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Analisi trend

VWAP Bias (STRONG ONLY) + Alerts (Time Window)VWAP Bias + NO TRADE Discipline Label Clean, execution-focused indicator that removes decision noise. Shows LONG / SHORT bias based on price vs VWAP, upgraded to STRONG or WEAK using VWAP slope and EMA(9/20) alignment. A separate NO TRADE label appears when conditions are weak or neutral, enforcing discipline and preventing low-quality entries. Designed for day trading VWAP pullbacks and momentum, especially on 1m–5m charts. No oscillators, no clutter — just directional clarity and risk control.
Indicatore Pine Script®
di NetJacobsson
MACD Matrix: Angle & SettlementThis indicator is a comprehensive Multi-Timeframe (MTF) Dashboard designed for technical traders who rely on MACD not just for crossovers, but for Momentum Angle and Settlement (Hooks). Instead of cluttering your screen with 5 different MACD charts, this Matrix calculates the math in the background and presents a clean "Heads-Up Display" of the MACD state across your specific timeframes (Default: 3m, 15m, 1h, 4h, 16h). The Concept: "Angle Settlement" Standard MACD indicators only show you when a cross happens. By then, the move is often halfway over. This script focuses on the Angle (Slope) of the MACD line to predict turns before they happen: Steep Angle: Momentum is accelerating. (Strong Trend) Settling Angle: The slope is flattening out. The MACD line is "hooking." (Reversal/Cross Imminent) Dashboard Columns Explained TF (Timeframe): Auto-formats your settings into readable text (e.g., "240" becomes "4h"). Zone: > 0 (Green): MACD is above the Zero Line (Bullish Trend context). < 0 (Red): MACD is below the Zero Line (Bearish Trend context). Cross: PCO (Green): Positive Crossover (MACD > Signal). NCO (Red): Negative Crossover (MACD < Signal). Deg (°): The calculated mathematical angle of the MACD line. Positive (+): Momentum is rising. Negative (-): Momentum is falling. State (The Strategy): STEEP (Bright Color): The angle is increasing. Do not trade against this momentum. SETTLE (Dim Color): The angle is decreasing compared to the previous bar. The momentum is "cooling off," often signaling a "Hook" or an upcoming crossover. Settings & Customization Custom Timeframes: You can freely change TF-1, TF-2, etc., in the settings. The table labels will auto-update (e.g., if you change 4h to 1D, the table will display "1D"). MACD Lengths: Fully customizable (Default 12, 26, 9). Angle Sensitivity: A multiplier to calibrate the "Degrees" to your specific asset class (Crypto, Forex, or Indices). If angles look too small, increase this value.
Indicatore Pine Script®
di PratikKharat1990
Sessions and Killzones [Tradeuminati]Tradeuminati – Sessions & Killzones is a New York local time based session toolkit designed for traders who want clean, objective session structure on their chart: session boundaries, killzones, session highs/lows, and previous day levels plus a live “liquidity taken” checklist. Key Features 1) Sessions (New York Time) London Session (0:00 – 6:00 NY) - Vertical start/end lines - Live session High and Low tracking during the session - High/Low levels extend until 16:00 NY - Labels: Ls - H and Ls - L - Option to display only the current day Asia Session (Previous Day, 18:00 – 00:00 NY) - Vertical start/end lines for the previous day session - Live session High and Low tracking - High/Low levels extend into the next day until 16:00 NY - Labels: As - H and As - L - Option to display only the current day 2) Killzones (New York Time) London Killzone: 2:00 – 5:00 NY - Optional DAX-only mode: If enabled, DAX uses 3:00 – 5:00 NY (DAX opening), while other assets remain 2:00 – 5:00 NY New York Killzone (auto-adjust by asset type) - Indices: 9:30 – 11:00 NY - Other assets (FX / Commodities / Crypto): 7:00 – 10:00 NY New York PM Killzone: 14:00 – 15:00 NY (all assets) ll killzone lines are placed from the start of the NY day, so you can see upcoming killzones in advance (not only after candles appear). 3) Previous Day High / Low (PDH / PDL) - Automatically calculates the full previous NY day range (00:00 – 23:59 NY) - Plots PDH and PDL into the current day - Labels: PDH and PDL 4) Live “Liquidity Taken” Table - A compact table in the bottom-left shows whether price has: - swept Asia High / Asia Low - swept London High / London Low - taken PDH / PDL A green checkmark appears instantly once a level is broken. Customization Fully adjustable colors, widths, and line styles for: - Session vertical lines - Session high/low lines - Killzones - PDH/PDL Adjustable label size Day filtering options (current day only) ----- Disclaimer This indicator is for educational and technical analysis purposes only. It does not constitute financial or investment advice. Trading involves risk.
Indicatore Pine Script®
di DonauTrading
Multi KI Agenten Strategie (Final V2)What's included in the Pine Script (Technical Analysis) These features are mathematically implemented in the script and function as "agent logic": • Trend Following: Integrated via EMAs (50, 100, 200). • Volume Analysis: An agent checks for institutional volume spikes. • Supply & Demand: Zones are calculated based on price extremes. • RSI & Fibonacci: Both are built in as decision criteria for the agents. • Controlling AI: The "veto logic" in the code acts as a controlling instance, blocking signals if the risk is too high or divergences exist. • Alerts: The "LONG" and "SHORT" alerts are only triggered after approval by the controlling mechanism.
Strategia Pine Script®
di sven_kittelmann
HTF Double BOS + Inducement (XAU) ebenThis indicator is a market structure and inducement scanner designed to assist discretionary traders. It identifies: • Higher-timeframe market regime using a double Break of Structure (BOS) on the Daily and 4H timeframes. • Lower-timeframe Break of Structure (BOS). • Valid inducement based on a minimum 70% retracement rule. The script is intended to be used as a confirmation and alert tool, not as a standalone buy/sell system. ⸻ How It Works 1. The indicator first confirms directional bias using Daily and 4H BOS alignment. 2. When higher-timeframe bias is valid, it scans the active chart timeframe for: • a Break of Structure, • followed by inducement using a retracement-based rule. 3. When conditions align, the script displays a visual marker and can trigger an alert. ⸻ Important Notes • This indicator does not predict price. • It does not automatically execute trades. • It should be used in conjunction with proper risk management and personal analysis. • Signals may appear less frequently due to strict filtering logic. ⸻ Recommended Usage • Best suited for trend-following strategies. • Works well on Gold (XAUUSD) and other liquid markets. • Designed for use on 30m, 15m, and 5m charts. • Alerts should be treated as areas of interest, not direct trade instructions. ⸻ Disclaimer This script is provided for educational and analytical purposes only. The author is not responsible for trading losses. Use at your own risk.
Indicatore Pine Script®
di hani_s
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.
Indicatore Pine Script®
di NeuraAlgo
Sameer Bandhara AlertsThis Sameer Bandhara (SB Trader) indicator is a dynamic trailing stop-loss system based on the Average True Range (ATR). Here's a comprehensive breakdown: It uses ATR to create an adaptive trailing stop that adjusts to market volatility, generating buy/sell signals when price breaks through this dynamic stop level. Forex/Stocks: Key Value 1.5-2.5, ATR Period 14-20 Crypto: Key Value 2.0-3.0 (higher volatility) Timeframes: 1H and above (reduces noise)
Indicatore Pine Script®
di sameer-1
1
RSI Divergence (No pivots, delta + cooldown)RSI Divergence (No Pivots, Delta + Cooldown) This indicator detects classic RSI divergence without using pivots/fractals and without looking into future bars. It is designed to behave closer to “human eyeballing” by comparing current extremes to the last N bars, and it triggers signals only on bar close (non-repainting after the candle closes). Logic Bearish divergence: Price makes a new lookback high (relative to the previous lookback bars), while RSI does not make a new high. A signal is printed only if RSI is at least Δ RSI points below the previous RSI high over the same lookback window. Bullish divergence: Price makes a new lookback low (relative to the previous lookback bars), while RSI does not make a new low. A signal is printed only if RSI is at least Δ RSI points above the previous RSI low over the same lookback window. Inputs RSI Length: RSI period. Lookback (bars): Number of past bars used to define “new high/low” for both price and RSI. Use High/Low (else Close): Choose whether price extremes are based on High/Low or Close. RSI delta (points): Minimum RSI gap required to confirm the divergence (reduces weak/noisy signals). Cooldown after signal (bars): After any signal, the indicator suppresses new signals for the next X bars to reduce alert/label spam. Alerts The script includes two alert conditions: Bearish divergence (delta + cooldown) Bullish divergence (delta + cooldown) Recommended alert setting: Once per bar close.
Indicatore Pine Script®
di inozemtsev999
Smart VWAP SignalsSmart VWAP Signals Smart VWAP Signals is an advanced indicator based on the VWAP Intraday V2 strategy, optimized using Grid Search to maximize performance. ⸻ 🎯 Key Features Trading Modes • BOTH: Combines mean reversion (Separator) and trend-following (KISS) signals • SEPARATOR: Mean reversion signals only, when price deviates significantly from VWAP • KISS: Trend-following signals only, aligned with VWAP direction ⸻ 🚦 Intelligent Traffic Light System • 🟢 GREEN: High Profit Factor – trade with confidence • 🟡 YELLOW: Medium Profit Factor – trade with caution • 🔴 RED: Low Profit Factor – avoid new entries ⸻ 🛡️ Risk Management • ATR-based Stop Loss with configurable maximum limit • Flexible Take Profit options: • VWAP target • Fixed Risk/Reward ratio • ATR multiple • Automatic stop-day after consecutive losses ⸻ 🔍 Configurable Filters • Signal cooldown between trades • Volatility filter (minimum ATR threshold) • Trend filter (EMA 200) • Volume filter • Multi-timeframe confirmation ⸻ 📊 Visualization & Analytics • Real-time statistics panel • VWAP with deviation bands • Trade history with WIN / LOSS percentages • Entry-to-exit lines • Fully customizable colors ⸻ ⚙️ Optimized Default Parameters Optimized via Grid Search, achieving: • ROI: 322% • Profit Factor: 1.97 • Win Rate: 68.4%
Indicatore Pine Script®
di tomasgres2911
[codapro] Tenkan Cloud Signals Cloud in the Skys — Tenkan Altitude Signals Above the Kumo Description: This is not your average Ichimoku script — this is “Cloud in the Skys”, a reimagined way to interpret the Tenkan line as an airplane navigating altitude around the Kumo cloud layer. Visual Metaphor Explained: Tenkan = Airplane The fast-reacting Conversion Line becomes your flight path. Cloud (Kumo) = Noise / Airspace The Ichimoku cloud is your visual weather system. When the plane (Tenkan) is: Above the cloud → Clear skies, likely breakout, nothing overhead Inside the cloud → Turbulence zone, indecision, avoid trading Below the cloud → Descending, seeing ground only, bearish sentiment This script helps you see trend structure like a pilot sees airspace — visually, directionally, and with awareness of turbulence zones. What It Includes: Tenkan (Conversion) and Kijun (Base) line calculations Full Kumo Cloud (Senkou A & B), with customizable displacement Buy/Sell Flags based on Kijun crossing the forward-displaced Span B Only plotted after a user-defined number of confirming closes Full visual controls: cloud fill, line colors, flag display toggle How to Use It: Long Bias: When Tenkan rises above the cloud and Buy flag confirms — sky’s clear Short Bias: When Tenkan descends and Sell flag confirms — plane is losing lift Stay Out: If Tenkan is inside the cloud, wait — this is chop/noise Pair this script with price action or volume confirmation for better clarity. Especially effective in trend-following or breakout strategies on mid-to-longer timeframes. Disclaimer: This tool was created using the CodaPro Pine Script indicator design system — a modular architecture for building visual signal overlays and automated alerts. It is provided for educational and informational purposes only and is not financial advice. Always test thoroughly before using in live market conditions.
Indicatore Pine Script®
di ArisCodes
1
TrendSurfer Lite TrendSurfer Lite ⚡ Advanced Multi-Signal Trading Indicator for Precision Market Analysis TrendSurfer Pro LITE is a comprehensive trading system combining multiple technical analysis tools into one powerful indicator. Designed for traders seeking high-probability setups with customizable filters. Key Features: 📊 Core Signals Triangle Signals (▲▼): Volume-weighted momentum entries with 10-level volume scoring Master Trend System (△▽): Multi-EMA confirmation with RSI validation Order Blocks (🟩🟥): Smart money institutional zones with rejection detection Take Profit System (🎯): 8-indicator confluence system (RSI, Stochastic, Supertrend, CCI, MACD, BB, EMA Cross, Price Action) 🎯 Rejection Signals Master Trend Rejections: Dynamic support/resistance from trend lines EMA750 Rejections (White "R"): Major trend filter bounces VWAP Rejections (Pink "W"): Institutional level reactions Butterworth Filter Rejections (🟡): Advanced smoothing algorithm reversals Session Rejections (⚡): Tokyo/London/NY session high/low bounces Session Midline Rejections (Orange "M"): Half-range mean reversion 🌍 Session Analysis Tokyo Session (💴): Asian market range with automatic extensions London Session (💶): European volatility zones New York Session (💵): US market key levels Auto-adjusting timezone with UTC offset support 🔧 Advanced Filters EMA750 Master Filter: Global trend alignment for all signals VWAP Filter: Institutional bias confirmation Yellow Box Filter (🟨): Consolidation zone proximity detection 3 Time Filters: Customizable trading windows with visual backgrounds Volume Filter: Signal strength validation (6-10 scale) 📈 Visual Tools VWAP Purple Candles: Special candle coloring for VWAP crosses above EMA750 Stochastic-based Candle Colors: Overbought/oversold visual cues Previous Day Close Line: Key reference level Master Trend Table: Real-time multi-indicator dashboard ⚙️ Customization Full color customization for all elements Adjustable line thickness and transparency Configurable alert system for every signal type 19 independent alert conditions Best For: Intraday scalping and swing trading Multi-timeframe analysis Confluence-based trading strategies Institutional level detection Version 1.0 | Clean interface | Maximum flexibility | Professional-grade signals
Indicatore Pine Script®
di jake_theboss
All-in-one trend clarityTrendLens is a multi-layer, all-in-one overlay indicator designed to visually detect and filter market direction — not a buy/sell strategy. It highlights early trend shifts based on candle behavior, then supports that view using Pivot High/Low structure, three customizable EMAs, and a visible daily session window to focus on active market hours. What’s included (All inside one indicator) Structural Trend Candles If price closes above the highest high of the previous N bars → candle turns white (bullish structural breakout). If price closes below the lowest low of the previous N bars → candle turns black (bearish structural breakdown). Pivot High / Pivot Low Markers Detects swing highs/lows using adjustable left/right bars (default 7) and plots small gray triangle markers on the chart. Active Session Window Highlights a fixed daily time window (default 06:00–18:00 UTC) with a transparent green background to visually mark the active trading session. 3 Customizable EMAs EMA Fast (default 10) EMA Mid (default 20) EMA Long (default 100) Each EMA supports custom length, source, color, and thickness. How to use it Use white/black candles as a quick trend filter and early structure shift cue. Use EMA100 as the main trend bias reference; use EMA10/EMA20 positioning to gauge momentum. Use Pivot High/Low to spot structure levels for potential support/resistance and risk management. Enable the session highlight to focus analysis on high-activity hours. Disclaimer This indicator is a technical analysis helper, not a trading strategy. It does not provide buy/sell recommendations. You are responsible for your own trade decisions and risk management.
Indicatore Pine Script®
di SmartChartX
Strength Relative to XXX [Hysteresis Smoothed]Strength Relative to XXX █ OVERVIEW This versatile indicator measures the relative strength of the current charted asset against any user-selected benchmark symbol (e.g., BTC, ETH, SP:SPX, TVC:GOLD, or any other asset). Green fill = Current asset outperforming the benchmark (bullish relative strength). Red fill = Current asset underperforming the benchmark (bearish relative weakness). Perfect for rotation strategies across crypto, stocks, forex, and commodities — quickly identify assets gaining momentum edge over a chosen benchmark. █ HOW IT WORKS • Relative Ratio : Calculates current close / benchmark close for normalized comparison. • Smoothing : Applies a Simple Moving Average (SMA) to the ratio (adjustable length). • Oscillator : Plots deviation from the SMA, centered around zero. • Hysteresis Enhancement : Adds a small relative threshold (~0.03% default) to prevent rapid color flips from minor noise. Color persists until a convincing cross — stable blocks without lag. █ FEATURES & INPUTS • Compare to : Symbol input for any benchmark (match exchange for accuracy). • MA Length : Smoothing period (default 10). • Relative Hysteresis Threshold : Noise filter strength (default 0.0003; tweak for responsiveness vs. stability). █ USAGE TIPS • Apply to ALT/BTC pairs for crypto rotations, stocks vs. SP:SPX for sector strength, or any custom comparison. • Works on all timeframes — ideal for short-term scans on 4H/daily. • Green zones = potential outperformance; red = caution. • Combine with volume or momentum for confluence. This refined relative strength oscillator delivers clean, reliable visuals in volatile markets.
Indicatore Pine Script®
di ThroatClogger
Volume-Weighted RSI [VWRSI 2D Pro]A modular, volume-weighted RSI indicator built for clarity and control. ✅ Profile-based auto modes (Scalping → Macro) ✅ Toggleable Buy/Sell signals with strict mode ✅ RSI MA overlays for smoother entries Buy Signal RSI crosses above RSI MA RSI > 50 (or > 55 in strict mode) Sell Signal RSI crosses below RSI MA RSI < 50 (or < 45 in strict mode) Strict mode filters out weak signals for higher conviction entries. Volatility-Adaptive RSI Thresholds: Traditional RSI uses static levels (70/30). VWRSI Pro replaces these with dynamic bands: 🔹dynHigh = mean + mult × deviation 🔹 dynLow = mean − mult × deviation Technical write-up can be found here: github.com
Indicatore Pine Script®
di followmytradingjournal
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.
Indicatore Pine Script®
di DskyzInvestments
2
Trend Harmony🚀 Trend Harmony: Multi-Timeframe Momentum & Trend Dashboard Trend Harmony is a sophisticated multi-timeframe (MTF) analysis tool designed to help traders identify high-probability setups by spotting "Market Harmony." Instead of flipping through charts, this indicator synthesizes RSI momentum and EMA trend structures from four different time horizons into a single, intuitive dashboard. 🔍 How It Works The core philosophy of this indicator is that the most powerful moves happen when short-term momentum aligns with long-term trend structure. The script tracks four user-defined timeframes simultaneously. 1. The Trend Scoring Engine The indicator evaluates the relationship between a Fast EMA (default 20) and a Slow EMA (default 50) across all active timeframes. Bullish Alignment: Fast EMA > Slow EMA. Bearish Alignment: Fast EMA < Slow EMA. 2. The Harmony Summary At the bottom of the dashboard, the "Summary" status calculates the total "Harmony" of the market: 🚀 FULL BULL HARMONY: All selected timeframes are in a bullish trend. 📉 FULL BEAR HARMONY: All selected timeframes are in a bearish trend. ⚠️ CAUTION (Overbought/Oversold): Triggered when the market is in "Full Harmony" but RSI levels suggest the price is overextended (>70 or <30). This warns you not to "chase" the trade. Neutral/Mixed: Timeframes are in conflict (e.g., 15m is bullish but Daily is bearish). 🛠 Key Features Unified RSI Pane: View four RSI lines on one chart to spot divergences or "clusters" where all timeframes bottom out at once. Dynamic Table: Real-time tracking of: Price vs EMA: Instant visual (▲/▼) showing if price is above/below your key averages. Smart RSI Coloring: RSI values turn Green during "Power Zones" (0–30 or 50–70) and Red otherwise. Full Customization: Change timeframes (1m, 5m, 1H, D, etc.), EMA lengths, and RSI parameters to fit your strategy. 📈 Trading Strategy Tips Wait for the Sync: The "Full Harmony" status is your signal that the "tide" is moving in one direction. Look for long entries when the status is Green and short entries when it is Red. The Pullback Entry: When the summary says "Caution (Overbought)," wait for the RSI lines to cool down toward the 50 level before entering the trend again. RSI Clustering: When all four RSI lines converge at extreme levels (30 or 70), a massive volatility expansion is usually imminent.
Indicatore Pine Script®
di ebecihalil
TrintityTrendIntroducing TrinityTrend A multi-signal indicator combining: Candle TrendStrength SuperTrend logic TTM Squeeze detection Built for clarity, momentum, and volatility awareness—across any timeframe. TrendStrength Mode Candle coloring reflects directional conviction. Strong uptrend Strong downtrend Neutral or indecisive Helps traders stay with momentum and avoid chop. SuperTrend Overlay SuperTrend Logic Dynamic trailing stop based on volatility. 🟩 Price above = bullish bias 🟥 Price below = bearish bias Great for swing entries and exits. TTM Squeeze Detection TTM Squeeze Mode Detects compression zones before breakout. Squeeze on = buildup (You can change the color of this) Pairs well with TrendStrength for timing entries. Multi-Timeframe Versatility Multi-Timeframe Ready: Intraday scalping Daily swing setups Weekly macro bias Toggle modes to match your strategy
Indicatore Pine Script®
di followmytradingjournal
Vortex Trend Matrix [JOAT]Vortex Trend Matrix - Multi-Factor Trend Confluence System Introduction and Purpose Vortex Trend Matrix is an open-source overlay indicator that combines Ichimoku-style equilibrium analysis with the Vortex Indicator to create a comprehensive trend confluence system. The core problem this indicator solves is that single trend indicators often give conflicting signals. Price might be above a moving average but momentum might be weakening. This indicator addresses that by combining five different trend factors into a single composite score, making it easy to identify when multiple factors align for high-probability trend trades. Why These Components Work Together Each component measures trend from a different perspective: 1. Cloud Position - Price above/below the equilibrium cloud indicates overall trend bias. The cloud acts as dynamic support/resistance. 2. TK Relationship - Conversion line vs Base line (like Tenkan/Kijun in Ichimoku). Conversion above Base = bullish momentum. 3. Lagging Span - Current price compared to price N bars ago. Confirms whether current move has follow-through. 4. Vortex Indicator - VI+ vs VI- measures directional movement strength. Provides momentum confirmation. 5. Base Direction - Whether the base line is rising or falling. Indicates medium-term trend direction. How the Trend Score Works float trendScore = 0.0 // Cloud position (+2/-2) trendScore += aboveCloud ? 2.0 : belowCloud ? -2.0 : 0.0 // TK relationship (+1/-1) trendScore += conversionLine > baseLine ? 1.0 : conversionLine < baseLine ? -1.0 : 0.0 // Lagging span (+1/-1) trendScore += laggingBull ? 1.0 : laggingBear ? -1.0 : 0.0 // Vortex (+1.5/-1.5) trendScore += vortexBull ? 1.5 : vortexBear ? -1.5 : 0.0 // Base direction (+0.5/-0.5) trendScore += baseDirection * 0.5 Score ranges from approximately -6 to +6: - +4 or higher = STRONG BULL - +2 to +4 = BULL - -2 to +2 = NEUTRAL - -4 to -2 = BEAR - -4 or lower = STRONG BEAR Signal Types TK Cross Up/Down - Conversion line crosses Base line (momentum shift) Base Direction Change - Base line changes direction (medium-term shift) Strong Bull/Bear Trend - Score reaches +4/-4 (high confluence) Dashboard Information Trend - Overall status with composite score Cloud - Price position (ABOVE/BELOW/INSIDE) TK Cross - Conversion vs Base relationship Lagging - Lagging span bias Vortex - VI+/VI- relationship VI+/VI- - Individual vortex values How to Use This Indicator For Trend Following: 1. Enter long when trend score reaches +4 or higher (STRONG BULL) 2. Enter short when trend score reaches -4 or lower (STRONG BEAR) 3. Use cloud as dynamic support/resistance for entries For Momentum Timing: 1. Watch for TK Cross signals for entry timing 2. Base direction changes indicate medium-term shifts 3. Vortex confirmation adds conviction For Risk Management: 1. Exit when trend score drops to neutral 2. Use cloud edges as stop-loss references 3. Reduce position when score weakens Input Parameters Conversion Period (9) - Fast equilibrium line Base Period (26) - Slow equilibrium line Lead Span Period (52) - Cloud projection period Displacement (26) - Cloud and lagging span offset Vortex Period (14) - Period for vortex calculation VI+ Strength (1.10) - Threshold for strong bullish vortex VI- Strength (0.90) - Threshold for strong bearish vortex Timeframe Recommendations 4H-Daily: Best for equilibrium-based analysis 1H: Good for intraday trend following Lower timeframes may require adjusted periods Limitations Equilibrium calculations have inherent lag Cloud displacement means signals are delayed Works best in trending markets May whipsaw in ranging conditions Open-Source and Disclaimer This script is published as open-source under the Mozilla Public License 2.0 for educational purposes. This indicator does not constitute financial advice. Trend analysis does not guarantee profitable trades. Always use proper risk management. - Made with passion by officialjackofalltrades
Indicatore Pine Script®
di officialjackofalltrades
MA 50/200This MA 50/200 indicator is a classic TradingView overlay that plots the 50-period Simple Moving Average (SMA) in solid green and the 200-period SMA in solid red directly on the price chart. It highlights major trend-reversal signals: A Golden Cross occurs when the faster 50-period SMA crosses above the slower 200-period SMA, often interpreted as a bullish signal suggesting potential upward momentum. This is marked by a prominent green cross symbol (linewidth 5) plotted at the level of the 200 SMA on the bar where the crossover happens. A Death Cross occurs when the 50-period SMA crosses below the 200-period SMA, often seen as a bearish signal indicating potential downward momentum. This is marked by a red cross symbol (slightly translucent for subtlety) at the 200 SMA level on the crossover bar. The layout keeps the chart clean and focused: continuous thick lines for the moving averages with clear, oversized cross markers only at crossover points to make Golden and Death Cross events instantly visible without clutter.
Indicatore Pine Script®
di CryptoHitchhiker