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Statistics

KNN Machine Learning Momentum IndicatorKNN Machine Learning Momentum Indicator 🌌 Overview This script implements a K-Nearest Neighbors (KNN) machine learning algorithm combined with Dimensionality Reduction to estimate short-term price momentum. 💬 Feedback & Suggestions If you have any questions regarding the logic, or suggestions for new features, please feel free to leave a comment below! Your feedback helps improve the algorithm for everyone. 🧠 Core Methodology The indicator follows a KNN machine learning pipeline: Feature Engineering: It utilizes a multi-faceted feature set including RSI variations, Price-to-MA deviations, and Oscillatory Momentum. Normalization (Z-Score): All features are standardized into Z-scores, ensuring the KNN distance calculation is not biased by different scales of data. Dimensionality Reduction: To reduce noise and the "curse of dimensionality," the script compresses features into three orthogonal Principal Components (Momentum, Mean Reversion, and Dynamics). KNN Engine: The algorithm searches the historical lookback window for the 'K' most similar patterns using the Minkowski Distance metric and applies a Gaussian Kernel to weight the closest neighbors more heavily. 🚀 Strategic Target: Momentum vs. Absolute Price A key distinction of this algorithm is its target objective. Rather than attempting to predict the exact future price (which is often prone to extreme noise), this model focuses on estimating latent market momentum.By analyzing how current feature sets relate to historical momentum shifts, the KNN engine identifies the underlying "energy" of the market. This approach allows traders to capture the probable direction and strength of the next move, providing a more robust edge in dynamic market regimes than unstable price forecasting. 🛡️ Understanding the "Curse of Dimensionality" A common pitfall in KNN-based trading strategies is the Curse of Dimensionality. This Script addresses this by implementing a Dimensionality Reduction layer. By condensing 9 raw technical features into 3 highly descriptive "Principal Components," we maintain a dense feature space. This ensures that the "nearest neighbors" found by the algorithm are truly statistically significant patterns rather than random noise. 🛠️ Key Features Dynamic Probability Engine: Visualizes the confidence of the model through gradient bar coloring. Trend Filter (EMA): Integrated EMA filter to distinguish between "Trend" signals (stronger) and "Counter-Trend" signals (lighter). Minkowski Distance Tuning: Adjust the p parameter to switch between Manhattan (p=1), Euclidean (p=2), or higher-order distance metrics. Visual Analytics: Clean, institutional-grade UI with clear signal shapes and background highlighting. 📈 How to Trade Bull/Bear Signals: Large shapes with labels indicate signals that align with the major EMA trend (High Conviction).Small Shapes: Indicate potential signals that are counter to the major trend (Use with caution/mean reversion). Bar Colors:Bright Cyan/Red: High confidence prediction. Slate Gray: Low confidence / Neutral market regime. ⚠️ Disclaimer Machine learning models are subject to overfitting and market regime shifts. This indicator is intended to be used as a decision-support tool and should be combined with proper risk management and additional technical analysis.Algorithm: K-Nearest Neighbors (KNN)Distance Metric: Minkowski DistancePreprocessing: Z-Score Normalization + Dimensionality Reduction
Pine Script® インジケーター
SatohKの投稿
6
Footprint Delta Divergence# Footprint Delta Divergence ## Overview This indicator automatically detects **delta divergences** on your chart — a powerful signal derived from order flow analysis. When price makes a new extreme but the underlying buying/selling pressure (delta) fails to confirm, it often signals an impending reversal. This is the core concept behind footprint chart divergence trading, now fully automated. ## What Is Delta Divergence? In footprint analysis, **delta** represents the net difference between aggressive buyers (market buy orders lifting the ask) and aggressive sellers (market sell orders hitting the bid). Delta divergence occurs when: - **Bullish Divergence**: Price prints a *lower low*, but delta prints a *higher low* — selling pressure is drying up despite the new price low. Smart money may be absorbing supply. - **Bearish Divergence**: Price prints a *higher high*, but delta prints a *lower high* — buying pressure is fading despite the new price high. Distribution may be underway. - **Hidden Bullish Divergence** *(optional)*: Price makes a higher low while delta makes a lower low — a trend continuation signal suggesting the uptrend is intact. - **Hidden Bearish Divergence** *(optional)*: Price makes a lower high while delta makes a higher high — suggesting the downtrend will continue. ## How It Works The indicator uses a **pivot-based detection engine** to identify swing highs and lows on both price and delta, then compares successive pivots to flag divergences in real time. **Delta Calculation** — Three methods available: - **Volume Delta (Tick)**: Splits each bar's volume into buy/sell components using intra-bar price position. Best accuracy with CME tick data. - **Volume Delta (Estimated)**: Williams-style weighted approximation — `delta = volume × (2 × close_position - 1)`. Solid fallback for instruments without tick-level data. - **OBV**: Classic On-Balance Volume approach. Simplest method, assigns full bar volume as positive or negative. **Pivot Detection**: Configurable lookback period scans for local highs and lows on both price and delta series simultaneously. **Divergence Matching**: When a new pivot forms, the indicator compares it against the previous pivot of the same type. If price and delta move in opposite directions beyond the minimum threshold, a divergence is flagged. ## Signal Filtering Raw divergence detection produces noise. This indicator includes multiple filters to improve signal quality: - **Minimum Delta Change %**: Requires a meaningful percentage difference between the two pivot delta values. Eliminates marginal, low-conviction signals. - **Volume Filter**: Optionally requires the bar's volume to exceed a multiple of the volume moving average. Ensures divergences occur on bars with meaningful participation. - **Maximum Bar Spacing**: Limits the distance between two pivots. Divergences spanning too many bars lose their predictive edge. ## Visual Output - **Labels**: Clear `🟢 Bull Δ Div` and `🔴 Bear Δ Div` markers at the divergence point. Hidden divergences shown with smaller, semi-transparent labels. - **Trend Lines**: Solid lines connecting the two pivot points on price for regular divergences; dashed lines for hidden divergences. - **Bar Coloring**: Divergence bars are highlighted in green (bullish) or red (bearish). - **Background Highlighting**: Subtle background shading on divergence bars for quick scanning. - **Info Panel**: Real-time table showing current delta, cumulative delta, volume ratio, and configuration. ## Recommended Settings | Timeframe | Pivot Lookback | Use Case | |-----------|---------------|----------| | 1-5 min | 3-4 | Scalping, intraday reversals | | 5-15 min | 5 (default) | Day trading | | 30-60 min | 6-8 | Swing entries | | Daily | 8-12 | Position trading | **Best pairs**: CME futures (ES, NQ, CL, GC, 6E) where tick-level volume data is available. The indicator works on any instrument, but delta accuracy improves significantly with real order flow data. ## Tips for Best Results 1. **Combine with key levels** — Delta divergences near visible support/resistance, POC (Point of Control), or VWAP carry significantly more weight. 2. **Watch cumulative delta context** — A bullish divergence forming while cumulative delta is trending up (buyers in control on higher timeframe) is a higher-probability setup. 3. **Volume matters** — Divergences on above-average volume bars represent genuine shifts in order flow, not just low-liquidity noise. 4. **Multi-timeframe confirmation** — A divergence on 5-min confirmed by a divergence or delta shift on 15-min is a strong signal. ## Alerts Built-in alert conditions for all four divergence types: - Bullish Delta Divergence - Bearish Delta Divergence - Hidden Bullish Divergence - Hidden Bearish Divergence Set alerts via TradingView's alert dialog to get notified in real time without watching the chart. ## Disclaimer This indicator is a tool for analysis, not a standalone trading system. Always use proper risk management and combine signals with your broader market analysis. Past divergence patterns do not guarantee future results.
Pine Script® インジケーター
Bying369の投稿
MikeNQ - KeyLevels and StatisticsThis script is an all-in-one indicator designed for precision day traders, ICT, and SMC practitioners. Instead of cluttering your chart with 5 different indicators, this script combines essential institutional reference points, liquidity levels, opening gaps, and real-time market data into one highly customizable, clean interface. Built with a strict focus on chart aesthetics, every single element can be toggled, styled, and repositioned to fit your exact trading plan. 🔥 CORE FEATURES: 1. Institutional Key Levels (Liquidity & Equilibrium) Automatically plots Previous Daily High/Low (PDH/PDL) and Previous Weekly High/Low (PWH/PWL). Includes the 50% Equilibrium (PDEq / PWEq) levels for both Daily and Weekly ranges to identify premium/discount zones. 2. Opening Gaps (NDOG & NWOG) Highlights the New Day Opening Gap (NDOG) and New Week Opening Gap (NWOG). Optionally displays the internal quartile levels (25%, 50% CE, 75%) to pinpoint highly sensitive gap-fill reactions. Auto-cleans older gaps based on user input to prevent chart clutter. 3. Precision Opening Lines Tracks the True Daily Open (18:00 NY Time) and Weekly Open (Sunday 18:00 NY Time) automatically. Includes 3 fully customizable Custom Open Lines (e.g., 09:30 NY AM, 03:00 London Open, midnight open). Built-in Timezone selector ensures your lines are accurate regardless of your local PC time. 4. Advanced Data Tables (Non-Intrusive) Volatility Tracker (ADR/CDR): Compares the Current Daily Range (CDR) against the Average Daily Range (ADR) calculated over X days. Displays exactly what percentage of the average range has been exhausted today. Correlated Sweeps Tracker: Input up to 3 correlated assets (e.g., ES, NQ, YM or CL, RB, HO). The table instantly updates in real-time, displaying a "✓" if any of the assets have swept their PDH or PDL. Perfect for spotting daily SMT divergences without constantly switching charts. ⚙️ QUALITY OF LIFE & CUSTOMIZATION: Project lines into the future by 'X' amount of bars. Fully adjustable text sizes, line styles, and line thickness. Align text labels to the Left, Right, Top, Bottom, or Middle of the lines. Toggle tables to any corner of your screen. If you trade institutional order flow, liquidity runs, or time-based setups, this module provides the exact daily roadmap you need.
Pine Script® インジケーター
MXVNQの投稿
Global Debt-to-GDP DashboardI've created this macro indicator to monitor world debt. The Global Debt-to-GDP Dashboard helps you to track, compare, and analyze sovereign and private debt levels across 20 major economies. It provides institutional-grade debt analysis, allowing traders, long term investors and macro investors to identify systemic risks, divergences from global norms, and accelerating debt trends that could signal future economic instability or opportunities. What It Does This indicator transforms complex macroeconomic data into actionable insights to understand country leverage by: Tracking Dual Debt Metrics: Monitors both government debt-to-GDP and private debt-to-GDP ratios for 20 countries. This provides a complete picture of total leverage in each economy. Divergence Analysis: Compares each country's debt levels against the world average (calculated from selected countries), instantly highlighting which economies are over-leveraged or under-leveraged relative to global norms. Velocity Tracking: Calculates the rate of change in debt divergence, identifying which countries are rapidly increasing or decreasing their debt burden. Risk Assessment: Automatically categorizes countries by risk level using color-coded visual indicators Key Features 20 Major Economies: USA, China, Japan, Germany, UK, France, Italy, Canada, Spain, Australia, South Korea, Brazil, India, Mexico, Switzerland, Singapore, Norway, Saudi Arabia, Russia, and Turkey Simultaneous Visualization: Plot all selected countries on a single chart with unique color coding for easy identification Dynamic Country Selection: Enable/disable countries to focus on specific regions or economic blocs Three Divergence Analysis Modes Government Only: Analyze sovereign debt divergence from government debt average Private Only: Focus exclusively on private sector leverage (excludes countries without private debt data) Total (Gov + Private): Comprehensive view of total economy-wide debt burden Use Cases For Macro Traders Identify Sovereign Risk: Spot countries with unsustainable debt trajectories before credit events Currency Pairs: Correlate debt divergence with currency strength/weakness Bond Markets: Anticipate yield spread movements based on relative debt positions Risk-On/Risk-Off: Use global debt velocity as a systemic risk indicator For Long-Term Investors Country Allocation: Make informed decisions about geographic exposure Risk Management: Avoid over-exposure to high-debt economies Opportunity Identification: Find under-leveraged economies with growth potential Portfolio Rebalancing: Use debt trends as signals for portfolio adjustments How to Use Initial Setup: Select the countries you want to monitor from the Settings panel Choose Divergence Type: Select Government Only, Private Only, or Total debt analysis Configure Display: Adjust table position, text size, and sorting preferences Set Alerts (Optional): Define your alert thresholds and enable notifications Table Risk Scores: 🔴🔴🔴 Extreme Risk: Divergence > +100pp above average 🔴🔴 High Risk: Divergence > +50pp above average 🟠 Moderate Risk: Divergence > 0pp above average 🟢 Low Risk: Divergence > -50pp below average 🟢🟢 Very Low Risk: Divergence < -50pp below average NOTE: "Low Risk" and low-debt might also mean that a country is unable to finance through the issuance of government debt. This is not necessarily a good thing and might not correspond to low risk. Velocity Indicators: ⬆️⬆️⬆️ Rapid Acceleration: +5pp or more per period ⬆️⬆️ Strong Acceleration: +2 to +5pp per period ⬆️ Moderate Increase: +0.5 to +2pp per period ➡️ Stable: -0.5 to +0.5pp per period ⬇️ Moderate Decrease: -2 to -0.5pp per period ⬇️⬇️ Strong Deceleration: -5 to -2pp per period ⬇️⬇️⬇️ Rapid Deceleration: -5pp or less per period Important Notes Data Availability: Some countries lack private debt data (e.g., China, India, Brazil). World Average Calculation: The world average is dynamically calculated based on your selected countries, not a fixed global figure. This allows for custom peer group comparisons. Percentage Points vs Percentages: All divergence values are in percentage points (pp), representing the absolute difference from the average, not a relative percentage change. Let me know if you have comments or suggestions. Truly yours, Henrique Centieiro
Pine Script® インジケーター
HenriqueCentieiroの投稿
Ornstein-Uhlenbeck Mean Reversion Probability Bands [UAlgo]Ornstein-Uhlenbeck Mean Reversion Probability Bands is a statistical mean reversion indicator that models price as a mean reverting process and projects dynamic probability style zones around an estimated equilibrium mean. The script uses a rolling lookback of closing prices, fits an Ornstein-Uhlenbeck inspired parameter set from recent behavior, and then converts that estimate into inner and outer deviation bands around the current mean. The indicator runs directly on price ( overlay=true ) and is built to help traders identify when price is stretched away from its estimated equilibrium. Instead of using a fixed moving average and static standard deviation, the script attempts to infer a mean reverting structure from the data itself. It estimates the long term mean, the speed of reversion, and an equilibrium style dispersion measure, then plots two upside and two downside mean reversion zones. When price pushes into the upper or lower band regions, the script calculates a standardized distance from the estimated mean and displays a probability style label with both the percentage score and the current z score. This gives the user a quick visual read of how statistically extended price is relative to the model. A key strength of this script is that it combines: A rolling Ornstein-Uhlenbeck style parameter estimation Adaptive mean reversion zones Probability style stretch labels at band events A clean overlay presentation with visible upper and lower probability regions Important note: The percentage label in this script is a normal distribution coverage style score derived from the current z score. It is best understood as a probabilistic stretch measure, not a literal exact OU first passage probability. 🔹 Features 🔸 1) Ornstein-Uhlenbeck Inspired Mean Reversion Model The script estimates a mean reverting process from recent closing prices instead of relying only on a moving average. It uses a rolling regression style approach on consecutive price observations, then converts those estimates into Ornstein-Uhlenbeck style parameters. This makes the indicator more model driven than a standard band tool. 🔸 2) Rolling Adaptive Mean Line The central mean line is not a fixed average only. It is the estimated equilibrium level ( mu ) of the fitted process. As the rolling price sample changes, the model updates and the mean shifts with changing market structure. The mean line also changes color depending on whether current price is above or below that estimated equilibrium. 🔸 3) Dual Mean Reversion Zones (Inner and Outer) The script builds two sets of reversion bands around the mean: Inner bands using the inner multiplier Outer bands using the outer multiplier This creates a layered framework where the inner zone marks an early stretch area and the outer zone marks a more extreme statistical extension. 🔸 4) Probability Style Stretch Labels When price crosses into the upper or lower band regions, the script calculates a z score based on current distance from the estimated mean and converts it into a percentage style probability score. The label shows: A directional marker The probability style percentage The current z score This gives the user both a visual event trigger and a numeric measure of extension. 🔸 5) Visual Zone Based Design The indicator uses filled upper and lower zones rather than emphasizing the band lines themselves. This creates a cleaner chart display where the mean line stays visible and the stretch regions are highlighted as colored areas above and below it. This makes the indicator easy to read during fast chart scanning. 🔸 6) Configurable Lookback, Time Step, and Band Width Users can customize: The rolling lookback period used for model estimation The time step parameter ( dt ) used in OU conversion The inner band multiplier The outer band multiplier This makes the script adaptable to different timeframes, instruments, and preferred sensitivity levels. 🔸 7) Built In Estimation Safeguards The parameter estimation logic includes fallback protections. If the inferred model parameters are unstable or unrealistic, the script falls back to simpler sample statistics. This helps prevent unusable outputs during difficult market regimes or low quality fits. 🔸 8) Directional Touch Event Logic The script tracks both upper side and lower side band interaction: Upper side events can signal statistically stretched bullish price movement Lower side events can signal statistically stretched bearish price movement Labels are only created on crossing events, which helps reduce repeated prints while price remains outside the band. 🔹 Calculations 1) Rolling Price Queue Management The script stores recent closing prices in an array with a fixed maximum length: price_array.update_queue(close, length_input) The queue update method behaves differently depending on bar state: On a new bar, it pushes the latest value On an updating live bar, it overwrites the last stored value This keeps the rolling sample aligned with the current chart state without duplicating the active bar. 2) Fallback Mean and Dispersion Estimates Before attempting the OU style fit, the script calculates simple fallback values: float fallback_mu = src_array.avg() float fallback_sigma = src_array.stdev() These act as safety defaults if the regression based OU estimate is not reliable. Important note: In this script, fallback_sigma is a simple sample standard deviation of price levels, not return volatility. 3) AR(1) Style Regression on Consecutive Prices The model estimation is built from consecutive price pairs: x = price y = price The script computes: Mean of x Mean of y Covariance between x and y Variance of x Then it estimates: float b = sum_cov / sum_var_x This creates an AR(1) style coefficient that is later translated into OU style parameters. 4) Conversion from AR(1) Form to OU Style Parameters If the estimated b is within a valid range: if b > 0.05 and b < 0.95 the script computes: float a = mean_y - b * mean_x float mu_exact = a / (1.0 - b) float theta_exact = -math.log(b) / dt Interpretation: mu_exact is the estimated long run mean. theta_exact is the implied mean reversion speed. The conversion assumes the AR(1) relation is a discrete time representation of a mean reverting process. 5) Residual Variance and Equilibrium Dispersion The script next measures residual error from the AR(1) fit: float err = y_i - (a + b * x_i) float var_err = sum_err_sq / (n - 1) Then it converts that residual variance into an equilibrium variance estimate: float var_eq = var_err / (1.0 - b * b) Finally: float calc_sigma = math.sqrt(var_eq) Important implementation note: The variable named sigma in this script is used as an equilibrium style standard deviation around the mean, not as the continuous time OU diffusion coefficient from the SDE form. 6) Stability Filter for the Estimated Sigma Even if the AR(1) fit is mathematically valid, the script only accepts the calculated sigma when it is reasonably close to the fallback sample standard deviation: if calc_sigma < fallback_sigma * 1.5 and calc_sigma > fallback_sigma * 0.5 If this test fails, the script keeps the fallback values instead. This helps avoid unstable band widths caused by bad short term fits. 7) Final Parameter Output The estimation method returns: OU_Params.new(theta, mu, sigma_eq) Where: theta is the estimated reversion speed mu is the estimated equilibrium mean sigma_eq is the accepted equilibrium dispersion measure These parameters are then used to build the bands. 8) Band Construction The script computes four band levels around the estimated mean: float up_out = mean_val + (dev_val * mult_outer) float up_in = mean_val + (dev_val * mult_inner) float dn_in = mean_val - (dev_val * mult_inner) float dn_out = mean_val - (dev_val * mult_outer) Interpretation: Inner bands represent a milder deviation from the mean. Outer bands represent a more extreme deviation from the mean. 9) Mean and Zone Visualization The mean line is explicitly plotted: p_mean = plot(ou_bands.mean, color=color_mean, linewidth=2, title="Mean") The inner and outer band plots are also created, but their colors are fully transparent: color color_inner_up = color.new(#ffb74d, 100) color color_outer_up = color.new(#ef5350, 100) ... This means the visible structure mainly comes from the zone fills: fill(p_ui, p_uo, ...) fill(p_li, p_lo, ...) So the user sees clean upper and lower probability zones rather than several bright boundary lines. 10) Touch and Crossing Logic The script first checks whether price is currently inside a stretch area: bool touch_upper = close >= ou_bands.upper_inner bool touch_lower = close <= ou_bands.lower_inner Then it checks for fresh crossings: bool cross_up_in = ta.crossover(close, ou_bands.upper_inner) bool cross_up_out = ta.crossover(close, ou_bands.upper_outer) bool cross_dn_in = ta.crossunder(close, ou_bands.lower_inner) bool cross_dn_out = ta.crossunder(close, ou_bands.lower_outer) Labels are only created when price is touching the region and a fresh crossing occurs. This avoids creating labels on every bar that remains outside the band. 11) Z Score Calculation When an event occurs, the script calculates the standardized distance from the mean: float current_z_score = dev_val != 0 ? math.abs(close - mean_val) / dev_val : 0.0 Interpretation: A z score of 1 means price is one equilibrium standard deviation away from the estimated mean. Higher values indicate a more statistically stretched condition. 12) Probability Style Score Calculation The script converts the z score into a percentage style score using an approximation of the error function: float x = math.abs(z_score) / math.sqrt(2.0) ... float prob = erf_approx * 100.0 Because erf(|z| / sqrt(2)) corresponds to the probability mass within plus or minus that z distance under a normal distribution, the output behaves like a confidence or coverage score. Important note: This is not a direct OU mean reversion probability in the strict stochastic process sense. It is a normal distribution style stretch score based on the current z distance. 13) Upper Event Label Logic When price crosses into the upper band region: if (touch_upper and cross_up_in) or (touch_upper and cross_up_out) the script prints a bearish styled label above the bar: "▼ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended above the mean and may be vulnerable to reversion. 14) Lower Event Label Logic When price crosses into the lower band region: if (touch_lower and cross_dn_in) or (touch_lower and cross_dn_out) the script prints a bullish styled label below the bar: "▲ %" + str.tostring(probability, "#.##") + " (Z:" + str.tostring(current_z_score, "#.##") + ")" This reflects the idea that price is statistically extended below the mean and may be vulnerable to reversion. 15) Role of the Time Step Input The dt_input parameter affects the conversion from the AR(1) coefficient into the OU reversion speed: float theta_exact = -math.log(b) / dt A larger dt lowers the inferred theta for the same b . A smaller dt raises the inferred theta for the same b .
Pine Script® インジケーター
UAlgoの投稿
HB - Rotational Stretch Engine (STRATEGY)NFA / DYOR HB - Rotational Stretch Engine Professional Strategy Documentation & Execution Manual 1. Strategy Overview • Mean-reversion rotational strategy designed for intraday index futures. • Captures price reversals at structural premium and discount extremes. • Uses RSI stretch and swing confirmation for precise timing. • Fully systematic with defined session, risk, and execution logic. • Optimized for MNQ / NQ micro futures environments. 2. Premium / Discount Range Framework • Calculates rolling high and low over configurable lookback period. • Defines Premium Zone near range highs. • Defines Discount Zone near range lows. • Zone width controlled by percentage input. • Ensures entries occur only at structural extremes. 3. RSI Stretch & Momentum Engine • Configurable RSI length (default 14). • Short Stretch level defines overextended upside momentum. • Long Stretch level defines overextended downside momentum. • Requires RSI swing high confirmation for shorts. • Requires RSI swing low confirmation for longs. • Momentum turn required before order execution. 4. Session Filter • Trades only within defined session hours. • Default: 02:00 – 15:59 (extended U.S. session). • Avoids overnight illiquid conditions. • Ensures participation during institutional volume cycles. 5. Entry Conditions • SHORT Entry: • • Price inside Premium Zone. • • RSI above Short Stretch threshold. • • RSI swing high detected. • • RSI momentum turning downward. • • No active short position. • LONG Entry: • • Price inside Discount Zone. • • RSI below Long Stretch threshold. • • RSI swing low detected. • • RSI momentum turning upward. • • No active long position. 6. Risk Management Model • Fixed tick-based profit target. • Fixed tick-based stop-loss. • Target and stop independently configurable. • Uses average entry price for bracket precision. • Commission and slippage modeled in strategy parameters. 7. Strategic Deployment Guidelines • Best suited for range-bound or rotational environments. • Avoid strong directional breakout expansions. • Effective during volatility cycling conditions. • Position sizing should align with account risk model. • Suitable for automation or disciplined discretionary execution.
Pine Script® ストラテジー
HillBillyKryptoの投稿
VWAP First Return Stats TableFirst VWAP Return Half-Hour Table (9:30–4:00 EST) This clean, real-time statistics table shows exactly which 30-minute window has historically been the most common for the first return to daily VWAP during regular trading hours (9:30 AM – 4:00 PM EST). For each of the 5 major instruments (ES1!, CL1!, GC1!, 6E1!, BTCUSD), the table displays the percentage of trading days where the very first touch of the daily volume-weighted average price occurred in each half-hour bucket. Perfect for: VWAP traders & mean-reversion strategies Intraday scalpers looking for high-probability reversion windows Futures & crypto day traders who want data-driven timing edges Key Features 13 precise half-hour buckets from 9:30 all the way to 15:30 (covers the 16:00 close bar) Percentages always sum to 100% for days that touched VWAP at least once by 4:00 PM EST Accurate daily VWAP anchored to EST midnight (same as your main VWAP Deviation Table) Full EST timezone handling — works regardless of your chart timezone Clean black table with customizable text size (tiny → large) Updates live as new days complete Works on any timeframe (1-min to 15-min recommended for best accuracy) Symbols included: ES1! CL1! GC1! 6E1! BTCUSD How to use: Simply add the indicator to any chart. The table appears in the top-right corner and shows historical probabilities instantly. Use it to quickly spot which time window has the highest chance of the first VWAP touch for your favorite symbol — extremely useful for planning entries, exits, or alerts. Combine this with the original “VWAP Deviation Table” for a complete intraday VWAP dashboard. Note: Percentages are calculated from all available historical data. The more days loaded, the more stable the stats become.
Pine Script® インジケーター
Resonant_Traderの投稿
PSL-BDI Spread-Based Z-Score BandsPSL-BDI Spread-Based Z-Score Bands ════════════════════════════════════════ 📌 ภาพรวม ───────────────────────────────────────── Indicator นี้ใช้หลักการ Statistical Arbitrage (Stat-Arb) วัดความสัมพันธ์ ระหว่างราคาหุ้น PSL กับ Baltic Dry Index (BDI) ผ่านการคำนวณ Spread แบบ Dynamic เพื่อหาจุด Overvalued / Undervalued เทียบกับ BDI ในเชิงสถิติ รองรับ 2 กลยุทธ์ตามสภาวะ Correlation: • Stat-Arb → Trade Spread เมื่อ PSL-BDI Correlated กันสูง • Lead-Lag → Accumulate เมื่อ BDI นำ PSL ในช่วง Discorrelation 📐 วิธีคำนวณ ───────────────────────────────────────── ① Dynamic Hedge Ratio (Rolling OLS Regression) ระบบคำนวณความสัมพันธ์แบบ Real-time ด้วยสมการ: PSL = alpha + beta × BDI + ε • beta (Hedge Ratio) = Corr(PSL,BDI) × Std(PSL) / Std(BDI) • alpha (Intercept) = Mean(PSL) − beta × Mean(BDI) ต่างจาก Fixed Hedge Ratio ตรงที่ค่าจะปรับตามสภาวะตลาดจริงทุก Bar ② Spread (OLS Residuals) Spread = PSL − (beta × BDI) − alpha → ส่วนเกินของราคา PSL ที่ BDI อธิบายไม่ได้ ③ Z-Score Z = (Spread − Mean(Spread)) / StdDev(Spread) → วัดว่า Spread ห่างจากค่าเฉลี่ยกี่ Standard Deviation 📊 การอ่าน Bands บนกราฟ ───────────────────────────────────────── Bands ทั้งหมดแสดง "ระดับราคา PSL" ที่ตำแหน่ง Z-Score นั้นๆ โดยคำนวณจาก Spread ระหว่าง PSL และ BDI และเคลื่อนที่ตาม BDI ทุก Bar 🔴 +2sd → Z = +2.0 (PSL แพงเกินกว่า BDI จะอธิบายได้มาก) 🟠 +1sd → Z = +1.0 ⬜ Mean → Z = 0.0 (Fair Value ตาม BDI ณ ขณะนั้น) 🟢 -1sd → Z = -1.0 💚 -2sd → Z = -2.0 (PSL ถูกเกินกว่า BDI จะอธิบายได้มาก) Z-Score และค่า Hedge Ratio ปัจจุบันแสดงใน Label มุมขวาของกราฟ 🎨 สีพื้นหลัง (Correlation Regime) ───────────────────────────────────────── ไม่มีสี Corr > 0.6 → Correlated — ใช้กลยุทธ์ Stat-Arb 🟡 เหลือง Corr 0–0.6 → Weak — ใช้กลยุทธ์ Lead-Lag ด้วยความระมัดระวัง 🟠 ส้ม Corr -0.4–0 → Discorrelated — ใช้กลยุทธ์ Lead-Lag เท่านั้น 🔴 แดง Corr ≤ -0.4 → Deep Dislocation — งดเทรด 📈 กลยุทธ์การใช้งาน ───────────────────────────────────────── ① Stat-Arb / Mean Reversion (พื้นหลังไม่มีสี) เงื่อนไขเข้า Buy : Z-Score ≤ -2sd + Corr > 0.6 เงื่อนไขเข้า Sell : Z-Score ≥ +2sd + Corr > 0.6 Target : ราคากลับเข้า Mean Band เหมาะกับ : Short-term, High Conviction ② Lead-Lag / Correlation Restoration (พื้นหลังเหลือง-ส้ม) สัญญาณ : BDI Trend ชัดเจนแต่ PSL ยังไม่ตาม (Z-Score ต่ำ) จังหวะเข้า : เริ่ม Accumulate เมื่อ Corr เริ่มกลับขึ้น Target : PSL ตามทัน BDI เมื่อ Correlation Restore เหมาะกับ : Swing Trade, Position Size เล็กกว่าปกติ ความเสี่ยง : ถ้าเป็น Structural Break จะรอเปล่า ⚙️ พารามิเตอร์ ───────────────────────────────────────── BDI Symbol : Symbol ของ BDI (Default: INDEX:BDI) Correlation Window : จำนวน Bar สำหรับคำนวณสีพื้นหลัง ไม่กระทบ Signal — ใช้ดู Regime เท่านั้น OLS / Z-Score Window : จำนวน Bar สำหรับคำนวณ Hedge Ratio, Spread และ Bands • เพิ่มค่า → Signal ช้าลง เหมาะ Swing Trade • ลดค่า → Signal เร็วขึ้น Bands แคบลง แนะนำ: 30–45 (Short), 45–60 (Swing), 60–90 (Position) Use Fixed HR & Intercept : เปิดเพื่อใช้ค่า Hedge Ratio และ Intercept แบบ Manual 📅 Timeframe ที่แนะนำ ───────────────────────────────────────── ✅ Daily เท่านั้น BDI เป็น Daily Index ที่เผยแพร่วันละครั้ง การใช้ใน TF ต่ำกว่า Daily จะทำให้ค่า BDI ซ้ำทุก Bar และ Correlation ไม่มีความหมายทางสถิติ ⚠️ ข้อควรระวัง ───────────────────────────────────────── • Indicator นี้ไม่ใช่ Buy/Sell Signal โดยตรง ใช้ประกอบการวิเคราะห์ • ประสิทธิภาพขึ้นอยู่กับความ Cointegrated จริงของ PSL และ BDI • ช่วง Deep Dislocation (แดง) อาจเกิดจาก Fundamental Shift ของอุตสาหกรรม Shipping ให้ตรวจสอบก่อนเสมอ • Spread อาจ Drift ได้นานกว่าที่คาด — ใช้ร่วมกับ Risk Management เสมอ
Pine Script® インジケーター
nutptの投稿
Sara Strat Snipers 50 Percent StatusSSS50 Status — Candle-State Dashboard + Key Levels SSS50 Status is a chart overlay tool that evaluates the current candle structure (Strat-style logic) on a selectable timeframe and instantly shows the setup state as INVALID, STANDBY, ACTIVE, or COMPLETE. It also projects the previous candle High / Low / 50% midpoint as clean reference levels to help you react faster and stay consistent. What it does Reads OHLC from your chosen timeframe Works on Chart timeframe (auto) or a fixed timeframe (example: Weekly). Classifies the current TF candle vs the previous TF candle Detects 2Up, 2Down, Inside Bar, Outside Bar Applies candle color (bull/bear) to spot “failed” moves. Shows a live status box A compact or normal dashboard appears in the top-right with: Current status Extra context text (ex: failed 2U / failed 2D / outside bar) Active timeframe Status logic overview COMPLETE Triggered on an Outside Bar (range breaks both sides). ACTIVE A “failed 2” candle that also closes beyond the previous candle’s 50% level (midpoint break = momentum confirmation). STANDBY A “failed 2” candle appears, but midpoint confirmation has not happened yet. INVALID Used when conditions are not trade-usable (example: Inside Bar, or “clean” 2Up/2Down that doesn’t qualify per rules). Auto levels & visual aids When enabled, the indicator draws: Prev High (dashed) Prev Low (dashed) Prev 50% midpoint (dotted) And optional labels for High/Low/50% are printed to the right for quick reading. Customization Choose timeframe mode (Chart vs Single TF) Toggle the status table, and switch between Normal / Compact Enable/disable auto levels and labels Set custom colors for each status state (Invalid / Standby / Active / Complete) Use-case: perfect for traders who want a simple “what state are we in?” answer, plus clean levels that stay consistent across timeframes.
Pine Script® インジケーター
hary349veo3の投稿
Option Moneyness Heatmap AutoOption Moneyness Background Auto is designed to make an option chart instantly more readable by coloring the chart background based on the option’s moneyness state relative to the underlying asset price and the option’s strike price . Unlike many existing moneyness-style scripts that are built for the underlying chart (or require manual inputs every time), this script is built to run directly on the option contract chart itself . It automatically parses the option symbol (when available in OPRA-style format) to detect the underlying ticker , whether the contract is a call or put , and the strike price , then applies ITM / ATM / OTM background highlighting in real time. Because it is designed to operate inline on the option chart being traded , it pairs especially well with a second chart showing the underlying asset . This setup gives a clean side-by-side workflow: one chart for the option’s price action and one chart for the underlying’s structure, while this indicator keeps moneyness context visible at a glance. What it does The script highlights the background using a simple visual system: Green = In The Money (ITM) Yellow = At The Money (ATM) Red = Out of The Money (OTM) The logic automatically handles the difference between calls and puts : Calls become more valuable as the underlying price rises relative to strike Puts become more valuable as the underlying price falls relative to strike So the ITM/OTM behavior is correctly inverted depending on contract type. Key features 1) Automatic option symbol parsing (OPRA-style) When the TradingView symbol format supports it, the script automatically detects: Underlying symbol Call vs Put Strike price This reduces setup friction and makes it easier to move between contracts quickly. 2) Manual override mode (fallback for non-standard symbols) If your feed or instrument uses a non-standard symbol format, the script includes manual inputs for: Underlying symbol Call/Put selection Strike price This allows the indicator to remain usable even when auto-parse is not available. 3) Adjustable ATM sensitivity ATM status can be tuned using an adjustable band: Percent mode (relative to underlying price) Fixed dollar mode This lets you define how tight or loose the “ATM” zone should be for your trading style and the instrument you trade. 4) Designed for option-chart workflow This script is not just a generic background highlighter. It is built specifically for option traders viewing the option contract chart itself , where moneyness context is often easy to lose while focusing on premium movement. Suggested use case (recommended layout) A very effective setup is: Chart 1: The option contract (with this indicator applied) Chart 2: The underlying asset (for market structure / levels / trend context) This gives you immediate visibility into both: what the option premium is doing, and where the underlying price sits relative to the strike. Notes Auto-detection depends on the option symbol format provided by your TradingView data feed (best compatibility with OPRA-style symbols). If auto-detection fails, use the built-in manual override inputs. ATM band settings are user-defined by design, since “ATM” tolerance can vary by instrument and trading approach. Screenshots / examples Call contract example (ITM / OTM) Put contract examples (ITM / ATM / OTM)
Pine Script® インジケーター
quickshiftinnの投稿
1
3 Day Change Percentage3-Day % Change (Futures + Indexes) – Global Session Performance Dashboard Instantly see how major assets have performed over the last 3 days at the exact moment each global session opens. This clean, professional overlay indicator tracks **six key instruments**: • 6E1! Euro FX Futures • DXY US Dollar Index • ES1! S&P 500 Futures • CL1! Crude Oil • GC1! Gold • BTCUSD Bitcoin **What the table shows:** - **AO / LO / NYO columns** → 3-day % change calculated precisely at; Asia Open (20:00 NY) London Open (03:00 NY) New York Open (09:30 NY) - **AO Avg / LO Avg / NYO Avg columns** → historical average of absolute 3-day moves (gives you instant context) - Smart background coloring: 🟢 Green = outperforming its own historical average 🔴 Red = significantly underperforming ⚪ Gray = within normal range **Extra visual power:** - On-chart session labels (custom colors) appear exactly when each session opens - The entire chart background automatically tints to match the current session’s performance color for the symbol you’re viewing (stays until the next session starts) **Customization:** - Table position (4 corners) - 5 text sizes (tiny → huge) - Individual colors for Asia, London & NY Open labels Perfect for forex, index, commodity, and crypto traders who want to know at a glance which assets are running hot or cold at the three most important liquidity windows of the day. Built in Pine Script v6 – uses `request.security` for clean multi-symbol data. Works on any chart/timeframe. Add it once and never miss session momentum again.
Pine Script® インジケーター
Resonant_Traderの投稿
Divergent Trader - ATH / 52W High Breakout StrategyStrategy Description This is a long-only breakout strategy designed to capture momentum when price moves into new highs. The system enters long positions when price breaks above either: The All-Time High (ATH), and/or The 52-Week High Both breakout conditions can be independently enabled or disabled. The idea is simple: when price pushes into uncharted territory, it often signals strength and expanding momentum. Rather than predicting reversals, this strategy focuses purely on participation in strength. Exit Logic Two exit methods are available: ATR-Based Stop (Default) A volatility-adjusted stop based on Average True Range (ATR). This allows positions room to move while adapting to changing market conditions. EMA Exit Option Alternatively, trades can be closed when price moves back below a chosen EMA length, providing a trend-based exit. Key Characteristics Fully mechanical rules Long-only (no shorting) Breakout-based entries Volatility-adjusted or trend-based exits Designed for trend continuation environments Concept Major highs represent areas where supply has previously entered the market. When price breaks above these levels, it can indicate strong demand and continuation potential. This strategy aims to systematically capture those expansion phases while managing downside risk through predefined exit rules.
Pine Script® ストラテジー
TheDivergentTraderの投稿
Monthly Returns HeatmapThis heat-map displays the month-by-month percentage return of the selected asset (e.g., BTC) using monthly candles, with green/red cells making it easy to spot periods that have historically been strong or weak. Seasonality matters for Bitcoin because its returns tend to cluster around recurring market behaviours liquidity cycles, risk-on/risk-off regimes, and the post-halving cycle, so certain months often show consistent tendencies across different years. Example use: if the heat-map shows that Q1 has frequently been weak during midterm/bear years, you can use it to plan a simple accumulation approach, buying in equal tranches during historically softer months and reducing risk-taking during months that repeatedly show poor performance.
Pine Script® インジケーター
Giovanni_Ambrosioの投稿
MVRV Z-Score (DEMA Smoothed) | CipherDecodedMVRV Z-Score (DEMA Smoothed) | CipherDecoded Overview The MVRV Z-Score (DEMA Smoothed) is a structural trend-following oscillator derived from Bitcoin’s on-chain capital positioning. Rather than interpreting MVRV purely as a valuation metric, this implementation treats the relationship between market value and realized value as a proxy for capital regime expansion and contraction. By statistically normalizing MVRV and applying Double Exponential Moving Average (DEMA) smoothing, the indicator converts on-chain profitability dynamics into a tradable trend signal. The result is a regime-sensitive momentum framework anchored to underlying cost basis structure. Structural Rationale Market cycles are driven by shifts in aggregate positioning: When market value persistently exceeds realized value, capital is in profit and reflexive expansion tends to dominate. When market value compresses toward or below realized value, distribution and contraction phases emerge. By standardizing MVRV into a rolling Z-score, the indicator measures the velocity and persistence of profitability expansion, not just its magnitude. The subsequent DEMA smoothing filters short-term volatility while preserving structural inflection points, making the signal more suitable for systematic trend models. Inputs BTC Market Capitalization BTC Realized Market Capitalization Daily confirmed data to prevent repainting ​ Z-Score Normalization Rolling lookback mean and standard deviation Converts raw ratio into standardized regime measure DEMA Smoothing Applied to the Z-score output Reduces noise while maintaining responsiveness to regime shifts Trend Threshold User-defined bias level (default: 0.0) Above threshold = expansion regime Below threshold = contraction regime Interpretation This indicator is designed to identify structural trend bias, not overbought/oversold extremes. Sustained positive readings indicate persistent capital expansion. Sustained negative readings indicate structural compression. Threshold crossovers signal potential regime transitions. Slope and persistence are often more informative than absolute level. Design Principles Statistical normalization separates signal from secular growth effects. Smoothing is applied post-normalization to preserve structural information. Inputs are modular, allowing independent control of regime sensitivity and signal responsiveness. Data is requested on confirmed daily closes to ensure signal stability. Strategic Context Unlike traditional price-only oscillators, this framework derives trend information from underlying capital positioning. It therefore reacts to structural shifts in profitability rather than short-term price volatility. This makes it particularly suited for: Medium- to long-horizon trend strategies Macro regime allocation models Risk scaling frameworks Summary The MVRV Z-Score (DEMA Smoothed) reframes on-chain valuation data into a structural trend engine. By combining statistical normalization with adaptive smoothing, it provides a capital-anchored momentum signal designed for regime-based trading and systematic bias control.
Pine Script® インジケーター
CipherDecodedの投稿
ATR Stop Level CheckerDynamic position sizing indicator - calculates difference of ATR of last price. Manually input risk based on your account size = If 100,000 account, risk 0.5% a trade = $500 risk This calculates shares based on ATR and LOD. Changeable settings of 3 ATR % lines If atr = 1 50% = .5 66% = .66 100% = 1 I use this to make sure my stop is never more than 1 ATR, and that my entry isn't extended from the low of day - letting me know my entry is not extended intraday. Jeff Sun uses 60% LOD maximum, this ensures he takes an optimal entry and his risk is not considered extended of the ATR.
Pine Script® インジケーター
JRienの投稿
NBSG_Market DashboardMarket Structure & Relative Strength Dashboard Overview The Market Structure & Relative Strength Dashboard is a comprehensive multi-timeframe analysis tool designed to identify leading sectors and stocks. By comparing a custom list of tickers against a benchmark (e.g., S&P 500), this dashboard ranks assets based on their true outperformance rather than just absolute price action. How It Works The dashboard evaluates assets using two primary metrics: 1. Relative Strength (RS) Scoring The script calculates the performance of each ticker minus the performance of the benchmark across three lookback periods: 1 Month (21 trading days) 3 Months (63 trading days) 6 Months (126 trading days) The table is then automatically sorted by the average score of these three periods, placing the strongest leaders at the top. 2. Trend Structure Analysis Beyond simple performance, the dashboard uses a proprietary trend-tracking logic based on Volume Weighted Moving Averages (VWMA). It classifies each asset into one of five states: BULLISH: Strong trend with momentum and price trading above the structural envelope. BULL MOMO: Momentum is positive (8/13/21 VWMA alignment). NEUTRAL: No clear trend or mean reversion. BEAR MOMO: Momentum is negative. BEARISH: Significant structural breakdown. Features Fully Customizable: Input up to 30 tickers of your choice (Sectors, Crypto, Forex, or Stocks). Benchmark Selection: Compare your list against the SPX, NASDAQ, Bitcoin, or any other index. Dynamic Sorting: The dashboard re-ranks the list in real-time based on relative performance. Visual Clarity: Heatmap-style coloring allows you to spot rotation and momentum shifts at a glance. How To Use Identify Leaders: Look for tickers at the top of the list that are highlighted in "Bullish" or "Bull Momo" states. Spot Divergence: If a ticker has high 6-month RS but low 1-month RS, it may be undergoing a healthy pullback or losing its leadership. Rotation Trading: Use the dashboard to see which sectors are beginning to show green RS values (outperforming the SPX) before the price breakout occurs on the main chart. Technical Settings Benchmark: The symbol used for comparison (Default: CBOE:SPX). Structure Calculation: Based on 8, 13, and 21 VWMAs for momentum, and 34-period High/Low VWMAs for trend support/resistance.
Pine Script® インジケーター
NotABigShortGuyの投稿
MonthlyPerformanceV2This library provides a plug-and-play monthly performance table for strategy scripts. It automatically tracks and displays profit/loss per month and year directly on your chart. ───────────────────────────────────── 🔧 FUNCTION ───────────────────────────────────── trackAndDraw(initialCapital, showInPercentage) Parameters: - initialCapital (float) — The starting capital of your strategy. Tip: use `strategy.initial_capital` for automatic sync. - showInPercentage (bool) — Display mode: `true` → shows monthly result in % (compounding) `false` → shows monthly result in USD (normalized to initial capital) ───────────────────────────────────── 📊 FEATURES ───────────────────────────────────── - Compounding % calculation per month and per year - Dual display mode: percentage or USD equivalent - Color-coded cells (green / red) for quick visual reading - Running month tracker (current open month, lighter color) - Annual total column with compounding yearly return - Auto-limits display to the 19 most recent years to prevent table overflow ───────────────────────────────────── 🚀 HOW TO USE ───────────────────────────────────── add this 2 lines code to your script import edwinardyanto/MonthlyPerformance/1 as mp mp.trackAndDraw(strategy.initial_capital, true) ───────────────────────────────────── 📌 NOTES ───────────────────────────────────── - Only compatible with strategy scripts (requires strategy.equity) - Call trackAndDraw() once, outside any conditional block - Table is displayed at bottom-right of the chart - Older years beyond the 19-year limit are excluded from display but still calculated internally
Pine Script® ライブラリ
edwinardyantoの投稿
NQ Reversal Framework NQ Reversal Framework The NQ Reversal Framework is a technical indicator designed to identify potential intraday reversals on the NASDAQ futures (NQ). It is inspired by the methodology associated with Austin Clark and combines MACD momentum signals with the structural reference of the Midnight Open level. This is a visual framework, not an automated trading system. Core Components 1) MACD-Based Reversal Signals The indicator uses classic MACD cross logic: Buy signal when MACD crosses above the signal line below the zero line Sell signal when MACD crosses below the signal line above the zero line This structure focuses on momentum shifts occurring after an extended move, rather than mid-range noise. 2) Midnight Open Reference Each day at midnight, a horizontal line is drawn at the session open price. This level acts as an intraday reference point: The line extends throughout the current session It resets when a new midnight session begins The Midnight Open provides structural context for price positioning during the trading day. 3) Custom Trading Session Filter Users can define a specific intraday session window (for example 08:00–11:00 in a chosen timezone). The chart background is highlighted during the selected session MACD signals are displayed only within this defined window This helps restrict signal generation to preferred trading hours. 4) Timezone Control A configurable timezone input (default: America/New_York) ensures proper alignment with exchange hours and session logic. What This Indicator Does Highlights structured MACD reversal signals Provides a daily Midnight Open reference Filters signals by user-defined session Improves intraday context visualization What This Indicator Does Not Do It does not place trades It does not manage risk It does not guarantee performance The NQ Reversal Framework is intended as a structured intraday analysis tool for traders seeking to identify momentum shifts around key time-based reference levels.
Pine Script® インジケーター
Konscioの投稿