+ grade: 100% position size • A grade: 75% position size • B grade: 50% position size • C grade: 25% position size (or skip) Session-Based Rules: • London/NY Overlap: Take all A/A+ signals • NY Session: Take all A+ signals, selective on A • Asian Session: Only A+ signals with extra confirmation • Off-Hours: No new positions Chop Zone Rules: • Chop >70%: Reduce position size 50% • Chop >80%: No new positions • Chop <50%: Full position size allowed Phase 4: Live Micro-Sizing (Month 2) Goal: Validate paper trading results with minimal risk Setup: • 10-20% of intended full position size • Take ONLY A+ signals initially • Follow trade management religiously Tracking: • Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus • Calculate: Win rate by grade, by session, by chop level • Compare to paper trading (should be within 15%) Red Flags: • Win rate diverges significantly from paper trading: Execution issues • Consistent losses during certain sessions: Adjust session rules • Losses cluster when specific agent dominates: Review that agent's logic Phase 5: Scaling Up (Months 3-6) Goal: Gradually increase to full position size Progression: • Month 3: 25-40% size (if micro-sizing profitable) • Month 4: 40-60% size • Month 5: 60-80% size • Month 6: 80-100% size Scale-Up Requirements: • Minimum 30 trades at current size • Win rate ≥50% • Net R positive • No revenge trading incidents • Emotional control maintained 💡 DEVELOPMENT INSIGHTS Why HMM Over Simple Indicators: Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend. The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP." The Multi-Agent Evolution: Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way. The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection. Chop Detection Revelation: Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones. Liquidity Anchoring Discovery: Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals. The Grade System Impact: Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3. 🚨 LIMITATIONS & CRITICAL ASSUMPTIONS What AMWT Is NOT: • NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty. • NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment. • NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis. • NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate. Core Assumptions: 1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure. 2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals. 3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns. 4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation. Performs Best On: • Liquid Futures : ES, NQ, MNQ, MES, CL, GC • Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY • Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap) • Liquid Crypto : BTC, ETH on major exchanges Performs Poorly On: • Illiquid Instruments : Low volume stocks, exotic pairs • Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal) • Binary Event Days : Earnings, FDA approvals, court rulings • Manipulated Markets : Penny stocks, low-cap altcoins Known Weaknesses: • Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable. • Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance. • Complexity : More parameters than simple indicators. Requires understanding to use effectively. ⚠️ RISK DISCLOSURE Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses. AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results. Hidden Markov Model assumptions may not hold during: • Major news events disrupting normal market behavior • Flash crashes or circuit breaker events • Low liquidity periods with erratic price action • Algorithmic manipulation or spoofing Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear. Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing. Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception. By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes. "Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable." Initial Public Release Core Engine: • True Hidden Markov Model with online Baum-Welch learning • Viterbi algorithm for optimal state sequence decoding • 6-state market regime classification Agent System: • 3-Bandit consensus (Trend, Reversion, Structure) • Thompson Sampling with true Beta distribution sampling • Adaptive weight learning based on performance Signal Generation: • Quality-based confluence grading (A+/A/B/C) • Four signal modes (Aggressive/Balanced/Conservative/Institutional) • Grade-based visual brightness Chop Detection: • 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume) • 7 regime classifications • Configurable signal suppression threshold Liquidity: • Volume spike detection • Stop run (liquidity sweep) identification • BSL/SSL pool mapping • Absorption zone detection Trade Management: • Trade lock with configurable duration • TP1/TP2/TP3 targets • ATR-based stop loss • Persistent execution markers Session Intelligence: • Asian/London/NY/Overlap detection • Smart weekend handling (Sunday futures open) • Session quality scoring Performance: • Statistics tracking with reset functionality • 7 currency display modes • Win rate and Net R calculation Visuals: • Macro channel with linear regression • Chop boxes • EMA ribbon • Liquidity pool lines • 6 professional themes Dashboards: • Main Dashboard: Market State, Consensus, Trade Status, Statistics 📋 AMWT vs AMWT-PRO: This version includes all core AMWT functionality: ✓ Full Hidden Markov Model state estimation ✓ 3-Bandit Thompson Sampling consensus system ✓ Complete 5-factor chop detection engine ✓ All four signal modes ✓ Full trade management with TP/SL tracking ✓ Main dashboard with complete statistics ✓ All visual features (channels, zones, pools) ✓ Identical signal generation to PRO ✓ Six professional themes ✓ Full alert system The PRO version adds the AMWT Advisor panel—a secondary dashboard providing: • Real-time Market Pulse situation assessment • Agent Matrix visualization (individual agent votes) • Structure analysis breakdown • "Watch For" upcoming setups • Action Command coaching Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals. Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
Pine Script® indicator
by DskyzInvestments
2
Contrarian Period High & LowContrarian Period High & Low This indicator pairs nicely with the Contrarian 100 MA and can be located here: Overview The "Contrarian Period High & Low" indicator is a powerful technical analysis tool designed for traders seeking to identify key support and resistance levels and capitalize on contrarian trading opportunities. By tracking the highest highs and lowest lows over user-defined periods (Daily, Weekly, or Monthly), this indicator plots historical levels and generates buy and sell signals when price breaks these levels in a contrarian manner. A unique blue dot counter and action table enhance decision-making, making it ideal for swing traders, trend followers, and those trading forex, stocks, or cryptocurrencies. Optimized for daily charts, it can be adapted to other timeframes with proper testing. How It Works The indicator identifies the highest high and lowest low within a specified period (e.g., daily, weekly, or monthly) and draws horizontal lines for the previous period’s extremes on the chart. These levels act as dynamic support and resistance zones. Contrarian signals are generated when the price crosses below the previous period’s low (buy signal) or above the previous period’s high (sell signal), indicating potential reversals. A blue dot counter tracks consecutive buy signals, and a table displays the count and recommended action, helping traders decide whether to hold or flip positions. Key Components Period High/Low Levels: Tracks the highest high and lowest low for each period, plotting red lines for highs and green lines for lows from the bar where they occurred, extending for a user-defined length (default: 200 bars). Contrarian Signals: Generates buy signals (blue circles) when price crosses below the previous period’s low and sell signals (white circles) when price crosses above the previous period’s high, designed to capture potential reversals. Blue Dot Tracker: Counts consecutive buy signals (“blue dots”). If three or more occur, it suggests a stronger trend, with the table recommending whether to “Hold Investment” or “Flip Investment.” Action Table: A 2x2 table in the bottom-right corner displays the blue dot count and action (“Hold Investment” if count ≥ 4, else “Flip Investment”) for quick reference. Mathematical Concepts Period Detection: Uses an approximate bar count to define periods (1 bar for Daily, 5 bars for Weekly, 20 bars for Monthly on a daily chart). When a new period starts, the previous period’s high/low is finalized and plotted. High/Low Tracking: Highest high (periodHigh) and lowest low (periodLow) are updated within the period. Lines are drawn at these levels when the period ends, starting from the bar where the extreme occurred (periodHighBar, periodLowBar). Signal Logic: Buy signal: ta.crossunder(close , prevPeriodLow) and not lowBroken and barstate.isconfirmed Sell signal: ta.crossover(close , prevPeriodHigh) and not highBroken and barstate.isconfirmed Flags (highBroken, lowBroken) prevent multiple signals for the same level within a period. Blue Dot Counter: Increments on each buy signal, resets on a sell signal or if price exceeds the entry price after three or more buy signals. Entry and Exit Rules Buy Signal (Blue Circle): Triggered when the price crosses below the previous period’s low, suggesting a potential oversold condition and buying opportunity. The signal appears as a blue circle below the price bar. Sell Signal (White Circle): Triggered when the price crosses above the previous period’s high, indicating a potential overbought condition and selling opportunity. The signal appears as a white circle above the price bar. Blue Dot Tracker: Increments blueDotCount on each buy signal and sets an entryPrice on the first buy. Resets on a sell signal or if price exceeds entryPrice after three or more buy signals. If blueDotCount >= 3, the table suggests holding; if >= 4, it reinforces “Hold Investment.” Exit Rules: Exit a buy position on a sell signal or when price exceeds the entry price after three or more buy signals. Combine with other tools (e.g., trendlines, support/resistance) for additional confirmation. Always apply proper risk management. Recommended Usage The "Contrarian Period High & Low" indicator is optimized for daily charts but can be adapted to other timeframes (e.g., 1H, 4H) with adjustments to the period bar count. It excels in markets with clear support/resistance levels and potential reversal zones. Traders should: Backtest the indicator on their chosen asset and timeframe to validate signal reliability. Combine with other technical tools (e.g., moving averages, Fibonacci levels) for stronger trade confirmation. Adjust barsPerPeriod (e.g., ~120 bars for Weekly on hourly charts) based on the chart timeframe and market volatility. Monitor the action table to guide position management based on blue dot counts. Customization Options Period Type: Choose between Daily, Weekly, or Monthly periods (default: Monthly). Line Length: Set the length of high/low lines in bars (default: 200). Show Highs/Lows: Toggle visibility of period high (red) and low (green) lines. Max Lines to Keep: Limit the number of historical lines displayed (default: 10). Hide Signals: Toggle buy/sell signal visibility for a cleaner chart. Table Display: A fixed table in the bottom-right corner shows the blue dot count and action, with yellow (Hold) or green (Flip) backgrounds based on the count. Why Use This Indicator? The "Contrarian Period High & Low" indicator offers a unique blend of support/resistance visualization and contrarian signal generation, making it a versatile tool for identifying potential reversals. Its clear visual cues (lines and signals), blue dot tracker, and actionable table provide traders with an intuitive way to monitor market structure and manage trades. Whether you’re a beginner or an experienced trader, this indicator enhances your ability to spot key levels and time entries/exits effectively. Tips for Users Test the indicator thoroughly on your chosen market and timeframe to optimize settings (e.g., adjust barsPerPeriod for non-daily charts). Use in conjunction with price action or other indicators for stronger trade setups. Monitor the action table to decide whether to hold or flip positions based on blue dot counts. Ensure your chart timeframe aligns with the selected period type (e.g., daily chart for Monthly periods). Apply strict risk management to protect against false breakouts. Happy trading with the Contrarian Period High & Low indicator! Share your feedback and strategies in the TradingView community!
Pine Script® indicator
by chuckaschultz