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Quantura - Quantified Price Action StrategyIntroduction “Quantura – Quantified Price Action Strategy” is an invite-only Pine Script strategy designed to combine multiple price action concepts into a single trading framework. It integrates supply and demand zones, liquidity sweeps and runs, fair value gaps (FVGs), RSI filters, and EMA trend confirmation. The strategy also provides a visual overlay with dynamic trend-colored candles for easier chart interpretation. It is intended for multi-market use across cryptocurrencies, Forex, equities, and indices. Originality & Value The strategy is original in how it unifies several institutional-style price action elements and validates trades only when they align. This reduces noise compared to using single indicators in isolation. Its unique value lies in the combination of: Supply & Demand detection: Dynamic boxes identified through pivots, ATR, and volume sensitivity. Liquidity sweeps and runs: Detects when swing highs/lows are broken and retested, distinguishing between liquidity grabs (sweeps) and directional runs. RSI filter: Can be set to normal or aggressive, confirming momentum before trades. Fair Value Gaps (FVGs): Optional detection and filtering of price inefficiencies. EMA filter: Aligns trades with the broader market trend. Trend candle visualization: Candles dynamically colored bullish, bearish, or neutral, based on strategy positions. This layered confluence approach ensures that entries are not taken on a single condition but require agreement across several dimensions of market structure, momentum, and order flow. Functionality & Indicators Supply & Demand Zones: Zones are created when pivots, ATR sensitivity, and volume thresholds overlap. Liquidity: Swing highs and lows are tracked, with options for sweep (fakeout/reversal) or run (continuation) detection. RSI: Confirms long signals when oversold and shorts when overbought, with configurable aggressiveness. FVG filter: Adds validation by requiring price interaction with inefficiency zones. EMA filter: Ensures longs are above EMA and shorts below EMA. Signals & Visualization: Trade entries are marked on the chart, while candles change color to reflect trade direction and status. Parameters & Customization Supply & Demand: Sensitivity (swing range, volume multiplier, ATR multiplier) and display options. Liquidity filter: Mode (Run or Sweep), display, and swing length. RSI: Enable/disable, length, and style (normal or aggressive). Fair Value Gaps: Sensitivity via ATR factor, optional volume filter, and display toggles. EMA: Length, enable/disable, and visualization. Risk management: Up to three configurable take-profit levels, stop-loss, break-even logic, and capital-based position sizing. Visualization: Custom candle coloring and optional overlay for better clarity. Default Properties (Strategy Settings) Initial Capital: 10,000 USD Position Size: 100% of equity per trade (backtest default) Commission: 0.1% Slippage: 1 Pyramiding: 0 (only one position at a time) Note: The default of 100% equity per trade is used for testing purposes only and would not be sustainable in real trading. A typical allocation in practice would be between 1–5% of account equity per trade, sometimes up to 10%. Backtesting & Performance Backtests on XPTUSD over 2.5 years with the default settings produced: 164 trades 67.68% win rate Profit factor: 1.7 Maximum drawdown: 27.81% These results show how the confluence of supply/demand, liquidity, and RSI filters can produce robust setups. However, past performance does not guarantee future results. While the trade count (164) is sufficient for statistical analysis, results may vary across markets and timeframes. Risk Management Three configurable take-profit levels with percentage allocation. Initial stop-loss based on user-defined percentage. Dynamic stop-loss that adjusts with market movement. Break-even logic that shifts stops to entry after predefined gains. Position sizing based on risk percentage of equity. This framework allows both conservative and aggressive configurations, depending on user preference. Limitations & Market Conditions Works best in volatile and liquid markets such as crypto, metals, indices, and FX. May produce false signals in low-volume or sideways environments. Unexpected news or macro events can override technical conditions. Default position sizing of 100% equity is highly aggressive and should be reduced before any practical use. Usage Guide Add “Quantura – Quantified Price Action Strategy” to your chart. Select Supply & Demand, Liquidity, RSI, EMA, and FVG settings according to your market and timeframe. Configure risk management: take-profits, stop-loss, and risk-per-trade percentage. Use the Strategy Tester to analyze statistics, equity curve, and performance under different conditions. Optimize parameters before applying the strategy to different markets. Author & Access Developed 100% by Quantura. Published as an Invite-Only script. Important This description complies with TradingView’s publishing rules. It clarifies originality, explains the underlying logic, discloses default properties, and presents backtest results with realistic disclaimers.
Pine Script® stratejisi
Quantura tarafından
OutsiderEdge - Adaptive Node Efficiency Function (ANEF)Overview - What is ANEF? ANEF is a zero-centered oscillator that blends price efficiency, effective volume around VWAP (node proximity), order-flow imbalance (uptick/downtick proxy), and returns volatility into a single, normalized score. The goal is to help you spot efficient breakouts and inefficient mean-reversions in a way that’s transparent, systematic, and easy to align with your own analysis. Users can combine ANEF’s components to build rules such as: “ Only consider short breakout signals when trend context is bearish and the ANEF score pushes into the Efficient Zone ,” or “ Look for mean-reversion setups when the ANEF score sinks into the Inefficient Zone while trend context remains bullish. ” While ANEF can stand on its own, it also works well as a secondary confirmation layer to a user’s primary process (volume profile, price action, S/R, market structure, or your preferred overlays). 🔹 FEATURES Below is each ANEF component/feature in the order that typically leads to the most confluence. ANEF Core (Normalized Score) Combines a price change term with effective volume near VWAP and order-flow imbalance, scaled by volatility and normalized into a zero-centered oscillator. Read it like a pressure gauge: high positive values = efficient upside impulse risk; deep negative values = inefficient pressure that often reverts. Efficient & Inefficient Zones (Thresholds) Two user-set levels (default ≥ +4.6 and ≤ −4.6) to quickly see when ANEF pushes into efficient breakout territory (top zone) or inefficient territory (bottom zone). Thresholds are not overbought/oversold; they’re contextual “efficiency bands.” 2nd-Signal Confirmation (Optional) An opt-in rule to ignore the first signal of a type and only print the second occurrence within X bars (default 6). Reduces one-off noise without repainting or lookahead. Trend Context (EMA-based Wave, Optional) A lightweight EMA context that lets you filter signals (e.g., only show ▼ in downtrend, only show ▲ in uptrend). The context is plotted as a sub-pane wave centered around zero so it doesn’t fight for price-panel space. Clean Alerts (Raw & Confirmed) Raw alerts fire at zone interactions. Confirmed alerts respect the 2nd-signal rule and (optionally) the trend filter. Price-Panel Markers (through force_overlay) Even with the oscillator in a separate pane, ANEF can print mini markers on the main chart. Useful to correlate impulses/reversions with structure, S/R, or higher-TF levels. 🔹 USAGE In the examples below, you see chart snapshot with five labeled points of (in)efficiency breakouts. ICMARKETS:UK100 Point 1 — Efficient Downside Breakout (▼) ANEF surges into the Efficient Zone, indicating downside momentum that’s aligned with node volume/imbalance and volatility. Typical use: trend-following continuation, takeprofit on existing long or tightening risk on existing shorts (invalidations above recent structure). Point 2 — Inefficient Upside Reversion (▲) First rebound after the selloff with ANEF deep in the Inefficient Zone. Not an ideal long entry on its own, but a good management cue: take partial profits on shorts or tighten stops as an early confirmation that the drop may be exhausting. Point 3, 4 and 5 — Inefficient Upside Reversion (▲) Another 3x ▲ appears as price forms a higher low and ANEF prints a less extreme negative reading. With the “second-signal within X bars” option enabled, this becomes a more credible mean-reversion attempt. Possible long entries or takeprofits on existing shorts. Trading involves substantial risk. This tool is for educational purposes only and is not financial advice. Past performance does not guarantee future results. You are solely responsible for your trading decisions and risk management. 🔹 NAVIGATING MARKET CONDITIONS Trending phases: Expect more time in or near the zones in the trend direction. Consider allowing only trend-aligned signals (filter ON) and using counter zone exits for trail/partials rather than counter-trend trades. Ranging phases: Expect frequent dips and surges into the (In)efficient Zones and back. Counter-moves (▲ in range downs, ▼ in range ups) can be productive with tight invalidation and the 2nd-signal rule to reduce noise. Regime shifts: Watch for repeated failures of one side’s signals plus cross-pane confluence (e.g., context flips while ANEF re-anchors around zero). That sequence often marks transitions where your rules should adapt (e.g., disable the trend filter temporarily or widen your 2nd-signal window). 🔹 SETTINGS SUMMARY ANEF Core: lengthPrice, lengthVol, lengthVolat, imbalanceCap Zones: Efficient (≥), Inefficient (≤) Confirmation: Require 2nd signal, Lookahead bars Trend Filter: Enable, EMA length, optional smoothing & “only show ▲/▼ with trend” Chart Markers: Also show on main chart (force_overlay) Alerts: Raw vs Confirmed (pick what suits your workflow) 🔹 GOOD PRACTICES Treat signals as context cues, not as mechanical buy/sell calls. You can align ANEF with structure (S/R, HTF bias, LVN, HVN or POC) and risk management (partials on zone exit, invalidation beyond recent swing). Start with defaults; tweak parameters to match your market/TF. 🔹 LIMITATIONS / DISCLAIMER ANEF does not use lookahead and does not repaint, but no indicator guarantees outcomes. Thresholds are heuristics; markets can remain efficient/inefficient longer than expected. Use appropriate position sizing and independent validation. Trading involves substantial risk. This tool is for educational purposes only and is not financial advice. Past performance does not guarantee future results. You are solely responsible for your trading decisions and risk management. Release Notes v1.0 — Initial invite-only release with: normalized ANEF core, Efficient/Inefficient zones, optional EMA trend context, 2nd-signal confirmation, raw & confirmed alerts, and optional price-panel markers via force_overlay.
Pine Script® göstergesi
OutsiderEdge tarafından
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Quantura - Quantitative AlgorythmIntroduction “Quantura – Quantitative Algorithm” is an invite-only Pine Script strategy designed for multi-timeframe analysis, combining technical filters with user-adjustable fundamental sentiment. It was primarily developed for cryptocurrency markets but can also be applied across other assets such as Forex, stocks, and indices. The goal is to generate structured trade signals through a confluence of techniques rather than relying on a single indicator. Originality & Value Quantura is not a simple mashup of indicators. Its originality comes from how multiple layers of analysis are integrated into a single decision framework . Instead of showing indicators separately, the strategy only issues trades when several conditions align simultaneously: RSI entry triggers confirm overbought/oversold reversals. Market structure on a higher timeframe confirms trend direction. Order block detection highlights zones of concentrated supply and demand. Premium/Discount zones identify potential over- and undervaluation. HTF EMA provides trend confirmation. Optional candlestick patterns strengthen reversal or continuation signals. An optional correlation filter compares the main asset to a reference instrument. This design forces agreement between different methodologies (momentum, structure, value, volume, sentiment), which reduces noise compared to using them in isolation. Functionality & Indicators Entry trigger: RSI exits from extreme zones. Filters: Only valid when all selected filters (HTF structure, EMA, order blocks, premium/discount, candlesticks, correlation, volume) confirm the direction. Fundamental bias: User-defined sentiment and analysis settings (bullish, bearish, neutral) influence whether long or short trades are permitted. Exits: ATR-based take profit and stop loss, with optional breakeven, opposite-signal exit, and session-end exit. Visualization: Buy/Sell markers, trend-colored candles, and an optional dashboard summarizing indicator status. Parameters & Customization Timeframes: Independent HTF and LTF selection. Trading direction: Long / Short / Both. Session and weekday filters. RSI length and thresholds. Filters: HTF structure, order blocks, premium/discount, EMA, candlestick, ATR volatility, volume zones, correlation. Exit rules: ATR multipliers for TP/SL, breakeven logic, session-end exit, opposite-signal exit. Visuals: Toggle signals, candles, dashboard, custom colors. Default Properties (Strategy Settings) Initial Capital: 100,000 USD Position Size: 15% of equity per trade Commission: 0.25% Slippage: enabled Pyramiding: 0 (one position at a time) Note: The position sizing of 15% equity per trade is intentionally set for backtesting demonstration. In real trading, risking this much is considered aggressive. Most traders prefer to risk 1-5% of equity, and rarely above 10%. Backtesting & Performance Backtests on BTCUSD (2 years) with the above defaults showed: 112 trades Win rate: 40% Profit factor: 1.4 Maximum drawdown: 34% These results illustrate how the confluence model behaves, but they are not predictive of future performance . The trade sample size (72 trades) is below the 100+ usually recommended for statistical robustness. Users should re-test with their own preferred symbols, settings, and timeframes. Risk Management ATR-based stops and targets scale with volatility. Commission and slippage are included by default for realistic modeling. Opposite-signal exit helps capture trend reversals. Session-end exit can close intraday positions before illiquid hours. Breakeven option protects profits when available. Although the default allocation uses 15% per trade for demonstration, this is not a recommendation. Users are encouraged to adjust risk sizing downwards to sustainable levels (commonly 1-5%). Limitations & Market Conditions Performs best in volatile, liquid markets (e.g., crypto). May struggle in prolonged sideways markets with low volatility. News events and fundamentals outside user inputs can override signals. Backtests below 100 trades should be considered exploratory, not statistically conclusive. Usage Guide Add “Quantura – Quantitative Algorithm” to your chart in strategy mode. Select HTF and LTF timeframes, trading direction, and session filters. Configure confluence filters (structure, EMA, order blocks, premium/discount, candlestick, correlation, volume). Set sentiment and analysis bias in fundamental settings. Adjust ATR multipliers and exits. Review buy/sell signals and analyze performance in the Strategy Tester. Author & Access Developed 100% by Quantura . Distributed as an Invite-Only script . Details are provided in the Author’s Instructions field. Important: This description complies with TradingView’s Script Publishing Rules and House Rules. It does not guarantee profitability, avoids unrealistic claims, and explains how the strategy integrates multiple methods into a coherent decision framework.
Pine Script® stratejisi
Quantura tarafından
KD-NewAutoTrade for Future Trading - Heikin Ashi candles The KD-NewAutoTrade strategy is a dynamic trend-following indicator designed for scalping and swing trading across crypto, forex, and index futures. It combines the precision of EMA crossovers, RSI momentum, and ADX trend strength to deliver clear Buy/Sell signals with high reliability. 🔹 Core Logic EMA Fast & Slow Crossover – Identifies short-term and long-term trend shifts. RSI Confirmation – Filters out false signals by requiring RSI to cross custom Buy/Sell thresholds. ADX Filter – Ensures trades only trigger when market trend strength exceeds your chosen ADX minimum. 🔹 Key Features Visual Buy/Sell triangles directly on the chart. Customizable inputs for EMA, RSI, and ADX lengths. Works efficiently on all timeframes and all markets (Crypto, Indices, Stocks, Commodities). Optional background highlights for active trade zones. Alert conditions for both BUY and SELL setups – ready to use in automated strategies or alert bots. 🔹 Recommended Usage Use Heikin Ashi candles Works best on 1M - 5M timeframes. Combine with volume or higher-timeframe trend confirmation for stronger signals.
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krish16887 tarafından
Bifurcation Point Adaptive (Auto Oscillator ML)Bifurcation Point Adaptive - Auto Oscillator ML Overview Bifurcation Point Adaptive (🧬 BPA-ML) represents a paradigm shift in divergence-based trading systems. Rather than relying on static oscillator settings that quickly become obsolete as market dynamics shift, BPA-ML employs multi-armed bandit machine learning algorithms to continuously discover and adapt to the optimal oscillator configuration for your specific instrument and timeframe. This self-learning core is enhanced by a Cognitive Analytical Engine (CAE) that provides market-state intelligence, filtering out low-probability setups before they reach your chart. The result is a system that doesn't just detect divergences - it understands context, learns from outcomes, and evolves with the market. What Sets This Apart: Technical Comparison The TradingView community has many excellent divergence indicators and several claiming "machine learning" capabilities. However, a detailed technical analysis reveals that BPA-ML operates at a fundamentally different level of sophistication. Machine Learning: Real vs Marketing Most indicators labeled "ML" or "AI" on TradingView use one of three approaches: K-Nearest Neighbors (KNN): These indicators find similar historical patterns and assume current price will behave similarly. This is pattern matching, not learning. The system doesn't improve over time or adapt based on outcomes - it simply searches historical data for matches. Clustering (K-Means): These indicators group volatility or market states into categories (high/medium/low). This is statistical classification, not machine learning. The clusters are recalculated but don't learn which classifications produce better results. Gaussian Process Regression (GPR): These indicators use kernel weighting to create responsive moving averages. This is advanced curve fitting, not learning. The system doesn't evaluate outcomes or adjust strategy. BPA-ML's Approach: True Reinforcement Learning BPA-ML implements multi-armed bandit algorithms - a proven reinforcement learning technique used in clinical trials, A/B testing, and recommendation systems. This is fundamentally different: Exploration vs Exploitation: The system actively balances trying new configurations (exploration) against using proven winners (exploitation). KNN and clustering don't do this - they simply process current data against historical patterns. Reward-Based Learning: Every configuration is scored based on actual forward returns, normalized by volatility and clipped to prevent outlier dominance. The system receives a bonus when signals prove profitable. This creates a feedback loop where the indicator literally learns what works for your specific instrument and timeframe. Four Proven Algorithms: UCB1 (Upper Confidence Bound), Thompson Sampling (Bayesian), Epsilon-Greedy, and Gradient-based learning. Each has different exploration characteristics backed by peer-reviewed research. You're not getting marketing buzzwords - you're getting battle-tested algorithms from academic computer science. Continuous Adaptation: The learning never stops. As market microstructure evolves, the bandit discovers new optimal configurations. Other "adaptive" indicators recalculate but don't improve - they use the same logic on new data. BPA-ML fundamentally changes which logic it uses based on what's working. The Configuration Grid: 40 Arms vs Fixed Settings Traditional divergence indicators use a single oscillator with fixed parameters - typically RSI with length 14. More advanced systems might let you choose between RSI, Stochastic, or CCI, but you're still picking one manually. BPA-ML maintains a grid of 40 candidate configurations: - 5 oscillator families (RSI, Stochastic, CCI, MFI, Williams %R) - 4 length parameters (short, medium, medium-long, long) - 2 smoothing settings (fast, slow) The bandit evaluates all 40 continuously and automatically selects the optimal one. When market microstructure changes - say, from trending crypto to ranging forex - the system discovers this and switches configurations without your intervention. Why This Matters: Markets exhibit different characteristics. Bitcoin on 5-minute charts might favor fast Stochastic (high sensitivity to quick moves), while EUR/USD on 4-hour charts might favor smoothed RSI (filtering noise in steady trends). Manual optimization is guesswork. The bandit discovers these nuances mathematically. Cognitive Analytical Engine: Beyond Simple Filters Many divergence indicators include basic filters - perhaps checking if RSI is overbought/oversold or if volume increased. These are single-metric gates that treat all market states the same. BPA-ML's CAE synthesizes five intelligence layers into a comprehensive market-state assessment: Trend Conviction Score (TCS): Combines ADX normalization, multi-timeframe EMA alignment, and structural persistence. This isn't just "is ADX above 25?" - it's a weighted composite that captures trending vs ranging regimes with nuance. The threshold itself is adaptive via mini-bandit if enabled. Directional Momentum Alignment (DMA): ATR-normalized EMA spread creates a regime-aware momentum indicator. The same price move reads differently in high vs low volatility environments. Most indicators ignore this context. Exhaustion Modeling: Aggregates volume spikes, pin bar formations, extended runs without pullback, and extreme oscillator readings into a unified probability of climax. This multi-factor approach catches exhaustion signals that single metrics miss. High exhaustion can override trend filters - allowing reversal trades at genuine turning points that basic filters would block. Adversarial Validation: Before approving a bullish signal, the engine quantifies both the bull case AND the bear case. If the opposing case dominates by a threshold, the signal is blocked. This is game-theory applied to trading - most indicators don't check if you're fighting obvious strength in the opposite direction. Confidence Scoring: Every signal receives a 0-1 quality score blending all CAE components plus divergence strength. You can size positions by confidence - a concept absent in most divergence indicators that treat all signals identically. Adaptive Parameters: Mini-Bandits Even the filtering thresholds themselves learn. Most indicators have you set pivot lookback periods, minimum divergence strength, and trend filter strictness manually. These are instrument-specific - what works for one asset fails on another. BPA-ML's mini-bandits optimize: - Pivot lookback strictness (balance between catching small structures vs requiring major swings) - Minimum slope change threshold (filter weak divergences vs allow early entries) - TCS threshold for trend filtering (how strict counter-trend blocking should be) These learn the same way the oscillator bandit does - via reward scoring and outcome evaluation. The entire system personalizes to your trading context. Visual Intelligence: Five Presentation Modes Most indicators offer basic customization - perhaps choosing colors or line thickness. BPA-ML includes five distinct visual modes, each designed for specific use cases: Quantum Mode: Renders signals as probability clouds where opacity encodes confidence. High-confidence signals are bold and opaque; low-confidence signals are faint and translucent. This visually guides position sizing in a way that static markers cannot. No other divergence indicator I've found uses confidence-based visual encoding. Holographic Mode: Multi-layer gradient bands create depth perception showing signal quality zones. Excellent for teaching and presentations. Cyberpunk Mode: Neon centerlines with particle glow trails. High-contrast for immersive dark-theme trading. Standard Mode: Professional dashed lines and zones. Clean, presentation-ready. Minimal Mode: Maximum performance for backtesting and low-powered devices. The visual system isn't cosmetic - it's part of the decision support infrastructure. Dashboard: Real-Time Intelligence Many indicators include dashboards showing current indicator values or basic statistics. BPA-ML's dashboard is a comprehensive control center: Oscillator Section: Shows which configuration is currently selected, why it's selected (pull statistics, reward scores), and learning progression (warmup, learning, active). CAE Section: Real-time TCS, DMA, Exhaustion, Adversarial cases, and Confidence scores with visual indicators (emoji-coded states, bar graphs, trend arrows). Bandit Performance: Algorithm selection, mode (Switch vs Blend), arm distribution, differentiation metrics, learning diagnostics. State Metrics Grid (Large mode): Normalized readings for trend alignment, momentum, volatility, volume flow, Bollinger position, ROC, directional movement, oscillator bias - all synthesized into a composite market state. This level of transparency is rare. Most "black box" indicators hide their decision logic. BPA-ML shows you exactly why it's making decisions in real-time, enabling informed discretionary overrides. Repainting: Complete Transparency Many divergence indicators don't clearly disclose repainting behavior. BPA-ML offers three explicit timing modes: Realtime: Shows developing signals on current bar. Repaints by design - this is a preview mode for learning, not for trading. Confirmed: Signals lock at bar close. Zero repainting. Recommended for live trading. Pivot Validated: Waits for full pivot confirmation (5+ bar delay). Highest purity, zero repainting, ideal for backtesting divergence quality. You choose the mode based on your priority - speed vs certainty. The transparency empowers rather than obscures. Educational Value: Learning Platform Most indicators are tools - you use them, but you don't learn from them. BPA-ML is designed as a learning platform: Advisory Mode: Signals always appear, but blocked signals receive warning annotations explaining why CAE would have filtered them. You see the decision logic in action without missing learning opportunities. Dashboard Transparency: Real-time display of all metrics shows exactly how market state influences decisions. Comprehensive Documentation: In-indicator tooltips, extensive publishing statement, and user guides explain not just what to click, but why the algorithms work and how to apply them strategically. Algorithm Comparisons: By trying different bandit algorithms (UCB1 vs Thompson vs Epsilon vs Gradient), you learn the differences between exploration strategies - knowledge applicable beyond trading. This isn't just a signal generator - it's an educational tool that teaches machine learning concepts, market intelligence interpretation, and systematic decision-making. What This System Is NOT To be completely transparent about positioning: Not a Prediction System: BPA-ML doesn't predict future prices. It identifies structural divergences, assesses current market state, and learns which oscillator configurations historically correlated with better forward returns. The learning is retrospective optimization, not fortune telling. Not Fully Automated: This is a decision support tool, not a push-button profit machine. You still need to execute trades, manage risk, and apply discretionary judgment. The confidence scores guide position sizing, but you determine final risk allocation. Not Beginner-Friendly: The sophistication comes with complexity. This system requires understanding of divergence trading, basic machine learning concepts, and market state interpretation. It's designed for intermediate to advanced traders willing to invest time in learning the system. Not Magic: Even with optimal configurations and intelligent filtering, markets are probabilistic. Losing trades are inevitable. The system improves your probability distribution - it doesn't eliminate risk or guarantee profits. The Fundamental Difference Here's the core distinction: Traditional Divergence Indicators: Detect patterns and hope they work. "ML" Indicators (KNN/Clustering): Detect patterns and compare to historical similarities. BPA-ML: Detects patterns, evaluates outcomes, learns which detection methods work best for this specific context, understands market state before suggesting trades, and continuously improves without manual intervention. The difference isn't incremental - it's architectural. This is trading system infrastructure with embedded intelligence, not just a pattern detector with filters. Who This Is For BPA-ML is ideal for traders who: - Value systematic approaches over discretionary guessing - Appreciate transparency in decision logic - Are willing to let systems learn over 200+ bars before judging performance - Trade liquid instruments on 5-minute to daily timeframes - Want to learn machine learning concepts through practical application - Seek professional-grade tools without institutional price tags It's not ideal for: - Absolute beginners needing simple plug-and-play systems - 1-minute scalpers (noise dominates at very low timeframes) - Traders of illiquid instruments (insufficient data for learning) - Those seeking magic solutions without understanding methodology - Impatient optimizers wanting instant perfection What Makes This Original The innovation in BPA-ML lies in three interconnected breakthroughs that work synergistically: 1. Multi-Armed Bandit Oscillator Selection Traditional divergence indicators require manual optimization - you choose RSI with a length of 14, or Stochastic with specific settings, and hope they work. BPA-ML eliminates this guesswork through machine learning. The system maintains a grid of 40 candidate oscillator configurations spanning five oscillator families (RSI, Stochastic, CCI, MFI, Williams %R), four length parameters, and two smoothing settings. Using proven bandit algorithms (UCB1, Thompson Sampling, Epsilon-Greedy, or Gradient-based learning), the system continuously evaluates which configuration produces the best forward returns and automatically switches to the winning arm. This isn't random testing - it's intelligent exploration with exploitation, balancing the discovery of new opportunities against leveraging proven configurations. 2. Cognitive Analytical Engine (CAE) Divergences occur constantly, but most fail. The CAE solves this by computing a comprehensive market intelligence layer: Trend Conviction Score (TCS): Synthesizes ADX normalization, multi-timeframe EMA alignment, and structural persistence into a single 0-1 metric that quantifies how strongly the market is trending. When TCS exceeds your threshold, the system knows to avoid counter-trend trades unless other factors override. Directional Momentum Alignment (DMA): Measures the spread between fast and slow EMAs, normalized by ATR. This creates a regime-aware momentum indicator that adjusts its interpretation based on current volatility. Exhaustion Modeling: Aggregates volume spikes, pin bar formations, extended runs above/below EMAs, and extreme RSI readings into a probability that the current move is reaching climax. High exhaustion can override trend filters, allowing reversal trades at genuine turning points. Adversarial Validation: Before approving a bullish signal, the engine quantifies both the bull case (proximity to support EMAs, oversold conditions, volume confirmation) and the bear case (distance to resistance, overbought conditions). If the opposing case dominates by your threshold, the signal is blocked or flagged with a warning. Confidence Scoring: Every signal receives a 0-1 confidence score blending TCS, momentum magnitude, pullback quality, market state metrics, divergence strength, and adversarial advantage. You can gate signals on minimum confidence, ensuring only high-probability setups reach your attention. 3. Adaptive Parameter Mini-Bandits Beyond the oscillator itself, BPA-ML uses additional bandit systems to optimize: - Pivot lookback strictness - Minimum slope change threshold - TCS threshold for trend filtering These parameters are often instrument-specific. The adaptive bandits learn these nuances automatically. Why These Components Work Together Each layer serves a specific purpose in the signal generation hierarchy: Layer 1 - Oscillator Selection: The bandit ensures you're always using the oscillator configuration best suited to current market microstructure. Layer 2 - Divergence Detection: With the optimal oscillator selected, the engine scans for structural divergences using confirmed pivots. Layer 3 - CAE Filtering: Raw divergences are validated against market intelligence. Layer 4 - Spacing & Timing: Quality signals need proper spacing to avoid over-trading. This isn't a random collection of indicators. It's a decision pipeline where each stage refines signal quality, and the machine learning ensures the entire system stays calibrated to your specific trading context. Core Components - Deep Dive Divergence Engine The foundation is a dual-mode divergence detector: Regular Divergence: Price makes a higher high while oscillator makes a lower high (bearish), or price makes a lower low while oscillator makes a higher low (bullish). These signal potential reversals. Hidden Divergence: Price makes a lower high while oscillator makes a higher high (bullish continuation), or price makes a higher low while oscillator makes a lower low (bearish continuation). These signal trend strength. Pivots are confirmed using symmetric lookback periods. Divergence strength is quantified via slope separation between price and oscillator. Signal Timing Modes Realtime (live preview): Shows potential signals on current bar. Repaints by design. Use for learning only. Confirmed (1-bar delay): Signals lock at bar close. No repainting. Recommended for live trading. Pivot Validated: Waits for full pivot confirmation (5+ bar delay). Highest purity, best for backtesting. Multi-Armed Bandit Algorithms UCB1: Optimism under uncertainty. Excellent balance for most use cases. Thompson Sampling: Bayesian approach with smooth exploration. Great for long-term adaptation. Epsilon-Greedy: Simple exploitation with random exploration. Easy to understand. Gradient-based: Lightweight weight adjustment based on rewards. Fast and efficient. Bandit Operating Modes Switch Mode: Uses top-ranked arm directly. Maximum amplitude, crisp signals. Blend Mode: Softmax mixture with dominant-arm preservation. Ensemble stability while maintaining amplitude for overbought/oversold crossings. How to Use This Indicator Initial Setup 1. Apply BPA-ML to your chart 2. Select visual mode (Minimal/Standard/Holographic/Cyberpunk/Quantum) 3. Choose signal timing - "Confirmed (1-bar delay)" for live trading 4. Set Oscillator Type to "Auto (ML)" and enable it 5. Select bandit algorithm - UCB1 recommended 6. Choose Blend mode with temperature 0.4-0.5 CAE Configuration Start with "Advisory" mode to learn the system. Signals appear with warnings if CAE would have blocked them. Switch to "Filtering" mode when comfortable - CAE actively blocks low-quality signals. Enable the three primary filters: - Strong Trend Filter - Adversarial Validation - Confidence Gating Parameter Guidance by Trading Style Scalping (1-5 minute charts): - Algorithm: Thompson or UCB1 - Mode: Blend (temp 0.3-0.4) - Horizon: 8-12 bars - Min Confidence: 0.30-0.40 - TCS Threshold: 0.70-0.80 - Spacing: 8-12 any, 16-24 same-side Day Trading (15min-1H charts): - Algorithm: UCB1 - Mode: Blend (temp 0.4-0.6) - Horizon: 12-24 bars - Min Confidence: 0.35-0.45 - TCS Threshold: 0.80-0.85 - Spacing: 12-20 any, 20-30 same-side Swing Trading (4H-Daily charts): - Algorithm: UCB1 or Thompson - Mode: Blend (temp 0.6-1.0) or Switch - Horizon: 20-40 bars - Min Confidence: 0.40-0.55 - TCS Threshold: 0.85-0.95 - Spacing: 20-40 any, 30-60 same-side Signal Interpretation Bullish Signals: Green markers below price. Enter long when detected. Bearish Signals: Red markers above price. Enter short when detected. Blocked Signals: Orange X markers show filtered signals (Advisory mode). Confidence Rings: Single ring at 50%+ confidence, double at 70%+. Use for position sizing. Dashboard Metrics Oscillator Section: Shows active type, value, state, and parameters. Cognitive Engine: - TCS: 0.80+ indicates strong trend - DMA: Momentum direction and strength - Exhaustion: 0.75+ warns of reversal - Bull/Bear Case: Adversarial scoring - Differential: Net directional advantage Bandit Performance: Shows algorithm, mode, selected configuration, and learning diagnostics. Visual Zones - Bullish Zone: Blue/cyan tint - favorable for longs - Bearish Zone: Red/magenta tint - favorable for shorts - Exhaustion Zone: Yellow warning - reduce sizing Visual Mode Selection Minimal: Clean triangles, maximum performance Standard: Dashed lines with zones, professional presentation Holographic: Gradient bands, excellent for teaching Cyberpunk: Neon glow trails, high contrast Quantum: Probability cloud with confidence-based opacity Calculation Methodology Oscillator Computation For each bandit arm: calculate base oscillator, apply smoothing, normalize to 0-100. Switch mode: use top arm directly. Blend mode: softmax mixture blended with dominant arm (70/30) to preserve amplitude. Divergence Detection 1. Identify price and oscillator pivots using symmetric periods 2. Store recent pivots with bar indices 3. Scan for slope disagreements within lookback range 4. Require minimum slope separation 5. Classify as regular or hidden divergence 6. Compute strength score CAE Metrics TCS: 0.35×ADX + 0.35×structural + 0.30×alignment DMA: (EMA21 - EMA55) / ATR14 Exhaustion: Aggregates volume, divergence, RSI extremes, pins, extended runs Confidence: 0.30×TCS + 0.25×|DMA| + 0.20×pullback + 0.15×state + 0.10×divergence + adversarial Bandit Rewards Every horizon period: compute log return normalized by ATR, clip to ±0.5, bonus if signal was positive. Update arm statistics per algorithm. Ideal Market Conditions Best Performance: - Liquid instruments with clear structure - Trending markets with consolidations - 5-minute to daily timeframes - Consistent volume and participation Learning Requirements: - Minimum 200 bars for warmup - Ideally 500-1000 bars for full confidence - Performance improves as bandit accumulates data Challenging Conditions: - Extremely low liquidity - Very low timeframes (1-minute or below) - Extended sideways consolidation - Fundamentally-driven gap markets Dashboard Interpretation Guide TCS: - 0.00-0.50: Weak trend, reversals viable - 0.50-0.75: Moderate trend, mixed approach - 0.75-0.85: Strong trend, favor continuation - 0.85-1.00: Very strong trend, counter-trend high risk DMA: - -2.0 to -1.0: Strong bearish - -0.5 to 0.5: Neutral - 1.0 to 2.0: Strong bullish Exhaustion: - 0.00-0.50: Fresh move - 0.50-0.75: Mature, watch for reversals - 0.75-0.85: High exhaustion - 0.85-1.00: Critical, reversal imminent Confidence: - 0.00-0.30: Low quality - 0.30-0.50: Moderate quality - 0.50-0.70: High quality - 0.70-1.00: Premium quality Common Questions Why no signals? - Blend mode: lower temperature to 0.3-0.5 - Loosen OB/OS to 65/35 - Lower min confidence to 0.35 - Reduce spacing requirements - Use Confirmed instead of Pivot Validated Why frequent oscillator switching? - Normal during warmup (first 200+ bars) - After warmup: may indicate regime shifting market - Lower temperature in Blend mode - Reduce learning rate or epsilon Blend vs Switch? Use Switch for backtesting and maximum exploitation. Use Blend for live trading with temperature 0.3-0.5 for stability. Recalibration frequency? Never needed. System continuously adapts via bandit learning and weight decay. Risk Management Integration Position Sizing: - 0.30-0.50 confidence: 0.5-1.0% risk - 0.50-0.70 confidence: 1.0-1.5% risk - 0.70+ confidence: 1.5-2.0% risk (maximum) Stop Placement: - Reversals: beyond divergence pivot plus 1.0-1.5×ATR - Continuations: beyond recent swing opposite direction Targets: - Primary: 2-3×ATR from entry - Scale at interim levels - Trail after 1.5×ATR in profit Important Disclaimers BPA-ML is an advanced technical analysis tool for identifying high-probability divergence patterns and assessing market state. It is not a complete trading system. Machine learning components adapt to historical patterns, which does not guarantee future performance. Proper risk management, position sizing, and additional confirmation methods are essential. No indicator eliminates losing trades. Backtesting results may differ from live performance due to execution factors and dynamic bandit learning. Always validate on demo before committing real capital. CAE filtering reduces but does not eliminate false signals. Market conditions change rapidly. Use appropriate stops and never risk excessive capital on any single trade. — Dskyz, Trade with insight. Trade with anticipation.
Pine Script® göstergesi
DskyzInvestments tarafından
2
NeuroPip OscillatorNeuroPip Oscillator – Adaptive Momentum Oscillator with Deviation “Bursts” Indicator published by PipGuard. NeuroPip Oscillator is an adaptive momentum oscillator displayed in a separate panel , designed to read market momentum and regime shifts through a dynamically adjusted signal line. The main signal ( NeuroPulse ) changes color according to the active regime, while the Synapse Burst line highlights real-time deviations and momentum acceleration phases. How it Works • Non-Classical Logic: Unlike conventional 3-candle swing models, NeuroPip uses a custom adaptive mechanism that blends trend behavior , volatility , and closing dynamics over a dynamic bar range . This allows the oscillator to filter noise and focus on true structural impulses , rather than random fluctuations, producing smoother and more reliable regime detection. • Color Shift & Waves: The NeuroPulse line turns orange in bullish phases and violet in bearish phases. A Colour fill between the signal and baseline visually represents the intensity and direction of momentum in real time. • Synapse Burst (Active Deviation): The Synapse Burst line measures the distance between the momentum curve and its adaptive baseline, revealing acceleration "bursts" or momentum drops as they occur. How to Use 1. Add the oscillator to your chart (separate panel). 2. Read the color of the signal to determine the current market regime (bullish/bearish). 3. Observe the wave strength to gauge momentum continuity and pressure . 4. Use Synapse Burst spikes to confirm acceleration or deceleration in price movement. 5. Combine its insights with your risk management and main chart analysis. EXAMPLE OF USE EXAMPLE OF USE Settings • All parameters are internally preconfigured for stability and visual consistency. • Colors and waves are optimized and not user-editable. • Works on all markets and timeframes (panel overlay=false ). Alerts (Recommended to Enable) Two built-in alerts trigger on bar close when the regime changes: • Bullish Cross → signal turning bullish . • Bearish Cross → signal turning bearish . Each alert includes the symbol and timeframe , ensuring you never miss a regime shift even when you’re away from the screen. Limitations • The oscillator confirms regime changes; it does not predict them. • In low-volatility environments, transitions may appear more frequent. • Past performance does not guarantee future results . Access This script is available under invite-only access . To request access, use the link provided in the Signature below the publication. Note: Technical analysis tool designed to study price momentum and structure. It does not constitute financial advice or guarantee performance. Indicator published by PipGuard.
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PipGuard tarafından
Directional Strength and Momentum Index█ OVERVIEW “Directional Strength and Momentum Index” (DSMI) is a technical analysis indicator inspired by DMI, but due to different source data, it produces distinct results. DSMI combines direction measurement, trend strength, and overheat levels into a single index, enhanced with gradient fills, extreme zones, entry signals, candle coloring, and a summary table. █ CONCEPT The classic DMI, despite its relatively simple logic, can seem somewhat chaotic due to separate +DI and -DI lines and the need for manual interpretation of their relationships. The DSMI indicator was created to increase clarity and speed up results, consolidating key information into a single index from 0 to 100 that simultaneously: - Indicates trend direction (bullish/bearish) - Measures movement strength - Identifies overheat levels - Generates ready entry signals DMI (ADX + +DI / -DI) measures trend direction and strength, but does so based solely on comparing price movements between candles. ADX shows whether the trend is orderly and growing (e.g., above 20–30), but does not assess how dynamic the movement is. DSMI, on the other hand, takes into account candle size and actual market aggression, thus showing directional momentum — whether the trend has real “fuel” to sustain or accelerate, not just whether it is orderly. The main calculation difference involves replacing True Range with candle size (high-low) and using directional EMA instead of Wilder smoothing. This allows DSMI to react faster to momentum changes, eliminating delays typical of classic DMI based on TR. This gives the trader an immediate picture of the market situation without analyzing multiple lines. █ FEATURES DSMI Main Line: - EMA(Directional Index) based on +DS and -DS - Scale 0–100, smooth color gradient depending on strength +DS / -DS: - Positive and Negative Directional Strength - Gradient fill between lines — more intense with stronger trend Extreme Zones: - Default 20 and 80 - Gradient fill outside zones Trend Strength Levels: - Weak (<10) → neutral - Moderate (up to 35) - Strong (up to 45) - Overheated (up to 55) - Extreme (>55) All levels editable Entry Signals: - Activated on crossing entry level (default 20) Or on direction change when DSMI already ≥ entry level - Highlighted background (green/red) Candle Coloring: - According to current trend Trend Strength Table: - Top-right corner - Shows current strength (WEAK/STRONG etc.) + DSMI value Alerts: - DSMI Bullish Entry - DSMI Bearish Entry █ HOW TO USE Add to Chart: Paste code in Pine Editor or find in indicator library. Settings: DSMI Parameters: - DSMI Period → default 20 - Show DSMI Line → on/off Extreme Zones: - Lower Level → default 20 - Upper Level → default 80 Trend Strength Levels: - Weak, Moderate, Strong, Overheated → adjust to strategy Trend Colors: - BULLISH → default green - BEARISH → default red - NEUTRAL → gray Entry Signals: - Show Highlight → on/off - DSMI Entry Level → default 20 Signal Interpretation: - DSMI Line: Main strength indicator. - Gradient between +DS and -DS: Visualizes side dominance. - Crossing 18 with direction confirmation → entry signal. - Extreme Zones: Potential reversal or continuation points after correction. - Table: Quick overview of current trend condition. █ APPLICATIONS The indicator works well in: - Trend-following: Enter on signal, exit on direction change or overheat. When a new trend appears, consider entering a position, preferably with a rising trend strength indicator. - Scalping/daytrading: Shorter period (7–10), lower entry level. - Swing/position: Longer period (20–30), higher entry level, extreme zones as filters. - Noise filtering: Ignores consolidation below “Weak” – increasing value e.g. to 15 highlights consolidation zones, but no signals appear there. Style Adjustment: - Aggressive strategies → shorten period and entry level - Conservative → extend period, raise entry level (25–30), watch “Overheated” “Weak” level (<10 default) → neutral; increasing it e.g. to 15 gives fewer but higher-quality signals. The Weak zone value controls the level below which no signals appear, and the gradient turns gray (often aligned with consolidation zones). Combine with: - Support/resistance levels - Fair Value Gaps (FVG) - Volume (Volume Profile, VWAP) - Other oscillators (RSI, Stochastic) █ NOTES - Works on all markets and timeframes. - Adjust period and levels to instrument volatility. - Higher entry level → fewer signals, higher quality. - Neutral color below “Weak” – avoids trading in consolidation. - Gradient and table enable quick assessment without line analysis.
Pine Script® göstergesi
Uncle_the_shooter tarafından
12
ADX Trend Color HistogramOverview: This script provides a visually enhanced version of the classic Average Directional Index (ADX) indicator. Instead of a simple line, it plots the ADX as a histogram, making it easier to gauge trend strength at a glance. The key feature is its dynamic color-coding, which shifts based on the relationship between the Directional Indicators (DI+ and DI-), offering immediate insight into market momentum. Features: Histogram Style: The ADX value is presented as a histogram for clear, easy-to-read visualization of trend strength. Dynamic Color-Coding: The histogram bars are colored green when DI+ is greater than DI-, indicating bullish momentum. They turn red when DI- is greater than DI+, signaling bearish momentum. Customizable Transparency: The default color transparency is set to 80% (20% opacity) for a clean look that doesn't overpower the main chart, but this can be adjusted in the script's color settings. Built-in Alerts: The script includes configurable alerts that trigger whenever the momentum shifts, i.e., when the color of the histogram changes from red to green or vice-versa. This allows you to stay notified of potential changes in trend direction without constantly watching the chart. Clean and Simple: The code is well-structured and commented for clarity, making it easy for other PineScripters to understand or modify. How to Use: Assess Trend Strength: The height of the histogram bars represents the strength of the current trend. Higher bars suggest a stronger trend (either bullish or bearish), while lower bars indicate a weak or non-trending market. Identify Momentum Direction: The color of the bars provides a quick guide to the direction of market momentum. Green Bars: Indicate that the upward momentum is dominant. Red Bars: Indicate that the downward momentum is dominant. Use Alerts for Signals: Set up alerts in TradingView based on the "ADX Green" and "ADX Red" conditions to receive notifications for potential entry or exit signals when the momentum shifts. A change from red to green can signal a potential bullish reversal or continuation, while a change from green to red can signal a bearish one.
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GlareTuesday tarafından
Nic RSI + MACD (single pane)📊 SPACE-SAVING COMBINED INDICATOR FOR FREE USERS This indicator combines RSI and MACD into a single pane, perfect for TradingView users with limited indicator slots. Designed to match the default TradingView styling you're familiar with. 🎯 USE AS A PACKAGE: For optimal trading analysis, use this indicator together with "Nic SMA 9, SMA 200, 9 count" which displays moving averages and the 9 count on your main chart. Together, these two indicators give you a complete technical analysis setup while staying within the 2-3 indicator limit for free TradingView accounts. 📈 WHAT'S INCLUDED: ✅ RSI (Relative Strength Index) - Top Section: • Default purple line matching TradingView's built-in RSI • Reference lines at 30, 50, and 70 levels • Background shading for overbought (>70) and oversold (<30) zones • Takes up 55% of the pane for better visibility • Fully customizable period (default: 14) ✅ MACD (Moving Average Convergence Divergence) - Bottom Section: • Classic histogram with TradingView's default color scheme: - Teal/cyan for positive momentum - Red/pink for negative momentum • Blue MACD line and orange Signal line • Clear zero line for easy reference • Takes up 45% of the pane • Fully customizable periods (default: 12, 26, 9) ⚙️ CUSTOMIZATION OPTIONS: • Adjust RSI length and source • Customize RSI line color • Adjust MACD fast, slow, and signal periods • Customize MACD source • Modify gap size between RSI and MACD sections 💡 WHY USE THIS? • Saves indicator slots - combines 2 indicators into 1 • Professional appearance matching TradingView defaults • Clean, uncluttered display • All the functionality of separate RSI and MACD indicators • Perfect for traders on free or limited plans 📋 RECOMMENDED SETUP: 1. Add "Nic SMA 9, SMA 200, 9 count" to your main chart (published separately) 2. Add this "Nic RSI top + MACD bottom" indicator 3. Optionally add Volume indicator if you have a slot available This gives you moving averages, the 9 count, RSI, and MACD - everything you need for comprehensive technical analysis! 🔔 WORKS WITH FREE ACCOUNTS: Both indicators in the Nic package are designed to maximize your analysis capabilities within TradingView's indicator limits. #RSI #MACD #TechnicalAnalysis #FreeIndicators #SpaceSaving #CombinedIndicator
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nbennett1106 tarafından
MCL RSI Conflux v2.5 — Multi-Timeframe Momentum & Z-Score Full Description Overview The MCL RSI Conflux v2.5 is a multi-timeframe momentum model that integrates daily, weekly, and monthly RSI values into a unified composite. It extends the classical RSI framework with adaptive overbought/oversold thresholds and statistical normalization (Z-score confluence). This combination allows traders to visualize cross-timeframe alignment, identify synchronized momentum shifts, and detect exhaustion zones with higher statistical confidence. Methodology The script extracts RSI data from three major time horizons: Daily RSI (short-term momentum) Weekly RSI (intermediate trend) Monthly RSI (macro bias) Each RSI is optionally smoothed, weighted, and aggregated into a Composite RSI. A Z-score transformation then measures how far each RSI deviates from its historical mean, revealing when momentum strength is statistically extreme or aligned across timeframes. Key Features Multi-Timeframe RSI Engine – Computes RSI across D/W/M intervals with individual weighting controls. Adaptive Overbought/Oversold Bands – Automatically adjusts OB/OS thresholds based on rolling volatility (standard deviation of daily RSI). Composite RSI Score – Weighted consensus RSI that represents total market momentum. Z-Score Confluence Analysis – Identifies when all three timeframes are statistically synchronized. Z-Composite Histogram – Displays aggregated Z-score strength around the midline (50). Divergence Detection – Flags confirmed pivot-based bull and bear divergences on the daily RSI. Dynamic Gradient Background – Shifts from red to green based on composite momentum regime. Customizable Control Panel – Displays RSI values, Z-scores, state, and adaptive bands for each timeframe. Integrated Alerts – For crossovers, risk-on/off thresholds, alignment, and Z-confluence events. Interpretation All RSI values above 50: multi-timeframe bullish alignment. All RSI values below 50: multi-timeframe bearish alignment. Composite RSI > 60: risk-on environment; momentum expansion. Composite RSI < 45: risk-off environment; momentum contraction. Adaptive OB/OS hits: potential exhaustion or mean reversion setup. Green Z-ribbon: all Z-scores positive and aligned (statistical confirmation). Red Z-ribbon: all Z-scores negative and aligned (broad market weakness). Divergences: short-term warning signals against the prevailing momentum bias. Practical Application Use the Composite RSI as a global momentum gauge for position bias. Trade only in the direction of higher-timeframe alignment (avoid countertrend RSI). Combine Z-ribbon confirmation with Composite RSI crosses to filter noise. Use divergence labels and adaptive thresholds for risk reduction or exit timing. Ideal for swing traders and macro momentum models seeking trend synchronization filters. Recommended Settings Market Mode k-Band Lookback Use Case Stocks / ETFs Adaptive 0.85 200 Medium-term rotation filter Crypto Adaptive 1.00 150 Volatility-responsive swing filter Commodities Fixed 70/30 100 Mean reversion model Alerts Included Daily RSI crossed above/below Weekly RSI Composite RSI > Risk-On threshold Composite RSI < Risk-Off threshold All RSI aligned above/below 50 Z-Score Conformity (All positive or all negative) Overbought/Oversold triggers Author’s Note This indicator was designed for research and systematic confluence analysis within Mongoose Capital Labs. It is not financial advice and should be used in combination with independent risk assessment, volume confirmation, and higher-timeframe context.
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TheRealMongoose tarafından
Ultimate MACD Suite [BigBeluga]🔵 OVERVIEW The Ultimate MACD Suite is an advanced momentum-based system that enhances the classic MACD with modern features tailored for professional traders. It transforms MACD into a full market-decision engine — offering multi-timeframe confluence, adaptive histogram behavior, divergence detection, heatmap trend visualization, and actionable reversal signals. This toolkit goes far beyond standard MACD, helping traders identify trend momentum shifts, exhaustion zones, high-probability reversal areas, and breakout confirmation signals across multiple timeframes simultaneously. It's to be used as part of a major trading system and to simplify usage of the MACD. ⚠️ Note: This is not a traditional MACD — it uses normalized values , enhanced visual feedback, and a multi-timeframe dashboard engine for superior signal quality and clarity. 🔵 CONCEPTS Combines MACD momentum, signal-line crossovers, and histogram reversals into one system Uses normalized scaling to detect extreme momentum levels and exhaustion zones Multi-timeframe dashboard displays consensus signal alignment across several timeframes Divergence engine identifies bullish & bearish trend weakening early Heatmap mode visually distinguishes strong trend phases from neutral or fading momentum Reversal arrows & crosses highlight actionable turning points on chart 🔵 FEATURES Normalized MACD Engine — improves signal clarity across all assets/timeframes MACD Heatmap Mode — color-coded slope intensity for trend strength monitoring MACD Rising and Falling Mode — color-coded rising and falling MACD regimes Histogram Reversal Detection — early momentum fade signal before price turns Signal-Line Momentum Shifts — bullish ▲ & bearish ▼ alerts on cross-confirmation Overbought/Oversold Bands — enhanced visual thresholds at ±80 levels Smart Divergence Detection (Non-Lag) — confirms regular bullish & bearish divergences Multi-Timeframe Dashboard — MACD, signal, histogram & divergence signals across 5+ TFs Reversal Push-Filter — ensures only clean signals after confirmed momentum inflection On-Chart Reversal Labels — optional compact signal markers for clean visual execution Histogram Color Logic — rising/falling or heatmap mode for deeper momentum reading 🔵 HOW TO USE Look for MACD crossing above signal + green histogram to confirm bullish momentum Use ▼ and ▲ arrows to catch confirmed momentum reversals Monitor the dashboard — the more timeframes align, the stronger the setup Watch divergences for trend exhaustion or reversal setups Treat histogram trend shifts as early momentum clues before price reacts Use ±80 levels to identify overheated conditions & fade opportunities Combine with structure, volume, or BigBeluga liquidity tools for higher accuracy 🔵 ALERTS The indicator includes a full alert suite for automation and real-time trade readiness: MACD crossovers (Bullish / Bearish) Histogram reversals & zero-line shifts Bullish / Bearish divergence detection Overbought / Oversold MACD alerts Bullish ▲ and bearish ▼ reversal triggers Use these alerts to automate signal monitoring or feed algorithmic systems. 🔵 CONCLUSION The Ultimate MACD Suite transforms a classic indicator into a powerful trading engine. With multi-timeframe alignment, heatmapping, divergence logic, normalized scaling and automated signals, it becomes an elite momentum-confirmation and reversal-timing system built for serious traders. Whether scalping intraday or managing swing positions, this MACD engine helps identify the most profitable phases of trend movement — while warning early when a trend is weakening.
Pine Script® göstergesiÜcretli komut dosyası
BigBeluga tarafından
22
Ultimate RSI Suite [BigBeluga]🔵 OVERVIEW The Ultimate RSI Suite elevates the classic RSI into a full professional trading system. It combines momentum analysis, advanced divergence detection, volatility-based RSI channels, multi-timeframe signals, deviation tracking, and reversal alerts into one powerful tool. This is no ordinary RSI — it’s a complete momentum intelligence engine designed to identify trend strength, exhaustion, breakout conditions, and reliable reversal points with high precision. ⚠️ Note: This suite enhances RSI with MTF dashboards, dynamic channels, deviation logic, and smart alerting — ideal for scalpers, swing traders, and institutional-style trend followers. 🔵 CONCEPTS Measures market momentum to detect overbought/oversold zones and trend health Tracks RSI behavior relative to dynamic channels (BB/Keltner/Donchian) Identifies regular bullish & bearish divergences Detects deviation moves after divergence to confirm trend continuation or exhaustion Multi-timeframe RSI conditions reveal higher-timeframe confluence Reversal triggers confirm early momentum shifts Overbought/oversold gradients visually highlight exhaustion zones 🔵 FEATURES Classic + Enhanced RSI with configurable lookback & price source RSI-Channel System (Bollinger, Keltner, Donchian) for volatility-adaptive trend structure RSI-Smoothing MA for trend direction filters RSI Reversal Signals for early trend inflection detection RSI Reversal Signals Deviation Levels +1 / +2 for advanced continuation confirmation Overbought/Oversold Gradient Zones at 35/65 or user-defined levels Divergence Engine for bullish & bearish momentum exhaustion signals On-Chart Divergence & Signals (full overlay capability) Divergence Engine Deviation Levels +1 / +2 for advanced continuation confirmation Multi-Timeframe Dashboard (RSI OB/OS, signals, divergences, channel breaks) • Hover your mouse over any signal cell to see how many bars ago it was triggered • Signals automatically expire after 50 bars Smart Alerts for divergence, reversals, channel breaks, and deviation triggers 🔵 HOW TO USE Enter long when RSI reverses from oversold & prints bullish divergence or a ▲ signal Enter short when RSI reverses from overbought & prints bearish divergence or ▼ Use channel breaks to confirm momentum expansions or trend shifts Look for deviation crosses (+1 / +2) for strong confirmation after divergence Track MTF table — more timeframe agreement = stronger conviction Avoid trading against MTF RSI extremes (OB/OS stacked zones) Combine with market structure or volume-based tools for maximum precision 🔵 ALERTS Includes full automation suite: Bullish / Bearish divergence Reversal signals (▲ / ▼) Channel breakouts (Up/Down) Deviation +1 / +2 confirmation triggers Extra RSI signal deviation alerts for precision continuation reads Great for automated systems, confirmation models, and high-probability intraday/swing entries. 🔵 CONCLUSION The Ultimate RSI Suite transforms RSI into a smart momentum-analysis system. With multi-timeframe logic, dynamic channels, advanced divergence/deviation systems, and powerful visual cues, it offers institutional-grade trend, exhaustion, and reversal detection. If you rely on RSI, this toolkit provides superior clarity, deeper context, and stronger execution timing — making it an elite upgrade for professional traders.
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BigBeluga tarafından
61
Local Hurst Slope [Dynamic Regime]1. HOW THE INDICATOR WORKS (Math → Market Edge)Step Math Market Intuition 1. Log-Returns r_t = log(P_t / P_{t-1}) Removes scale, makes series stationary 2. R/S per τ R = max(cum_dev) - min(cum_dev) S = stdev(segment) Measures memory strength over window τ 3. H(τ) = log(R/S) / log(τ) Di Matteo (2007) H > 0.5 → Trend memory H < 0.5 → Mean-reversion 4. Slope = dH/d(log τ) Linear regression of H vs log(τ) Slope > 0.12 → Trend accelerating Slope < -0.08 → Reversion emerging LEADING EDGE: The slope changes 3–20 bars BEFORE price confirms → You enter before the crowd, exit before the trap Slope > +0.12 + Strong Trend = Bullish = Long Slope +0.05 to +0.12 = Weak Trend = Cautious = Hold/Trail Slope -0.05 to +0.05 = Random = No Edge Slope-0.08 to -0.05 = Weak Reversion = Bearish setup = Prepare Short Slope < -0.08 = Strong Reversion = Bearish= Short PRO TIPS Only trade in direction of 200-day SMA Filters false signals Avoid trading 3 days before/after earnings Volatility kills edge Use on ETFs (SPY, QQQ) Cleaner than single stocks Combine with RSI(14) RSI < 30 + Hurst short = nuclear reversal
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chuckb504 tarafından
Crypto Breadth Engine [alex975] A normalized crypto market breadth indicator with a customizable 40 coin input panel — revealing whether rallies are broad and healthy across major coins and altcoins or led by only a few. 📊 Overview The Crypto Breadth Engine measures the real participation strength of the crypto market by analyzing the direction of the 40 largest cryptocurrencies by market capitalization. ⚙️ How It Works Unlike standard breadth tools that only count assets above a moving average, this indicator measures actual price direction: +1 if a coin closes higher, –1 if lower, 0 if unchanged. The total forms a Breadth Line, statistically normalized using standard deviation to maintain consistent readings across timeframes and volatility conditions. 🧩 Dynamic Input Mask All 40 cryptocurrencies are fully editable via the input panel, allowing users to easily replace or customize the basket (Top 40, Layer-1s, DeFi, Meme Coins, AI Tokens, etc.) without touching the code. This flexibility keeps the indicator aligned with the evolving crypto market. 🧭 Trend Bias The indicator classifies market structure as Bullish, Neutral, or Bearish, based on how the Breadth Line aligns with its moving averages (10, 20, 50). 💡 Dashboard A compact on-chart table displays in real time: • Positive and negative coins • Participation percentage • Current trend bias 🔍 Interpretation • Rising breadth → broad, healthy market expansion • Falling breadth → narrowing participation and structural weakness Ideal for TOTAL, TOTAL3, or custom crypto baskets on 1D,1W. Developed by alex975 – Version 1.0 (2025). ------------------------------------------------------------------------------------- 🇮🇹 Versione Italiana 📊 Panoramica Il Crypto Breadth Engine misura la partecipazione reale del mercato crypto, analizzando la direzione delle 40 principali criptovalute per capitalizzazione. Non si limita a contare quante coin sono sopra una media mobile, ma calcola la variazione effettiva del prezzo: +1 se sale, –1 se scende, 0 se invariato. La somma genera una Breadth Line normalizzata statisticamente, garantendo letture coerenti su diversi timeframe e fasi di volatilità. 🧩 Mascherina dinamica L’indicatore include una mascherina d’input interattiva che consente di modificare o sostituire liberamente i 40 ticker analizzati (Top 40, Layer-1, DeFi, Meme Coin, ecc.) senza intervenire nel codice. Questo lo rende sempre aggiornato e adattabile all’evoluzione del mercato crypto. ⚙️ Funzionamento e Trend Bias Classifica automaticamente il mercato come Bullish, Neutral o Bearish in base alla relazione tra la breadth e le medie mobili (10, 20, 50 periodi). 💡 Dashboard Una tabella compatta mostra in tempo reale: • Numero di coin positive e negative • Percentuale di partecipazione • Stato attuale del trend 🔍 Interpretazione • Breadth in crescita → mercato ampio e trend sano • Breadth in calo → partecipazione ridotta e concentrazione su pochi asset Ideale per analizzare TOTAL, TOTAL3 o panieri personalizzati di crypto. Funziona su timeframe 1D, 4H, 1W. Sviluppato da alex975 – Versione 1.0 (2025).
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Alex975 tarafından
4