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Keltner SD SuperTrend | RakoQuantKeltner SD SuperTrend by RakoQuant is a structural trend-following system that replaces ATR volatility with Standard Deviation inside a SuperTrend framework. Instead of using raw range-based expansion, this model measures statistical dispersion around an EMA baseline, producing cleaner volatility envelopes in both compression and expansion phases. The result is a SuperTrend variant that reacts to true deviation structure, not just candle range. RakoQuant Architecture 1. EMA Baseline (Structural Mean) The core baseline is an EMA: * Provides directional bias * Anchors volatility expansion * Serves as slope reference for momentum gating This keeps the model responsive without being overly reactive. 2. Standard Deviation Volatility (σ Engine) Instead of ATR, this system uses: Upper Band = EMA + (Multiplier × StdDev)
Lower Band = EMA − (Multiplier × StdDev) This shifts the logic from range volatility to statistical dispersion. Key effects: * Compression phases tighten sharply * Breakouts emerge from structured contraction * Noise-based volatility spikes are reduced * Trend shifts become more statistically defined 3. SuperTrend Trailing Logic Classic trailing band mechanics are applied: * Bands trail only in trend direction * Once flipped, they do not reset until structurally broken * Regime continuity is maintained This prevents band “repainting” behavior and keeps state transitions clean. 4. Momentum Gate (Structural Confirmation) An optional slope-based confirmation layer is included: Momentum = EMA slope normalized by Standard Deviation This ensures: * Flips require directional bias * Weak breaks in flat conditions are filtered * Volatility expansion aligns with structural movement It adds discipline without over-complicating the model. Signal Model (RakoQuant Regime Logic) The indicator operates using state-based architecture: * Bullish Regime when SuperTrend flips upward * Bearish Regime when SuperTrend flips downward Flip events are: * Deterministic * Backtest-ready * Alert-enabled No repainting. No hidden smoothing. Clean state transitions. Visual System Keltner SD SuperTrend includes modular visual configuration: * Multiple palette options (RakoQuant Neon, Classic, Gold/Indigo, Ocean/Coral, Mono) * Line style control (Line Break default to prevent shelf artifacts) * Dual-layer glow system * Optional fill (to mid or to price) * Optional EMA baseline display * Candle painting toggle * Optional UP/DN markers The default Line Break style avoids the “box shelf” effect common in naive SuperTrend implementations. Practical Use Cases Trend Continuation
Use flips to capture directional expansion from statistical compression. Breakout Detection
Watch for SD tightening before regime transition. Volatility Rotation
Observe how dispersion expands during strong directional phases. System Integration
Pairs cleanly with: * Momentum oscillators * Volume filters * Higher timeframe bias systems Design Philosophy (RakoQuant) This tool reflects the RakoQuant framework: * Statistical dispersion > raw range volatility * Structural regime tracking > visual-only overlays * Deterministic outputs > black-box smoothing * Strategy-ready architecture Everything is manual, open-source, and reproducible. Chart Example
Wskaźnik Pine Script®
od RakoQuant
1
TX Ultra Pulse TWH## Overview TX Ultra Pulse TWH is a normalized momentum oscillator designed to visualize trend strength and identify potential reversal points. Unlike standard oscillators that use fixed ranges (0-100), this script normalizes its output into a standardized histogram (typically fluctuating between -1.5 and +1.5), making it easier to compare volatility across different assets. ## How It Works (The Logic) The indicator allows users to switch between 4 different calculation "Engines". Each engine processes price data differently but outputs a normalized result: 1. Composite Mode (Default & Recommended) This mode creates a "consensus" signal by blending three classic momentum indicators to filter out noise. Logic: It calculates the 14-period RSI, 14-period Stochastic, and 20-period CCI. Normalization: RSI and Stochastic are centered around zero (subtracting 50). CCI is divided by 150 to match the scale. Weighting: The formula uses a weighted average: (RSI + (Stoch * 2) + CCI) / 3. The Stochastic component is given double weight to prioritize reaction to recent price closes. Result: A smoother oscillator that reacts to overbought/oversold conditions with less "whipsaw" than a raw RSI. 2. Deviation Mode Logic: Calculates the percentage distance between the Close price and a Moving Average (default 20 SMA). Scaling: The result is normalized using Standard Deviation (Z-Score concept) to fit the histogram scale. Use Case: Best for spotting mean-reversion opportunities when price extends too far from its baseline. 3. Momentum Mode Logic: Pure Rate-of-Change (ROC). It measures the percentage change between current close and close n periods ago. Use Case: Ideal for identifying pure trend velocity without the smoothing lag of complex averages. 4. RS Index Mode Logic: Comparative Relative Strength. It compares the performance of the current asset against a user-defined benchmark (e.g., SPY, BTC, or IDX:COMPOSITE) over a lookback period. Formula: (Asset % Change - Benchmark % Change). Positive values indicate the asset is outperforming the market. ## Features & Settings Noise Filter: A built-in EMA smoothing layer (default 15) is applied to the final calculation to reduce visual noise. Color Grading: Green: Positive Momentum (Bullish). Red/Orange: Negative Momentum (Bearish). Color Intensity: Brighter colors indicate accelerating momentum, while darker/faded colors indicate deceleration (divergence). Dashboard: Displays the current real-time values, trend direction, and signal status directly on the chart. ## How to Use Trend Confirmation: Use the histogram color to confirm the trend direction. Do not go Long if the histogram is Red. Zero Cross: A crossover above 0 indicates a shift to bullish momentum. A cross below 0 indicates bearish momentum. Divergence: If price makes a Higher High but the Pulse Histogram makes a Lower High, this indicates momentum exhaustion (Bearish Divergence). ## Disclaimer This script is a technical analysis tool intended for educational purposes. It does not guarantee profits. Past performance is not indicative of future results.
Wskaźnik Pine Script®
od Tonzlnxz
LSMA SD | GForgeLSMA SD | GForge LSMA SD is a trend-following oscillator built for swing trading on higher timeframes. It generates rules-based long and exit signals by measuring where price sits within a statistically-defined volatility envelope anchored to a regression-based trend line. Core Calculation The basis line is a Least Squares Moving Average. Unlike a standard moving average which weights past prices, LSMA computes the mathematically optimal straight-line fit across a defined lookback window. This means the basis reflects the actual gradient of a trend — its slope tells you the rate and direction of price movement, not a smoothed echo of where price has been. A short EMA pass is applied to the raw LSMA output as a robustness measure, absorbing single-bar snap artifacts that occur when outlier candles enter or exit the regression window. This is not a smoothing aesthetic — it directly addresses a known fragility in raw LinReg endpoints. The default source is hlc3 — the average of high, low, and close — rather than close alone. This distributes the regression input across the full bar range, reducing sensitivity to end-of-session price mechanics such as stop runs and last-minute order flow that can distort the trend line without reflecting genuine directional movement. A Standard Deviation envelope is then constructed around the LSMA basis at a fixed multiplier. The band width is driven entirely by actual price volatility — it widens during high-volatility periods and tightens during quiet ones. There is no secondary adaptive scaling layer. This is intentional: additional dynamic scaling introduces a second noisy signal on top of the basis movement, which in practice degrades signal quality. The Oscillator The oscillator expresses where price currently sits within the SD bands on a 0–100 scale. A reading of 0 means price is at the lower band. A reading of 100 means price is at the upper band. A reading of 50 means price is sitting directly on the LSMA trend line itself — the neutral zone between the two signal thresholds represents price consolidating around the regression basis. Long signals fire when the oscillator crosses above the long threshold (default 74), meaning price has broken decisively into the upper band zone — a momentum confirmation in the direction of the trend, not a mean-reversion trigger. Exit and short signals fire when the oscillator crosses below the short threshold (default 33). This is a trend-continuation system, not a reversal indicator. Parameters The indicator is intentionally low-parameter. LSMA Length sets the regression window. StdDev Length sets the band width lookback and can differ from the LSMA length. StdDev Multiplier sets the fixed band scale. Endpoint Smoothing controls how aggressively window-edge artifacts are absorbed — setting it to 1 disables it entirely. Fewer parameters means less surface area for curve-fitting to historical data. Default settings are optimised for BTC on the 1D timeframe. Optimize thresholds and lengths for different assets and timeframes before use. Risk Warning This indicator is provided for informational and educational purposes only. Past performance, including any results visible on historical bars, does not guarantee or imply future returns. All trading involves risk. You should not make trading decisions based solely on any single indicator. Always apply independent analysis and appropriate risk management. Developed by GForge
Wskaźnik Pine Script®
od GForge
Ultimate RegimeUltimate Regime | MisinkoMaster Ultimate Regime is an advanced market environment classification tool designed to identify whether an asset is currently operating in a trending or mean-reverting regime. Instead of focusing on entry signals, the indicator concentrates on answering a more fundamental question: what type of market are we trading right now? By continuously evaluating market structure, volatility behavior, and directional persistence, the script provides a unified regime view that helps traders adapt strategy selection, risk management, and trade expectations to current conditions. This makes Ultimate Regime particularly valuable for traders using multiple systems, algorithmic frameworks, or discretionary approaches that perform differently depending on market state. Core Concept Markets alternate between expansion phases where directional movement dominates and contraction phases where price oscillates around equilibrium. Strategies built for one condition often underperform in the other. Ultimate Regime solves this by aggregating several environment measurements into a single regime score that expresses whether the market currently favors: • Trend continuation strategies • Breakout participation • Momentum trading or instead • Range trading • Mean reversion strategies • Oscillation-based setups The indicator therefore acts as a decision filter rather than a trade trigger. Key Features Unified regime classification combining multiple market characteristics Automatic detection of trending vs mean-reverting environments Smooth regime transitions to reduce noise and false flips Visual histogram representing regime strength Automatic chart candle coloring based on environment On-chart regime change labeling for clarity Configurable lookback and smoothing controls Works across all timeframes and asset classes Suitable for discretionary and systematic traders Designed for integration into multi-indicator workflows How It Works (Conceptual) Instead of relying on a single measurement, Ultimate Regime evaluates several dimensions of market behavior simultaneously, such as: • Price expansion versus contraction • Volatility shifts • Directional persistence • Structural movement characteristics These components are normalized and combined into a composite regime value. The result is then smoothed to ensure regime changes reflect genuine environment shifts rather than short-term fluctuations. When the combined regime value turns positive, the market is considered to favor directional movement. When it turns negative, price behavior favors oscillation and mean reversion. The internal weighting and transformation methods remain proprietary in the invite-only version. Regime States Explained Trending Regime Indicates directional dominance where price tends to move persistently in one direction. Momentum and breakout systems typically perform better under these conditions. Mean Reverting Regime Indicates oscillatory behavior where price frequently returns toward equilibrium zones. Range strategies and reversal setups often become more effective. Neutral Transitions Short transition periods may occur during regime changes as the environment reorganizes before committing to a dominant state. Visual Components Regime Histogram A histogram displays regime strength and direction, making it easy to gauge whether trending or reverting behavior dominates. Colored Candles Price candles automatically change color according to regime classification, allowing instant environment recognition directly on the chart. Regime Change Labels Labels appear when regime shifts occur, helping traders visually track transitions between trending and mean-reverting phases. Reference Thresholds Visual guide levels help users understand regime extremes and neutral zones. Inputs Overview Source Selects the price data used for regime analysis. High-Low Difference Lookback Controls how far back structural price expansion is evaluated. ATR Lookback Adjusts how volatility expansion or contraction is measured. Standard Deviation Lookback Defines the evaluation window for statistical price dispersion. ADX Lookback Controls directional persistence measurement sensitivity. Smoothing Period Applies smoothing to regime calculations, balancing responsiveness and stability. Higher smoothing reduces noise but delays regime changes. Lower smoothing reacts faster but may increase regime flipping. Usage Guidelines Use Ultimate Regime as a strategy filter rather than a direct entry signal. Trending regime environments generally favor: • Breakout systems • Momentum entries • Trend-following approaches • Pullback continuation trades Mean-reverting environments generally favor: • Range trading • Support and resistance reversals • Oscillation strategies • Counter-trend setups Regime analysis works best when combined with entry and risk tools rather than used standalone. Practical Applications Strategy selection switching between trend and range systems Position sizing adjustments based on environment strength Filtering trades that conflict with prevailing market behavior Algorithmic system optimization Portfolio regime monitoring Timeframe alignment analysis Parameter Tuning Notes Lower lookback values increase responsiveness but may produce faster regime changes. Higher lookback values stabilize regime detection for swing or position trading. Short smoothing periods work better for intraday trading. Longer smoothing periods help long-term traders avoid noise. Optimal settings vary by asset volatility and timeframe. Best Practices Combine regime detection with price structure and confirmation tools. Avoid forcing trend systems in reverting environments and vice versa. Use regime awareness to improve trade selection discipline. Backtest strategies separately for trending and mean-reverting periods. Summary Ultimate Regime provides a structured and adaptive view of market conditions by classifying whether the environment favors trend continuation or mean reversion. By separating environment analysis from trade signals, traders gain clarity in strategy selection and improve consistency across changing market conditions. The invite-only version preserves proprietary calculation methods while delivering a robust regime detection framework suitable for discretionary traders, system developers, and algorithmic strategies alike.
Wskaźnik Pine Script®
od MisinkoMaster
Standard Deviation Supertrend | GForgeStandard Deviation Supertrend ~ 𝒢𝐹𝑜𝓇𝑔𝑒 A Supertrend indicator that replaces ATR with Standard Deviation for volatility measurement, combined with a selectable Moving Average anchor for noise reduction. ━━━━━━━━━━━━━━━━━━━━━━━━ What This Indicator Does This is a trend-following overlay that plots a single trailing line on your chart. When price is above the line, the trend is bullish. When price crosses below, the trend flips bearish. Signals fire on each flip. The core mechanic is identical to the classic Supertrend — ratcheting bands that tighten in the direction of the trend and only reset when price breaks through the opposite side. ━━━━━━━━━━━━━━━━━━━━━━━━ Why Standard Deviation Instead of ATR ATR measures the average candle range. It treats all bars the same — a strong directional candle and a choppy gap produce equal ATR contributions. Standard Deviation measures how far price disperses from its mean. During clean directional moves, prices cluster on one side of the mean, producing low StdDev and tighter bands. During erratic, sideways price action, prices scatter around the mean, producing high StdDev and wider bands. The result: the trailing stop naturally tightens when the trend is clean and loosens when conditions are noisy. This is adaptive behavior that ATR-based Supertrends don't provide. ━━━━━━━━━━━━━━━━━━━━━━━━ Two Smoothing Layers Raw Supertrend inputs can be noisy. A single wick or volatile candle can jerk the trailing band and cause a premature flip. This indicator addresses that with two optional smoothing layers: Anchor MA — applies a Moving Average to the price source before bands are calculated. Instead of building bands around raw hl2 (which reacts to every wick), the bands are built around a smoother baseline. 11 MA types are available: • None (hl2) — raw, classic Supertrend behavior • SMA, EMA, WMA — standard options with varying lag • HMA — very low lag, can overshoot on reversals • DEMA, TEMA — reduced lag variants of EMA • VWMA — volume-weighted, naturally anchors to high-volume levels • RMA — Wilder's smoothing, very stable • ALMA — Gaussian-weighted with tunable offset and sigma • T3 — Tillson, extremely smooth with adjustable volume factor StdDev Smoothing — applies an EMA to the raw Standard Deviation output before it scales the bands. This prevents abrupt band width changes when a volatile bar enters or exits the lookback window. Set to 1 to disable. Together, these improve parameter robustness — small changes to settings produce smaller changes in output, meaning the indicator is less likely to break under slight parameter variation. ━━━━━━━━━━━━━━━━━━━━━━━━ Settings Overview • Anchor Source — price input for the Supertrend. hl2 is the classic default. • StdDev Length — lookback period for the Standard Deviation calculation. • StdDev Multiplier — band width. Higher values require a larger move to flip direction. This serves the same purpose as a "threshold" in oscillator-based indicators. • Anchor MA Type / Length — which Moving Average smooths the anchor, and its period. • StdDev Smoothing — EMA period applied to the raw StdDev. 1 = no smoothing. • ALMA Offset / Sigma — only active when ALMA is selected. • T3 Volume Factor — only active when T3 is selected. • Current settings work best on BTC 1D ━━━━━━━━━━━━━━━━━━━━━━━━ Visual Elements • Glow trail — the Supertrend line pulses with a layered glow that changes color on trend direction. • Trend fill — gradient fill between price and the trailing line. • Inactive band — shown as crosses, marking where the opposite flip point sits. • Anchor MA line — subtle reference line showing the smoothed anchor (hidden when set to None). • Bar coloring — candles colored by current trend direction. • Signal diamonds — dual-layer markers (halo + core) on trend flips. All visual elements can be toggled on or off individually. 13 color themes are included. ━━━━━━━━━━━━━━━━━━━━━━━━ ⚠️ Disclaimer This indicator is a technical analysis tool, not financial advice. It does not guarantee profitable results. Past performance on any asset or timeframe does not indicate future results. No indicator can predict market direction with certainty. Always use proper risk management. Do not rely on any single indicator for trading decisions. Test thoroughly on your chosen instruments and timeframes before applying to live markets. You are solely responsible for your own trading decisions and outcomes. ━━━━━━━━━━━━━━━━━━━━━━━━ Developed by 𝒢𝐹𝑜𝓇𝑔𝑒
Wskaźnik Pine Script®
od GForge
Adaptive BSP v6The Adaptive Buying and Selling Pressure (ABSP) indicator is the "engine" of your system. Unlike standard volume oscillators that just look at total quantity, this logic dissects the internal price action of every candle to determine who is actually in control. 1. The Core Calculation (Intra-Bar Delta) Instead of just looking at the candle color, the ABSP logic calculates pressure based on where the price closes relative to the high and low of the bar: • Buying Pressure (BP): Measured as the distance from the candle's Low to its Close. BP = Close - min(Low, Close) • Selling Pressure (SP): Measured as the distance from the candle's High to its Close. SP = max(High, Close) - Close 2. The Adaptive Lookback (The "Pulse") Standard indicators use a "static" period (like 14 or 20). The ABSP is different; it uses the Market Pulse to change its own length: • It tracks the number of bars since the last significant structural pivot. • If the market is moving fast with frequent pivots, the lookback shortens (more sensitive). • If the market is trending smoothly without pivots, the lookback lengthens (more stable). 3. Statistical Normalization (Z-Score) To make the data readable across different assets (like Crypto vs. Forex), we apply a Z-Score calculation. This measures how many standard deviations the current pressure is away from the mean: • Neutral: Z = approx 0 (Balanced market). • High Intensity: Z > 2.0 (Significant buying surge). • Extreme Exhaustion: Z > 3.0 (Potential blow-off top/bottom). 4. Key Logic Points Feature | Function | Trading Benefit ============================= Net Delta | Subtracts SP from BP. | Instant view of which side is winning the tug-of-war. ---------------------------------------------------------------------------- EMA Smoothing | Uses a Series EMA on the raw values. | Filters out "noise" while remaining responsive to price. ---------------------------------------------------------------------------- Divergence Logic | Compares Price Highs to Pressure Highs. | Flags when a trend is losing "gas" before price actually drops. ---------------------------------------------------------------------------- Z-Intensity Filter | Only flags "PRO" signals at extremes. | Ensures you aren't entering during "retail chop." How it drives the "Fusion" System: In your current setup, the ABSP acts as the ultimate filter. A "Wave" is just a zig-zag on the chart, but the ABSP tells the script: "This wave is legitimate because the Z-Score is at 2.1 and Buying Pressure is exponentially higher than Selling Pressure." Would you like me to add a specific "Exhaustion" alert to the ABSP logic that pings you when the Z-Score hits an extreme level (>3.0), even if a new wave hasn't formed yet?
Wskaźnik Pine Script®
od kimlombard
Fusion Elite: Smart-Alert + ADR [v6]🔱 The Fusion Elite Trading Manifesto Version 1.0 — Execution Strategy & Rules I. The Three Pillars of Confluence Every high-probability trade must be a "meeting of the minds" between three distinct market forces: 1. Market Structure (The Wave): A structural pivot must be confirmed. We don't guess bottoms or tops; we wait for the pivot to print. 2. Internal Pressure (The ABSP): The wave must be backed by net buying or selling pressure. A bullish wave with negative net pressure is a "Fakeout." 3. Momentum (Auto-Lens MACD): The move must have the "wind at its back." We look for the histogram to be in sync with our entry direction. II. Signal Hierarchy Not all labels are created equal. Use this hierarchy to manage your risk: III. The "Gas Tank" (ADR) Rule The Average Daily Range is your most important filter for trend longevity. • Fuel to Burn (>50\% ADR Room): Aggressive entries allowed. The trend has room to expand into a "runner." • Running on Fumes (<20\% ADR Room): No new trend entries. Focus on trailing stops. • Tank Empty (<10\% ADR Room): Look for SESS HUNT 🎯 reversal signals. The market is overextended and likely to "snap back" to the mean. IV. The Trend Shutter (Macro Bias) The 1-Hour background shadow is your "North Star." • Emerald Shadow: Long-bias only. Ignore bearish waves; only take PRO BUY and ADD+ signals. • Crimson Shadow: Short-bias only. Ignore bullish waves; only take PRO SELL and ADD- signals. V. Defensive Procedures (The Warnings) • !! DIV WARNING !!: If the dashboard flashes a divergence warning, the current move is "weak." Move Stop Loss to break-even or take 50\% profit immediately. • Sync Divergence: If the 15s and 5m timeframes are "CHOP" (disagreeing), stay flat. We only strike when the Confluence Meter shows dominance (>75\%). VI. The Professional Mindset "I do not trade price; I trade the confluence of structural pivots, institutional liquidity hunts, and statistical pressure extremes." 1. Verify the Shadow (1H Bias). 2. Check the Gas Tank (ADR Room). 3. Wait for the Confluence (Triple Threat / PRO Signal). 4. Manage the Trade (Trust the ATR-based SL/TP).
Wskaźnik Pine Script®
od kimlombard
ALMA SD Bands | RakoQuantALMA SD Bands | RakoQuant is a volatility-regime band system built from first principles using an institutional smoothing framework: an ALMA baseline combined with ALMA-smoothed standard deviation width, designed for clean trend containment and controlled regime classification. This tool is part of the RakoQuant protected research line, focusing on minimal noise, persistent state logic, and volatility-aware market structure rather than traditional reactive Bollinger-style band behavior. Core Concept This indicator answers one key structural question: Is price operating inside a stable volatility regime, or transitioning into a new directional band expansion phase? Unlike classical deviation band systems that fluctuate aggressively candle-to-candle, ALMA SD Bands introduce: * Ultra-smooth baseline structure * Smoothed volatility width * Persistent directional regime logic * Deadband-based flip stabilization The result is a clean institutional containment model rather than noisy retail band plotting. How It Works 1. ALMA Baseline (Institutional Mean Structure) The centerline of the system is computed using: Arnaud Legoux Moving Average (ALMA) ALMA provides: * Reduced lag compared to EMA * Superior smoothness compared to SMA * Stable regime structure across crypto volatility This baseline acts as the equilibrium axis of the band system. 2. Standard Deviation Volatility Width (Smoothed) Band width is driven by volatility, measured through standard deviation, with two selectable modes: * Price Standard Deviation * Return Standard Deviation (log-return volatility) Rather than using raw deviation directly, volatility is passed through a second ALMA smoothing layer: Smoothed Volatility = ALMA(StdDev) This eliminates the jitter and band shaking that defines most Bollinger-type systems. 3. Adaptive Containment Bands Final bands are constructed as: * Upper Band = ALMA Basis + Multiplier × Smoothed Volatility * Lower Band = ALMA Basis − Multiplier × Smoothed Volatility Unlike traditional ±2σ envelopes, the multiplier is intentionally adjustable and tuned for regime containment rather than extreme tagging. 4. Deadband Regime Engine (Persistent State Logic) A defining feature of this protected release is its regime persistence model. Instead of flipping trend bias instantly, the script applies a volatility-scaled deadband buffer: * Bull regime activates only above Basis + Deadband * Bear regime activates only below Basis − Deadband This removes micro-flips and produces a true structural regime state: * Bullish containment (green) * Bearish containment (red) * Neutral transition zone suppression Regime state persists until a confirmed boundary transition occurs. Visual Engine ALMA SD Bands follows the RakoQuant minimal institutional plotting standard: * Active volatility bands only * Smooth containment fill * Optional candle painting by regime bias * Ultra-clean overlays suitable for confluence stacking This indicator is designed as a structural layer, not a clutter generator. How To Use ✅ Volatility containment framework
✅ Trend regime bias overlay
✅ Expansion / contraction classifier
✅ Portfolio directional filter (RSPS compatible) Recommended workflow: * Trade long only during bullish regime containment * Defensive during bearish containment * Watch for regime flips as volatility transition events * Combine with momentum triggers for execution Best environments: * 4H–1D swing trend structure * Volatility breakout classification * Institutional band containment systems Screenshot Placement 📸 Example chart / screenshot:
Wskaźnik Pine Script®
od RakoQuant
1
MACD Standard DeviationMACD Standard Deviation The MACD Standard Deviation is a smoother, volatility-adjusted version of MACD designed to improve signal quality and reduce noise while preserving fast market responsiveness. 🚀 Benefits • Strong performance on assets like BNBUSDT • Faster entries with reduced signal noise • Simple and efficient calculation method • Improved trend clarity compared to classic MACD 💡 Core Idea The objective is to create a cleaner MACD signal by measuring and adapting to its volatility. By accounting for dispersion, the indicator filters weak fluctuations and keeps meaningful momentum moves. ⚙️ How It Works A standard MACD is calculated using selected moving averages. Standard deviation of the MACD is computed over a chosen period. Upper and lower dynamic levels are derived from MACD median and volatility. These adaptive bands help filter false signals and better capture trend direction. The result is a smoother, more stable MACD-based trend tool. 📌 Usage Notes • Crosses around the zero line indicate potential trend shifts. • Expanding band distance suggests rising momentum volatility. • Contracting distance often signals consolidation phases. • Histogram changes help visualize acceleration or weakening momentum.
Wskaźnik Pine Script®
od MisinkoMaster
1
Volume Weighted LR Z ScoreThis indicator calculates the Volume Weighted Linear Regression Z-Score (VWLRZS). Unlike a standard Z-Score which measures deviation from a static mean, this oscillator measures the statistical distance of price from a dynamic Volume-Weighted Linear Regression Line (Analysis of Residuals). Key Features: 1. **Volatility Decomposition:** The indicator separates volatility based on the 'Estimate Bar Statistics' option. - **Standard Mode (`Estimate Bar Statistics` = OFF):** Calculates standard Regression Residuals using the selected `Source` for both the regression line (baseline) and the signal. - **Decomposition Mode (`Estimate Bar Statistics` = ON):** Uses a hybrid statistical approach: a) **The Model (Baseline):** Uses an estimator to calculate the 'within-bar' mean and fits the Linear Regression through these statistical centers. This creates a stable, trend-following expectation model. b) **The Signal (Observation):** Compares the actual `Source` (e.g., Close) against this regression line. (Result: A Z-Score that measures deviations from the current trend slope rather than a flat average). 2. **Visual Decomposition Logic:** Total Standard Deviation (of Residuals) is the primary metric displayed. Since Standard Deviations are not linearly additive (sqrt(a+b) != sqrt(a)+sqrt(b)), this indicator calculates the *exact* Total Z-Score and partitions the area underneath based on the Variance Ratio. This ensures the displayed total volatility remains mathematically accurate while showing relative composition. 3. **Normalization (Exponential Regression):** Includes an optional 'Normalize' mode. When enabled, the indicator calculates the Linear Regression on logarithmic data. Mathematically, this transforms the baseline into an **Exponential Regression Curve**, making it ideal for analyzing assets with compounding growth characteristics (constant percentage trend). 4. **Full Divergence Suite (Class A, B, C):** The indicator's primary feature is its integrated divergence engine. It automatically detects and plots all three major divergence classes between price and the Z-Score: - Regular (A): Signals potential trend exhaustion and reversals. - Hidden (B): Signals potential trend continuations during pullbacks. - Exaggerated (C): Signals weakness at double tops/bottoms. 5. **Divergence Filtering and Visualization:** - **Price Tolerance Filter:** Divergence detection is enhanced with a percentage-based price tolerance (`pivPrcTol`) to filter out insignificant market noise, leading to more robust signals. - **Persistent Visualization:** Divergence markers are plotted for the entire duration of the signal and are visually anchored to the oscillator level of the confirming pivot. - **Flexible Pivot Algorithms:** Supports various underlying mathematical models for pivot detection provided by the core library 6. **Note on Confirmation (Lag):** Divergence signals rely on a pivot confirmation method to ensure they do not repaint. - The **Start** of a divergence is only detected *after* the confirming pivot is fully formed (a delay based on `Pivot Right Bars`). - The **End** of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed). 7. **Multi-Timeframe (MTF) Capability:** - **MTF Calculation:** The Z-Score line *itself* can be calculated on a higher timeframe, with standard options to handle gaps (`Fill Gaps`) and prevent repainting (`Wait for...`). - **Limitation:** The Divergence detection engine (`pivDiv`) is designed for the active timeframe. Using it in MTF mode is not recommended as step-data can lead to inaccurate pivot detection. 8. **Integrated Alerts:** Includes a comprehensive set of built-in alerts for the Z-Score crossing the neutral line, the configured Threshold levels, and the start/end of all divergence types. --- **DISCLAIMER** 1. **For Informational/Educational Use Only:** This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset. 2. **Use at Your Own Risk:** All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk. 3. **No Guarantee of Performance:** Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability. 4. **No Liability:** The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator. 5. **Signals Are Not Recommendations:** The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Wskaźnik Pine Script®
od AustrianTradingMachine
Volume Weighted Z ScoreThis indicator calculates the Volume Weighted Z-Score (VWZS), a statistical oscillator that measures the number of standard deviations the price is removed from its mean. It combines robust volatility decomposition with advanced divergence detection. Key Features: 1. **Volatility Decomposition:** The indicator separates volatility based on the 'Estimate Bar Statistics' option. - **Standard Mode (`Estimate Bar Statistics` = OFF):** Calculates a simple (Volume-Weighted) Standard Deviation using the selected `Source` for both the baseline and the signal. - **Decomposition Mode (`Estimate Bar Statistics` = ON):** Uses a hybrid statistical approach: a) **The Model (Baseline):** Uses an estimator to calculate the 'within-bar' mean and volatility. This creates a stable, mathematically idealized expectation value (mu). b) **The Signal (Observation):** Compares the actual `Source` (e.g., Close) against this statistical baseline. (Result: A Z-Score that combines a noise-filtered trend baseline with a highly reactive price signal). 2. **Visual Decomposition Logic:** Total Standard Deviation is the primary metric displayed. Since Standard Deviations are not linearly additive (sqrt(a+b) != sqrt(a)+sqrt(b)), this indicator plots the *exact* Total StdDev and partitions the area underneath based on the Variance Ratio. This ensures the displayed total volatility remains mathematically accurate while showing relative composition. 3. **Normalization (Geometric Average):** Includes an optional 'Normalize' mode. When enabled, the indicator uses a Geometric Moving Average (GMA) as its baseline and applies a statistical correction for the log-normal distribution ensuring symmetry between upside and downside movements. 4. **Full Divergence Suite (Class A, B, C):** The indicator's primary feature is its integrated divergence engine. It automatically detects and plots all three major divergence classes between price and the Z-Score: - Regular (A): Signals potential trend exhaustion and reversals. - Hidden (B): Signals potential trend continuations during pullbacks. - Exaggerated (C): Signals weakness at double tops/bottoms. 5. **Divergence Filtering and Visualization:** - **Price Tolerance Filter:** Divergence detection is enhanced with a percentage-based price tolerance (`pivPrcTol`) to filter out insignificant market noise, leading to more robust signals. - **Persistent Visualization:** Divergence markers are plotted for the entire duration of the signal and are visually anchored to the oscillator level of the confirming pivot. - **Flexible Pivot Algorithms:** Supports various underlying mathematical models for pivot detection provided by the core library 6. **Note on Confirmation (Lag):** Divergence signals rely on a pivot confirmation method to ensure they do not repaint. - The **Start** of a divergence is only detected *after* the confirming pivot is fully formed (a delay based on `Pivot Right Bars`). - The **End** of a divergence is detected either instantly (if the signal is invalidated by price action) or with a delay (when a new, non-divergent pivot is confirmed). 7. **Multi-Timeframe (MTF) Capability:** - **MTF Calculation:** The Z-Score line *itself* can be calculated on a higher timeframe, with standard options to handle gaps (`Fill Gaps`) and prevent repainting (`Wait for...`). - **Limitation:** The Divergence detection engine (`pivDiv`) is designed for the active timeframe. Using it in MTF mode is not recommended as step-data can lead to inaccurate pivot detection. 8. **Integrated Alerts:** Includes a comprehensive set of built-in alerts for the Z-Score crossing the neutral line, the configured Threshold levels, and the start/end of all divergence types. --- **DISCLAIMER** 1. **For Informational/Educational Use Only:** This indicator is provided for informational and educational purposes only. It does not constitute financial, investment, or trading advice, nor is it a recommendation to buy or sell any asset. 2. **Use at Your Own Risk:** All trading decisions you make based on the information or signals generated by this indicator are made solely at your own risk. 3. **No Guarantee of Performance:** Past performance is not an indicator of future results. The author makes no guarantee regarding the accuracy of the signals or future profitability. 4. **No Liability:** The author shall not be held liable for any financial losses or damages incurred directly or indirectly from the use of this indicator. 5. **Signals Are Not Recommendations:** The alerts and visual signals (e.g., crossovers) generated by this tool are not direct recommendations to buy or sell. They are technical observations for your own analysis and consideration.
Wskaźnik Pine Script®
od AustrianTradingMachine
STDV Extension Zones from Daily Open - OnlyFlowSTDV Extension Zones from Daily Open This indicator plots standard deviation extension zones based on the current day’s opening price. At the start of each trading day, it calculates the daily standard deviation using a configurable lookback and projects price zones at ±0.5 and ±1.0 standard deviations above and below the daily open. Each zone is displayed as a horizontal band with a center line and a customizable thickness, extending forward throughout the session. Zones automatically reset and lock in place when a new day begins, preserving prior sessions for historical context. The indicator is designed to visually highlight statistically significant price extensions relative to the daily open, helping users quickly identify areas where price may be stretched, balanced, or reacting around volatility-based levels.
Wskaźnik Pine Script®
od ofderk
Std Dev Channel [fmb]What it is A professional regression channel that combines standard deviation divisions, an extreme price envelope, and a trend quality gauge. It is designed for fast read-and-act decisions on any timeframe, with sensible presets and log-space math for instruments that trend exponentially. Why it’s different Most channels draw fixed ±1σ and ±2σ around a regression line. This tool adds: - Fibonacci-spaced σ divisions for precise scaling - An objective MaxEnvelope of actual extremes with optional 1.272 and 1.618 extensions - Pearson’s R labelling that classifies the trend as Strong Up, Moderate, Weak, or Strong Down - A log-space option so channels behave correctly on long trends and high beta charts How it works Base line - Linear regression of the last Length bars, drawn as a ray. - Optional colour change by regime using Pearson’s R. Divisions (StdDev or MaxEnvelope) - StdDev basis: σ of residuals around the regression line. - MaxEnvelope basis: distances from the base line to the farthest highs and lows in the lookback. - Divisions can be Fibonacci multiples (0.382, 0.618, 1.000, 1.272 by default) or uniform steps. Outer rails - ENV 1.0 touches the farthest highs and lows within the window. - Optional extensions at 1.272 and 1.618 highlight stretch and breakout zones. Trend quality (Pearson’s R) - R is computed on the same series and window. - Default thresholds: Strong when |R| ≥ 0.70, Weak when |R| < 0.40. - The label reads: R 0.XXX • Class, plotted near the most recent base value. Log-space math - When enabled, the model runs on ln(price) and converts the outputs back to price. - Safer on multi-year charts and large percentage trends. Presets - Swing: Length 125, StdDev basis, Fib divisions, ENV 1.0 and 1.272 on - Intraday: Length 240, StdDev basis, simple ±1 and ±2 style divisions, ENV off by default - Position: Length 200, StdDev basis, compact Fib set for higher timeframes You can turn preset overrides off to make every input respond instantly. Inputs you will actually use - Length, Source, Log-space ON or OFF - Basis: StdDev or MaxEnvelope - Divisions: Fib list or Step and Max multiple - Outer rails: show ENV 1.0, show 1.272, show 1.618 - Labels and sizes, extend left or right - Hide divisions or outer rails automatically when the regime is Weak Alerts included - Close crosses above or below ENV 1.0 - Close crosses above or below ENV 1.272 and 1.618 (if enabled) Practical playbook Trend following - In Strong Uptrend: buy pullbacks near 0.382 to 0.618 above the base with stops just beyond the next lower division. - In Strong Downtrend: sell bounces into 0.382 to 0.618 below the base with stops just beyond the next upper division. Mean reversion - When R is Moderate or Weak, fade moves that tag ENV 1.0 back toward the base. - If price closes through an ENV extension, treat it as potential regime change and stand down on fades. Breakouts - A close through ENV 1.0 with R rising toward Strong often precedes trend acceleration. - Use the next division or the 1.272 rail as the first target and trail on the base. Tips - Keep Length stable across symbols you compare. Consistency beats curve fitting. - Use log-space on multi-year equities and crypto. Use linear for short intraday work. - If you want a classic look, disable Fib and rails, set Step 1.0 and Max 2.0. Notes - The tool draws more lines when Fib divisions are active. If it feels busy, show divisions only and hide labels, or keep ENV 1.0 plus one extension. - Pearson’s R is descriptive, not predictive. Combine with price structure and volume for entries.
Wskaźnik Pine Script®
od Fullymobile
5
Adaptive Pullbacks ML v2.5Adaptive Pullbacks ML - Context-Aware Trend Trading Overview Adaptive Pullbacks ML is a sophisticated trend-following tool that solves the biggest problem in pullback trading: "Is this a dip to buy, or the start of a reversal?" Unlike standard indicators that use fixed percentages or static moving averages, this script uses a 5-Dimensional k-Nearest Neighbors (k-NN) machine learning engine to learn the specific characteristics of successful pullbacks for the asset you are trading. The 5-Dimensional ML Engine The market is dynamic. A pullback depth that works in a low-volatility lunch session might fail during a high-volatility news event. This indicator tracks 5 key dimensions for every pullback: Depth (ATR Normalized): How deep is the pullback relative to volatility? Trend Slope: Is the trend steep (parabolic) or flat (grinding)? ADX: How strong is the directional energy? VWAP Distance: Is price extended or close to value? Time of Day: Is this a morning drive or an afternoon fade? When a new pullback occurs, the k-NN engine finds the 5 most similar historical events across these dimensions and predicts the probability of success. Core Features 1. Fractal Normalization The indicator speaks the language of ATR (Average True Range). It doesn't care if you trade the 15-second chart or the Daily chart. A "1.5 ATR Pullback" is a statistically comparable event across all timeframes, allowing for robust, scale-invariant analysis. 2. HTF Stats Bridge (Higher Timeframe Data) You can trade on lower timeframes (e.g., 1-minute) while using statistics derived from higher timeframes (e.g., 15-minute). This ensures your signals are based on significant market structure, not microstructure noise. 3. Smart Zones The indicator plots dynamic "Value Zones" based on learning: Cyan Zone (Avg Depth): The "Sweet Spot". High probability bounce area. Yellow Zone (Sigma): The "Extension". Price is stretching elastic limits. Red Zone (Deep): The "Danger/Opportunity". Statistical anomaly. 4. PQS & k-NN Filters Two layers of filtering protect your capital: PQS (Probability Qualification Score): Based on raw win-rate of the zone. k-NN Probability: Based on similarity to past winners. Settings Guide Stats Timeframe: The timeframe to learn from (Leave empty for Chart). Trend/Trigger Settings: Define what constitutes a trend for your strategy. k-Neighbors: Number of historical twins to compare (Default: 5). Min PQS / k-NN: Thresholds for filtering weak signals. Disclaimer: This tool is for educational purposes. Past performance of the k-NN engine does not guarantee future results.
Wskaźnik Pine Script®
od Selfsimilarity
1
Adaptive ML VWAP v1.0Overview Adaptive ML VWAP is a next-generation "Smart Indicator" that moves beyond static deviations (Standard Deviation). Instead of assuming market volatility is distributed normally (Bell Curve), this indicator uses a k-Nearest Neighbors (k-NN) machine learning engine to learn the specific volatility behavior of the asset you are trading. It answers the question: "When price extends away from VWAP, how far does it actually go before reversing?" The Adaptive ML Engine This script features a 5-Dimensional ML Engine that tracks every major extension or pullback event. It records: Deviation Depth (Normalized to ATR) Trend Slope (Is the trend steep or flat?) ADX (Trend Strength) VWAP Deviation (Relative Position) Time of Day (Session Context) When a new setup occurs, the k-NN engine instantly searches its memory for the 5 most similar historical events and calculates the probability of success based on what happened last time. Two Strategy Modes You can toggle the logic to suit your trading style: 1. Mean Reversion Mode (Default) "Fade The Move" Goal: Catch price at an exhaustion point returning to VWAP. Signal: Triggers when price touches a Smart Band and reverses back toward the center. k-NN Learning: Learns which conditions favor a snap-back. Best For: Ranging markets, Lunch hours, Choppy sessions. 2. Trend Following Mode "Ride The Move" Goal: Catch breakouts that are launching away from value. Signal: Triggers when price breaks out of the Inner Band (1.0). k-NN Learning: Learns which breakouts tend to extend to the Outer Bands. Best For: Morning Drives, News Events, Strong Trends. Visual Guide The indicator uses a Dynamic Gradient system to visualize risk/reward: Cyan Mist (0.5 - 1.0): The Value Zone. Noise area. Safe for trend entries. Deep Cyan (1.0 - 2.0): The Trend Zone. Price is moving proactively. Orange Glow (2.0 - 3.0): The Danger Zone. Price is statistically overextended. Reversals are highly probable here. "Fractal" Math Unlike standard indicators that break when you change timeframes, Adaptive ML VWAP uses Fractal Normalization. A "2.0 Band" on a 15-second chart means the same statistical extreme as a "2.0 Band" on a 4-hour chart. Auto-Adaptive Lookback: The indicator automatically boosts the ML memory (Lookback) on lower timeframes (seconds/minutes) where more noise requires larger sample sizes, ensuring robust predictions without manual tweaking. Settings Auto-Adapting Lookback: (Default: True) automatically increases Lookback to 100+ for seconds charts and 50+ for minute charts. Lookback (Events): Manual override base value (Default: 100). Strategy Mode: Toggle between Mean Reversion and Trend Following. k-Neighbors: The number of similar past events to structurally compare (Default: 5). Disclaimer: This tool is for educational purposes. Machine learning performance is dependent on market conditions and historical recursion.
Wskaźnik Pine Script®
od Selfsimilarity
DCA + Martingale strategy.DCA + Martingale: smart synergy for volatile markets Tame market swings with a powerful hybrid strategy that marries the discipline of Dollar‑Cost Averaging (DCA) with the aggressive recovery logic of the Martingale system. This approach turns price dips into opportunities — systematically building positions while keeping risk in check. How it works: 1. Entry trigger The strategy activates when the asset price drops by a predefined percentage on the 1‑hour timeframe. This ensures you only engage when a meaningful pullback occurs, avoiding premature entries. 2. DCA grid for controlled averaging Once the entry condition is met, a grid of buy orders is deployed: Each subsequent order is placed at progressively lower price levels (e.g., every 2–5% drop). Order sizes can be fixed or follow a progressive scale (e.g., 1x, 1.5x, 2x the initial amount). This dilutes your average entry price, improving the breakeven point as the market corrects. 3. Martingale‑style recovery mechanism After each unsuccessful trade (i.e., price continues falling), the next position size is increased — not necessarily doubled, but scaled according to your risk tolerance. This accelerates recovery potential when the trend reverses. 4. Take‑profit with a fixed percentage target A simple, predefined profit target (e.g., +3–7%) is set for the entire averaged position. Once hit, all open trades close, locking in gains. This prevents over‑exposure during uncertain reversals. Key advantages Psychological edge: removes emotional decision‑making by automating entries and exits. Cost optimization: lowers average entry during downtrends, improving profit potential. Controlled aggression: Martingale logic helps recoup losses faster without infinite scaling. Flexibility: parameters (entry %, grid spacing, position sizing, TP) are fully customizable. Risk management essentials Stop‑loss safeguard: a hard stop‑loss (e.g., 10–15% below the lowest grid level) prevents catastrophic drawdowns in prolonged downtrends. Position sizing: never risk more than 1–3% of capital per grid cycle. Market context: best suited for assets with mean‑reverting behavior and moderate volatility. Avoid strong, sustained trends. Capital buffer: ensure sufficient reserves to withstand multiple grid levels without margin calls. When to use it During sideways or range‑bound markets with regular pullbacks. On assets with historical tendency to recover from short‑term dips. When you expect a bounce but can’t pinpoint the exact bottom. Bottom line DCA + Martingale isn’t a «set‑and‑forget» miracle — it’s a disciplined framework for turning volatility into opportunity. Combine it with rigorous risk rules, and you’ll navigate downtrends with precision, turning market noise into structured profit potential.
Strategia Pine Script®
od lordos2003
ATR Stop LinesATR Stop Lines Plots dynamic stop-loss levels on the price chart based on ATR (Average True Range). Optionally adjusts stop distance based on volatility regime. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 WHAT IT DOES Green line — Long stop (Close − ATR × multiplier) Red line — Short stop (Close + ATR × multiplier) Lines move with price and volatility. When regime-adjust is enabled, stop distance widens in high volatility and tightens in low volatility. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📐 REGIME-ADJUSTED MULTIPLIERS When enabled, the multiplier auto-adjusts based on the ATR percentile: LOW (< 25th pctl) — 1.0× ATR — Tight stops, small moves expected NORMAL (25–50th pctl) — 1.5× ATR — Standard distance HIGH (50–75th pctl) — 2.0× ATR — Wider to avoid noise EXTREME (> 75th pctl) — 2.5× ATR — Widest, or skip the trade Disable regime-adjust to use a fixed multiplier for all conditions. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📈 HOW TO USE Entry: Note stop line level when entering a trade. Set stop-loss at or beyond that level. Trailing: Move stop to new line level as price advances in your favor. Sizing: Wider stop = smaller position to maintain constant risk. Example: BTC Daily, ATR = \$2,000, Regime = HIGH (2.0×) Entry: \$50,000 → Long stop: \$46,000 / Short stop: \$54,000 ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 STATUS LABEL VOL — Current regime (LOW / NORMAL / HIGH / EXTREME) ATR — Raw ATR value in price units Mult — Active multiplier Stop Dist — Current stop distance in price units ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ ⚙️ SETTINGS ATR Settings: ATR Length (default: 14) Percentile Lookback (default: 100) Timeframe: Use Fixed Timeframe — Lock to specific TF Fixed Timeframe (default: D) Stop Settings: Regime-Adjusted Multiplier — Toggle auto-adjust on/off Base ATR Multiplier — Used when regime-adjust is off LOW/NORMAL/HIGH/EXTREME Multipliers — Customize per regime Display: Show Long Stop / Show Short Stop Show Status Label Long/Short Stop Colors ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🔔 ALERTS Vol → EXTREME Vol → LOW ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 💡 COMPANION INDICATOR Use with ATR Volatility Regime (separate pane) for full context: Pane indicator → percentile visualization, zone backgrounds This indicator → actionable stop levels on price chart Both use identical ATR/percentile logic and stay in sync. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📝 NOTES Works on any timeframe Stops are dynamic — recalculate each bar Not a signal generator — use with your own entry logic ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🏷️ TAGS ATR, stop-loss, volatility, risk-management, position-sizing, trailing-stop, swing-trading
Wskaźnik Pine Script®
od gokcenbuy
Intermarket Divergence (Futures vs Equity)Intermarket Divergence (Futures vs Equity) This indicator detects intermarket divergence between a traded instrument (futures, CFD, or spot) and a related equity or ETF. It highlights moments where price and its underlying market drivers disagree, often appearing before reversals or expansions. 🎯 What It Shows Bullish divergence: Price makes a lower low while the equity makes a higher low Bearish divergence: Price makes a higher high while the equity makes a lower high Based on swing pivots, not candle noise Designed for intraday context, not mechanical entries ✅ Recommended Use XAUUSD (Gold) → GDX (default) XAGUSD (Silver) → SIL USOIL / WTI → XLE (These guidelines are included directly in the indicator settings.) 🧭 How to Use Apply on 15m–30m Look for signals near key levels (PDH/PDL, Asia high/low, HTF structure) Use price action for entries Divergence is context, not a signal. ⚠️ Notes Non-repainting Signals are selective by design Best during London & New York sessions
Wskaźnik Pine Script®
od odoyebisi
[GYTS] Volatility Toolkit Volatility Toolkit 🌸 Part of GoemonYae Trading System (GYTS) 🌸 🌸 --------- INTRODUCTION --------- 🌸 💮 What is Volatility Toolkit? Volatility Toolkit is a comprehensive volatility analysis indicator featuring academically-grounded range-based estimators. Unlike simplistic measures like ATR, these estimators extract maximum information from OHLC data — resulting in estimates that are 5-14× more statistically efficient than traditional close-to-close methods. The indicator provides two configurable estimator slots, weighted aggregation, adaptive threshold detection, and regime identification — all with flexible smoothing options via GYTS FiltersToolkit integration. 💮 Why Use This Indicator? Standard volatility measures (like simple standard deviation) are highly inefficient, requiring large amounts of data to produce stable estimates. Academic research has shown that range-based estimators extract far more information from the same price data: • Statistical Efficiency — Yang-Zhang achieves up to 14× the efficiency of close-to-close variance, meaning you can achieve the same estimation accuracy with far fewer bars • Drift Independence — Rogers-Satchell and Yang-Zhang correctly isolate variance even in strongly trending markets where simpler estimators become biased • Gap Handling — Yang-Zhang properly accounts for overnight gaps, critical for equity markets • Regime Detection — Built-in threshold modes identify when volatility enters elevated or suppressed states ↑ Overview showing Yang-Zhang volatility with dynamic threshold bands and regime background colouring 🌸 --------- HOW IT WORKS --------- 🌸 💮 Core Concept The toolkit groups volatility estimators by their output scale to ensure valid comparisons and aggregations: • Log-Return Scale (σ) — Close-to-Close, Parkinson, Garman-Klass, Rogers-Satchell, Yang-Zhang. These are comparable and can be aggregated. Annualisable via √(periods_per_year) scaling. • Price Unit Scale ($) — ATR. Measures volatility in absolute price terms, directly usable for stop-loss placement. • Percentage Scale (%) — Chaikin Volatility. Measures the rate of change of the trading range — whether volatility is expanding or contracting. Only estimators with the same scale can be meaningfully compared or aggregated. The indicator enforces this and warns when mixing incompatible scales. 💮 Range-Based Estimator Overview Range-based estimators utilise High, Low, Open, and Close prices to extract significantly more information about the underlying diffusion process than close-only methods: • Parkinson (1980) — Uses High-Low range. ~5× more efficient than close-to-close. Assumes zero drift. • Garman-Klass (1980) — Incorporates Open and Close. ~7.4× more efficient. Assumes zero drift, no gaps. • Rogers-Satchell (1991) — Drift-independent. Superior in trending markets where Parkinson/GK become biased. • Yang-Zhang (2000) — Composite estimator handling both drift and overnight gaps. Up to 14× more efficient. 💮 Theoretical Background • Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI • Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI • Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI • Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI 🌸 --------- KEY FEATURES --------- 🌸 💮 Feature Reference Estimators (8 options across 3 scale groups): • Close-to-Close — Classical benchmark using closing prices only. Least efficient but useful as baseline. Log-return scale. • Parkinson — Range-based (High-Low), ~5× more efficient than close-to-close. Assumes zero drift. Log-return scale. • Garman-Klass — OHLC-optimised, ~7.4× more efficient. Assumes zero drift, no gaps. Log-return scale. • Rogers-Satchell — Drift-independent, handles trending markets where Parkinson/GK become biased. Log-return scale. • Yang-Zhang — Gap-aware composite, most comprehensive (up to 14× efficient). Uses internal rolling variance (unsmoothed). Log-return scale. • Std Dev — Standard deviation of log returns. Log-return scale. • ATR — Average True Range in absolute price units. Useful for stop-loss placement. Price unit scale. • Chaikin — Rate of change of range. Measures volatility expansion/contraction, not level. Percentage scale. Smoothing Filters (10 options via FiltersToolkit): • SMA / EMA — Classical moving averages • Super Smoother (2-Pole / 3-Pole) — Ehlers IIR filter with excellent noise reduction • Ultimate Smoother (2-Pole / 3-Pole) — Near-zero lag in passband • BiQuad — Second-order IIR with configurable Q factor • ADXvma — Adaptive smoothing, flat during ranging periods • MAMA — MESA Adaptive Moving Average (cycle-adaptive) • A2RMA — Adaptive Autonomous Recursive MA Threshold Modes: • Static — Fixed threshold values you define (e.g., 0.025 annualised) • Dynamic — Adaptive bands: baseline ± (standard deviation × multiplier) • Percentile — Threshold at Nth percentile of recent history (e.g., 80th percentile for high) Visual Features: • Level-based colour gradient — Line colour shifts with percentile rank (warm = high vol, cool = low vol) • Fill to zero — Gradient fill intensity proportional to volatility level • Threshold fills — Intensity-scaled fills when thresholds are breached • Regime background — Chart background indicates HIGH/NORMAL/LOW volatility state • Legend table — Displays estimator names, parameters, current values with percentile ranks (P##) 💮 Dual Estimator Slots Compare two volatility estimators side-by-side. Each slot independently configures: • Estimator type (8 options across three scale groups) • Lookback period and smoothing filter • Colour palette and visual style This enables direct comparison between estimators (e.g., Yang-Zhang vs Rogers-Satchell) or between different parameterisations of the same estimator. ↑ Yang-Zhang (reddish) and Rogers-Satchell (greenish) 💮 Flexible Smoothing via FiltersToolkit All estimators (except Yang-Zhang, which uses internal rolling variance) support configurable smoothing through 10 filter types. Using Infinite Impulse Response (IIR) filters instead of SMA avoids the "drop-off artefact" where volatility readings crash when old spikes exit the window. Example: Same estimator (Parkinson) with different smoothing filters Add two instances of Volatility Toolkit to your chart: • Instance 1: Parkinson with SMA smoothing (lookback 14) • Instance 2: Parkinson with Super Smoother 2-Pole (lookback 14) Notice how SMA creates sharp drops when volatile bars exit the window, while Super Smoother maintains a gradual transition. ↑ Two Parkinson estimators — SMA (red mono-colour, showing drop-off artefacts) vs Super Smoother (turquoise mono colour, with smooth transitions) ↑ Garman-Klass with BiQuad (orangy) and 2-pole SuperSmoother filters (greenish) 💮 Weighted Aggregation Combine multiple estimators into a single weighted average. The indicator automatically: • Validates scale compatibility (only same-scale estimators can be aggregated) • Normalises weights (so 2:1 means 67%:33%) • Displays clear warnings when scales differ Example: Robust volatility estimate Combine Yang-Zhang (handles gaps) with Rogers-Satchell (handles drift) using equal weights: • E1: Yang-Zhang (14) • E2: Rogers-Satchell (14) • Aggregation: Enabled, weights 1:1 The aggregated line (with "fill to zero" enabled) provides a more robust estimate by averaging two complementary methodologies. ↑ Yang-Zhang + Rogers-Satchell with aggregation line (thicker) showing combined estimate (notice how opening gaps are handled differently) Example: Trend-weighted aggregation In strongly trending markets, weight Rogers-Satchell more heavily since it's drift-independent: • Estimator 1: Garman-Klass (faster, higher weight in ranging) • Estimator 2: Rogers-Satchell (drift-independent, higher weight in trends) • Aggregation: weights 1:2 (favours RS during trends) 💮 Adaptive Threshold Detection Three threshold modes for identifying volatility regime shifts. Threshold breaches are visualised with intensity-scaled fills that grow stronger the further volatility exceeds the threshold. Example: Dynamic thresholds for regime detection Configure dynamic thresholds to automatically adapt to market conditions: • High Threshold Mode: Dynamic (baseline + 2× std dev) • Low Threshold Mode: Dynamic (baseline - 2× std dev) • Show threshold fills: Enabled This creates adaptive bands that widen during volatile periods and narrow during calm periods. Example: Percentile-based thresholds Use percentile mode for context-aware regime detection: • High Threshold Mode: Percentile (96th) • Low Threshold Mode: Percentile (4th) • Percentile Lookback: 500 This identifies when volatility enters the top/bottom 4% of its recent distribution. ↑ Different threshold settings, where the dynamic and percentile methods show adaptive bands that widen during volatile periods, with fill intensity varying by breach magnitude. Regime detection (see next) is enabled too. 💮 Regime Background Colouring Optional background colouring indicates the current volatility regime: • High Volatility — Warm/alert background colour • Normal — No background (neutral) • Low Volatility — Cool/calm background colour Select which source (Estimator 1, Estimator 2, or Aggregation) drives the regime display. Example: Regime filtering for trade decisions Use regime background to filter trading signals from other indicators: • Regime Source: Aggregation • Background Transparency: 90 (subtle) When the background shows HIGH volatility (warm), consider tighter stops. When LOW (cool), watch for breakout setups. ↑ Regime background emphasis for breakout strategies. Note the interesting A2RMA smoothing for this case. 🌸 --------- USAGE GUIDE --------- 🌸 💮 Getting Started 1. Add the indicator to your chart 2. Estimator 1 defaults to Yang-Zhang (14) — the most comprehensive estimator for gapped markets 3. Keep "Annualise Volatility" enabled to express values in standard annualised form 4. Observe the legend table for current values and percentile ranks (P##). Hover over the table cells to see a little more info in the tooltip. 💮 Choosing an Estimator • Trending equities with gaps — Yang-Zhang. Handles both drift and overnight gaps optimally. • Crypto (24/7 trading) — Rogers-Satchell. Drift-independent without Yang-Zhang's multi-period lag. • Ranging markets — Garman-Klass or Parkinson. Simpler, no drift adjustment needed. • Price-based stops — ATR. Output in price units, directly usable for stop distances. • Regime detection — Combine any estimator with threshold modes enabled. 💮 Interpreting Output • Value (P##) — The volatility reading with percentile rank. "0.1523 (P75)" means 0.1523 annualised volatility at the 75th percentile of recent history. • Colour gradient — Warmer colours = higher percentile (elevated volatility), cooler colours = lower percentile. • Threshold fills — Intensity indicates how far beyond the threshold the current reading is. • ⚠️ HIGH / 🔻 LOW — Table indicators when thresholds are breached. 🌸 --------- ALERTS --------- 🌸 💮 Direction Change Alerts • Estimator 1/2 direction change — Triggers when volatility inflects (rising to falling or vice versa) 💮 Cross Alerts • E1 crossed E2 — Triggers when the two estimator lines cross 💮 Threshold Alerts • E1/E2/Aggr High Volatility — Triggers when volatility breaches the high threshold • E1/E2/Aggr Low Volatility — Triggers when volatility falls below the low threshold 💮 Regime Change Alerts • E1/E2/Aggr Regime Change — Triggers when the volatility regime transitions (High ↔ Normal ↔ Low) 🌸 --------- LIMITATIONS --------- 🌸 • Drift bias in Parkinson/GK — These estimators overestimate variance in trending conditions. Switch to Rogers-Satchell or Yang-Zhang for trending markets. • Yang-Zhang minimum lookback — Requires at least 2 bars (enforced internally). Cannot produce instantaneous readings like other estimators. • Flat candles — Single-tick bars produce near-zero variance readings. Use higher timeframes for illiquid assets. • Discretisation bias — Estimates degrade when ticks-per-bar is very small. Consider higher timeframes for thinly traded instruments. • Scale mixing — Different scale groups (log-return, price unit, percentage) cannot be meaningfully compared or aggregated. The indicator warns but does not prevent display. 🌸 --------- CREDITS --------- 🌸 💮 Academic Sources • Parkinson, M. (1980). The Extreme Value Method for Estimating the Variance of the Rate of Return. Journal of Business, 53 (1), 61–65. DOI • Garman, M.B. & Klass, M.J. (1980). On the Estimation of Security Price Volatilities from Historical Data. Journal of Business, 53 (1), 67–78. DOI • Rogers, L.C.G. & Satchell, S.E. (1991). Estimating Variance from High, Low and Closing Prices. Annals of Applied Probability, 1 (4), 504–512. DOI • Yang, D. & Zhang, Q. (2000). Drift-Independent Volatility Estimation Based on High, Low, Open, and Close Prices. Journal of Business, 73 (3), 477–491. DOI • Wilder, J.W. (1978). New Concepts in Technical Trading Systems . Trend Research. 💮 Libraries Used • VolatilityToolkit Library — Range-based estimators, smoothing, and aggregation functions • FiltersToolkit Library — Advanced smoothing filters (Super Smoother, Ultimate Smoother, BiQuad, etc.) • ColourUtilities Library — Colour palette management and gradient calculations
Wskaźnik Pine Script®
od GoemonYae
Liquidation Bubbles [OmegaTools]🔴🟢 Liquidation Bubbles — Advanced Volume & Price Stress Detector Liquidation Bubbles is a professional-grade analytical tool designed to identify forced positioning events, stop-runs, and liquidation clusters by combining price displacement and volume imbalance into a single, statistically normalized framework. This indicator is not a repainting signal tool and not a simple volume spike detector. It is a contextual market stress mapper, built to highlight areas where one-sided positioning becomes unstable and the probability of forced order execution (liquidations, stops, margin calls) materially increases. --- ## 🔬 Core Concept Market liquidations do not occur randomly. They emerge when price deviates aggressively from its volume-weighted equilibrium while volume itself becomes abnormal. Liquidation Bubbles detects exactly this condition by: * Estimating a **dynamic equilibrium price** using an *inverted volume-weighted moving average* * Measuring **directional price stress** relative to that equilibrium * Measuring **volume stress** relative to its own adaptive baseline * Normalizing both into **Z-score–like metrics** * Highlighting only **statistically extreme, asymmetric events** The result is a clear visual map of stress points where market participants are most vulnerable. --- ⚙️ Methodology (How It Works) 1️⃣ Advanced Inverted VWMA (Equilibrium Engine) The script uses a custom Advanced VWMA, where: * High volume bars receive less weight * Low volume bars receive more weight This produces a **robust equilibrium level**, resistant to manipulation and volume bursts. This equilibrium is used for **both price and volume normalization**, creating a consistent statistical framework. --- 2️⃣ Price Stress (Directional) Price stress is calculated as: * The **maximum deviation** between high/low and equilibrium * Directionally signed (upside vs downside) * Normalized by its own historical volatility This allows the script to distinguish: * Aggressive upside exhaustion * Aggressive downside capitulation --- 3️⃣ Volume Stress Volume stress is measured as: * Deviation from volume equilibrium * Normalized by historical volume dispersion This filters out: * Normal high-volume sessions * Illiquid noise And isolates abnormal participation imbalance. --- 4️⃣ Liquidation Logic A liquidation event is flagged when: * Both price stress and volume stress exceed adaptive thresholds * The imbalance is directional and statistically extreme Optional Combined Score Mode allows aggregation of price & volume stress into a single composite metric for smoother signals. --- 🔵 Bubble System (Signal Hierarchy) The indicator plots **two tiers of bubbles**: 🟢🔴 Small Bubbles * Early warning stress points * Localized stop-runs * Micro-liquidations * Often precede reactions or short-term reversals 🟢🔴 Big Bubbles * Full liquidation clusters * Forced unwinds * High probability exhaustion zones * Frequently align with: * Intraday extremes * Range boundaries * Reversal pivots * Volatility expansions Bubble color: * **Green** → Downside liquidation (sell-side exhaustion) * **Red** → Upside liquidation (buy-side exhaustion) Bubble placement is **ATR-adjusted**, ensuring visual clarity without overlapping price. --- 🔄 Cross-Market Volume Analysis The script allows optional **external volume sourcing**, enabling: * Futures volume applied to CFDs * Index volume applied to ETFs * Spot volume applied to derivatives This is critical when: * Your traded instrument has unreliable volume * You want **institutional-grade confirmation** --- 🧠 How to Use Liquidation Bubbles This indicator is **not meant to be traded alone**. Best use cases: * 🔹 Confluence with support & resistance * 🔹 Contextual confirmation for reversals * 🔹 Identifying fake breakouts * 🔹 Liquidity sweep detection * 🔹 Risk management (avoid entering into liquidation zones) Ideal for: * Futures * Indices * Crypto * High-liquidity FX pairs * Intraday & swing trading --- 🎯 Who This Tool Is For Liquidation Bubbles is designed for: * Advanced discretionary traders * Order-flow & liquidity-based traders * Macro & index traders * Professionals seeking **context**, not signals If you want **where the market is fragile**, not just where price moved — this tool was built for you. --- 📌 Key Characteristics ✔ Non-repainting ✔ Statistically normalized ✔ Adaptive to volatility ✔ Works on all timeframes ✔ Futures & crypto ready ✔ No lagging indicators ✔ No moving average crosses --- Liquidation Bubbles does not predict the future. It shows you where the market is most likely to break. — OmegaTools
Wskaźnik Pine Script®
od OmegaTools
1
Volume-Weighted Hybrid Channel [Capitalize Labs]Volume-Weighted Hybrid Channel (VWHC) is a channel-only indicator designed to visualise mean and volatility structure using a blended framework. It combines a configurable mean engine (SuperSmoother, EMA, SMA, or RMA) with an anchored VWAP component, then builds a four-level band ladder around a hybrid mean using a hybrid width that blends a range engine (ATR or true range variants) with anchored, volume-weighted standard deviation. The result is a smooth, adaptive channel intended to help us contextualise price location and volatility expansion or contraction relative to the hybrid mean. The indicator supports Weekly or Session anchoring for the VWAP and sigma components, and includes optional transition smoothing after anchor resets to reduce visual stepping. Band levels are user-defined (with automatic ordering enforcement), and optional gradient fills can be enabled for clearer zone recognition. An optional Band Occupancy Table is included to show how frequently price closes inside each zone, either over a rolling lookback or since the most recent anchor reset. This table is informational only and does not generate signals. This script is an indicator, not a strategy. It does not place trades, generate alerts, or provide entry or exit instructions. Outputs depend on chart symbol, timeframe, and data quality, including volume availability. The channel is designed to be non-repainting in the sense that it uses confirmed bar data and does not use forward-looking logic; however, like all indicators, the current bar can update until it closes. Risk Warning This material is educational research only and does not constitute financial advice, investment recommendation, or a solicitation to buy or sell any instrument. Foreign exchange and CFDs are complex, leveraged products that carry a high risk of rapid losses; leverage amplifies both gains and losses, and you should not trade with funds you cannot afford to lose. Market conditions can change without notice, and news or illiquidity may cause gaps and slippage; stop-loss orders are not guaranteed. The analysis presented does not take into account your objectives, financial situation, or risk tolerance. Before acting, assess suitability in light of your circumstances and consider seeking advice from a licensed professional. Past performance and back-tested or hypothetical scenarios are not reliable indicators of future results, and no outcome or level mentioned here is assured. You are solely responsible for all trading decisions, including position sizing and risk management. No external links, promotions, or contact details are provided, in line with TradingView House Rules. Disclaimer Use of this indicator is at our own discretion and risk. It is a visual analysis tool and should be validated through independent testing and a documented trading plan before being used in live decision-making.
Wskaźnik Pine Script®
od CapitalizeLabs