Impulsive Trend Detector [dtAlgo]This advanced Pine Script indicator identifies and tracks impulsive price movements based on Break of Structure (BOS) and Change of Character (CHoCH) concepts from Smart Money trading methodology.
The indicator automatically detects pivot highs and lows, then monitors when price breaks these key levels to signal potential impulsive moves. BOS indicates continuation in the current trend direction, while CHoCH signals potential trend reversals. Each detected move is measured from the break point to the next opposing pivot, providing accurate percentage calculations that match TradingView's measuring tool.
Impulsive moves are categorized into four levels based on magnitude (Level 1: 5-10%, Level 2: 10-15%, Level 3: 15-20%, Level 4: 20%+), with color-coded visual labels and connecting lines displayed directly on the chart.
Comprehensive Session Analysis:
Track moves across 11 distinct trading sessions in Eastern Time: Pre-London/NY, London/NY overlap, NY (with Power Hour and End subdivisions), Sydney, Asia, Sake Time, Asia/London overlap, London, Weekend, and No Session periods.
Three Dynamic Tables provide:
Real-time statistics (bullish/bearish, BOS/CHoCH, levels)
Session breakdown with move counts and average percentages
Event log showing last 10 moves with date, day, session, direction, type, level, percentage, duration, and bar count
Perfect for Smart Money traders seeking data-driven insights into market structure behavior across global trading sessions.
Trend Analizi
TwinSmooth ATR Bands | QuantEdgeBTwinSmooth ATR Bands | QuantEdgeB
🔍 Overview
TwinSmooth ATR Bands | QuantEdgeB is a dual-smoothing, ATR-adaptive trend filter that blends two complementary smoothing engines into a single baseline, then builds dynamic ATR bands around it to detect decisive breakouts. When price closes above the upper band it triggers a Long regime; when it closes below the lower band it flips to Short—otherwise it stays neutral. The script enhances clarity with regime-colored candles, an active-band fill, and an optional on-chart backtest table.
✨ Key Features
1. 🧠 Twin-Smooth Baseline (Dual Engine Blend)
- Computes two separate smoothed baselines (a slower “smooth” leg + a faster “responsive” leg).
- Blends them into a single midpoint baseline for balanced stability + speed.
- Applies an extra EMA smoothing pass to produce a clean trend_base.
2. 📏 ATR Volatility Bands
- Builds upper/lower bands using ATR × multiplier around the trend_base.
- Bands expand in volatile conditions and contract when markets quiet down—auto-adapting without manual tweaks.
3. ⚡ Clear Breakout Regime Logic
- Long when close > upperBand.
- Short when close < lowerBand.
- Neutral otherwise (no forced signals inside the band zone).
4. 🎨 Visual Clarity
- Plots only the active band (lower band in long regime, upper band in short regime).
- Fills between active band and price for instant regime context.
- Colors candles to match the current state (bullish / bearish / neutral).
- Multiple color palettes + transparency control.
💼 Use Cases
• Trend Confirmation Filter: Use the regime as a higher-confidence trend gate for entries from other indicators.
• Breakout/Breakdown Trigger: Trade closes outside ATR bands to catch momentum expansions.
• Volatility-Aware Stops/Targets: Bands naturally reflect volatility, making them useful as adaptive reference levels.
• Multi-Timeframe Alignment: Confirm higher-timeframe regime before executing on lower timeframes.
🎯 For Who
• Trend Traders who want clean regime shifts without constant whipsaw.
• Breakout Traders who prefer confirmation via ATR expansion rather than raw MA crossovers.
• System Builders needing a simple, robust “state engine” (Long / Short / Neutral) to plug into larger strategies.
• Analysts who want quick on-chart validation with a backtest table.
⚙️ Default Settings
• SMMA Length (Base Smooth Leg): 24
• TEMA Length (Base Responsive Leg): 8
• EMA Extra Smoothing: 14
• ATR Length: 14
• ATR Multiplier: 1.1
• Color Mode: Alpha
• Color Transparency: 30
• Backtest Table: On (toggleable)
• Backtest Start Date: 09 Oct 2017
• Labels: Off by default
📌 Conclusion
TwinSmooth ATR Bands | QuantEdgeB merges a dual-speed smoothing core into a single trend baseline, then wraps it with ATR-based bands to deliver clean, volatility-adjusted breakout signals. With regime coloring, active-band plotting, and optional backtest stats, it’s a compact, readable tool for spotting momentum shifts and trend continuation across any market and timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Adaptive ML Trailing Stop [BOSWaves]Adaptive ML Trailing Stop – Regime-Aware Risk Control with KAMA Adaptation and Pattern-Based Intelligence
Overview
Adaptive ML Trailing Stop is a regime-sensitive trailing stop and risk control system that adjusts stop placement dynamically as market behavior shifts, using efficiency-based smoothing and pattern-informed biasing.
Instead of operating with fixed ATR offsets or rigid trailing rules, stop distance, responsiveness, and directional treatment are continuously recalculated using market efficiency, volatility conditions, and historical pattern resemblance.
This creates a live trailing structure that responds immediately to regime change - contracting during orderly directional movement, relaxing during rotational conditions, and applying probabilistic refinement when pattern confidence is present.
Price is therefore assessed relative to adaptive, condition-aware trailing boundaries rather than static stop levels.
Conceptual Framework
Adaptive ML Trailing Stop is founded on the idea that effective risk control depends on regime context rather than price location alone.
Conventional trailing mechanisms apply constant volatility multipliers, which often results in trend suppression or delayed exits. This framework replaces static logic with adaptive behavior shaped by efficiency state and observed historical outcomes.
Three core principles guide the design:
Stop distance should adjust in proportion to market efficiency.
Smoothing behavior must respond to regime changes.
Trailing logic benefits from probabilistic context instead of fixed rules.
This shifts trailing stops from rigid exit tools into adaptive, regime-responsive risk boundaries.
Theoretical Foundation
The indicator combines adaptive averaging techniques, volatility-based distance modeling, and similarity-weighted pattern analysis.
Kaufman’s Adaptive Moving Average (KAMA) is used to quantify directional efficiency, allowing smoothing intensity and stop behavior to scale with trend quality. Average True Range (ATR) defines the volatility reference, while a K-Nearest Neighbors (KNN) process evaluates historical price patterns to introduce directional weighting when appropriate.
Three internal systems operate in tandem:
KAMA Efficiency Engine : Evaluates directional efficiency to distinguish structured trends from range conditions and modulate smoothing and stop behavior.
Adaptive ATR Stop Engine : Expands or contracts ATR-derived stop distance based on efficiency, tightening during strong trends and widening in low-efficiency environments.
KNN Pattern Influence Layer : Applies distance-weighted historical pattern outcomes to subtly influence stop placement on both sides.
This design allows stop behavior to evolve with market context rather than reacting mechanically to price changes.
How It Works
Adaptive ML Trailing Stop evaluates price through a sequence of adaptive processes:
Efficiency-Based Regime Identification : KAMA efficiency determines whether conditions favor trend continuation or rotational movement, influencing stop sensitivity.
Volatility-Responsive Scaling : ATR-based stop distance adjusts automatically as efficiency rises or falls.
Pattern-Weighted Adjustment : KNN compares recent price sequences to historical analogs, applying confidence-based bias to stop positioning.
Adaptive Stop Smoothing : Long and short stop levels are smoothed using KAMA logic to maintain structural stability while remaining responsive.
Directional Trailing Enforcement : Stops advance only in the direction of the prevailing regime, preserving invalidation structure.
Gradient Distance Visualization : Gradient fills reflect the relative distance between price and the active stop.
Controlled Interaction Markers : Diamond markers highlight meaningful stop interactions, filtered through cooldown logic to reduce clustering.
Together, these elements form a continuously adapting trailing stop system rather than a fixed exit mechanism.
Interpretation
Adaptive ML Trailing Stop should be interpreted as a dynamic risk envelope:
Long Stop (Green) : Acts as the downside invalidation level during bullish regimes, tightening as efficiency improves.
Short Stop (Red) : Serves as the upside invalidation level during bearish regimes, adjusting width based on efficiency and volatility.
Trend State Changes : Regime flips occur only after confirmed stop breaches, filtering temporary price spikes.
Gradient Depth : Deeper gradient penetration indicates increased extension from the stop rather than imminent reversal.
Pattern Influence : KNN weighting affects stop behavior only when historical agreement is strong and remains neutral otherwise.
Distance, efficiency, and context outweigh isolated price interactions.
Signal Logic & Visual Cues
Adaptive ML Trailing Stop presents two primary visual signals:
Trend Transition Circles : Display when price crosses the opposing trailing stop, confirming a regime change rather than anticipating one.
Stop Interaction Diamonds : Indicate controlled contact with the active stop, subject to cooldown filtering to avoid excessive signals.
Alert generation is limited to confirmed trend transitions to maintain clarity.
Strategy Integration
Adaptive ML Trailing Stop fits within trend-following and risk-managed trading approaches:
Dynamic Risk Framing : Use adaptive stops as evolving invalidation levels instead of fixed exits.
Directional Alignment : Base execution on confirmed regime state rather than speculative reversals.
Efficiency-Based Tolerance : Allow greater price fluctuation during inefficient movement while enforcing tighter control during clean trends.
Pattern-Guided Refinement : Let KNN influence adjust sensitivity without overriding core structure.
Multi-Timeframe Context : Apply higher-timeframe efficiency states to inform lower-timeframe stop responsiveness.
Technical Implementation Details
Core Engine : KAMA-based efficiency measurement with adaptive smoothing
Volatility Model : ATR-derived stop distance scaled by regime
Machine Learning Layer : Distance-weighted KNN with confidence modulation
Visualization : Directional trailing stops with layered gradient fills
Signal Logic : Regime-based transitions and controlled interaction markers
Performance Profile : Optimized for real-time chart execution
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Tight adaptive trailing for short-term momentum control
15 - 60 min : Structured intraday trend supervision
4H - Daily : Higher-timeframe regime monitoring
Suggested Baseline Configuration:
KAMA Length : 20
Fast/Slow Periods : 15 / 50
ATR Period : 21
Base ATR Multiplier : 2.5
Adaptive Strength : 1.0
KNN Neighbors : 7
KNN Influence : 0.2
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive chop or overreaction : Increase KAMA Length, Slow Period, and ATR Period to reinforce regime filtering.
Stops feel overly permissive : Reduce the Base ATR Multiplier to tighten invalidation boundaries.
Frequent false regime shifts : Increase KNN Neighbors to demand stronger historical agreement.
Delayed adaptation : Decrease KAMA Length and Fast Period to improve responsiveness during regime change.
Adjustments should be incremental and evaluated over multiple market cycles rather than isolated sessions.
Performance Characteristics
High Effectiveness:
Markets exhibiting sustained directional efficiency
Instruments with recurring structural behavior
Trend-oriented, risk-managed strategies
Reduced Effectiveness:
Highly erratic or event-driven price action
Illiquid markets with unreliable volatility readings
Integration Guidelines
Confluence : Combine with BOSWaves structure or trend indicators
Discipline : Follow adaptive stop behavior rather than forcing exits
Risk Framing : Treat stops as adaptive boundaries, not forecasts
Regime Awareness : Always interpret stop behavior within efficiency context
Disclaimer
Adaptive ML Trailing Stop is a professional-grade adaptive risk and regime management tool. It does not forecast price movement and does not guarantee profitability. Results depend on market conditions, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates structure, volatility, and contextual risk management.
Volatility Regimes | GainzAlgo📊 OVERVIEW
This is a comprehensive ATR-based trading system designed for professional traders who need advanced volatility analysis, precise trade management, and intelligent market-regime detection.
The indicator combines multiple proven volatility concepts into one powerful, highly customizable tool.
⚙️ CORE FEATURES
1️⃣ ATR BANDS (Dynamic Support & Resistance)
- Three levels of ATR-based bands plotted around price
- Band 1 (1× ATR): Closest support/resistance, primary TP target
- Band 2 (2× ATR): Secondary TP target, stronger S/R zone
- Band 3 (3× ATR): Extended TP target, major S/R level
- Bands adapt to volatility in real time
- Dotted lines mark TP points on the latest candle
2️⃣ VOLATILITY REGIME DETECTION (Market Phase Analysis)
Automatically classifies the market into four distinct volatility regimes:
🟢 COMPRESSION
ATR < 70% of baseline
Low-volatility consolidation, market is coiling
Best for: Preparing breakouts, tightening stops
🟠 EXPANSION
ATR 115–140% of baseline
Volatility breakout, early trend formation
Best for: Breakout entries, momentum trades
🔴 HIGH VOLATILITY
ATR > 140% of baseline
Strong sustained trend, maximum participation
Best for: Trend following, trailing stops
🟣 EXHAUSTION
Declining ATR after high volatility
Trend maturity, potential pause or reversal
Best for: Profit taking, reducing exposure
Additional details:
- Uses ATR Ratio (Current ATR / Long-term Baseline)
- Non-repainting logic with historical confirmation
- Background shading + regime labels for instant clarity
- Diamond markers highlight regime changes
3️⃣ DYNAMIC STOP-LOSS SYSTEM
- Automatically calculates optimal stop distance using ATR
- Adapts to current market volatility
- Separate logic for bullish and bearish trades
- Default 2× ATR multiplier (adjustable 0.5× – 5×)
- Visual cross markers display stop levels
- Tighter stops in low volatility, wider in high volatility
4️⃣ MULTIPLE TAKE-PROFIT LEVELS (TP1 / TP2 / TP3)
- Three progressive profit targets for scaling out
- TP1 (1.5× ATR): First partial profit
- TP2 (2.5× ATR): Secondary scale-out
- TP3 (4.0× ATR): Final target or runner
- Dashed lines with labels on the current bar
- Automatically aligns with trend direction
- Fully customizable multipliers
5️⃣ SUPPORT & RESISTANCE LEVELS
- Dynamic S/R detection using price extremes
- ATR-weighted significance filtering
- Adjustable lookback period (10–100 bars)
- Circle markers for visual clarity
- Updates in real time as new highs/lows form
6️⃣ RISK MANAGEMENT CALCULATOR
- Real-time position-size calculation
- Based on account size, risk percentage, and ATR stop distance
- Formula: Position Size = Risk Amount ÷ Stop Distance
- Example: $10,000 account, 1% risk, $50 stop = 200 shares
- Displays position size and dollar risk directly on chart
- Ensures consistent risk across all trades
7️⃣ ATR PERCENTILE RANKING
- Shows where current ATR ranks historically (0–100%)
- Above 80%: Extremely high volatility
- 20–80%: Normal volatility
- Below 20%: Extremely low volatility
- Adjustable lookback (50–500 bars)
- Alerts trigger at above 90% and below 10% extremes
- Adds context to all regime-based decisions
8️⃣ VOLATILITY CONTRACTION PATTERN
- Detects tight consolidation (volatility squeeze)
- Requires consecutive bars of low ATR
- Default: 7 bars below 50% of average ATR
- Yellow triangle alert when pattern completes
- Often precedes strong breakout moves
- Works on all timeframes
9️⃣ TREND DETECTION SIGNALS
- Up and down arrows on trend change with rising ATR
- Combines price direction with volatility confirmation
- Smoothing filters reduce false signals
- Green arrow for bullish, red arrow for bearish
🔟 VOLATILITY BREAKOUT SIGNALS
- Circle markers when ATR exceeds threshold
- Default threshold: 1.5× ATR average
- Indicates surge in market activity
- Can signal the start of new trends
🧠 RECOMMENDED SETTINGS BY TRADING STYLE
Day Trading (1m–15m)
ATR Length: 14
Regime Baseline: 30
SL Multiplier: 1.5–2.0
TP: 1.5 / 2.5 / 4.0
Risk: 0.5–1%
Swing Trading (1H–4H)
ATR Length: 14
Regime Baseline: 50
SL Multiplier: 2.0–2.5
TP: 2.0 / 3.5 / 6.0
Risk: 1–2%
Position Trading (Daily)
ATR Length: 14–21
Regime Baseline: 100
SL Multiplier: 2.5–3.0
TP: 3.0 / 5.0 / 8.0
Risk: 2–3%
Scalping (15s–5m)
ATR Length: 10
Regime Baseline: 20
SL Multiplier: 1.0–1.5
TP: 1.0 / 1.5 / 2.5
Risk: 0.5–1%
🧭 HOW TO USE
1. Identify the current volatility regime
2. Wait for entry confirmation (breakouts, trend arrows, contraction patterns)
3. Set stop loss using dynamic ATR-based levels
4. Scale out at TP1, TP2, TP3 or use ATR bands
5. Use the risk calculator for consistent position sizing
6. Monitor regime changes and manage exposure accordingly
🚨 ALERT SYSTEM
Alerts included for volatility breakouts, trend changes, regime transitions, ATR band crosses, contraction pattern completion, and ATR percentile extremes.
All alerts are fully configurable in TradingView.
🎨 VISUAL GUIDE
Background colors: Volatility regimes
Solid lines: ATR bands
Dotted lines: Latest TP points
Dashed lines: Take-profit levels
Cross markers: Stop-loss levels
Circles: Support, resistance, and breakouts
Arrows: Trend direction
Diamonds: Regime changes
Triangles: Contraction alerts
Labels: Regime info, ATR percentile, position size
🛠️ CUSTOMIZATION
- Toggle any feature on or off
- Adjust all thresholds and multipliers
- Customize colors
- Configure alerts
- Set account size and risk parameters
⚠️ IMPORTANT NOTES
- This indicator provides analytical tools, not trading signals
- Always apply proper risk management
- Backtest before live use
- ATR adapts to volatility, not direction
If you find this indicator useful, please leave a rating and comment ⭐
SD-Range Oscillator | QuantEdgeBSD-Range Oscillator | QuantEdgeB
🔍 Overview
SD-Range Oscillator | QuantEdgeB (SDRO) is a normalized momentum oscillator that compresses a low-lag trend core into a 0–100 style range using standard-deviation (SD) bands. It builds a smooth baseline from a fast triple-smoothed average, wraps it with ±2×SD volatility bounds, then normalizes the core value inside that envelope. Clear Long/Short regimes trigger when the normalized value crosses user-defined thresholds, with optional labels, regime-colored candles, and intuitive filled zones.
✨ Key Features
1.⚡ Low-Lag Core (Triple-Smooth Engine)
- Uses a fast, low-lag triple-smoothed average as the oscillator’s primary signal input.
- Helps keep momentum readings responsive while filtering noise.
2. 📏 SD Volatility Envelope (±2×SD)
- Builds a volatility channel around a smoothed baseline using standard deviation.
- Automatically adapts to changing market turbulence.
3. 🧮 Normalized Range Output
- Converts the core signal into a normalized value by mapping it between the upper/lower SD bounds.
- Makes readings consistent across assets and timeframes.
4. 🎯 Threshold-Based Regimes
- Long when the normalized value exceeds the Long threshold.
- Short when it falls below the Short threshold.
- Includes an additional safety filter to reduce “forced” longs when price is already extended near the upper envelope.
5. 🎨 Visual Clarity & Zones
- Regime-colored oscillator line and candles.
- Filled SD bands around the baseline for quick volatility context.
- Optional highlight fills between the oscillator and thresholds to show active long/short phases.
- Extra OB/OS background zones for quick overextension awareness.
6. 🔔 Signals & Alerts
- Optional “Long/Short” labels on confirmed regime flips.
- Alert conditions fire on long/short regime crossovers.
💼 Use Cases
• Momentum Confirmation: Validate breakouts by requiring SDRO to hold above the Long threshold.
• Mean-Reversion Awareness: Watch for extreme normalized readings near upper/lower bounds.
• Regime Filtering: Use SDRO state (Long/Short/Neutral) to filter trades from other systems.
• Cross-Market Comparison: Normalization makes it easier to compare momentum across different tickers.
🎯 For Who
• Trend traders who want a clean momentum filter with adaptive volatility context.
• System builders needing a simple regime variable (1 / -1 / neutral) to gate entries.
• Discretionary traders who like visual confirmation (fills, candle coloring, threshold zones).
• Multi-asset traders who benefit from normalized, comparable oscillator readings.
⚙️ Default Settings
• TEMA Period: 7
• Base Length (SMMA): 25
• Long Threshold: 55
• Short Threshold: 45
• SD Multiplier: 2× (fixed in code)
• Color Mode: Alpha
• Color Transparency: 60
• Labels: Off by default
📌 Conclusion
SD-Range Oscillator | QuantEdgeB blends a low-lag triple-smoothed core with an adaptive SD envelope to produce a normalized, easy-to-read momentum signal. With clear threshold regimes, volatility-aware context, and strong visuals (fills + candle coloring), SDRO helps separate meaningful momentum shifts from noise across any asset or timeframe.
🔹 Disclaimer: Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Kalman Hull Kijun [BackQuant]Kalman Hull Kijun
A trend baseline that merges three ideas into one clean overlay, Kalman filtering for noise control, Hull-style responsiveness, and a Kijun-like Donchian midline for structure and bias.
Context and lineage
This indicator sits in the same family as two related scripts:
Kalman Price Filter
This is the foundational building block. It introduces the Kalman filter concept, a state-estimation algorithm designed to infer an underlying “true” signal from noisy measurements, originally used in aerospace guidance and later adopted across robotics, economics, and markets.
Kalman Hull Supertrend
This is the original script made, which people loved. So it inspired me to create this one.
Kalman Hull Kijun uses the same core philosophy as the Supertrend variant, but instead of building a Supertrend band system, it produces a single structural baseline that behaves like a Kijun-style reference line.
What this indicator is trying to solve
Most trend baselines sit on a bad trade-off curve:
If you smooth hard, the line reacts late and misses turns.
If you react fast, the line whipsaws and tracks noise.
Kalman Hull Kijun is designed to land closer to the middle:
Cleaner than typical fast moving averages in chop.
More responsive than slow averages in directional phases.
More “structure aware” than pure averages because the baseline is range-derived (Kijun-like) after filtering.
Core idea in plain language
The plotted line is a Kijun-like baseline, but it is not built from raw candles directly.
High level flow:
Start with a chosen price stream (source input).
Reduce measurement noise using Kalman-style state estimation.
Add Hull-style responsiveness so the filtered stream stays usable for trend work.
Build a Kijun-like baseline by taking a Donchian midpoint of that filtered stream over the base period.
So the output is a single baseline that is intended to be:
Less jittery than a simple fast MA.
Less laggy than a slow MA.
More “range anchored” than standard smoothing lines.
How to read it
1) Trend and bias (the primary use)
Price above the baseline, bullish bias.
Price below the baseline, bearish bias.
Clean flips across the baseline are regime changes, especially when followed by a hold or retest.
2) Retests and dynamic structure
Treat the baseline like dynamic S/R rather than a signal generator:
In uptrends, pullbacks that respect the baseline can act as continuation context.
In downtrends, reclaim failures around the baseline can act as continuation context.
Repeated back-and-forth around the line usually means compression or chop, not clean trend.
3) Extension vs compression (using the fill)
The fill is meant to communicate “distance” and “pressure” visually:
Large separation between price and baseline suggests expansion.
Price compressing into the baseline suggests rebalancing and decision points.
Inputs and what they change
Kijun Base Period
Controls the structural memory of the baseline.
Higher values track broader swings and reduce flips.
Lower values track tighter swings and react faster.
Kalman Price Source
Defines what data the filter is estimating.
Close is usually the cleanest default.
HL2 often “feels” smoother as an average price.
High/Low sources can become more reactive and less stable depending on the market.
Measurement Noise
Think of this as the main smoothness knob:
Higher values generally produce a calmer filtered stream.
Lower values generally produce a faster, more reactive stream.
Process Noise
Think of this as adaptability:
Higher values adapt faster to changing conditions but can get twitchy.
Lower values adapt slower but stay stable.
Plotting and UI (what you see on chart)
1) Adaptive line coloring
Baseline turns bullish color when price is above it.
Baseline turns bearish color when price is below it.
This makes the state readable without extra panels.
2) Gradient “energy” fill
Bull fill appears between price and baseline when above.
Bear fill appears between price and baseline when below.
The goal is clarity on separation and control, not decoration.
3) Rim effect
A subtle band around price that only appears on the active side.
Helps highlight directional control without hiding candles.
4) Candle painting (optional)
Candles can be colored to match the current bias.
Useful for scanning many charts quickly.
Disable if you prefer raw candles.
Alerts
Long state alert when price is above the baseline.
Short state alert when price is below the baseline.
Best used as a bias or regime notification, not a standalone entry trigger.
Where it fits in a workflow
This is a context layer, it pairs well with:
Market structure tools, BOS/MSB, OBs, FVGs.
Momentum triggers that need a regime filter.
Mean reversion tools that need “do not fade trends” context.
Limitations
No baseline eliminates chop whipsaws, tuning only manages the trade-off.
Settings should not be copy pasted across assets without checking behavior.
This does not forecast, it estimates and smooths state, then expresses it as a structural baseline.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
If you use it in any trading workflow, do proper backtesting, forward testing, and risk management before any live execution.
Trend Stress Quant [MarkitTick]💡This indicator combines a liquidity-based stress model with a dynamic linear regression channel to identify potential market exhaustion points and assess trend quality. By merging volume impact analysis with statistical deviation, this tool aims to highlight moments where price action may be overextended relative to the underlying liquidity conditions.
● Originality and Utility
Standard volatility indicators often rely solely on price range (like Bollinger Bands). This script introduces a Stress Engine that normalizes the relationship between Price Range (True Range) and Volume. This helps distinguish between healthy price movements and liquidity-stress events (illiquidity). Furthermore, instead of using a fixed-length channel, this tool offers a Dynamic Mode that anchors the regression channel to recent pivot points, ensuring the statistical analysis aligns with the current market structure rather than an arbitrary timeframe.
● Methodology
The script operates on two distinct mathematical models:
• Illiquidity Stress Engine
The core formula calculates a raw illiquidity metric based on the log-normal distribution of the ratio between True Range and Volume. A Z-Score (standard score) is then derived from this data over a specific lookback period. High Z-Scores indicate that price is moving disproportionately fast relative to the available volume, often a signature of panic selling or euphoric buying (exhaustion).
• Linear Regression Channel
The script calculates an Ordinary Least Squares (OLS) regression line (the line of best fit) to determine the mean price trend.
Standard Deviation Bands are plotted parallel to this mean.
Pearson Correlation Coefficient (R) is calculated to quantify the strength of the linear trend. Values closer to 1 or -1 indicate a strong trend, while values near 0 indicate a chaotic or ranging market.
📑 How to Use
Traders can utilize the visual outputs for mean reversion or trend continuation context:
• Exhaustion Signals (SE / BE Labels)
SE (Seller Exhaustion): Appears when the market is in a downtrend, but the Stress Engine detects a statistical anomaly (High Z-Score) on a down candle. This suggests panic selling may be peaking.
BE (Buyer Exhaustion): Appears when the market is in an uptrend, but the Stress Engine detects high stress on an up candle, suggesting a potential blow-off top.
• Regression Channel
The dashed middle line represents the fair value (mean) of the current trend.
The outer bands represent statistical extremes. Price interacting with the outer bands (default 2 Standard Deviations) while coincident with an Exhaustion Signal provides a high-confluence area of interest.
• Metrics Dashboard
A dashboard displays the current Trend Regime, Exhaustion Status, and Channel Width (volatility percentage).
● Settings
• Exhaustion Model
Trend Filter Length: Sets the baseline EMA to determine if the market is bullish or bearish.
Stress Threshold (Sigma): The Z-Score required to trigger an exhaustion signal (default is 2.0).
• Channel Configuration
Dynamic Pivot Mode: If enabled, automatically calculates the channel length based on recent pivots. If disabled, uses the Fixed Length.
Standard Deviations: Controls the width of the inner and outer channel bands.
📖This guide explains how to interpret and utilize signals for trading:
The script is designed primarily for Mean Reversion and Exhaustion trading strategies.
● The Core Strategy: Volatility Exhaustion
The script uses a "Stress Engine" to identify when price movement is statistically overextended relative to the available liquidity (Volume).
• Setup A: The "Seller Exhaustion" (Bullish Bounce)
Look for this setup during a downtrend to catch a temporary bottom or a reversal.
Trend Condition: The dashboard shows Bearish (Price is below the trend filter).
Trigger: The label SE (Seller Exhaustion) appears below a candle.
Why? This indicates that selling pressure was intense but likely panic-driven (High Z-Score/Stress) and may be drying up.
Confluence: Ideally, this signal appears when the price is touching or piercing the Lower Channel Band (dotted or solid lines).
Action: Traders often use this as a signal to close Short positions or enter a speculative Long (counter-trend) targeting the middle line.
• Setup B: The "Buyer Exhaustion" (Bearish Pullback)
Look for this setup during an uptrend to catch a local top.
Trend Condition: The dashboard shows Bullish .
Trigger: The label BE (Buyer Exhaustion) appears above a candle.
Why? This indicates euphoric buying on low liquidity or extreme volatility that is statistically unsustainable.
Confluence: Look for price rejection at the Upper Channel Band.
Action: Traders often use this to close Long positions or enter a Short targeting the mean.
● The Filter: Trend & Correlation
The script includes a Linear Regression Channel that quantifies the quality of the trend.
• Channel Slope
If the channel is angling steeply up or down, the trend is strong.
• Pearson R (Correlation)
The script calculates the Pearson R coefficient.
Weak Correlation: If the channel turns Gray/Neutral (or the fill becomes weak), it means the correlation is below the threshold (default 0.5).
Trading Rule: Avoid trading exhaustion signals when the channel is Gray/Neutral, as the market is likely chopping sideways with no clear direction.
● Risk Management & Targets
• Stop Loss
Since this is a volatility tool, a common technique is to place stops just outside the Outer Deviation Band (the widest line). If price expands beyond the outer band with no exhaustion signal, the trend may be entering a "runaway" phase.
• Take Profit
Target 1: The Middle Regression Line (The dashed center line). Prices tend to revert to this mean after an exhaustion event.
Target 2: The opposite channel band (e.g., if you bought at the bottom, hold until the top).
● Summary of Dashboard Metrics
The table on your chart provides a quick snapshot:
Trend Regime: Tells you if you should fundamentally look for Shorts (Bearish) or Longs (Bullish).
Seller/Buyer Status: Alerts you if the current bar is EXHAUSTED or Normal .
Channel Width %: Indicates volatility. If the width is very low (percentage is small), a breakout might be imminent (squeezing). If high, be careful of chop.
⚙️ Indicator settings
• Signal Parameters
Exhaustion & Stress Model: Controls signal sensitivity.
Trend Filter: Decides if the market is Bullish or Bearish.
Stress Threshold (Sigma): Higher values (e.g., 2.5) make the script stricter, showing fewer but potentially stronger signals.
• Channel Configuration
Dynamic Pivot Mode: If ON, the channel length auto-adjusts to recent market pivots. If OFF, it uses the Fixed Length you set.
Channel Bands: Adjusts the channel width.
Outer Deviation: The boundary for "extreme" moves. Price hitting this often signals a reversal.
• Quality Filter
Filter Weak Correlations: If enabled, the channel turns gray during choppy/sideways markets to warn you not to trust trend signals.
• Visuals
Display Options: Toggles the "Stats" dashboard and adjusts volatility coloring.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Box Theory [Interactive Zones] PyraTimeThis script combines Nicholas Darvas’s "Box Theory" with modern Supply and Demand (Premium/Discount) concepts. It automatically identifies the most recent Swing High and Swing Low to delineate the current trading range.
The purpose of this tool is to visualize market structure and help traders identify when price is relatively expensive (Premium) or cheap (Discount) within a defined range.
Visual Guide: What You Are Seeing
The Box: Represents the active trading range defined by the most recent significant Swing High and Swing Low.
Red Zone (Premium): The top 25% of the range. Mathematically, prices here are considered "expensive" relative to the current structure.
Green Zone (Discount): The bottom 25% of the range. Prices here are considered "cheap" relative to the current structure.
Grey Zone (Equilibrium): The middle 50% of the range. This is the area of fair value where price often consolidates.
Dashed Line (EQ): The exact 50% midpoint of the range.
Tutorial: How to Trade Using This Indicator
Method 1: Mean Reversion (Range Trading) This method applies when the market is moving sideways.
Identify Structure: Wait for a box to form.
Wait for Extremes: Do not trade when price is in the middle (Grey/White area). Wait for price to enter the Red or Green zones.
Entry Trigger:
Shorts: When price enters the Red Zone, look for a rejection (wicks leaving the zone) or a lower timeframe breakdown. Target the EQ (Midline) as your first take profit.
Longs: When price enters the Green Zone, look for support formation. Target the EQ (Midline) as your first take profit.
Method 2: Trend Continuation (Breakouts) This method applies when the market is trending strongly.
Breakout: Monitor the alerts. A close outside the box indicates a potential shift in market structure.
Retest: After a breakout up, the old "Red Zone" (Resistance) often flips to become new Support. Wait for price to pull back to the top of the old box before entering.
Configuration Guide (Settings)
Pivot Left/Right Bars (Sensitivity):
Default (20/20): Best for Swing Trading. It filters out market noise and only draws boxes based on major structural points.
Lower (5/5): Best for Scalping. It will create smaller, more frequent boxes but increases the risk of false signals.
Zone Percentage:
Default (25%): Standard deviation for Supply/Demand zones.
Alternative (15%): Use this for "sniping" entries at the absolute extremes of the range.
Multi-Timeframe (MTF):
Enable "Use Higher Timeframe" to see Daily or Weekly ranges while trading on lower timeframes (like the 15m or 1H). This helps keep your intraday trades aligned with the major trend.
Technical Note on "Lag" This indicator uses Pivots to draw the box. A pivot is only confirmed after a certain number of bars have passed (the "Pivot Right Bars" setting).
Example: If "Pivot Right Bars" is set to 20, the box will update 20 bars after the actual high or low occurred. This is necessary to confirm that the point was indeed a Swing High/Low. Do not treat the box lines as predictive; they are reactive to confirmed structure.
Single Candle Order Block (ICT) [Kodexius]Single Candle Order Block (ICT) is a chart-focused implementation of the ICT style Single Candle Order Block (SCOB) concept. It detects a strict 3 candle displacement pattern and projects the originating “order block candle” as a live zone that extends forward in time until price mitigates it.
The script is designed for practical trading workflows:
- It plots only the most recent active zones (user-defined limit) to keep charts readable.
- It supports optional multi-timeframe (MTF) detection, so you can project higher-timeframe SCOBs onto a lower-timeframe execution chart.
- It includes a mitigation engine (Close or Wick) to automatically invalidate and remove zones once they are decisively broken.
🔹 Features
🔸 ICT Single Candle Order Block Pattern Detection (Bull and Bear)
The indicator identifies a clean displacement sequence that implies a potential order block formed by the middle candle of a 3-candle structure.
Bullish SCOB: bearish candle at , bullish continuation at , then bullish displacement that closes above the prior candle’s high, with a sweep condition on the order block candle’s low.
Bearish SCOB: inverse structure requiring bearish displacement that closes below the prior candle’s low, with a sweep condition on the order block candle’s high.
The plotted zone boundaries are derived from the order block candle:
Top = high
Bottom = low
🔸 Multi-Timeframe Detection (Optional)
The script can compute SCOBs on a selected timeframe and display them on the current chart using request.security. This is ideal for mapping higher-timeframe order blocks onto lower-timeframe execution charts.
If the timeframe input is left empty, detection runs on the chart timeframe.
🔸 Volatility Filter (Optional)
When enabled, detections are filtered by volatility regime:
A SCOB is only displayed if ATR(14) > SMA(ATR(14), 200)
This helps reduce signals during compressed, low-range conditions where displacement patterns are often less meaningful.
🔸 Overlap Control (De-Cluttering)
Before a new zone is added, the script checks for overlap against existing zones of the same direction. If the new zone intersects an existing one, it is ignored. This reduces redundant stacking of zones in the same price area.
🔸 Mean Threshold (50%) Midline (Optional)
Each active SCOB is drawn as a semi-transparent box with:
Direction label text (Bu-SCOB / Be-SCOB)
Optional midpoint line at 50% of the zone height (Mean Threshold)
🔸 Automatic Zone Extension and Object Management
Zones extend forward on each bar to remain visible until mitigation. The script also manages object count and chart cleanliness by:
Keeping internal arrays for bull and bear zones
Removing older stored zones if internal history grows too large
Displaying only the most recent “Active SCOB Limit” zones while hiding older ones
🔸 Alerts
Alerts are provided for newly confirmed detections:
Bullish SCOB Detected
Bearish SCOB Detected
Duplicate prints are prevented by tracking the last detected zone time for each direction.
🔹 Calculations
1) Volatility Regime Check (ATR vs ATR SMA)
float myAtr = ta.atr(14)
float atrSma = ta.sma(myAtr, 200)
bool isVolatile = myAtr > atrSma
If the Volatility Filter is enabled, the script requires isVolatile to be true before creating a SCOB zone.
2) Bullish SCOB Detection Logic
bool isBull = open > close and close > open and close > open and low < low and close > high
Interpretation of the conditions:
open > close confirms the candle at is bearish.
close > open confirms the order block candle at is bullish.
close > open confirms current candle is bullish.
low < low indicates a relative sweep on the order block candle’s low.
close > high confirms displacement by closing above the order block candle’s high.
Zone bounds for a bullish SCOB come from candle :
[isBull, high , low , time , isBear, high , low , time , isVolatile]
3) Bearish SCOB Detection Logic
bool isBear = open < close and close < open and close < open and high > high and close < low
Interpretation of the conditions:
open < close confirms the candle at is bullish.
close < open confirms the order block candle at is bearish.
close < open confirms current candle is bearish.
high > high indicates a relative sweep on the order block candle’s high.
close < low confirms displacement by closing below the order block candle’s low.
Zone bounds for a bearish SCOB also come from candle :
[isBull, high , low , time , isBear, high , low , time , isVolatile]
4) Multi-Timeframe (MTF) Selection
The script runs the detection logic on the chosen timeframe and projects results onto the current chart:
=
request.security(syminfo.tickerid, i_tf, detectLogic())
It also prevents duplicate zone creation by checking the last processed detection time:
var int lastBullTime = 0
var int lastBearTime = 0
if mtf_isBull and mtf_bullTime != lastBullTime
lastBullTime := mtf_bullTime
if mtf_isBear and mtf_bearTime != lastBearTime
lastBearTime := mtf_bearTime
5) Overlap Validation
Before pushing a new zone, overlap is checked against existing zones:
if volPass and not bullArray.hasOverlap(mtf_bullTop, mtf_bullBot)
SCOB newScob = SCOB.new(top = mtf_bullTop, bottom = mtf_bullBot, barStart = mtf_bullTime, isBull = true)
bullArray.push(newScob)
if volPass and not bearArray.hasOverlap(mtf_bearTop, mtf_bearBot)
SCOB newScob = SCOB.new(top = mtf_bearTop, bottom = mtf_bearBot, barStart = mtf_bearTime, isBull = false)
bearArray.push(newScob)
6) Mitigation Logic (Close vs Wick)
Mitigation is evaluated every bar. Bullish zones mitigate below the bottom; bearish zones mitigate above the top:
method isMitigated(SCOB this, string style, float currentClose, float currentHigh, float currentLow) =>
bool mitigated = false
if this.isBull
float price = style == "Close" ? currentClose : currentLow
mitigated := (price < this.bottom)
else
float price = style == "Close" ? currentClose : currentHigh
mitigated := (price > this.top)
mitigated
tncylyv - Improved Delta Volume BubbleThis script is a specialized modification and structural upgrade of the excellent "Delta Volume Bubble " by tncylyv.
While the original tool provided a fantastic foundation for statistical volume analysis, this "Zero Float" Edition was built to solve specific visual challenges faced by active traders—specifically the issue of indicators "floating" or disconnecting from price when zooming in on lower timeframes.
The Straight Improvements
This version turns a "Signal Indicator" into a complete "Trading System" with five specific upgrades:
1. Visual Stability (The "Zero Float" Fix)
Original: Used complex coordinates that could desynchronize, causing bubbles to drift or float away from candles on fast charts (1m/5m).
My Upgrade: Implemented "Magnetic Anchoring." Labels and bubbles are now physically locked to the candle wicks. They never drift, overlap, or float, no matter how much you zoom or resize the chart.
2. Cognitive Load (The HUD)
Original: Displayed raw numbers inside colored circles, requiring you to memorize color codes.
My Upgrade: Replaced numbers with Semantic Text Labels (e.g., "ABSORB", "SQUEEZE", "MOMENTUM"). You can read the market intent instantly without decoding it.
3. Regime Adaptation (AI Engine)
Original: Used a fixed threshold (e.g., Z-Score > 2.0).
My Upgrade: Added an Adaptive Learning Window. The script scans recent volatility to automatically raise the threshold during choppy markets (filtering noise) and lower it during quiet sessions (catching subtle entries).
4. Market Memory (Smart Structure)
Original: Signals disappeared into history.
My Upgrade: Draws Support/Resistance Rails extending from major volume events. This helps you visualize exactly where institutions are defending their positions.
5. Robust Data Handling
My Upgrade: Added a Hybrid Fallback Engine. If granular 1-minute data isn't available (e.g., on historical charts), the script seamlessly switches to an estimation model so the indicator never "breaks" or disappears.
Core Logic
Z-Score Normalization: We don't look at raw volume; we look at statistical anomalies (Standard Deviations).
Absorption: Detects "Effort vs. Result"—high volume with tiny price movement (Trapped Traders).
Squeeze: Highlights areas where a breakout is imminent due to volatility compression.
Credits
Original Concept & Code: tncylyv (Delta Volume Bubble ). This script would not exist without his brilliant groundwork.
Modifications: Visual Anchoring, HUD Text System, AI Thresholding, and Structure Rails added in this edition.
This script is open-source to keep the spirit of the original author alive. Use it to understand the "Why" behind the move.
Commodity Pulse Matrix v3 [WavesUnchained]Overview
Multi-Timeframe Confluence Indicator for Commodities. Combines 6 scoring categories across multiple timeframes with advanced entry timing and risk management.
Key Features
6-Category Scoring System
• Flow: Money flow and volume pressure
• Momentum: RSI, CCI, Rate of Change
• Trend: ADX, EMA alignment, directional movement
• Volatility: ATR-based market conditions
• Structure: Price position relative to key MAs
• Divergence: Price/indicator divergence detection
Multi-Timeframe Analysis
• Automatic TF hierarchy based on chart timeframe
• Entry/Bias/Trend from different timeframes
• Consensus scoring across all active TFs
• HTF confirmation mode (non-repainting)
Entry Engine
• Breakout entries with momentum confirmation
• Pullback entries at support/resistance
• Continuation entries in trending markets
• Counter-trend filter (optional)
• Signal density: Few / Moderate / Many
Diamond Zones
• Pivot-based support/resistance detection
• ATR-padded zone boundaries
• Zone strength scoring
• Visual boxes on chart
Signal Quality Gate
• ATR filter: No trend signals in ranging markets
• Volume filter: No entries on low volume
• Mean-reversion allowed in range markets
Heat Score System
• Setup quality assessment (0-1 scale)
• MTF alignment component
• Signal strength component
• Confluence component
Exhaustion Detection
• RSI extreme zones
• Large range candles (ATR expansion)
• High volume spikes
• Rejection wicks
• Small body candles
Mean Reversion System
• WaveTrend-based signals
• Dynamic overbought/oversold zones
• JMA smoothing for reduced lag
• Signal cooldown management
Risk Management
• ATR-based stop-loss calculation
• Multi-target take-profit levels
• Regime-aware position sizing
• Risk quality grading
Visualization
Matrix Table
• 6 category scores per timeframe
• Total score with color coding
• Setup status and confluence
• Heat score and confidence level
• TF action recommendations
Chart Elements
• JMA gradient fill (trend visualization)
• Diamond zone boxes (S/R levels)
• Signal shapes (triangles)
• Volatility stop lines
• HTF midline
• Pivot labels (S/R markers)
Configuration
Timeframes
• Confirmed HTF bars only (prevents repainting)
• Chart TF priority weight
Entry Engine
• Enable/disable entry types (Breakout/Pullback/Continuation)
• Allow counter-trend entries
• Trend JMA settings
• Volatility stop multiplier
Signal Boost
• RSI extreme boost
• WaveTrend extreme boost
• Strength threshold
Take-Profit
• Modes: Simple / Smart / Conservative / Multi-Target
• ATR multipliers for each level
• Regime-adjusted targets
Visualization
• Matrix table position and mode
• JMA lines and gradient
• Diamond zone boxes
• Pivot labels
• Signal age display
• Bottom area indicator
Mean Reversion
• WaveTrend smoothing lengths
• Zone lookback and multiplier
• Signal cooldown
• Show zones/labels/exits
TradingView Alerts
• Entry Long/Short signals
• Strong/Moderate signal differentiation
• Webhook compatible
Recommended Usage
1. Select chart timeframe (15M-Daily recommended)
2. Watch matrix table for MTF confluence
3. Wait for signal shapes on chart
4. Confirm with Heat Score (>0.5 = quality setup)
5. Check Diamond Zones for S/R context
6. Use ATR-based SL/TP from risk management
Input Groups
• Timeframes: HTF confirmation, chart weight
• Entry Engine: Entry types, density, JMA settings
• Signal Boost: RSI/WT boost settings
• Signal Quality: ATR/Volume thresholds
• Technical: ATR length, SL multiplier
• Take-Profit: Mode, ATR multiples, regime adjustment
• Visualization: Matrix, JMA, zones, labels
• HTF Midline: Mode, resolution, color
• Mean Reversion: WaveTrend settings, zones
• Colors: Bull/bear color scheme
---
Educational purposes only. Not financial advice. Test thoroughly before live trading.
Harmonic Patterns [kingthies]Harmonic Patterns
This indicator scans price swings for classic X-A-B-C-D harmonic patterns and plots the structure plus a PRZ (Potential Reversal Zone) to help you frame areas where reactions are statistically more likely. It supports both bullish and bearish setups and can trigger alerts when a new D pivot confirms a pattern.
What it does
Builds a pivot-based swing map (ZigZag-style) using a configurable Pivot Length .
Evaluates the most recent 5 swing points (X, A, B, C, D) against harmonic ratio rules with a user-defined tolerance .
Detects: Gartley, Bat, Butterfly, Crab, Deep Crab, Cypher, Shark (loose) .
Draws the pattern legs (X-A-B-C-D), labels the detection with ratio readouts, and projects a PRZ using 3 target levels (derived from XA/BC logic per pattern).
Offers two rendering modes:
Best only : picks the closest match (lowest score) to reduce clutter.
Show all : plots every valid match (uses filled PRZ boxes to keep object usage under control).
PRZ (Potential Reversal Zone)
PRZ is built from three target levels and expanded into a zone.
Optional padding uses ATR (ATR multiplier) to widen/narrow the zone for volatility.
Display modes: Off, Box, Lines, Both .
Zones can be extended forward by a configurable number of bars to keep the area visible as price develops.
How to use
Start with Confirm only when D pivot forms enabled (recommended) to reduce false positives while patterns are still forming.
Adjust Pivot Length based on timeframe:
Lower values = more swings, more signals, more noise.
Higher values = cleaner structures, fewer signals.
Use Ratio Tolerance to control strictness:
Lower tolerance = fewer, higher-confidence matches.
Higher tolerance = more matches, potentially lower quality.
Treat harmonics as context , not a standalone entry system:
Look for confluence (HTF levels, structure, volume, momentum/RSI divergence, etc.).
Use your own confirmation and risk plan (invalidations beyond PRZ / beyond D).
Settings overview
Swings (Pivot ZigZag)
Pivot Length: pivot sensitivity.
Use Wicks: uses High/Low; if off, uses Close.
Max Stored Swings: limits stored pivots for performance/object control.
Harmonic Detection
Ratio Tolerance (%): allowed deviation around ideal ratios.
Confirm only when D pivot forms: reduces repaint-like behavior.
When multiple match: Best only vs Show all.
Pattern Filters enable/disable each pattern type.
PRZ
PRZ Display: Off / Box / Lines / Both.
PRZ Padding (ATR multiplier): volatility-adjusted zone padding.
PRZ Extend (bars): how far to project the zone.
Visuals
Draw Legs: draws X-A-B-C-D.
Show Pattern Label: prints pattern name, direction, ratios, and score.
Label Offset: shift label forward if you want more space.
Alerts
“Bullish/Bearish Harmonic (Any)” triggers on any detected pattern.
Per-pattern alerts are included for each supported pattern type.
Notes
This indicator is educational and intended to assist with pattern recognition and confluence mapping.
Harmonic patterns do not guarantee reversals—always manage risk and confirm with your own process.
Market Acceptance Zones [Interakktive]Market Acceptance Zones (MAZ) identifies statistical price acceptance — areas where the market reaches agreement and price rotates rather than trends.
Unlike traditional support/resistance tools, MAZ does not assume where price "should" react. Instead, it highlights regions where multiple internal conditions confirm balance: directional efficiency drops, effort approximately equals result, volatility contracts, and participation remains stable.
This is a market-state diagnostic tool, not a signal generator.
█ WHAT THE ZONES REPRESENT
MAZ (ATF) — Chart Timeframe Acceptance
A MAZ marks an area where price displayed rotational behaviour and the auction temporarily agreed on value. These zones often act as compression regions, fair-price areas, or boundaries of consolidation where impulsive follow-through is less likely.
Use ATF MAZs to:
- Identify rotational environments
- Avoid chasing price inside balance
- Frame consolidation prior to expansion
MAZ • HTF / MAZ • 2/3 — Multi-Timeframe Acceptance (AMTF)
When Multi-Timeframe mode is enabled, MAZ evaluates acceptance on:
- The chart timeframe
- Two higher structural timeframes
If the minimum consensus threshold is met (default: 2 of 3), the zone is classified as AMTF. These zones represent stronger agreement and typically decay more slowly than single-timeframe acceptance.
AMTF zones are structurally stronger and are useful for:
- Higher-quality rotation areas
- Pullback framing within trends
- Context alignment across timeframes
H • MAZ — Historic Acceptance Zones
Historic MAZs represent older acceptance that has transitioned out of active relevance. These zones are hidden by default and can be enabled to provide long-term memory context.
█ AUTO MULTI-TIMEFRAME LOGIC
When MTF Mode is set to Auto, MAZ uses a deterministic structural mapping based on the current chart timeframe:
- 5m → 15m + 1H
- 15m → 1H + 4H
- 1H → 4H + 1D
- 4H → 1D + 1W
- 1D → 1W + 1M
This ensures consistent higher-timeframe context without manual configuration. Advanced users may switch to Manual mode to define custom timeframes.
█ ZONE LIFECYCLE
MAZ zones are dynamic and maintain an internal lifecycle:
- Active — Acceptance remains relevant
- Aging — Acceptance quality is degrading
- Historic — Retained only for memory context
Zones track price interaction and re-acceptance, which can stabilise or strengthen them. Weak or stale zones are automatically removed to keep the chart clean.
█ HOW TRADERS USE MAZ
MAZ is designed to provide structure, not entries.
Common applications include:
- Avoiding chop when price is inside acceptance
- Framing expansion after clean breaks from MAZ
- Identifying higher-quality rotational pullbacks (AMTF zones)
- Defining objective invalidation using zone boundaries
█ SETTINGS OVERVIEW
Market Acceptance Zones — Core
- Acceptance Lookback
- ATR Length
- Zone Frequency (Conservative / Balanced / Aggressive)
Market Acceptance Zones — Zones
- Maximum Zones
- Fade & Stale Bars
- Historic Zone Visibility (default OFF)
Market Acceptance Zones — Timeframes
- MTF Mode (Off / Auto / Manual)
- Manual Higher Timeframes
- Minimum Consensus Requirement
Market Acceptance Zones — Visuals
- Neon / Muted Theme
- Zone Labels & Consensus Detail
- Optional Midline Display
█ DISCLAIMER
This indicator is a market context and diagnostic tool only.
It does not generate trade signals, entries, or exits.
Past acceptance behaviour does not guarantee future price action.
Always combine with independent analysis and proper risk management.
Dragon Flow Arrows (LITE)🚀 DRAGON FLOW ARROWS | Smart Trend Engine + Clean Reversal Arrows
A lightweight but highly-optimized trend system designed for clean charts, powerful visual signals, and no-noise directional flow. Built for traders who want simplicity, clarity, and professional-level momentum-filtered signals without over-complication.
🔥 Dragon Channel (Clean 3-Line Ribbon)
A smooth adaptive channel formed from ATR + EMA, giving you structural trend zones without clutter.
✅ Dragon Flow Gradient
A horizontal, color-shifted flow:
🟢 Bull flow → green glow
🔴 Bear flow → red glow
Automatic blend based on trend direction
Smooth visual transitions (no vertical stripes)
✅ Momentum-Filtered Arrows
BUY/SELL arrows only print when:
Price breaks outside the Dragon Channel
Momentum confirms (RSI + MACD filters)
Trend flips → one clean arrow per direction
✅ Smart Header Panel
At the top of your chart:
📌 Trend: Uptrend / Downtrend / Neutral
⚡ Impulse Strength: Weak / Normal / Strong
📊 How to Use
Entry:
- BUY Setup
Price moving above baseline
Dragon Flow turns bullish (cyan side)
Arrow appears below channel
- SELL Setup
Price breaks below baseline
Dragon Flow turns bearish (magenta side)
Arrow pops above channel
Exit / Filter:
Opposite arrow
Flow color shift
Trend panel flips
Works on Forex, Crypto, Stocks, Indices — all timeframes (just adjust the channel length).
Happy trading!
Supply & Demand Zones (Volume-Based)📌 Supply & Demand Zones (Volume-Based) — Indicator Description
Overview
This indicator visually highlights potential supply and demand price zones using historical candle structure combined with relative volume behavior.The zones are intended to help users observe areas of increased market activity where price has previously reacted. This tool is designed for visual analysis only.
How the Zones Are Identified
Demand zones are highlighted when price shows a strong bullish reaction following a bearish candle.Supply zones are highlighted when price shows a strong bearish reaction following a bullish candle.Relative volume is used as context, not as a predictive input, to classify zones into higher or lower activity levels.Zones automatically invalidate when price structurally breaks them.
About the Percentage Display
The percentage shown on a zone represents normalized relative volume strength at the time the zone was formed.This value is not a probability, not a success rate, and not a performance metric.It should not be interpreted as a prediction or trading signal.Percentages are displayed only for active zones and are removed once a zone is invalidated.
How This Indicator Is Intended to Be Used
As a visual reference tool for identifying historical supply and demand areas.As a contextual overlay alongside other forms of technical analysis.To observe how price behaves when revisiting previously active zones.This indicator does not suggest trade direction, entry timing, or exit levels.
Important Notes & Limitations
All zones are derived from historical price and volume data.Market conditions change, and historical zones may lose relevance over time.No trading decisions should be made based solely on this indicator.Users are encouraged to apply their own analysis and risk management.
Disclaimer
This indicator is provided for educational and informational purposes only.It does not constitute trading, investment, or financial advice.The author assumes no responsibility for decisions made using this tool.
TICK.US Dashboard 5mIt's a very simple script, It displays the TICK.US Timeframe 5 mn on your template
IDAHL | QuantEdgeBIDAHL | QuantEdgeB
🔍 Overview
The IDAHL indicator builds adaptive, volatility-aware threshold bands from two separate ALMA lines—one smoothed from recent highs, the other from recent lows—then uses percentiles of those lines to define a dynamic “high/low” channel. Price crossing above or below that channel triggers clear long/short signals, with on-chart candle coloring, fills, optional labels and even a built-in backtest table.
✨ Key Features
• 📈 Dual ALMA Bands (with DEMA pre-smoothing)
o High ALMA: ALMA applied to DEMA-smoothed highs (high → DEMA(30) → ALMA).
o Low ALMA: ALMA applied to DEMA-smoothed lows (low → DEMA(30) → ALMA).
• 📊 Percentile Thresholds
o Computes a high threshold at the Xth percentile of the High ALMA over a lookback window.
o Computes a low threshold at the Yth percentile of the Low ALMA.
o Shifts each threshold forward by a small period to reduce repainting.
• ⚡ Dynamic Channel Logic
o When price closes above the high percentile line, the “final” threshold flips down to the low percentile line (and vice versa), creating an adaptive channel that only moves when the outer bound is violated.
o Inside the channel, the threshold holds its last value to avoid whipsaw.
• 🎨 Visual & Alerts
o Plots the two percentile lines and fills between them with a color that reflects the current regime (green for long, yellow for neutral, orange for short).
o Colors your candles to match the active signal.
o Optional “Long”/“Short” labels on confirmed flips.
o Alert conditions fire on each long/short crossover.
• 📊 On-Chart Backtest Metrics
o Toggle on a small performance table—complete with win-rate, net P/L, drawdown—from your chosen start date, without any extra code.
⚙️ How It Works
1. Adaptive Smoothing (ALMA)
o Uses ALMA (Arnaud Legoux Moving Average) for smooth, low-lag filtering. In this script, the inputs are additionally pre-smoothed with DEMA(30) to reduce noise before ALMA is applied—improving stability on highs/lows.
2. Percentile Lines
o The High ALMA series feeds a linear-interpolation percentile function to generate the upper bound; the Low ALMA produces the lower bound.
o These lines are offset by a small look-ahead (X bars) to reduce repaint behavior.
3. Channel Logic
o Breakout Flip: When the selected source (default: Close) closes above the upper bound, the active threshold “jumps” to the lower bound—locking in a new channel until price next crosses.
o Breakdown Flip: Conversely, a close below the lower bound flips the threshold to the upper bound.
4. Signal Generation
o Long while the source is above the current “final” threshold.
o Short while below.
o Neutral inside the channel before any flip.
5. Visualization & Alerts
o Dynamic fills between the two percentile lines change hue as the regime flips.
o Candles adopt the regime color.
o Optional pinned “Long”/“Short” labels at flip bars.
o Alerts on every signal crossover of the zero-based regime line.
6. Backtest Table
o From your chosen start date, a mini-table displays cumulative P/L, win rate and drawdown for this strategy—handy for quick in-chart validation.
🎯 Who Should Use It
• Breakout Traders hunting for adaptive channels that auto-recenter on new highs/lows.
• Volatility Traders who want thresholds that expand and contract with market turbulence.
• Trend-Chasers seeking a fresh take on high/low channels with built-in smoothing.
• Systematic Analysts who appreciate on-chart backtesting without leaving TradingView.
⚙️ Default Settings
• ALMA Length: 14
• Percentile Length: 35 bars
• Percentile Lookback Period (offset): 4 bars
• Upper Percentile: 92%
• Lower Percentile: 50%
• Threshold Source: Close
• Visuals: Candle coloring on, labels off by default, “Strategy” palette
• Backtest Table: on by default (toggleable)
• Start Date (Backtest): 09 Oct 2017
📌 Conclusion
IDAHL blends two smooth, low-lag ALMA filters (fed by DEMA-smoothed highs/lows) with percentile-based channel construction for a self-rewiring high/low envelope. It gives you robust breakout/breakdown signals, immediate visual context via colored fills and candles, optional labels, alerts, and even performance stats—everything you need to spot and confirm regime shifts in one compact script.
🔹 Disclaimer : Past performance is not indicative of future results. Always backtest and align settings with your risk tolerance and objectives before live trading.
🔹 Strategic Advice : Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
#BLTA - CARE 7891🔷 #BLTA - CARE 7891 is an overlay toolkit designed to support structured trading preparation and chart reading. It combines a manual Trade Box + Lot Size/Risk panel, session background highlights (NY time), confirmed Previous Day/Week High-Low levels, an Asian range liquidity box, a 1H ZigZag market-structure projection, and an imbalance map (FVG / OG / VI) with an optional dashboard.
This script is an indicator (not a strategy). It does not place orders and is intended for planning, risk visualization, and market context.
✅ Main Modules
1) 💸 Risk Module (Trade Box + Lot Calculation + Table)
A complete manual trade-planning tool:
Pick an Entry Point (EP) and Stop Loss (SL) directly on the chart using input.price(..., confirm=true).
Automatically calculates:
Cash at Risk
SL distance (pips) (Forex-aware)
Lot size based on your:
Account balance
Risk %
Units per lot
Account base currency (with conversion if needed)
Draws:
Risk box (EP ↔ SL)
Target box (RR-based TP)
Displays a clean table panel with the key values.
🔁 Re-confirm Mode (Wizard)
Use “Re-confirm Trade Box Points” to force a clean logical reset and re-pick EP/SL/time anchors:
Shows temporary EP/SL labels
Shows a small wizard table guiding you step-by-step
Turn it OFF to return to normal risk table + boxes
Tip: If your chart timeframe changes or you want a fresh selection, Re-confirm mode is the safest way to reset everything cleanly.
2) 🎨 Session Visualization (New York Time)
Highlights chart background for these windows:
Day Division (17:00–17:01 NY)
London (03:00–05:00 NY) + sub-windows
New York (08:00–10:30 NY) + sub-windows
Colors are fully configurable from inputs.
3) 📰 Confirmed PDH/PDL (Previous Days)
Optional module that plots confirmed Previous Day High (PDH) and Previous Day Low (PDL):
Trading day is defined as 17:00 → 17:00 NY
Lines start exactly at the candle where the high/low occurred
Lines extend forward and can freeze when price touches them
Configurable: days to keep, style, width, and “stop on hit”
4) 📅 Confirmed Weekly High/Low (Previous Weeks)
Optional module that plots confirmed Weekly High/Low:
Confirmation occurs at Sunday 17:00 NY (typical FX week boundary)
Lines begin at the candle where the weekly extremes formed
Extends forward and can freeze on touch
Configurable: weeks to keep, style, width, stop-on-hit
5) 🈵 Asian Range Liquidity Box
Draws a session box that tracks high/low and optional midline (50%):
Uses New York time
Dynamic updates while session is active
Optional mid label and configurable line style/width
6) 📈 Market Structure - ZigZag (1H projected)
A ZigZag structure engine calculated on 1H and projected onto any timeframe:
Configurable:
Length
Source type (High/Low or Open/Close)
Colors and width
Opacity when viewing non-1H charts
Optional live extension of the last leg
Includes safe cleanup when toggling OFF (no leftover objects)
7) 📊 Imbalance Detector (FVG / OG / VI) + Dashboard
Detects and draws:
Fair Value Gaps (FVG)
Opening Gaps (OG)
Volume Imbalances (VI)
Optional dashboard shows frequencies and fill rates.
Attribution / Credits
This module is inspired by / adapted from the public concept widely known as “Imbalance Detector” (LuxAlgo-style logic). This script is independently packaged and integrated as part of the toolkit with additional modules and custom structure.
⚙️ How to Use (Quick Steps)
Add the indicator to the chart (overlay).
Enable 💸 Risk Module if you want trade planning.
Go to Trade Box Location and pick:
Entry Point (EP)
Stop Loss (SL)
Time anchors for box edges
Adjust:
Account balance, risk %, units per lot, RR target
Enable additional modules as needed:
Session backgrounds
PDH/PDL
Weekly High/Low
Asian range box
ZigZag
Imbalances + dashboard
🔎 Notes & Limitations
This script is for visual planning and context, not trade execution.
Lot sizing is based on the selected EP/SL and your inputs; always double-check broker rules, symbol specifications, and contract size.
Object-heavy features (boxes/lines/tables) may increase load on lower-end devices or very small timeframes.
RS Rating Multi-Timeframe v2RS Rating Multi-Timeframe
A relative strength rating indicator modeled after IBD's proprietary RS Rating system. This indicator measures a stock's price performance relative to the S&P 500 (or any benchmark you choose) and converts it to a 1-99 rating scale.
How It Works
The indicator calculates weighted performance ratios across four timeframes:
40% weight: 63-day (3-month) performance
20% weight: 126-day (6-month) performance
20% weight: 189-day (9-month) performance
20% weight: 252-day (12-month) performance
This weighting emphasizes recent performance while still accounting for longer-term strength—the same methodology used by leading growth stock research services.
Rating Scale
90-99: Elite relative strength (top 10% of stocks)
80-89: Strong relative strength (top 20%)
50-79: Average performance
30-49: Below average
1-29: Weak relative strength (bottom 30%)
Features
Customizable benchmark index (default: S&P 500)
Optional moving average overlay (EMA or SMA)
Visual zones with color-coded backgrounds
Signal markers when RS crosses key thresholds (80 and 30)
Info table showing current rating, daily change, MA value, and raw score
Built-in alerts for threshold crossovers
Pine Screener Compatible
This indicator includes state-based plots specifically designed for TradingView's Pine Screener. You can screen watchlists for:
RS Above 90, 80, 70, or 50
RS Below 50 or 30
RS Above/Below its moving average
Custom thresholds using the raw RS Rating value
In the Pine Screener, select the "Screener RS Above 80" output and set it to "True" (or equals 1) to find all stocks currently above 80—not just those crossing on that bar.
Usage Tips
Growth investors typically look for stocks with RS Ratings above 80, indicating the stock is outperforming 80% of the market. Combining high RS Rating with other technical signals (breakouts, volume, moving averages) can help identify leading stocks.
Hurst-Optimized Adaptive Channel [Kodexius]Hurst-Optimized Adaptive Channel (HOAC) is a regime-aware channel indicator that continuously adapts its centerline and volatility bands based on the market’s current behavior. Instead of using a single fixed channel model, HOAC evaluates whether price action is behaving more like a trend-following environment or a mean-reverting environment, then automatically selects the most suitable channel structure.
At the core of the engine is a robust Hurst Exponent estimation using R/S (Rescaled Range) analysis. The Hurst value is smoothed and compared against user-defined thresholds to classify the market regime. In trending regimes, the script emphasizes stability by favoring a slower, smoother channel when it proves more accurate over time. In mean-reversion regimes, it deliberately prioritizes a faster model to react sooner to reversion opportunities, similar in spirit to how traders use Bollinger-style behavior.
The result is a clean, professional adaptive channel with inner and outer bands, dynamic gradient fills, and an optional mean-reversion signal layer. A minimalist dashboard summarizes the detected regime, the current Hurst reading, and which internal model is currently preferred.
🔹 Features
🔸 Robust Regime Detection via Hurst Exponent (R/S Analysis)
HOAC uses a robust Hurst Exponent estimate derived from log returns and Rescaled Range analysis. The Hurst value acts as a behavioral filter:
- H > Trend Start threshold suggests trend persistence and directional continuation.
- H < Mean Reversion threshold suggests anti-persistence and a higher likelihood of reverting toward a central value.
Values between thresholds are treated as Neutral, allowing the channel to remain adaptive without forcing a hard bias.
This regime framework is designed to make the channel selection context-aware rather than purely reactive to recent volatility.
🔸 Dual Channel Engine (Fast vs Slow Models)
Instead of relying on one fixed channel, HOAC computes two independent channel candidates:
Fast model: shorter WMA basis and standard deviation window, intended to respond quickly and fit more reactive environments.
Slow model: longer WMA basis and standard deviation window, intended to reduce noise and better represent sustained directional flow.
Each model produces:
- A midline (basis)
- Outer bands (wider deviation)
- Inner bands (tighter deviation)
This structure gives you a clear core zone and an outer envelope that better represents volatility expansion.
🔸 Rolling Optimization Memory (Model Selection by Error)
HOAC includes an internal optimization layer that continuously measures how well each model fits current price action. On every bar, each model’s absolute deviation from the basis is recorded into a rolling memory window. The script then compares total accumulated error between fast and slow models and prefers the one with lower recent error.
This approach does not attempt curve fitting on multiple parameters. It focuses on a simple, interpretable metric: “Which model has tracked price more accurately over the last X bars?”
Additionally:
If the regime is Mean Reversion, the script explicitly prioritizes the fast model, ensuring responsiveness when reversals matter most.
🔸 Optional Output Smoothing (User-Selectable)
The final selected channel can be smoothed using your choice of:
- SMA
- EMA
- HMA
- RMA
This affects the plotted midline and all band outputs, allowing you to tune visual stability and responsiveness without changing the underlying decision engine.
🔸 Premium Visualization Layer (Inner Core + Outer Fade)
HOAC uses a layered band design:
- Inner bands define the core equilibrium zone around the midline.
- Outer bands define an extended volatility envelope for extremes.
Gradient fills and line styling help separate the core from the extremes while staying visually clean. The midline includes a subtle glow effect for clarity.
🔸 Adaptive Bar Tinting Strength (Regime Intensity)
Bar coloring dynamically adjusts transparency based on how far the Hurst value is from 0.5. When market behavior is more decisively trending or mean-reverting, the tint becomes more pronounced. When behavior is closer to random, the tint becomes more subtle.
🔸 Mean-Reversion Signal Layer
Mean-reversion signals are enabled when the environment is not classified as Trending:
- Buy when price crosses back above the lower outer band
- Sell when price crosses back below the upper outer band
This is intentionally a “return to channel” logic rather than a breakout logic, aligning signals with mean-reversion behavior and avoiding signals in strongly trending regimes by default.
🔸 Minimalist Dashboard (HUD)
A compact table displays:
- Current regime classification
- Smoothed Hurst value
- Which model is currently preferred (Fast or Slow)
- Trend flow direction (based on midline slope)
🔹 Calculations
1) Robust Hurst Exponent (R/S Analysis)
The script estimates Hurst using a Rescaled Range approach on log returns. It builds a returns array, computes mean, cumulative deviation range (R), standard deviation (S), then converts RS into a Hurst exponent.
calc_robust_hurst(int length) =>
float r = math.log(close / close )
float returns = array.new_float(length)
for i = 0 to length - 1
array.set(returns, i, r )
float mean = array.avg(returns)
float cumDev = 0.0
float maxCD = -1.0e10
float minCD = 1.0e10
float sumSqDiff = 0.0
for i = 0 to length - 1
float val = array.get(returns, i)
sumSqDiff += math.pow(val - mean, 2)
cumDev += (val - mean)
if cumDev > maxCD
maxCD := cumDev
if cumDev < minCD
minCD := cumDev
float R = maxCD - minCD
float S = math.sqrt(sumSqDiff / length)
float RS = (S == 0) ? 0.0 : (R / S)
float hurst = (RS > 0) ? (math.log10(RS) / math.log10(length)) : 0.5
hurst
This design avoids simplistic proxies and attempts to reflect persistence (trend tendency) vs anti-persistence (mean reversion tendency) from the underlying return structure.
2) Hurst Smoothing
Raw Hurst values can be noisy, so the script applies EMA smoothing before regime decisions.
float rawHurst = calc_robust_hurst(i_hurstLen)
float hVal = ta.ema(rawHurst, i_smoothHurst)
This stabilized hVal is the value used across regime classification, dynamic visuals, and the HUD display.
3) Regime Classification
The smoothed Hurst reading is compared to user thresholds to label the environment.
string regime = "NEUTRAL"
if hVal > i_trendZone
regime := "TRENDING"
else if hVal < i_chopZone
regime := "MEAN REV"
Higher Hurst implies more persistence, so the indicator treats it as a trend environment.
Lower Hurst implies more mean-reverting behavior, so the indicator enables MR logic and emphasizes faster adaptation.
4) Dual Channel Models (Fast and Slow)
HOAC computes two candidate channel structures in parallel. Each model is a WMA basis with volatility envelopes derived from standard deviation. Inner and outer bands are created using different multipliers.
Fast model (more reactive):
float fastBasis = ta.wma(close, 20)
float fastDev = ta.stdev(close, 20)
ChannelObj fastM = ChannelObj.new(fastBasis, fastBasis + fastDev * 2.0, fastBasis - fastDev * 2.0, fastBasis + fastDev * 1.0, fastBasis - fastDev * 1.0, math.abs(close - fastBasis))
Slow model (more stable):
float slowBasis = ta.wma(close, 50)
float slowDev = ta.stdev(close, 50)
ChannelObj slowM = ChannelObj.new(slowBasis, slowBasis + slowDev * 2.5, slowBasis - slowDev * 2.5, slowBasis + slowDev * 1.25, slowBasis - slowDev * 1.25, math.abs(close - slowBasis))
Both models store their structure in a ChannelObj type, including the instantaneous tracking error (abs(close - basis)).
5) Rolling Error Memory and Model Preference
To decide which model fits current conditions better, the script stores recent errors into rolling arrays and compares cumulative error totals.
var float errFast = array.new_float()
var float errSlow = array.new_float()
update_error(float errArr, float error, int maxLen) =>
errArr.unshift(error)
if errArr.size() > maxLen
errArr.pop()
Each bar updates both error histories and computes which model has lower recent accumulated error.
update_error(errFast, fastM.error, i_optLookback)
update_error(errSlow, slowM.error, i_optLookback)
bool preferFast = errFast.sum() < errSlow.sum()
This is an interpretable optimization approach: it does not attempt to brute-force parameters, it simply prefers the model that has tracked price more closely over the last i_optLookback bars.
6) Winner Selection Logic (Regime-Aware Hybrid)
The final model selection uses both regime and rolling error performance.
ChannelObj winner = regime == "MEAN REV" ? fastM : (preferFast ? fastM : slowM)
rawMid := winner.mid
rawUp := winner.upper
rawDn := winner.lower
rawUpInner := winner.upper_inner
rawDnInner := winner.lower_inner
In Mean Reversion, the script forces the fast model to ensure responsiveness.
Otherwise, it selects the lowest-error model between fast and slow.
7) Optional Output Smoothing
After the winner is selected, the script optionally smooths the final channel outputs using the chosen moving average type.
smooth(float src, string type, int len) =>
switch type
"SMA" => ta.sma(src, len)
"EMA" => ta.ema(src, len)
"HMA" => ta.hma(src, len)
"RMA" => ta.rma(src, len)
=> src
float finalMid = i_enableSmooth ? smooth(rawMid, i_smoothType, i_smoothLen) : rawMid
float finalUp = i_enableSmooth ? smooth(rawUp, i_smoothType, i_smoothLen) : rawUp
float finalDn = i_enableSmooth ? smooth(rawDn, i_smoothType, i_smoothLen) : rawDn
float finalUpInner = i_enableSmooth ? smooth(rawUpInner, i_smoothType, i_smoothLen) : rawUpInner
float finalDnInner = i_enableSmooth ? smooth(rawDnInner, i_smoothType, i_smoothLen) : rawDnInner
This preserves decision integrity since smoothing happens after model selection, not before.
8) Dynamic Visual Intensity From Hurst
Transparency is derived from the distance of hVal to 0.5, so stronger behavioral regimes appear with clearer tints.
int dynTrans = int(math.max(20, math.min(80, 100 - (math.abs(hVal - 0.5) * 200))))
QuantLabs MASM Correlation TableThe Market is a graph. See the flows:
The QuantLabs MASM is not a standard correlation table. It is an Alpha-Grade Scanner architected to reveal the hidden "hydraulic" relationships between global macro assets in real-time.
Rebuilt from the ground up for Version 3, this engine pushes the absolute limits of the Pine Script™ runtime. It utilizes a proprietary Logarithmic Math Engine, Symmetric Compute Optimization, and a futuristic "Ghost Mode" interface to deliver a 15x15 real-time correlation matrix with zero lag.
Under the Hood: The Quant Architecture
We stripped away standard libraries to build a lean, high-performance engine designed for institutional-grade accuracy.
1. Alpha Math Engine (Logarithmic Returns) Most tools calculate correlation based on Price, which generates spurious signals (e.g., "Everything is correlated in a bull run").
The Solution: Our engine computes Logarithmic Returns (log(close/close )) by default. This measures the correlation of change (Velocity & Vector), not price levels.
The Result: A mathematically rigorous view of statistical relationships that filters out the noise of general market drift.
Dual-Core: Toggle seamlessly between "Alpha Mode" (Log Returns) for verified stats and "Visual Mode" (Price) for trend alignment.
Calculation Modes: Pearson (Standard), Euclidean (Distance), Cosine (Vector), Manhattan (Grid).
2. Symmetric Compute Optimization Calculating a 15x15 matrix requires evaluating 225 unique relationships per bar, which often crashes memory limits.
The Fix: The V3 Engine utilizes Symmetric Logic, recognizing that Correlation(A, B) == Correlation(B, A).
The Gain: By computing only the lower triangle of the matrix and mirroring pointers to the upper triangle, we reduced computational load by 50%, ensuring a lightning-fast data feed even on lower timeframes.
3. Context-Aware "Ghost Mode" The UI is designed for professional traders who need focus, not clutter.
Smart Detection: The matrix automatically detects your current chart's Ticker ID. If you are trading QQQ, the matrix will visually highlight the Nas100 row and column, making them opaque and bright while dimming the rest.
Dynamic Transparency: Irrelevant data ("Noise" < 0.3 correlation) fades into the background. Only significant "Alpha Signals" (> 0.7) glow with full Neon Saturation.
Key Features
Dominant Flow Scanner: The matrix scans all 105 unique pairs every tick and prints the #1 Strongest Correlation at the bottom of the pane (e.g., DOMINANT FLOW: Bitcoin ↔ Nas100 ).
Streak Counter: A "Stubbornness" metric that tracks how many consecutive days a strong correlation has persisted. Instantly identify if a move is a "flash event" or a "structural trend."
Neon Palette: Proprietary color mapping using Electric Blue (+1.0) for lockstep correlation and Deep Red (-1.0) for inverse hedging.
Usage Guide
Placement: Best viewed in a bottom pane (Footer).
Assets: Pre-loaded with the Essential 15 Macro Drivers (Indices, BTC, Gold, Oil, Rates, FX, Key Sectors). Fully editable via settings (Ticker|Name).
Reading the Grid:
🔵 Bright Blue: Assets moving in lockstep (Risk-On).
🔴 Bright Red: Assets moving perfectly opposite (Hedge/Risk-Off).
⚫ Faded/Black: No statistical relationship (Decoupled).
Key Improvements Made:
Formatting: Added clear bullet points and bolding to make it scannable.
Clarity: Clarified the "Logarithmic Returns" section to explain why it matters (Velocity vs. Price Levels).
Tone: Maintained the "high-tech/quant" vibe but removed slightly clunky phrases like "spurious signals" (unless you prefer that academic tone, in which case I left it in as it fits the persona).
Structure: Grouped the "Modes" under the Math Engine for better logic.
Created and designed by QuantLabs
Buying Opportunity Score V2.2Buying Opportunity Indicator V2.2
What This Indicator Does
This indicator identifies potential buying opportunities during market fear and pullbacks by combining multiple technical signals into a single composite score (0-100). Higher scores indicate more fear/oversold conditions are present simultaneously.
Why These Components?
Market bottoms typically occur when multiple fear signals align. This indicator combines five complementary measurements that each capture different aspects of market stress:
1. VIX Level (30 points) - Measures implied volatility/fear. VIX spikes during selloffs as traders buy protection. Thresholds based on historical percentiles (VIX 25+ is ~85th percentile historically).
2. Price Drawdown (30 points) - Distance from 52-week high. Larger drawdowns create better risk/reward for mean reversion entries. A 10%+ drawdown from highs historically presents better entry points than buying at all-time highs.
3. RSI 14 (12 points) - Classic momentum oscillator measuring oversold conditions. RSI below 30 indicates short-term selling exhaustion.
4. Bollinger Band Position (13 points) - Statistical measure of price extension. Price below the lower band (2 standard deviations) indicates statistically unusual weakness.
5. VIX Timing (15 points) - Bonus points when VIX is declining from a recent peak. This helps avoid catching falling knives by waiting for fear to subside.
How The Score Works
- Each component contributes points based on severity
- Components are weighted by predictive value from historical analysis
- Score of 70+ means multiple fear signals are present
- Score of 80+ means extreme fear across most components
How To Use
1. Apply to SPY, QQQ, or IWM on daily timeframe
2. Monitor the Current Score in the statistics table
3. Scores below 50 = normal conditions, no action needed
4. Scores 60-69 = elevated fear, monitor closely
5. Scores 70+ = consider entering long positions
6. Scores 80+ = strongest historical entry points
Important Limitations
- This is a research tool, not financial advice
- Past patterns may not repeat in the future
- Signals are infrequent (typically 2-4 per year reaching 70+)
- Works best on broad market ETFs; not validated for individual stocks
- Always use proper position sizing and risk management
- The indicator identifies conditions that have historically been favorable, but cannot predict future returns
Statistics Table
The table shows:
- Current Score with context message
- Chart Results: Rolling 1Y/3Y/5Y statistics from your loaded chart data
Alerts
Multiple alert options available for different score thresholds.
Open Source
Code is fully visible for review and educational purposes.
ICT ORB Killzones by MaxN (15 / 30m)Trading session open/close with first 15/30 min orbs
will just have to adjust time zones to your current time line
GMT +0
I use
Asia 23.00 - 06.00
London 07.00 - 16.00
New York 12.00 - 22.00
