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The Hunting GroundsLiquid Hunter - The Hunting Grounds Professional-grade reversal detection system designed for identifying high-probability entry zones. Overview The Hunting Grounds utilizes a proprietary framework, we call SBI (Snap Back Index) to identify extreme market conditions where price reversals are statistically more likely to occur. The indicator visualizes these zones through dynamic cloud formations and precision signal markers. Key Features 📊 Dual-Strength Signal System EXTREME Signals (🔥): Highest-probability reversal zones - rare but powerful MEDIUM Signals (💎/⚠️): Secondary reversal opportunities with solid statistical edge ☁️ Dynamic Cloud Visualization Clouds automatically form around price during extreme conditions Color-coded by signal strength and direction Adjustable size and transparency for personal preference Adapts to market volatility 🎨 Signal Types 🔥 EXTREME LONG (Green): Major oversold reversal zone 💎 MEDIUM LONG (Cyan): Secondary oversold opportunity 🔥 EXTREME SHORT (Red): Major overbought reversal zone ⚠️ MEDIUM SHORT (Yellow): Secondary overbought opportunity How It Works The indicator employs a sophisticated multi-layer system that processes price action, volume momentum, and volatility to identify market extremes. When conditions align, visual clouds appear to highlight the reversal zone, accompanied by precise entry markers. The underlying calculation methodology is proprietary and optimized through extensive back-testing across multiple timeframes and asset classes. Recommended Usage Best Timeframes: Works on small timeframes for scalping ; 15m-4H recommended for swing trading Asset Classes: Crypto, Forex, Stocks, Indices Strategy: Mean reversion, counter-trend entries, liquidation hunting Risk Management: Always use stop losses; EXTREME signals offer tighter stops Customization Options Signal direction filter (LONG only, SHORT only, or Both) Signal strength filter (EXTREME only, or include MEDIUM) Cloud display toggle and size adjustment Transparency control for visual preference Built-in alert system for all signal types What Makes This Different Unlike standard indicators, SBI is specifically calibrated to identify institutional moves and extreme market exhaustion. The cloud visualization provides clear, actionable entry zones rather than abstract numerical values. Note: This indicator does not repaint. All signals are confirmed in real-time and suitable for live trading. ⚠️ Disclaimer This indicator is a tool for technical analysis and should be used as part of a complete trading strategy. Past performance does not guarantee future results. Always practice proper risk management.
Pine Script® indicator
by Liquid-Hunter
VuManChu Filtered OverlayVuManChu Filtered Overlay is a price-overlay signal tool inspired by VuManChu Cipher B. Instead of plotting the full oscillator in a separate pane, this script focuses on generating clean long/short signals directly on the chart, combining WaveTrend, Money Flow–style momentum, and an adjustable overbought/oversold threshold. Under the hood, the script builds a smoothed “Inertia Wave” using a normalized (close–open)/(high–low) money-flow proxy and a long SMA. This is used together with a classic WaveTrend (wt1 / wt2) calculation. Signals are only triggered when: WaveTrend lines cross (wt1 vs wt2), The cross direction matches the expected bias Bull: cross up from below, WaveTrend below zero Bear: cross down from above, WaveTrend above zero The custom money-flow curve (rsiMFI) confirms direction Bull: rsiMFI > 0 Bear: rsiMFI < 0 The WaveTrend line is beyond a user-defined OS/OB magnitude (Wavetrendtrigger), so only meaningful extremes are considered. The “VuManChu WaveTrend OS/OB threshold (+/-)” input lets you control how aggressive the signals are: Lower values (e.g. 5–10) → more frequent, more sensitive signals Higher values (e.g. 40–60) → fewer signa ls, focused on strong exhaustion moves Bullish and bearish opportunities are plotted as green and red dots on the candles, and corresponding alerts are fired: 🟢 Optimized VuManChu LONG signal detected on timeframe: X 🔴 Optimized VuManChu SHORT signal detected on timeframe: X This script is meant as a filter / confirmation layer, not a standalone system. For best results, combine it with your own trend, volume, or higher-timeframe context. This is not financial advice and should be used for educational and experimental purposes only.
Pine Script® indicator
by BTraderMS
Ata Low rsi macd aomacd stochastic and divergensesBrief Description of the Script The script is a multi‑indicator trading tool for the TradingView platform (Pine Script v5) that combines several technical analysis elements to help traders identify market trends, potential reversals, and entry/exit points. эту версию скрипта не обновляю. для получения обновлений в лс. Key features: Multiple Oscillators The user can select one of four oscillators to display: RSI (Relative Strength Index) — identifies overbought/oversold conditions; Stoch (Stochastic Oscillator) — detects potential reversals via %K and %D line interactions; MACD (Moving Average Convergence/Divergence) — shows trend direction and momentum shifts; AO+MACD — combines Awesome Oscillator (AO) for momentum with MACD for trend confirmation. Divergence Detection Identifies four types of price‑oscillator divergences: Bullish regular (price lows vs. higher oscillator lows); Bullish hidden (higher price lows vs. lower oscillator lows); Bearish regular (price highs vs. lower oscillator highs); Bearish hidden (lower price highs vs. higher oscillator highs). Divergences are marked on the chart with labels and lines. Customizable Parameters Users can adjust: Oscillator periods (e.g., RSI length, Stoch K/D smoothing, MACD fast/slow/signal lengths); Source prices (close, high, low, etc.); Visual settings (colors, line widths, label styles); Divergence sensitivity (minimum bars between swing points). Trend and Volatility Analysis EMA crossover (fast/slow) to determine trend direction; ATR‑based volatility score (1–5 scale); RSI‑derived trend strength (1–50 scale); ADX filter to confirm trend strength (>20). Additional Signals Awesome Oscillator “Tea Saucer” patterns for potential long/short entries; Fibonacci‑Bollinger bands to spot price deviations and reversal zones; Volume filter to confirm reversals; Session timing table (optional) showing active/upcoming market sessions (Asia, London, NYSE, etc.). Visual Outputs Plots for selected oscillator (RSI, Stoch, MACD, or AO); Shaded zones (e.g., RSI overbought/oversold areas); Divergence lines and labels (color‑coded by type); Reversal “circles” (blue for bullish, red for bearish); Summary label with trend direction, volatility, and strength; Optional session timing table. Purpose: To provide a comprehensive view of market momentum, trend, and potential reversal setups by combining oscillator crossovers, divergences, volatility, volume, and session context — helping traders time entries and exits across multiple timeframes.
Pine Script® indicator
by vslvnvch
Chronos Reversal Labs - SPChronos Reversal Labs - Shadow Portfolio Chronos Reversal Labs - Shadow Portfolio: combines reinforcement learning optimization with adaptive confluence detection through a shadow portfolio system. Unlike traditional indicator mashups that force traders to manually interpret conflicting signals, this system deploys 4 multi-armed bandit algorithms to automatically discover which of 5 specialized confluence strategies performs best in current market conditions, then validates those discoveries through parallel shadow portfolios that track virtual P&L for each strategy independently. Core Innovation: Rather than relying on static indicator combinations, this system implements Thompson Sampling (Bayesian multi-armed bandits), contextual bandits (regime-specific learning), advanced chop zone detection (geometric pattern analysis), and historical pre-training to build a self-improving confluence detection engine. The shadow portfolio system runs 5 parallel virtual trading accounts—one per strategy—allowing the system to learn which confluence approach works best through actual position tracking with realistic exits. Target Users: Intermediate to advanced traders seeking systematic reversal signals with mathematical rigor. Suitable for swing trading and day trading across stocks, forex, crypto, and futures on liquid instruments. Requires understanding of basic technical analysis and willingness to allow 50-100 bars for initial learning. Why These Components Are Combined The Fundamental Problem No single confluence method works consistently across all market regimes. Kernel-based methods (entropy, DFA) excel during predictable phases but fail in chaos. Structure-based methods (harmonics, BOS) work during clear swings but fail in ranging conditions. Technical methods (RSI, MACD, divergence) provide reliable signals in trends but generate false signals during consolidation. Traditional solutions force traders to either manually switch between methods (slow, error-prone) or interpret all signals simultaneously (cognitive overload). Both fail because they assume the trader knows which regime the market is in and which method works best. The Solution: Meta-Learning Through Reinforcement Learning This system solves the problem through automated strategy selection : Deploy 5 specialized confluence strategies designed for different market conditions, track their real-world performance through shadow portfolios, then use multi-armed bandit algorithms to automatically select the optimal strategy for the next trade. Why Shadow Portfolios? Traditional bandit implementations use abstract "rewards." Shadow portfolios provide realistic performance measurement : Each strategy gets a virtual trading account with actual position tracking, stop-loss management, take-profit targets, and maximum holding periods. This creates risk-adjusted learning where strategies are evaluated on P&L, win rate, and drawdown—not arbitrary scores. The Five Confluence Strategies The system deploys 5 orthogonal strategies with different weighting schemes optimized for specific market conditions: Strategy 1: Kernel-Dominant (Entropy/DFA focused, optimal in predictable markets) Shannon Entropy weight × 2.5, DFA weight × 2.5 Detects low-entropy predictable patterns and DFA persistence/mean-reversion signals Failure mode: High-entropy chaos (hedged by Technical-Dominant) Strategy 2: Structure-Dominant (Harmonic/BOS focused, optimal in clear swing structures) Harmonics weight × 2.5, Liquidity (S/R) weight × 2.0 Uses swing detection, break-of-structure, and support/resistance clustering Failure mode: Range-bound markets (hedged by Balanced) Strategy 3: Technical-Dominant (RSI/MACD/Divergence focused, optimal in established trends) RSI weight × 2.0, MACD weight × 2.0, Trend weight × 2.0 Zero-lag RSI suite with 4 calculation methods, MACD analysis, divergence detection Failure mode: Choppy/ranging markets (hedged by chop filter) Strategy 4: Balanced (Equal weighting, optimal in unknown/transitional regimes) All components weighted 1.2× Baseline performance during regime uncertainty Strategy 5: Regime-Adaptive (Dynamic weighting by detected market state) Chop zones: Kernel × 2.0, Technical × 0.3 Bull/Bear trends: Trend × 1.5, DFA × 2.0 Ranging: Mean reversion × 1.5 Adapts explicitly to detected regime Multi-Armed Bandit System: 4 Core Algorithms What Is a Multi-Armed Bandit Problem? Formal Definition: K arms (strategies), each with unknown reward distribution. Goal: Maximize cumulative reward while learning which arms are best. Challenge: Balance exploration (trying uncertain strategies) vs. exploitation (using known-best strategy). Trading Application: Each confluence strategy is an "arm." After each trade, receive reward (P&L percentage). Bandits decide which strategy to trust for next signal. The 4 Implemented Algorithms 1. Thompson Sampling (DEFAULT) Category: Bayesian approach with probability distributions How It Works: Model each strategy as Beta(α, β) where α = wins, β = losses. Sample from distributions, select highest sample. Properties: Optimal regret O(K log T), automatic exploration-exploitation balance When To Use: Best all-around choice, adaptive markets, long-term optimization 2. UCB1 (Upper Confidence Bound) Category: Frequentist approach with confidence intervals Formula: UCB_i = reward_mean_i + sqrt(2 × ln(total_pulls) / pulls_i) Properties: Deterministic, interpretable, same optimal regret as Thompson When To Use: Prefer deterministic behavior, stable markets 3. Epsilon-Greedy Category: Simple baseline with random exploration How It Works: With probability ε (0.15): random strategy. Else: best average reward. Properties: Simple, fast initial learning When To Use: Baseline comparison, short-term testing 4. Contextual Bandit Category: Context-aware Thompson Sampling Enhancement: Maintains separate alpha/beta for Bull/Bear/Ranging regimes Learning: "Strategy 2: 60% win rate in Bull, 40% in Bear" When To Use: After 100+ bars, clear regime shifts Shadow Portfolio System Why Shadow Portfolios? Traditional bandits use abstract scores. Shadow portfolios provide realistic performance measurement through actual position simulation. How It Works Position Opening: When strategy generates validated signal: Opens virtual position for selected strategy Records: entry price, direction, entry bar, RSI method Optional: Open positions for ALL strategies simultaneously (faster learning) Position Management (Every Bar): Current P&L: pnl_pct = (close - entry) / entry × direction × 100 Exit if: pnl_pct <= -2.0% (stop-loss) OR pnl_pct >= +4.0% (take-profit) OR held ≥ 100 bars (time) Position Closing: Calculate final P&L percentage Update strategy equity, track win rate, gross profit/loss, max drawdown Calculate risk-adjusted reward: text base_reward = pnl_pct / 10.0 win_rate_bonus = (win_rate - 0.5) × 0.3 drawdown_penalty = -max_drawdown × 0.05 total_reward = sigmoid(base + bonus + penalty) Update bandit algorithms with reward Update RSI method bandit Statistics Tracked Per Strategy: Equity curve (starts at $10,000) Win rate percentage Max drawdown Gross profit/loss Current open position This creates closed-loop learning : Strategies compete → Best performers selected → Bandits learn quality → System adapts automatically. Historical Pre-Training System The Problem with Live-Only Learning Standard bandits start with zero knowledge and need 50-100 signals to stabilize. For weekly timeframe traders, this could take years. The Solution: Historical Training During Chart Load: System processes last 300-1000 bars (configurable) in "training mode": Detect signals using Balanced strategy (consistent baseline) For each signal, open virtual training positions for all 5 strategies Track positions through historical bars using same exit logic (SL/TP/time) Update bandit algorithms with historical outcomes CRITICAL TRANSPARENCY: Signal detection does NOT look ahead—signals use only data available at entry bar. Exit tracking DOES look ahead (uses future bars for SL/TP), which is acceptable because: ✅ Entry decisions remain valid (no forward bias) ✅ Learning phase only (not affecting shown signals) ✅ Real-time mirrors training (identical exit logic) Training Completion: Once chart reaches current bar, system transitions to live mode. Dashboard displays training vs. live statistics for comparison. Benefit: System begins live trading with 100-500 historical trades worth of learning, enabling immediate intelligent strategy selection. Advanced Chop Zone Detection Engine The Innovation: Multi-Layer Geometric Chop Analysis Traditional chop filters use simple volatility metrics (ATR thresholds) that can't distinguish between trending volatility (good for signals) and choppy volatility (bad for signals). This system implements three-layer geometric pattern analysis to precisely identify consolidation zones where reversal signals fail. Layer 1: Micro-Structure Chop Detection Method: Analyzes micro pivot points (5-bar left, 2-bar right) to detect geometric compression patterns. Slope Analysis: Calculates slope of pivot high trendline and pivot low trendline Compression ratio: compression = slope_high - slope_low Pattern Classification: Converging slopes (compression < -0.05) → "Rising Wedge" or "Falling Wedge" Flat slopes (|slope| < 0.05) → "Rectangle" Parallel slopes (|compression| < 0.1) → "Channel" Expanding slopes → "Expanding Range" Chop Scoring: Rectangle pattern: +15 points (highest chop) Low average slope (<0.05): +15 points Wedge patterns: +12 points Flat structures: +10 points Why This Works: Geometric patterns reveal market indecision. Rectangles and wedges create false breakouts that trap technical traders. By quantifying geometric compression, system detects these zones before signals fire. Layer 2: Macro-Structure Chop Detection Method: Tracks major swing highs/lows using ATR-based deviation threshold (default 2.0× ATR), projects channel boundaries forward. Channel Position Calculation: proj_high = last_swing_high + (swing_high_slope × bars_since) proj_low = last_swing_low + (swing_low_slope × bars_since) channel_width = proj_high - proj_low position = (close - proj_low) / channel_width Dead Zone Detection: Middle 50% of channel (position 0.25-0.75) = low-conviction zone Score increases as price approaches center (0.5) Chop Scoring: Price in dead zone: +15 points (scaled by centrality) Narrow channel width (<3× ATR): +15 points Channel width 3-5× ATR: +10 points Why This Works: Price in middle of range has equal probability of moving either direction. Institutional traders avoid mid-range entries. By detecting "dead zones," system avoids low-probability setups. Layer 3: Volume Chop Scoring Method: Low volume indicates weak conviction—precursor to ranging behavior. Scoring: Volume < 0.5× average: +20 points Volume 0.5-0.8× average: +15 points Volume 0.8-1.0× average: +10 points Overall Chop Intensity & Signal Filtering Total Chop Calculation: chop_intensity = micro_score + macro_score + (volume_score × volume_weight) is_chop = chop_intensity >= 40 Signal Filtering (Three-Tier Approach): 1. Signal Blocking (Intensity > 70): Extreme chop detected (e.g., tight rectangle + dead zone + low volume) ALL signals blocked regardless of confluence Chart displays red/orange background shading 2. Threshold Adjustment (Intensity 40-70): Moderate chop detected Confluence threshold increased: threshold += (chop_intensity / 50) Only highest-quality signals pass 3. Strategy Weight Adjustment: During Chop: Kernel-Dominant weight × 2.0 (entropy detects breakout precursors), Technical-Dominant weight × 0.3 (reduces false signals) After Chop Exit: Weights revert to normal Why This Three-Tier Approach Is Original: Most chop filters simply block all signals (loses breakout entries). This system adapts strategy selection during chop—allowing Kernel-Dominant (which excels at detecting low-entropy breakout precursors) to operate while suppressing Technical-Dominant (which generates false signals in consolidation). Result: System remains functional across full market regime spectrum. Zero-Lag Filter Suite with Dynamic Volatility Scaling Zero-Lag ADX (Trend Regime Detection) Implementation: Applies ZLEMA to ADX components: lag = (length - 1) / 2 zl_source = source + (source - source ) × strength Dynamic Volatility Scaling (DVS): Calculates volatility ratio: current_ATR / ATR_100period_avg Adjusts ADX length dynamically: High vol → shorter length (faster), Low vol → longer length (smoother) Regime Classification: ADX > 25 with +DI > -DI = Bull Trend ADX > 25 with -DI > +DI = Bear Trend ADX < 25 = Ranging Zero-Lag RSI Suite (4 Methods with Bandit Selection) Method 1: Standard RSI - Traditional Wilder's RSI Method 2: Ehlers Zero-Lag RSI ema1 = ema(close, length) ema2 = ema(ema1, length) zl_close = close + (ema1 - ema2) Method 3: ZLEMA RSI lag = (length - 1) / 2 zl_close = close + (close - close ) Method 4: Kalman-Filtered RSI - Adaptive smoothing with process/measurement noise RSI Method Bandit: Separate 4-arm bandit learns which calculation method produces best results. Updates independently after each trade. Kalman Adaptive Filters Fast Kalman: Low process noise → Responsive to genuine moves Slow Kalman: Higher measurement noise → Filters noise Application: Crossover logic for trend detection, acceleration analysis for momentum inflection What Makes This Original Innovation 1: Shadow Portfolio Validation First TradingView script to implement parallel virtual portfolios for multi-armed bandit reward calculation. Instead of abstract scoring metrics, each strategy's performance is measured through realistic position tracking with stop-loss, take-profit, time-based exits, and risk-adjusted reward functions (P&L + win rate + drawdown). This provides orders-of-magnitude better reward signal quality for bandit learning than traditional score-based approaches. Innovation 2: Three-Layer Geometric Chop Detection Novel multi-scale geometric pattern analysis combining: (1) Micro-structure slope analysis with pattern classification (wedges, rectangles, channels), (2) Macro-structure channel projection with dead zone detection, (3) Volume confirmation. Unlike simple volatility filters, this system adapts strategy weights during chop —boosting Kernel-Dominant (breakout detection) while suppressing Technical-Dominant (false signal reduction)—allowing operation across full market regime spectrum without blind signal blocking. Innovation 3: Historical Pre-Training System Implements two-phase learning : Training phase (processes 300-1000 historical bars on chart load with proper state isolation) followed by live phase (real-time learning). Training positions tracked separately from live positions. System begins live trading with 100-500 trades worth of learned experience. Dashboard displays training vs. live performance for transparency. Innovation 4: Contextual Multi-Armed Bandits with Regime-Specific Learning Beyond standard bandits (global strategy quality), implements regime-specific alpha/beta parameters for Bull/Bear/Ranging contexts. System learns: "Strategy 2: 60% win rate in ranging markets, 45% in bull trends." Uses current regime's learned parameters for strategy selection, enabling regime-aware optimization. Innovation 5: RSI Method Meta-Learning Deploys 4 different RSI calculation methods (Standard, Ehlers ZL, ZLEMA, Kalman) with separate 4-arm bandit that learns which calculation works best. Updates RSI method bandit independently based on trade outcomes, allowing automatic adaptation to instrument characteristics. Innovation 6: Dynamic Volatility Scaling (DVS) Adjusts ALL lookback periods based on current ATR ratio vs. 100-period average. High volatility → shorter lengths (faster response). Low volatility → longer lengths (smoother signals). Applied system-wide to entropy, DFA, RSI, ADX, and Kalman filters for adaptive responsiveness. How to Use: Practical Guide Initial Setup (5 Minutes) Theory Mode: Start with "BALANCED" (APEX for aggressive, CONSERVATIVE for defensive) Enable RL: Toggle "Enable RL Auto-Optimization" to TRUE, select "Thompson Sampling" Enable Confluence Modules: Divergence, Volume Analysis, Liquidity Mapping, RSI OB/OS, Trend Analysis, MACD (all recommended) Enable Chop Filter: Toggle "Enable Chop Filter" to TRUE, sensitivity 1.0 (default) Historical Training: Enable "Enable Historical Pre-Training", set 300-500 bars Dashboard: Enable "Show Dashboard", position Top Right, size Large Learning Phase (First 50-100 Bars) Monitor Thompson Sampling Section: Alpha/beta values should diverge from initial 1.0 after 20-30 trades Expected win% should stabilize around 55-60% (excellent), >50% (acceptable) "Pulls" column should show balanced exploration (not 100% one strategy) Monitor Shadow Portfolios: Equity curves should diverge (different strategies performing differently) Win rate > 55% is strong Max drawdown < 15% is healthy Monitor Training vs Live (if enabled): Delta difference < 10% indicates good generalization Large negative delta suggests overfitting Large positive delta suggests system adapting well Optimization: Too few signals: Lower "Base Confluence Threshold" to 2.5-3.0 Too many signals: Raise threshold to 4.0-4.5 One strategy dominates (>80%): Increase "Exploration Rate" to 0.20-0.25 Excessive chop blocking: Lower "Chop Sensitivity" to 0.7-0.8 Signal Interpretation Dashboard Indicators: "WAITING FOR SIGNAL": No confluence "LONG ACTIVE ": Validated long entry "SHORT ACTIVE ": Validated short entry Chart Visuals: Triangle markers: Entry signal (green = long, red = short) Orange/red background: Chop zone Lines: Support/resistance if enabled Position Management Entry: Enter on triangle marker, confirm direction matches dashboard, check confidence >60% Stop-Loss: Entry ± 1.5× ATR or at structural swing point Take-Profit: TP1: Entry + 1.5R (take 50%, move SL to breakeven) TP2: Entry + 3.0R (runner) or trail Position Sizing: Risk per trade = 1-2% of capital Position size = (Account × Risk%) / (Entry - SL) Recommended Settings by Instrument Stocks (Large Cap): Balanced mode, Threshold 3.5, Thompson Sampling, Chop 1.0, 15min-1H, Training 300-500 bars Forex Majors: Conservative-Balanced mode, Threshold 3.5-4.0, Thompson Sampling, Chop 0.8-1.0, 5min-30min, Training 400-600 bars Cryptocurrency: Balanced-APEX mode, Threshold 3.0-3.5, Thompson Sampling, Chop 1.2-1.5, 15min-4H, Training 300-500 bars Futures: Balanced mode, Threshold 3.5, UCB1 or Thompson, Chop 1.0, 5min-30min, Training 400-600 bars Technical Approximations & Limitations 1. Thompson Sampling: Pseudo-Random Beta Distribution Standard: Cryptographic RNG with true beta sampling This Implementation: Box-Muller transform using market data as entropy source Impact: Not cryptographically random but maintains exploration-exploitation balance. Sufficient for strategy selection. 2. Shadow Portfolio: Simplified Execution Model Standard: Order book simulation with slippage, partial fills This Implementation: Perfect fills at close price, no fees modeled Impact: Real-world performance ~0.1-0.3% worse per trade due to execution costs. 3. Historical Training: Forward-Looking for Exits Only Entry signals: Use only past data (causal, no bias) Exit tracking: Uses future bars to determine SL/TP (forward-looking) Impact: Acceptable because: (1) Entry logic remains valid, (2) Live trading mirrors training, (3) Improves learning quality. Training win rates reflect 8-bar evaluation window—live performance may differ if positions held longer. 4. Shannon Entropy & DFA: Simplified Calculations Impact: 10-15% precision loss vs. academic implementations. Still captures predictability and persistence signals effectively. General Limitations No Predictive Guarantee: Past performance ≠ future results Learning Period Required: Minimum 50-100 bars for stable statistics Overfitting Risk: May not generalize to unprecedented conditions Single-Instrument: No multi-asset correlation or sector context Execution Assumptions: Degrades in illiquid markets (<100k volume), major news events, flash crashes Risk Warnings & Disclaimers No Guarantee of Profit: All trading involves substantial risk of loss. This indicator is a tool, not a guaranteed profit system. System Failures: Software bugs possible despite testing. Use appropriate position sizing. Market Regime Changes: Performance may degrade during extreme volatility (VIX >40), low liquidity periods, or fundamental regime shifts. Broker-Specific Issues: Real-world execution includes slippage (0.1-0.5%), commissions, overnight financing costs, partial fills. Forward-Looking Bias in Training: Historical training uses 8-bar forward window for exit evaluation. Dashboard "Training Win%" reflects this method. Real-time performance may differ. Appropriate Use This Indicator IS: ✅ Entry trigger system with confluence validation ✅ Risk management framework (automated SL/TP) ✅ Adaptive strategy selection engine ✅ Learning system that improves over time This Indicator IS NOT: ❌ Complete trading strategy (requires position sizing, portfolio management) ❌ Replacement for due diligence ❌ Guaranteed profit generator ❌ Suitable for complete beginners Recommended Complementary Analysis: Market context, volume profile, fundamental catalysts, higher timeframe alignment, support/resistance from other sources. Conclusion Chronos Reversal Labs V2.0 - Elite Edition synthesizes research from multi-armed bandit theory (Thompson Sampling, UCB, contextual bandits), market microstructure (geometric chop detection, zero-lag filters), and machine learning (shadow portfolio validation, historical pre-training, RSI method meta-learning). Unlike typical indicator mashups, this system implements mathematically rigorous bandit algorithms with realistic performance validation, three-layer chop detection with adaptive strategy weighting, regime-specific learning, and full transparency on approximations and limitations. The system is designed for intermediate to advanced traders who understand that no indicator is perfect, but through proper machine learning and realistic validation, we can build systems that improve over time and adapt to changing markets without manual intervention. Use responsibly. Understand the limitations. Risk disclosure applies. Past performance does not guarantee future results. Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script® indicator
by DskyzInvestments
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Trade4Freedom## 🔷 Trade4Freedom – Market Logic Framework **Not a group of indicators. One continuous system of reading market behaviour.** The script is designed to follow the same decision flow I use in trading. Every tool here supports the others — there are no standalone modules. The market is analysed layer by layer, but always as one sequence: --- ### 🔄 **How the logic works (continuous process)** 1. **Structure first** – BOS/ChoCH levels show where the market changed behaviour. The projected dotted line is not a signal — it is a place where I wait and observe. I do not enter until price interacts with structure. 2. **Liquidity next** – if the structure level aligns with a liquidity bag (retest), the zone becomes important. Active liquidity lines are potential targets or reasons to avoid trading against the area. 3. **Context filter** – I use CCI only when structure + liquidity are already active. Example of long bias: −200 level is broken → candle closes above the MA → CCI rises from the channel. From this point I begin to trail stops and start building position if structure supports it. 4. **Confirmation & positioning** Stochastic heatmap is not for entries – it confirms pressure. Divergences on CCI or price are additional evidence when forming or adjusting a position. 5. **Execution zones** – only after structure → liquidity → context, I use deviation levels (1–5) to define where to place orders. On higher timeframes they work for accumulation models, on intraday levels they work for tactical entry zones. Dev1/Dev2 boxes exist only to make limit-order planning faster. --- ### 📌 **Purpose of the script** This tool does not predict price or generate signals. It creates the same structured environment on any chart: **Structure → Liquidity → Context → Deviation → Decision** This helps avoid random trading and replaces guessing with logic and observation.
Pine Script® indicator
by TRADE4FREEDOMM
EQT Stochastic RibbonEQT Stochastic Ribbon is a modified Stochastic Oscillator with ribbon fill visualization. Features: - Dynamic color ribbon that changes based on trend direction (Blue for bullish, White for bearish) - Crossover signals with triangle markers when %K crosses %D - Customizable colors and signal offset - Dashed lines at 80/20 levels for overbought/oversold zones How to use: - Blue ribbon = Bullish momentum (%K above %D) - White ribbon = Bearish momentum (%K below %D) - Triangle up = Buy signal (K crosses above D) - Triangle down = Sell signal (K crosses below D) Settings: - K, D, Smooth - Standard Stochastic parameters - Signal Offset - Distance of signal arrows from the line - Bullish/Bearish Colors - Customize ribbon and signal colors
Pine Script® indicator
by Openfort
Momentum Divergence Oscillator by JJMomentum Divergence Oscillator by JJ A powerful, all-in-one momentum tool designed to streamline trade confluence, combining multi-timeframe trend analysis with automatic divergence spotting and classic MACD signals. How to Use This Indicator This oscillator is designed to be used in the lower pane of your chart, beneath your primary price chart. It provides three main types of signals: 1. Multi-Timeframe (MTF) Trend Confirmation The background shading is your primary trend filter. It looks at the MACD trend on two higher timeframes (30m and 60m by default) to confirm the market's overarching direction. Green Shading: Indicates that both higher timeframes are in a bullish trend (MACD above signal line). Focus on looking for BUY signals during this time. Red Shading: Indicates that both higher timeframes are in a bearish trend. Focus on looking for SELL signals during this time. Grey/No Shading: The higher timeframes are not in agreement or are consolidating. Exercise caution or stick to standard price action rules. 2. Automatic Divergence Signals Divergence is a powerful early warning system where the indicator moves in the opposite direction of the price. The indicator automatically flags these occurrences: "Bull RSI Div" (Green Label-Up): Bullish divergence identified using the RSI oscillator. This suggests a potential reversal to the upside after a downtrend. "Bear RSI Div" (Red Label-Down): Bearish divergence identified using the RSI oscillator. This suggests a potential reversal to the downside after an uptrend. Tip: These signals are often most reliable when they occur within the corresponding MTF background colour (e.g., a "Bull RSI Div" during a Green MTF background). 3. Momentum Shifts and Crossovers The standard plots provide immediate insight into market momentum: Blue/Orange Lines: The traditional MACD line (Blue) and Signal line (Orange). Histogram (Green/Red Bars): Represents the momentum difference between the MACD and Signal lines. Zero-Line Crosses (Triangles): Tiny triangles appear when the MACD line crosses the zero line, indicating a shift in long-term momentum. Peaks & Troughs (X-Crosses): The 'X' markers identify local peaks and troughs in the histogram, sometimes indicating short-term exhaustion of the current move. Disclaimer: Trading involves significant risk and is not suitable for every investor. This indicator is for educational purposes only and should not be considered financial advice. Always use appropriate risk management.
Pine Script® indicator
by junaid8883
RayAlgo Flux Velocity & Volume OscillatorThe RayAlgo Oscilator uses a three-step calculation process: Volume-Weighted Momentum: It starts by calculating price momentum but weights the result by volume. If price moves strongly on low volume, the signal is dampened. If the move is supported by high volume, the signal is amplified. This filters out "fake" moves. The Fisher Transform: This is the secret sauce. The Fisher Transform converts the volume-weighted data into a Gaussian Normal Distribution. This process forces the data to create sharp, well-defined peaks and valleys, clearly defining statistical extremes (tops and bottoms) that standard oscillators simply blur. Hull Moving Average (HMA) Smoothing: The final signal is smoothed using the HMA. This provides the fast, liquid, wave-like motion you see, virtually eliminating lag without introducing choppiness.
Pine Script® indicator
by Ray_Algo
Cjack COT IndexHere's the updated description with the formula and additional context: --- **Cjack COT Index - Commitment of Traders Positioning Indicator** This indicator transforms raw Commitment of Traders (COT) data into normalized 0-100 index values, making it easy to identify extreme positioning across different trader categories. **How It Works:** The indicator calculates a min-max normalized index for three trader groups over your chosen lookback period (default 26 weeks): - **Large Speculators** (Non-commercial positions) - typically trend followers - **Small Speculators** (Non-reportable positions) - retail traders - **Commercial Hedgers** - producers and consumers hedging business risk The normalization formula is: **Index = (Current Position - Minimum Position) / (Maximum Position - Minimum Position) × 100** This calculation shows where current net positioning sits between the minimum and maximum levels observed in the lookback window. A reading of 100 means current positioning equals the maximum net long over that period, 0 equals the minimum (most net short), and 50 is the midpoint of the range. **Important:** The lookback period critically affects index readings - shorter lookbacks (13-26 weeks) make the index more sensitive to recent extremes, while longer lookbacks (52-78 weeks) provide broader historical context and identify truly exceptional positioning. Min-max normalization is essential because it makes positioning comparable across different contracts and time periods, regardless of the absolute size of positions. **What It's Good For:** The indicator excels at identifying **crowded trades** and potential reversals by tracking contrarian setups where commercials (smart money) position opposite to speculators. Background highlighting automatically flags: - **Long setups** (green): Commercials heavily long while speculators are heavily short - **Short setups** (red): Commercials heavily short while speculators are heavily long The "Shift Index" option (enabled by default) displays last week's tradeable COT data aligned with current price action, ensuring you're working with actionable information since COT reports publish with a delay. Works on weekly timeframes and below for commodities and futures with available COT data.
Pine Script® indicator
by Cjackjamie
Quant Master Z-Oscillator [Risk + Bias]his indicator is a statistically-driven oscillator designed to measure the extreme deviation of price from its recent mean, identifying both reversal risk and directional bias within the current trend. It reframes classic Z-Score analysis to provide a quantified framework for trade timing and risk assessment. Core Philosophy The primary goal is to determine the statistical probability of a mean-reversion event. By measuring how many standard deviations the current price is away from its simple moving average (the basis), the indicator identifies moments of maximum risk (Extremes) and optimal entry (Oversold/Overbought zones). Key Components Z-Score Calculation: Measures the distance of the closing price from the Lookback Length Simple Moving Average (SMA), normalized by the Standard Deviation (Volatility). The raw score is then smoothed using an Exponential Moving Average (EMA) to filter noise, providing a clearer reading of the underlying statistical position. Statistical Thresholds: $\pm 2\sigma$ (High/Low): Defines the standard Overbought/Oversold zones (Trigger Zones). Movement into these areas suggests a pullback or reversal is increasingly likely. $\pm 3\sigma$ (Extreme): Defines the "Kill Zone" of maximum statistical risk. Price reaching this level is highly unlikely to sustain itself, triggering an Extreme Overbought/Oversold warning. Risk & Bias Dashboard (Table): A real-time dashboard displayed on the chart (bottom right) provides a quantified summary of the current market state: Current Z: The exact Z-Score value and its gradient color (green for positive pressure, red for negative). Market Risk: Flags the statistical risk (e.g., OVERBOUGHT or EXTREME OVERSOLD ⚠️) based on the $\sigma$ thresholds. Next Bias: Suggests the immediate directional bias (e.g., LONG SETUP NEXT or SHORT REVERSAL), helping the user prepare for the next high-probability setup based on the Z-Score's position relative to the mean. Divergence Engine: Detects standard Bullish and Bearish divergences between the Z-Score and the price action, signaling potential trend exhaustion or hidden momentum shifts. Interpretation & Use Risk Management: Treat the $\pm 3\sigma$ (Extreme) levels as mandatory profit-taking or high-alert reversal zones. Trading against these extremes carries the highest statistical risk. Entry Timing: High-probability entries are found when the Z-Score is at $\pm 2\sigma$ (Oversold/Overbought) and a momentum shift (e.g., a green bar after an Oversold red sequence) is observed. Trend Confirmation: When the Z-Score operates between $0$ and $\pm 2\sigma$, it confirms the direction of the current trend (Positive Z-Score = Bullish bias).
Pine Script® indicator
by CustomQuantLabs
Percentage Distance from 200-Week SMA200-Week SMA % Distance Oscillator (Clean & Simple) This lightweight, no-nonsense indicator shows how far the current price is from the classic 200-week Simple Moving Average, expressed as a percentage. Key features: • True percentage distance: (Price − 200w SMA) / 200w SMA × 100 • Auto-scaling oscillator (no forced ±100% range → the line actually moves and looks alive) • Clean zero line • +10% overbought and −10% oversold levels with subtle background shading • Real-time table showing the exact current percentage • Small label on the last bar for instant reading • Alert conditions when price moves >10% above or below the 200-week SMA Why 200-week SMA? Many legendary investors and hedge funds (Stan Druckenmiller, Paul Tudor Jones, etc.) use the 200-week SMA as their ultimate long-term trend anchor. Being +10% or more above it has historically signaled extreme optimism, while −10% or lower has marked deep pessimism and generational buying opportunities. Perfect for Bitcoin, SPX, gold, individual stocks – works on any timeframe (looks especially good on daily and weekly charts). Open-source • No repainting • Minimalist & fast Enjoy and trade well!
Pine Script® indicator
by notoriousBlue
Delta Volume RSI1. Introduction The Delta Volume RSI (Relative Strength Index based on Volume Delta) indicator provides a unique perspective on market momentum by analyzing the average gains and losses of the volume delta —the difference between buying and selling volume—over a specified period. Unlike traditional RSI, which focuses on price changes, this indicator evaluates shifts in market participation intensity, helping traders detect periods of accumulation and distribution through volume action. 2. Key Features - Volume-Based Calculation: Computes RSI using the average gains and losses of delta volume rather than price changes, offering insights into buying/selling pressure. - Dynamic Color Coding: Paints the indicator line green when above the 50 level, and red when below, enabling quick visual identification of momentum shifts around neutrality. - Reference Levels: Clearly displays overbought (70), neutral (50), and oversold (30) lines for context on volume-driven market extremes. - Customizable Period: Users can set the period for RSI calculation to fit their trading style and timeframe preferences. 3. How to Use 1. Interpret Colors: The indicator line turns green when volume delta momentum is bullish (above 50) and red when bearish (below 50). Overbought and oversold zones (above 70 or below 30) may highlight exhaustion in volume-driven pushes. 2. Adjustment: Modify the RSI period in the settings to tailor responsiveness. 3. Reference Line: Use the dashed gray line at 50 as a core threshold for detecting transitions between buyer and seller dominance. How It Differs From Standard RSI The standard RSI uses changes in closing price to calculate market momentum. In contrast, this indicator calculates RSI using the average gains and losses of the delta volume , capturing underlying shifts in buying and selling activity—even when price is flat. This makes the Delta Volume RSI especially useful for identifying divergence between volume flow and price movement, potentially signaling strong accumulation/distribution or market reversals not visible on price-based RSI alone.
Pine Script® indicator
by destrobr0685
Vortex Pro with Moving average [point algo]Vortex Pro with MA Dropdown is an enhanced version of the classic Vortex Indicator (VI), designed to help visualize directional strength by comparing positive and negative trend movement. This version includes a smoothed “Vortex Pro” line, adjustable moving-average filtering, and dynamic zone coloring for improved readability. How It Works: The script calculates VI+ and VI− using directional movement and true range. “Vortex Pro” is derived from the difference between VI+ and VI−, scaled for clarity. A customizable moving average (EMA, SMA, HMA, WMA) is applied to help smooth volatility and highlight shifts in momentum. Features : • Vortex Pro Line A scaled trend-strength line showing when positive movement is dominating or weakening. • MA Type Dropdown Choose between EMA, SMA, HMA, or WMA to smooth the Vortex Pro line. • Zero-Line Structure A plotted zero line is used to compare positive vs. negative strength visually. • Dynamic Fill Zones Green shading when the Vortex Pro line is above zero, red when below. Usage: This tool is designed for visual analysis of trend direction and momentum strength. It does not generate buy/sell signals and should be used as part of a broader analysis approach. Suitable for all timeframes and markets.
Pine Script® indicator
by pointalgo
Spot-Futures SpreadSpot-Futures Spread Indicator A comprehensive indicator that automatically calculates and visualizes the percentage spread between spot and perpetual futures prices across multiple exchanges. Key Features: Automatic Exchange Detection - Automatically detects your current exchange and finds the corresponding spot/futures pair Smart Fallback System - If the counterpart isn't available on your exchange, it automatically searches across 7+ major exchanges (Binance, Bybit, OKX, Gate.io, MEXC, KuCoin, HTX) and uses the first valid match Multi-Exchange Support - Works with 14 exchanges including Binance, Bybit, OKX, MEXC, BitGet, Gate.io, KuCoin, and more Clear Exchange Attribution - Shows exactly which exchanges are providing spot and futures data in the statistics table Configurable Moving Average - Track the average spread with customizable period Standard Deviation Bands - Identify unusual spread conditions with Bollinger-style bands Built-in Alerts - Get notified when spread crosses bands or zero (parity) Statistics Table - Real-time stats showing current spread, MA, std dev, and bands Manual Override Options - Advanced users can manually specify exchanges and symbols How It Works: The indicator calculates the spread as: (Futures Price - Spot Price) / Spot Price × 100 Positive spread = Futures trading at a premium (contango) Negative spread = Futures trading at a discount (backwardation) Zero = Parity between spot and futures Use Cases: Funding Rate Analysis - Correlates with perpetual funding rates Arbitrage Opportunities - Identify significant spot-futures divergences Market Sentiment - Premium/discount indicates bullish/bearish positioning Cross-Exchange Analysis - Compare spreads when spot and futures are on different exchanges Smart Features: Works whether you're viewing a spot or futures chart Automatically handles exchange-specific perpetual contract naming (.P, PERP, SWAP, etc.) Color-coded visualization (green for premium, red for discount) Customizable colors and display options Background shading based on spread direction Perfect For: Crypto traders monitoring funding rates, arbitrage traders, market makers, and anyone interested in spot-futures dynamics across multiple exchanges. Getting Started: Simply add the indicator to any spot or perpetual futures chart. It will automatically detect the exchange and find the corresponding pair. The statistics table shows which exchanges are being used for maximum transparency. Note: The indicator automatically ignores invalid symbols, so you'll never see errors even if a specific pair doesn't exist on a particular exchange. Kudos to @AlekMel that made the "Spot - Fut Spread v2" indicator that I enhance the Automatic detection feature which was not working in some case.
Pine Script® indicator
by sharkonet
RSI PriceThe relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to detect overbought or oversold conditions in the price of that security. The RSI is displayed as an oscillator (a line graph) on a scale of 0 to 100. Traditionally, an RSI reading of 70 or above indicates an overbought condition. A reading of 30 or below indicates an oversold condition. In addition to identifying overbought and oversold securities, the RSI can also indicate securities that may be primed for a trend reversal or a corrective pullback in price.
Pine Script® indicator
by ryan027
1
All-in-One RSI & StochRSI: 4x MTF View Matrix by Jenn.ioAll-in-One RSI & StochRSI: 4x MTF View Matrix (Momentum Dashboard) by Jenn.io Indicator Overview This indicator is a complete momentum tool that combines the Relative Strength Index (RSI) and the Stochastic RSI (StochRSI) into a single pane, complemented by a powerful Multi-Timeframe (MTF) Table of up to 4 timeframes for a comprehensive market view. It is ideal for traders looking to confirm overbought/oversold conditions across multiple timeframes before making a trading decision. Key Features and Logic: Dual Oscillator Display: It plots the RSI (to measure the speed and change of price movements) and the %K and %D lines of the StochRSI (to measure the RSI relative to its range). Visual Signaling: Background Shading: The RSI area is shaded in Red or Green (overbought or oversold) for quick identification of extreme zones. Optional Labels: Displays clear labels like "OB" (Overbought) or "OS" (Oversold) when the oscillators cross critical levels. Multi-Timeframe Table (MTF 4): The core feature. It displays the values of the RSI and the StochRSI Average ((K + D) / 2) across four different timeframes fully customizable by the user (e.g., 15m, 1h, 4h, Daily). Heatmap Matrix: The MTF table values are dynamically colored:Red or Green: If the value is in the Overbought zone ($\geq 70$ by default) or Oversold zone ($\leq 30$ by default). Recommended Usage: Signal Confluence: Use the primary oscillators to identify an entry signal on your operating timeframe. MTF Confirmation: Check the MTF table to confirm that momentum on higher timeframes (e.g., 4H or Daily) is moving in the same direction (e.g., if the current timeframe oscillator is oversold, look for higher TFs to show a neutral or low value to confirm exhaustion). Risk Management: Avoid taking buy signals if the higher TFs are already showing a strong overbought condition (Red or Green).
Pine Script® indicator
by Jenn_io