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Emerson v8.4 – Kulture Metrics🜂 Emerson v8.4 – Kulture Metrics “When volatility breathes, probability answers.” The Emerson Engine isn’t another indicator—it’s a precision instrument built to exploit the hidden mathematics of motion. Born from Kulture Metrics’ Nosreme lineage, this model fuses trend architecture, volatility anatomy, and Linetsky’s path-integral weighting into one living signal core. It doesn’t predict — it quantifies belief. Each trigger passes through three unforgiving filters: Classical Trend & Momentum Logic — directional strength, pure and unadulterated. Squeeze Regime Anticipation — volatility compression before the break. Path-Integral Confirmation — stochastic payoffs weighted by risk-free discounting and volatility density. The result? Only signals where the math, the market, and the moment all align — Absolute Confirmations. No noise. No guessing. No emotion. In practice, Emerson waits. It calculates. Then it strikes with surgical precision — entries that respect volatility, discount rates, and expected path contributions like a derivatives desk built into your chart. Each decision point carries the full weight of stochastic probability theory — the same principles driving modern option pricing — yet distilled into something you can read at a glance. Benefits that separate you from the herd: ✅ Trades filtered by volatility percentile and expected payoff distribution — not gut feel. ✅ Dotted bias line reveals the “probabilistic current” beneath price itself. ✅ Alerts trigger only when logic, momentum, and probability form a unanimous verdict. ✅ Dynamic macro-window shading adapts to volatility pressure in real time. ✅ Every entry inherently respects your risk, target, and discounting horizon. Emerson v8.4 doesn’t ask the market what’s happening — it tells it what must happen next, given the probabilities. It’s not designed to comfort. It’s designed to confirm. Kulture Metrics. Built for traders who understand that randomness is just order not yet resolved.
Pine Script® indicator
by kulturemetrics
RSI Divergence DetectorOverview The RSI Divergence Detector is a comprehensive technical analysis tool designed to identify both regular and hidden divergences between price action and the Relative Strength Index (RSI). This indicator helps traders spot potential trend reversals and continuations by automatically detecting when price movements diverge from RSI momentum. What are Divergences? Regular Divergences signal potential trend reversals: Bullish Divergence: Price makes a lower low while RSI makes a higher low → Potential upward reversal Bearish Divergence: Price makes a higher high while RSI makes a lower high → Potential downward reversal Hidden Divergences signal trend continuation: Hidden Bullish Divergence: Price makes a higher low while RSI makes a lower low → Uptrend continuation Hidden Bearish Divergence: Price makes a lower high while RSI makes a higher high → Downtrend continuation Automatic Divergence Detection Detects all four types of divergences automatically Draws connecting lines between divergence points on the RSI Labels each divergence with clear text indicators ("Bull", "Bear", "HBull", "HBear") Independent toggle switches for each divergence type Dynamic RSI Display RSI line changes color based on momentum: Green when RSI is above 50 (bullish momentum) Red when RSI is below 50 (bearish momentum) Standard overbought (70) and oversold (30) levels marked Shaded background zones for overbought/oversold areas Pivot Detection System Adjustable pivot lookback period (default: 4 bars) Visual pivot markers at tops and bottoms of RSI Configurable maximum divergence range (default: 60 bars) Adjust the setting to you desired sensitivity on each timeframe. Full Customization Suite Label Customization: Choose label size (Tiny, Small, Normal, Large, Huge) Separate color selection for each divergence type Adjustable transparency (0-100%) Line Customization: Independent color control for bullish and bearish lines Line style options for each type (Solid, Dashed, Dotted) Default: Regular divergences use dashed lines, hidden divergences use dotted lines Visual Settings: Customizable overbought/oversold zone colors and transparency Gray horizontal reference lines (70, 50, 30) Pivot markers with adjustable visibility Default Settings RSI Length: 14 periods Pivot Lookback: 4 bars Max Divergence Range: 60 bars Label Size: Normal Bullish Color: #4CAF50 (Material Green) Bearish Color: #FF5252 (Material Red) Regular Line Style: Dashed Hidden Line Style: Dotted How to Use Customize Settings: Adjust colors, line styles, and detection parameters to your preference Toggle Divergence Types: Enable/disable specific divergence types based on your trading strategy Identify Signals: Look for labeled divergences with connecting lines on the RSI pane Confirm with Price Action: Use divergences in conjunction with other technical analysis tools Best Practices Regular Divergences: Best used to spot potential reversals at market extremes Hidden Divergences: Best used to identify pullback entry points in trending markets Confirmation: Always wait for price confirmation before entering trades based on divergences Multiple Timeframes: Check for divergences across multiple timeframes for stronger signals Risk Management: Use proper stop-losses as not all divergences lead to reversals Technical Specifications PineScript Version: v6 Indicator Type: Oscillator (separate pane) Maximum Lines: 500 Calculation Method: Pivot-based divergence detection using price and RSI comparisons
Pine Script® indicator
by xrischosser
Smart Divergence Engine [ChartNation]What this does Smart Divergence Engine is an RSI-based analysis panel that helps you spot momentum exhaustion and structure-backed reversals. It blends four concepts into one workflow: a smoothed RSI “price line,” volatility bands around that RSI, a “Shark Fin” re-entry filter that highlights stretched moves snapping back inside the bands, and pivot-confirmed RSI divergences (bullish/bearish) rendered cleanly on the panel with optional glow. This script is designed to be a clear decision aid, not a mashup for its own sake—the components work together to qualify divergences with volatility context and proper swing confirmation. How it works? RSI engine. The script computes RSI on your chosen source, then applies a light RMA smoothing to form the “price line.” Volatility bands. A 34-period SMA of the RSI creates a basis; standard deviation bands are projected using a configurable multiplier (default 1.618). The dotted 50 line anchors bias. Shark Fin (exhaustion cue). When RSI stretches beyond the outer band by a small buffer and then re-enters the band with slope confirmation and a minimum stdev (volatility) condition, the script fills the gap between RSI and the violated band (20% style by default). A cooldown avoids back-to-back signals. Confirmed divergences. Swing points are detected using Pivot Left/Right. When a new pivot confirms (i.e., after Pivot Right bars), the script compares price vs RSI at the pivot bar (rsi ). Bullish divergence: price makes a lower low while RSI makes a higher low. Bearish divergence: price makes a higher high while RSI makes a lower high. Confirmed events are drawn as lines between the last two pivots with compact labels (“Bull” / “Bear”). Once printed, they do not update historically. Why this is useful Divergences alone can be noisy. By waiting for swing confirmation and adding a volatility-aware re-entry filter, the panel focuses attention on exhaustion areas that align with structure—reducing false positives during choppy conditions. The gradient “beauty mode” improves readability of RSI regimes around the 50 midline without cluttering the pane. Inputs (key settings) RSI Length (default 14) – momentum window. Volatility Band Length (34) and Band Multiplier (1.618) – widen/narrow band sensitivity. Overbought / Oversold (68/32) – horizontal guides and internal offsets for labels. Pivot Left / Pivot Right (default 10/10) – swing definition; divergence is evaluated at the pivot bar (rsi ). Shark Fin controls: Fin depth buffer (RSI pts) – how far beyond the band counts as “stretched.” Min band stdev – volatility threshold to qualify fins. Min bars between fins – cooldown. Style / Beauty Mode: optional gradient fill above/below 50, divergence line glow and widths, top/bottom colors, and opacity. Visuals RSI line (thin, smoothed), upper/lower bands, 50 midline (dotted). Shark Fin shows only as a soft fill while forming; confirmations are alertable. Divergences draw compact lines + tiny dot + “Bull/Bear” labels on the panel. Glow and widths are user-tunable. Alerts Configure alerts on any chart/timeframe using these built-in conditions: “RSI Shark Fin — Bullish” – RSI re-entered from below the lower band (with slope + stdev + cooldown). “RSI Shark Fin — Bearish” – RSI re-entered from above the upper band (with slope + stdev + cooldown). “Bullish Divergence (Panel)” – pivot-confirmed bullish divergence. “Bearish Divergence (Panel)” – pivot-confirmed bearish divergence. How to use (practical playbook) Confluence first. Divergences are stronger when Shark Fin confirms exhaustion and RSI is transitioning around the 50 midline. Trend context. In strong trends, counter-trend divergences can fail; consider waiting for RSI to re-enter the band or reclaim/loss the 50 line. Risk management. Treat signals as context, not entries on their own—pair with price action (structure, S/R, candles) and a predefined stop/size plan. Notes & limitations Divergences and labels only appear after a swing completes (after Pivot Right bars). This keeps signals tied to confirmed structure. This panel operates in oscillator space (overlay=false). If you prefer price-chart markers/lines, use the companion overlay version built on the same logic.
Pine Script® indicator
by chartnation
MPO4 Lines – Modal Engine█ OVERVIEW MPO4 Lines – Modal Engine is an advanced multi-line modal oscillator for TradingView, designed to detect momentum shifts, trend strength, and reversal points through candle-based pressure analysis with multiple fast lines and a reference slow line. It features divergence detection on Fast Line A, overbought/oversold return signals, dynamic coloring modes, and layered gradient visualizations for enhanced clarity and decision-making. █ CONCEPT The indicator is built upon the Market Pressure Oscillator (MPO) and serves as its expanded evolution, aimed at enabling broader market analysis through multiple lines with varying parameters. It calculates modal pressure using candle body size and direction, weighted against average body size over a lookback period, then normalized and smoothed via EMA. It generates four distinct oscillator lines: a heavily smoothed Slow Line (trend reference), two Fast Lines (A & B) for momentum and support/resistance, and an optional Line 4 for additional confirmation. Divergence is calculated solely on Fast Line A, with visual gradients between lines and bands for intuitive interpretation. █ WHY USE IT? - Multi-Layer Momentum: Combines slow trend reference with dual fast lines for precise entry/exit timing. - Divergence Precision: Bullish/bearish divergences on Fast Line A with labeled confirmation. - OB/OS Return Signals: Clear buy/sell markers when Fast Line A exits oversold/overbought zones. - Dynamic Visuals: Gradient fills, line-to-line shading, and band gradients for instant market state recognition. - Flexible Coloring: Slow Line color by direction or zero-position; fast lines by sign. - Full Customization: Independent lengths, smoothing, visibility, and transparency — by adjusting the lengths of different lines, you can tailor results for various strategies; for example, enabling Line 4 and tuning its length allows trading based on crossovers between different lines. █ HOW IT WORKS? - Candle Pressure Calculation: Body = math.abs(close - open); avgBody = ta.sma(body, len). Direction = +1 (bull), –1 (bear), 0 (neutral). Weight = body / avgBody. Contribution = direction × weight. - Rolling Sum & Normalization: Sums contributions over lookback, normalizes to ±100 scale (÷ (len × 2) × 100). Smoothing: Applies primary EMA (smoothLen), with extra EMA on Slow Line for stability. Line Structure: - Slow Line = calcCPO(len1=20, smoothLen1=5) → extra EMA (5) - Fast Line A = calcCPO(len2=6, smoothLen2=7) - Fast Line B = calcCPO(len3=6, smoothLen3=10) - Line 4 = calcCPO(len4=14, smoothLen4=1) Divergence Detection: Uses ta.pivothigh/low on price and Fast Line A (pivotLength left/right). Bullish: lower price low + higher osc low. Bearish: higher price high + lower osc high. Valid within 5–60 bar window. Signals: - Buy: Fast Line A crosses above oversold (–30) - Sell: Fast Line A crosses below overbought (+30) - Slow Line color flip (direction or zero-cross) - Divergence labels ("Bull" / "Bear") - Band Coloring as Momentum Signal: When Fast Line A ≤ Fast Line B → Overbought band turns red (bearish pressure building) When Fast Line A > Fast Line B → Oversold band turns green (bullish pressure building) This dynamic coloring serves as visual confirmation of momentum shift following fast line crossovers Visualization: - Gradients: Fast B → Zero (multi-layer fade), Fast A ↔ B fill, OB/OS bands - Dynamic colors: Green/red based on sign or trend - Zero line + dashed OB/OS thresholds Alerts: Trigger on OB/OS returns, Slow Line changes, and divergences. █ SETTINGS AND CUSTOMIZATION - Line Visibility: Toggle Slow, Fast A, Fast B, Line 4 independently. Line Lengths: - Slow Line: Base (20), Primary EMA (5), Extra EMA (5) - Fast A: Lookback (6), EMA (7) - Fast B: Lookback (6), EMA (10) - Line 4: Lookback (14), EMA (1) - Slow Line Coloring Mode: “Direction” (trend-based) or “Position vs Zero”. - Bands & Thresholds: Overbought (+30), Oversold (–30), step 0.1. - Signals: Enable Fast A OB/OS return markers (default: on). - Divergence: Enable/disable, Pivot Length (default: 2, min 1). - Colors & Appearance: Full control over bullish/bearish hues for all lines, zero, bands, divergence, and text. Gradients & Transparency: - Fast B → Zero: 75 (default) - Fast A ↔ B fill: 50 - Band gradients: 40 - Toggle each gradient independently █ USAGE EXAMPLES The indicator allows users to configure various strategies manually, though no built-in alerts exist for them. Entry signals can include color of fast lines, crossovers between different lines, alignment of colors across lines, or consistency in direction. - Trend Confirmation: Slow Line above zero + green = bullish bias; below + red = bearish. - Entry Timing: Buy on Fast A crossing above –30 (circle marker), especially if Slow Line is rising or near zero. - Reversal Setup: Bullish divergence (“Bull” label) + Fast A in oversold + green gradient band = high-probability long. - Scalping: Fast A vs Fast B crossover in direction of Slow Line trend. - Noise Reduction: Increase extraSmoothLen on Slow Line █ USER NOTES - Best combined with volume, support/resistance, or trend channels. - Adjust lookback and smoothing to asset volatility. - Divergence delay = pivotLength; plan entries accordingly.
Pine Script® indicator
by Uncle_the_shooter
2
PTM Momentum v1.6 (QS)PTM Momentum v1.6 (QS): Decode Market Momentum with Quantitative Insight The PTM Momentum indicator is a sophisticated yet intuitive tool designed to provide traders with a deeper understanding of market momentum. Moving beyond traditional RSI and Stochastic analysis, PTM Momentum utilizes a proprietary quantitative scoring engine to measure not just the direction of momentum, but its quality and reliability. This allows traders to filter out market noise, avoid false signals, and make decisions with greater confidence. Version 1.6 (QS - Quant Score) represents a major leap forward, transforming a classic oscillator into an intelligent momentum analysis tool. Key Features of PTM Momentum v1.6 (QS): 1. The Quant Score (QS) Engine: A Dual-Analysis System The heart of PTM Momentum is the proprietary Quant Score engine, which delivers two critical metrics in a simple, easy-to-read label: * Momentum Score (0-100): This score measures the true strength of the current momentum. By analyzing both the level and the rate-of-change of smoothed RSI and Stochastic, it provides a normalized score that clearly defines the market state: Very Bullish, Bullish, Neutral, Bearish, or Very Bearish. * Confidence Score (Low/Medium/High): This score acts as a reliability filter. It cross-references seven different market conditions—including trend strength (ADX), oscillator agreement, and non-extreme levels—to determine the conviction behind the current momentum. A "High" confidence score indicates that multiple factors align, validating the signal. Rationale for Integration: This dual-score system prevents the common trap of chasing momentum that lacks real conviction. A "Very Bullish" momentum score with "Low" confidence is a clear warning sign, while a "Bullish" score that transitions to "High" confidence provides a high-quality trading signal. 2. Clear, Actionable Visual Label All complex calculations are distilled into a single, non-intrusive label on your chart. This allows you to assess the complete momentum profile of the market in a single glance, without cluttering your screen. The label includes: * Classic RSI and %K values with directional arrows. * The current Momentum Score status (e.g., "Bullish 🟢"). * The current Confidence Score (e.g., "Conf. > High"). 3. Fully Customizable Visuals While the core logic is proprietary, the visual representation is fully customizable. You can toggle the display of RSI/Stochastic plots, adjust background colors based on oscillator consensus, and show/hide OB/OS guide levels to tailor the indicator to your specific charting style. Why Every Trader Needs PTM Momentum In today's volatile markets, simply knowing if an asset is overbought or oversold is not enough. PTM Momentum provides the crucial missing context: Is the current momentum strong and reliable, or is it weak and likely to reverse? By answering this question, it empowers traders to filter out low-quality setups, improve entry timing, and manage trades more effectively. Value of an Invite-Only Script: PTM Momentum is not just another oscillator. It is a proprietary analytical engine that provides a quantifiable edge. The "secret sauce" behind the Momentum and Confidence scoring algorithms offers a level of insight that standard, free indicators cannot match, justifying its value as a premium, invite-only tool. Elevate your momentum analysis with PTM Momentum v1.6 (QS) today!
Pine Script® indicator
by Thethanaphat
Sniper StrategyThe Sniper Strategy is a clean and data-driven RSI-based system designed for precision entries and exits. It combines multi-timeframe RSI analysis, automated labeling, and dynamic P/L tracking — perfect for traders who want clarity, visual feedback, and strict risk control in one tool. 🧩 Core Features Dual RSI Framework: Calculates both the current timeframe RSI and a higher timeframe RSI to confirm trend strength and avoid false signals. Smart Entry Logic: Long signals when RSI drops below oversold level. Short signals when RSI exceeds overbought level. Automatic Exit Management: Configurable Stop Loss and Take Profit percentages. Optional RSI-based exit for flexible trade closures. All exits are visually labeled for transparency. Real-Time Profit Tracking: Displays a floating label above each bar showing current P/L (%), updated live while the position is open — giving you instant insight into trade performance. Clean Visual Design: Uses arrows and colored labels for entry/exit clarity. Optional RSI line and higher timeframe RSI plot included. Alerts Ready: Built-in alert conditions for both Long and Short signals — ideal for automation or notifications. ⚙️ Inputs & Customization Adjustable RSI lengths for both timeframes. Selectable RSI source (Close, HL2, etc.). Configurable stop loss and take profit levels. Customizable leverage and precision for P/L display. Optional wick-based calculation for sensitivity tuning. 💡 How to Use Apply the strategy on your preferred symbol and timeframe. Adjust RSI and risk settings to match your trading style. Optionally enable higher timeframe RSI confirmation. Set alerts for “Long Entry Signal” and “Short Entry Signal.” Backtest and fine-tune before going live. ⚠️ Disclaimer This script is for educational and research purposes only. It is not financial advice. Always backtest thoroughly and manage your risk before using it in live trading.
Pine Script® strategy
by Tg965
Quantura - Trendchange ZonesIntroduction “Quantura – Trendchange Zones” is an advanced technical indicator that identifies and visualizes potential market reversal zones using dynamic RSI-based logic. It highlights areas of overbought and oversold conditions, marking them as visual zones directly on the price chart, and generates corresponding bullish and bearish signals when the RSI exits these extremes. The tool helps traders anticipate possible trend change regions and confirm momentum shifts in a clean, intuitive way. Originality & Value Unlike traditional RSI indicators that only show a static oscillator, this tool transforms RSI behavior into on-chart visual zones that represent structural overbought and oversold phases. It converts RSI threshold breaches into price-based regions (boxes) and marks reversal signals at the moment of momentum change. The indicator’s originality and usefulness come from its: Direct visualization of RSI overbought and oversold areas as dynamic chart zones. Automatic detection of potential reversal regions where momentum exhaustion is likely. Integration of RSI-based signals and visual cues without requiring users to monitor the RSI window. Adjustable sensitivity for RSI length and upper/lower levels. Clear color-coded separation of bullish and bearish phases. Functionality & Core Logic The indicator continuously monitors RSI values relative to the user-defined thresholds. When RSI moves above the upper level, an Overbought Zone is created and extends until RSI falls back below that threshold. When RSI moves below the lower level, an Oversold Zone is generated and extends until RSI returns above that level. When RSI exits one of these zones, a corresponding Trendchange Signal (▲ bullish or ▼ bearish) appears at the transition point. Each zone dynamically adjusts its high and low levels during formation, representing the complete range of the exhaustion phase. Parameters & Customization RSI Length: Defines the sensitivity of RSI calculation. Shorter lengths make signals more responsive; longer lengths filter noise. Upper Level / Lower Level: Set thresholds for overbought and oversold conditions (default 70 / 30). Signals: Toggle on/off for displaying bullish (▲) and bearish (▼) reversal signals. Zones: Toggle the visualization of shaded RSI-based zones. Colors: Fully customizable bullish and bearish colors for both signals and zones. Visualization & Display Bullish reversal zones (oversold exits) are shaded using the chosen bullish color (default: blue). Bearish reversal zones (overbought exits) are shaded using the chosen bearish color (default: red). Each completed zone is outlined and filled with transparent shading for better clarity. Reversal arrows (▲ for bullish, ▼ for bearish) are displayed at the bar where RSI exits the extreme level. Clean overlay design ensures compatibility with any chart style or color scheme. Use Cases Identify overbought and oversold periods directly on the price chart without switching to the RSI window. Anticipate potential market reversals or exhaustion points based on RSI momentum shifts. Combine with trend indicators, moving averages, or volume tools for confirmation. Apply across multiple timeframes to align short-term reversal signals with higher timeframe momentum. Use zone width and duration to assess the strength and persistence of overbought/oversold conditions. Limitations & Recommendations The indicator is not a standalone trading system but a visual confirmation tool. False signals may occur in strongly trending markets where RSI remains overextended. Optimal RSI settings may differ between assets (e.g., crypto vs. equities). Combining this indicator with additional trend or structure filters can enhance accuracy. Markets & Timeframes The “Quantura – Trendchange Zones” indicator works across all markets and timeframes, including cryptocurrencies, Forex, stocks, and commodities. It is suitable for both short-term scalping and long-term swing analysis. Author & Access Developed 100% by Quantura. Published as a Open-source script indicator. Access is free. Important This description complies with TradingView’s Script Publishing and House Rules. It provides a clear explanation of the indicator’s originality, logic, and function while avoiding unrealistic performance or predictive claims.
Pine Script® indicator
by Quantura
3
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® strategy
by Quantura
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® indicator
by OutsiderEdge
1
Fat Tony's Composite Momentum + ROC (v0.4)Fat Tony's Composite Momentum + ROC Indicator Overview Fat Tony's Composite Momentum + ROC is a sophisticated momentum oscillator that combines multiple technical indicators into a single, volume-weighted signal. This indicator helps traders identify overbought/oversold conditions and potential reversal points by synthesizing Williams %R, Stochastic, MACD, and Rate of Change (ROC) into one composite reading. Key Features Multi-Indicator Composite: Combines Williams %R, Stochastic %K, MACD Histogram, and ROC for a comprehensive momentum view Volume Weighting: Optional volume-based amplification to filter out low-conviction moves Volume Filter: Requires minimum volume threshold (last 2 bars combined) before triggering signals Adaptive MACD Scaling: Uses tanh normalization to keep MACD contribution proportional regardless of price volatility Clear Visual Signals: Triangle markers appear only when crossing extreme levels with sufficient volume Customizable Thresholds: Adjust overbought/oversold levels, volume sensitivity, and component lengths How It Works The indicator normalizes each component to a ±50 scale, then averages them together. The composite reading oscillates around zero, with positive values indicating bullish momentum and negative values indicating bearish momentum. Signal Generation: 🟢 Rebound Watch (Green Triangle): Fires when the composite crosses UP through the oversold level with adequate volume 🔴 Fade Watch (Red Triangle): Fires when the composite crosses DOWN through the overbought level with adequate volume Customizing Settings After adding to your chart, click the gear icon next to the indicator name to access settings: Length: Base period for Williams %R and Stochastic (default: 14) MACD Fast/Slow/Signal: Standard MACD parameters (default: 12/26/9) Overbought/Oversold Levels: Threshold values for signals (default: ±100) Use Volume Weighting: Toggle volume amplification on/off Volume Sensitivity: Multiplier for volume weighting (default: 1.5) Include ROC: Toggle Rate of Change component on/off ROC Length: Lookback period for ROC calculation (default: 10) Minimum Volume: Required volume (sum of last 2 bars) for signals to trigger (default: 50,000) Usage Tips Works best on liquid instruments with consistent volume Lower timeframes (5m-15m) benefit from higher minimum volume settings Volume weighting helps filter out noise during consolidation periods Watch for signal triangles at key support/resistance levels for highest probability setups The indicator works as a momentum gauge and reversal spotter - not an entry system by itself Alerts The indicator includes built-in alert conditions: Click the "⏰" (alarm clock) icon on your chart Select "Fat Tony's Composite Momentum + ROC" Choose "Rebound Watch" or "Fade Watch" Configure your notification preferences
Pine Script® indicator
by robbooker
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® strategy
by Quantura
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.
Pine Script® indicator
by krish16887
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® indicator
by DskyzInvestments
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.
Pine Script® indicator
by PipGuard