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.
Analyse de la tendance
Pivot Levels [BigBeluga]🔵 OVERVIEW
The Pivot Levels indicator automatically detects and draws key market pivot levels across multiple sensitivity settings. Each pivot level represents a significant local high or low in price structure, acting as potential zones of support and resistance. Traders can visualize short-, medium-, and long-term pivot layers simultaneously, helping to identify where price may react, reverse, or break out.
🔵 CONCEPTS
Different pivot lengths provide multi-length sensitivity on the same timeframe — shorter lengths detect local micro-swings, while longer lengths capture broader swing structure within the current chart.
ATR-based color logic marks active, bullish, or bearish pivot zones dynamically.
Lines can extend to the right or both sides to track reactions over time.
🔵 FEATURES
Detects up to four custom pivot levels simultaneously.
Each pivot level has independent settings for length , style , and extension mode .
Auto-colors each pivot as support (green), resistance (orange), or active zone (blue).
Displays dual-width line layers: a solid base and a transparent overlay for visual depth.
Dynamic price labels show exact pivot levels for clarity.
Fully customizable line styles: dashed (--), solid (-), or dotted (..).
Extends lines to the right for future reaction tracking or both directions for structure alignment.
🔵 HOW TO USE
Enable or disable pivot levels (1–4) to control how many layers of structure you want visible.
Use shorter pivot lengths for intraday turning points and longer ones for macro structure.
Watch for multiple pivot lines clustering in the same region — these often mark strong reversal zones.
Observe color changes: green = support, orange = resistance, blue = active neutral zone.
Combine with price action or volume analysis to confirm reactions near major pivots.
🔵 CONCLUSION
The Pivot Levels indicator provides a clean, multi-layered visualization of market structure.
By tracking pivots of varying lengths, traders can easily identify overlapping support and resistance regions, gauge breakout strength, and align trades with the dominant structural zones visible across multiple time horizons.
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.
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.
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.
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.
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.
Smart Gap Concepts [MarkitTick]💡 This indicator automates the identification and classification of price gaps, commonly known as Fair Value Gaps (FVG) or Imbalances, by integrating market structure and volume analysis. Unlike standard gap detectors that simply highlight empty space on a chart, this script applies algorithmic filters to categorize gaps into three distinct phases of market movement: Breakaway, Runaway, and Exhaustion. This helps traders understand the potential context of a move rather than just seeing a support or resistance zone.
● Originality and Utility
The primary innovation of this tool is its dynamic classification system. It moves beyond visual detection by checking the "why" behind the gap. By referencing Swing Highs and Swing Lows (Market Structure) alongside Volume efficiency, it determines if a gap represents a breakout, a trend continuation, or a climatic end to a move. Additionally, the script features an automated mitigation tracking system that removes gaps from the chart once price has re-tested the midpoint, ensuring the visual workspace remains clean and relevant to current price action.
● Methodology
The script operates on a multi-stage logic engine:
• Gap Detection
It first identifies the core imbalance where the Low of the current bar does not overlap with the High of the bar two periods prior (for bullish gaps), ensuring the intervening candle represents a strong displacement.
• Structural Analysis (Breakaway Gaps)
The script monitors Pivot Highs and Lows. If a gap occurs simultaneously with a close beyond a key structural Pivot, it is classified as a "Breakaway Gap." This signals the potential start of a new trend.
• Volume and Time Analysis (Exhaustion Gaps)
To identify potential reversals, the script looks for "Trend Maturity." If a gap forms after a long duration since the last pivot and is accompanied by a volume spike (defined by the Volume Spike Multiplier), it is labeled as an "Exhaustion Gap."
• Continuation (Runaway Gaps)
If a gap is valid but meets neither the Breakaway nor Exhaustion criteria, it is considered a "Runaway Gap," typically found in the middle of an established trend.
• Dynamic Cleanup
The script tracks the midpoint of every active gap. If price creates a lower low (for bullish gaps) or higher high (for bearish gaps) beyond this midpoint, the gap is considered mitigated and is removed from the screen.
📖 How to Use
Traders can utilize the color-coded classifications to gauge market intent:
Breakaway (Default Blue): Watch these zones for potential trend initiations. These are often high-probability areas for a retest entry after a structure break.
Runaway (Default Orange): These indicate strong momentum. They can be used to trail stop-losses or add to winning positions, as price should ideally not close below these gaps in a healthy trend.
Exhaustion (Default Red): Be cautious when these appear. They suggest the current move is overextended and a reversal or complex pullback may be imminent.
• Exhaustion Gap : A Practical Case Study
• Breakaway Gap: A Practical Case Study
• Runaway Gap : A Practical Case Study
⚙️ Inputs and Settings
Min Gap Size (Points): Filters out insignificant gaps smaller than this threshold.
Structure Lookback: Defines the sensitivity of the Pivot detection (Swing High/Low).
Volume Avg Length & Multiplier: Determines what qualifies as a "Volume Spike" for exhaustion logic.
Trend Maturity: The minimum number of bars required to consider a trend "old" enough for an exhaustion signal.
Visual Settings: Custom colors for each gap type and box extension length.
● 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.
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.
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))))
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!
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.
Advanced Multi-Level S/R ZonesAdvanced Multi-Level S/R Zones: The Comprehensive Guide
1. Introduction: The Evolution of Support & Resistance:
Support and Resistance (S/R) is the backbone of technical analysis. However, traditional methods of drawing these levels are often plagued by subjectivity. Two traders looking at the same chart will often draw two different lines. Furthermore, standard indicators often treat every price point equally, ignoring the critical context of Volume and Time.
The Advanced Multi-Level S/R Zones script represents a paradigm shift. It moves away from subjective line drawing and toward Quantitative Zoning. By utilizing statistical measures of variability (Standard Deviation, MAD, IQR) combined with Volume-Weighting and Time-Decay algorithms, this tool identifies where price is mathematically most likely to react. It treats S/R not as thin lines, but as dynamic zones of probability.
2. Core Logic and Mathematical Foundation:
To understand how to use this tool optimally, one must understand the "engine" under the hood. The script operates on four distinct pillars of logic:
A. Session-Based Data Collection:
The script does not look at every single tick. Instead, it aggregates data into "Sessions" (daily bars by default logic). It extracts the High, Low, and Total Volume for every session within the user-defined lookback period. This filters out intraday noise and focuses on the macro structure of the market.
B. Adaptive Statistical Variability:
Most Bollinger Band-style indicators use Standard Deviation (StdDev) to measure width. However, StdDev is heavily influenced by outliers (extreme wicks). This script offers a sophisticated Adaptive Method-Skewness Detection: The script calculates the skewness of the price distribution. Adaptive Selection: If the data is highly skewed (lots of outliers, typical in Crypto), it switches to MAD (Median Absolute Deviation). MAD is robust and ignores outliers. If the data is moderately skewed, it uses IQR (Interquartile Range). If the data is normal (Gaussian), it uses StdDev.
Benefit: This ensures the zone widths are accurate regardless of whether you are trading a stable Forex pair or a volatile Altcoin.
C. The Weighting Engine (Volume + Time)
Not all price history is equal. This script assigns a "Weight Score" to every session based on two factors:
Volume Weighting: Sessions with massive volume (institutional activity) are given higher importance. A high formed on low volume is less significant than a high formed on peak volume.
Time Decay: Recent price action is more relevant than price action from 50 bars ago. The script applies a decay factor (default 0.85). This means a session from yesterday has 100% impact, while a session from 10 days ago has significantly less influence on the zone calculation.
D. Clustering Algorithm
Once the data is weighted, the script runs a clustering algorithm. It looks for price levels where multiple session Highs (for Resistance) or Lows (for Support) congregate.
It requires a minimum number of points to form a zone (User Input: minPoints).
It merges nearby levels based on the Cluster Separation Factor.
This results in "Primary," "Secondary," and "Tertiary" zones based on the strength and quantity of data points in that cluster.
3. Detailed Features and Inputs Breakdown:
Group 1: Main Settings
Lookback Sessions (Default: 10): Defines how far back the script looks for pivots. A higher number (e.g., 50) creates long-term structural zones. A lower number (e.g., 5) creates short-term scalping zones.
Variability Method (Adaptive): As described above, leave this on "Adaptive" for the best results across different assets.
Zone Width Multiplier (Default: 0.75): Controls the vertical thickness of the zones. Increase this to 1.0 or 1.5 for highly volatile assets to ensure you catch the wicks.
Minimum Points per Zone: The strictness filter. If set to 3, a price level must be hit 3 times within the lookback to generate a zone. Higher numbers = fewer, but stronger zones.
Group 2: Weighting
Volume-Weighted Zones: Crucial for identifying "Smart Money" levels. Keep this TRUE.
Time Decay: Ensures the zones update dynamically. If price moves away from a level for a long time, the zone will fade in significance.
ATR-Normalized Zone Width: This is a dynamic volatility filter. If TRUE, the zone width expands and contracts based on the Average True Range. This is vital for maintaining accuracy during market breakouts or crashes.
Group 3: Zone Strength & Scoring
The script calculates a "Score" (0-100%) for every zone based on:
-Point Count: More hits = higher score.
-Touches: How many times price wicked into the zone recently.
-Intact Status: Has the zone been broken?
-Weight: Volume/Time weight of the constituent points.
-Track Zone Touches: Looks back n bars to see how often price respected this level.
-Touch Threshold: The sensitivity for counting a "touch."
Group 4: Visuals & Display
Extend Bars: How far to the right the boxes are drawn.
Show Labels: Displays the Score, Tier (Primary/Secondary), and Status (Retesting).
Detect Pivot Zones (Overlap): This is a killer feature. It detects where a Support Zone overlaps with a Resistance Zone.
Significance: These are "Flip Zones" (Old Resistance becomes New Support). They are colored differently (Orange by default) and represent high-probability entry areas.
Group 5: Signals & Alerts
Entry Signals: Plots Buy/Sell labels when price rejects a zone.
Detect Break & Retest: specifically looks for the "Break -> Pullback -> Bounce" pattern, labeled as "RETEST BUY/SELL".
Proximity Alert: Triggers when price gets within x% of a zone.
4. Understanding the Visuals (Interpreting the Chart)
When you load the script, you will see several visual elements. Here is how to read them:
The Boxes (Zones)
Red Shades: Resistance Zones.
Dark Red (Solid Border): Primary Resistance. The strongest wall.
Lighter Red (Dashed Border): Secondary/Tertiary. Weaker, but still relevant.
Green Shades: Support Zones.
Dark Green (Solid Border): Primary Support. The strongest floor.
Orange Boxes: Pivot Zones. These are areas where price has historically reacted as both support and resistance. These are the "Line in the Sand" for trend direction.
The Labels & Emojis
The script assigns emojis to zone strength:
🔥 (Fire): Score > 80%. A massive level. Expect a strong reaction.
⭐ (Star): Score > 60%. A solid structural level.
✓ (Check): Score > 40%. A standard level.
"⟳ RETESTING": Appears when a zone was broken, and price is currently pulling back to test it from the other side.
The Dashboard (Top Right)
A statistics table provides a "Head-Up Display" for the asset:
High/Low σ (Sigma): The variability of the highs and lows. If High σ is much larger than Low σ, it implies the tops are erratic (wicks) while bottoms are clean (flat).
Method: Shows which statistical method the Adaptive engine selected (e.g., "MAD (auto)").
ATR: Current volatility value used for normalization.
5. Strategies for Optimum Output
To get the most out of this script, you should not just blindly follow the lines. Use these specific strategies:
Strategy A: The "Zone Fade" (Range Trading)
This works best in sideways markets.
Identify a Primary Support (Green) and Primary Resistance (Red).
Wait for price to enter the zone.
Look for the "SUPPORT BOUNCE" or "RESISTANCE REJECTION" signal label.
Entry: Enter against the zone (Buy at support, Sell at resistance).
Stop Loss: Place just outside the zone width. Because the zones are calculated using volatility stats, a break of the zone usually means the trade is invalid.
Strategy B: The "Pivot Flip" (Trend Following)
This is the highest probability setup in trending markets.
Look for an Orange Pivot Zone.
Wait for price to break through a Resistance Zone cleanly.
Wait for the price to return to that zone (which may now turn Orange or act as Support).
Look for the "RETEST BUY" label.
Logic: Old resistance becoming new support is a classic sign of trend continuation. The script automates the detection of this exact geometric phenomenon.
Strategy C: The Volatility Squeeze
Look at the Dashboard. Compare High σ and Low σ.
If the values are dropping rapidly or becoming very small, the zones will contract (become narrow).
Narrow zones indicate a "Squeeze" or compression in price.
Prepare for a violent breakout. Do not fade (trade against) narrow zones; look to trade the breakout.
6. Optimization & Customization Guide
Different markets require different settings. Here is how to tune the script:
For Crypto & Volatile Stocks (Tesla, Nvidia)
Method: Set to Adaptive (Mandatory, as these assets have "Fat Tails").
Multiplier: Increase to 1.0 - 1.25. Crypto wicks are deep; you need wider zones to avoid getting stopped out prematurely.
Lookback: 20-30 sessions. Crypto has a long memory; short lookbacks generate too much noise.
For Forex (EURUSD, GBPJPY)
Method: You can force StdDev or IQR. Forex is more mean-reverting and Gaussian.
Multiplier: Decrease to 0.5 - 0.75. Forex levels are often very precise to the pip.
Volume Weighting: You may turn this OFF for Forex if your broker's volume data is unreliable (since Forex has no centralized volume), though tick volume often works fine.
For Scalping (1m - 15m Timeframes)
Lookback: Decrease to 5-10. You only care about the immediate session history.
Decay Factor: Decrease to 0.5. You want the script to forget about yesterday's price action very quickly.
Touch Lookback: Decrease to 20 bars.
For Swing Trading (4H - Daily Timeframes)
Lookback: Increase to 50.
Decay Factor: Increase to 0.95. Structural levels from weeks ago are still highly relevant.
Min Points: Increase to 3 or 4. Only show levels that have been tested multiple times.
7. Advantages Over Standard Tools:
Feature Standard S/R Indicator, Advanced Multi-Level S/R Calculation, Uses simple Pivots or Fractals, Uses Statistical Distributions (MAD/IQR). Zone Width Arbitrary or Fixed Adaptive based on Volatility & ATR.
Context Ignores Volume Volume Weighted (Smart Money tracking).
Time Relevance Old levels = New levels Time Decay (Recency bias applied).
Overlaps Usually ignores overlaps Detects Pivot Zones (Res/Sup Flip).
Scoring None 0-100% Strength Score per zone.
8. Conclusion:
The Advanced Multi-Level S/R Zones script is not just a drawing tool; it is a statistical analysis engine. By accounting for the skewness of data, the volume behind the moves, and the decay of time, it provides a strictly objective roadmap of the market structure.
For the optimum output, combine the Pivot Zone identification with the Retest Signals. This aligns you with the underlying flow of order blocks and prevents trading against the statistical probabilities of the market.
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.
PyraTime FVG [Pro] | Smart Anchored Price ActionPyraTime FVG is a professional-grade institutional trading suite designed to declutter price action analysis. Unlike standard indicators that flood the chart with infinite zones, this tool uses a proprietary "Velcro" Anchoring Engine that physically snaps Fair Value Gaps (FVGs) and Order Blocks to the exact candle geometry.
This tool replaces 4 separate indicators (FVG, Market Structure, Order Blocks, and Trend Dashboard) with a single, performance-optimized Pine Script v6 script.
🎯 Key Features
1. The "Velcro" FVG Engine Most FVG indicators draw boxes that extend infinitely, making charts messy.
Smart Extension: Zones extend to the right but automatically "snap" and cut off the moment price mitigates (fills) them.
Precision Anchoring: Boxes are drawn from the exact wick/body limits of the originating candles—no floating pixels.
Mitigation Tracking: Mitigated zones are instantly dimmed and archived, keeping your chart clean for current price action.
2. Intelligent Structure Mapping (BOS & CHoCH) The script distinguishes between trend continuation and trend reversals:
BOS (Break of Structure): Marked with Dotted Lines. Signals that the current trend is healthy and continuing.
CHoCH (Change of Character): Marked with Solid Lines. Signals a potential major trend reversal (e.g., the first Lower Low after an uptrend).
3. Multi-Timeframe (MTF) Scanner A non-intrusive dashboard in the bottom-right corner scans the 1H, 4H, and Daily timeframes in real-time.
IN BULL GAP: Price is currently inside a Higher Timeframe Buying Zone.
IN BEAR GAP: Price is currently inside a Higher Timeframe Selling Zone.
CLEAR: No major HTF obstacles nearby.
📚 How to Trade With This Tool (Tutorial)
Step 1: Check the "Big Picture" Look at the MTF Scanner (Bottom Right).
If the 1H and 4H say "IN BEAR GAP" (Gold), you know the higher timeframe bias is Down. You should prioritize selling opportunities.
Step 2: Wait for Price to Visit a Zone On your current chart (e.g., 5m or 15m), wait for price to enter a Gold FVG (Resistance).
Note: The box will be bright gold. Once price touches it, the script will snap the box to that candle, confirming the test.
Step 3: Confirm with Structure Don't sell blindly. Wait for a CHoCH Label (Change of Character) to appear. This confirms that the short-term uptrend has broken and sellers are stepping in.
Step 4: Target the Opposing Zone Aim for the next unmitigated Teal FVG (Bullish Support) or Order Block below.
⚙️ Settings & Customization
Filter Small Gaps: Uses an ATR filter (default 0.5) to ignore insignificant noise. Increase to 1.0 for a cleaner "Swings Only" view.
Show Midpoint: Toggles a dotted 50% equilibrium line inside every active gap.
Visual Style: Fully customizable colors. Default scheme is PyraTime Desert Gold & Oasis Teal.
CCI Standard DeviationCCI Standard Deviation – Asymmetric Volatility-Adjusted Trend Filter (CCI SD)
The Commodity Channel Index (CCI), created by Donald Lambert in 1980, measures how far the typical price deviates from its statistical average to identify cyclical momentum and trend strength.
The standard formula is:
CCI = (Typical Price − SMA(Typical Price, n)) / (0.015 × Mean Deviation)
where Typical Price = (High + Low + Close)/3.
CCI is unbounded and centered around zero: sustained readings above zero indicate bullish momentum, below zero bearish. Classic interpretations often use zero-line crosses or fixed levels (±100, ±200, ±250), but these can be unreliable when CCI volatility changes across market regimes.
This indicator was developed to create a more disciplined trend-following tool that aligns with my core risk principle: “always protect to the downside.”
Starting from the standard CCI zero-line concept for trend direction, I experimented with standard deviation bands to make the oscillator volatility-adjusted. I then applied deliberate asymmetry: requiring the lower 1σ envelope (CCI − stdev) to cross above a positive threshold for bullish confirmation (high-probability entry only in robust trends), while exiting immediately on any raw CCI weakness below a negative threshold (quick downside protection). User inputs for both thresholds were added to allow fine-tuning and adaptability across different assets and timeframes.
An optional DEMA-smoothed version of the lower envelope provides additional clarity when desired.
Extreme zones
raw CCI ±240 and lower envelope > 200 or < –200 - are highlighted with background shading to flag rare acceleration or capitulation phases.
How it works
Standard CCI calculated on typical price (default length 38).
Rolling standard deviation of the CCI itself (default length 13) measures the oscillator’s recent volatility.
Lower envelope = CCI − stdev (dn).
Optional DEMA smoothing (default length 12) can be toggled.
Trend logic:
Bullish regime only when lower envelope
→ Long Threshold (default +10)
→ statistical proof of strength
Bearish/neutral immediately when raw CCI
→ Short Threshold (default –25)
→ fast downside protection
Origin and development
The indicator emerged from wanting a cleaner, more reliable CCI for trend direction. After testing volatility-adjusted versions, the asymmetric design proved superior:
it enters only high-conviction uptrends and exits rapidly on weakness, significantly reducing whipsaws while preserving trend capture.
Parameters were optimized through extensive backtests on major assets (BTC, ETH, SOL and many more Cryptos; Magnificent 7 stocks, QQQ, SPX, gold).
The defaults were selected for the best average Sortino ratio and lowest maximum drawdown across this broad universe, ensuring robustness and avoiding single-asset overfitting.
How to use it
Green triangle below bar
→ lower envelope crosses above Long Threshold
→ high-conviction bullish trend confirmed
→ enter or add to longs
Magenta triangle above bar
→ CCI crosses below Short Threshold
→ exit longs or go cash/short
While lower envelope remains above Long Threshold
→ hold bullish positions
Extreme background shading (dn >200 or CCI ±240)
→ rare high-attention zones (potential acceleration or exhaustion)
Recommended defaults
CCI length: 38
SD length: 13
Long threshold: +10
Short threshold: –25
Optional MA length: 12 (DEMA of lower envelope)
All visual elements (bar coloring, signals, background, smoothed line) are toggleable for personal preference.
This indicator is designed as a trend-strength and risk-management filter and is not intended as a standalone trading system.
Disclaimer:
This is not financial advice. Backtests are based on past results and are not indicative of future performance.
SMC Post-Analysis Lab [PhenLabs]📊 SMC Post-Analysis Lab
Version: PineScript™ v6
📌 Description
The SMC Post-Analysis Lab is a dedicated hindsight analysis tool built for traders who want to understand what really happened during any historical trading period. Unlike forward-looking indicators, this tool lets you scroll back through time and instantly receive algorithmic classification of market states using Smart Money Concepts methodology.
Whether you’re reviewing a losing trade, studying a successful session, or building your pattern recognition skills, this indicator provides immediate context. The expansion-aware algorithm processes price action within your selected window and outputs clear, actionable classifications ranging from Parabolic Expansion to Consolidation Inducements.
Stop relying on subjective post-trade analysis. Let the algorithm objectively tell you whether institutional players were accumulating, distributing, or running inducements during your trades.
🚀 Points of Innovation
First indicator specifically designed for SMC-based post-trade review rather than live signal generation
Dual-mode analysis system allowing both dynamic scrollback and precise date selection
Expansion-aware classification algorithm that weighs range position against net displacement
Real-time efficiency metrics calculating directional quality of price movement
Integrated visual FVG detection within the analysis window only
Interactive table with clickable date range adjustment via chart interface
🔧 Core Components
Pivot Detection Engine: Uses configurable pivot length to identify significant swing highs and lows for structure break detection
Window Calculator: Determines active analysis zone based on either bar offset or timestamp boundaries
Data Aggregator: Tracks window open, high, low, close and counts bullish/bearish structure break events
State Classification Algorithm: Applies hierarchical logic to determine market state from six possible classifications
Visual Renderer: Draws structure breaks, FVG boxes, and window highlighting within the active zone
🔥 Key Features
Sliding Window Mode: Use the Scroll Back slider to dynamically move your analysis zone backwards through history bar-by-bar
Date Range Mode: Select specific start and end timestamps for precise session or trade review
Six Market State Classifications: Parabolic Expansion (Bull/Bear), Bullish/Bearish Order Flow, Accumulation/Distribution Reversal, and Consolidation/Inducement
Range Position Percentile: See exactly where price closed relative to the window’s high-low range as a percentage
Bull/Bear Event Counter: Quantified count of structure breaks in each direction during the analysis period
Efficiency Calculation: Net move divided by total range reveals trending quality versus chop
🎨 Visualization
Blue Window Highlight: Active analysis zone is clearly marked with blue background shading on the chart
Structure Break Lines: Dashed lines appear at each bullish or bearish structure break within the window
FVG Boxes: Fair Value Gaps automatically render as semi-transparent boxes in bullish or bearish colors
Dashboard Table: Top-right positioned table displays State, Analysis description, and Metrics in real-time
Color-Coded States: Each classification uses distinct coloring for immediate visual recognition
Interactive Tip Row: Optional help text guides users on clicking the table to adjust date range
📖 Usage Guidelines
General Configuration
Analysis Mode: Default is Sliding Window. Choose Date Range for specific timestamp analysis.
Sliding Window Settings
Scroll Back (Bars): Default 0. Increase to move window backwards into history.
Window Width (Bars): Default 100. Range 20-50 for scalping, 100+ for swing analysis.
Date Range Settings
Start Date: Select the beginning timestamp for your analysis period.
End Date: Select the ending timestamp for your analysis period.
Visual Settings
Show Help Tip: Default true. Toggle to hide instructional row in dashboard.
Bullish Color: Default teal. Customize for bullish elements.
Bearish Color: Default red. Customize for bearish elements.
SMC Parameters
Pivot Length: Default 5. Lower values (3-5) catch minor breaks. Higher values (10+) focus on major swings.
✅ Best Use Cases
Post-trade review to understand why entries succeeded or failed
Session analysis to identify institutional activity patterns
Trade journaling with objective algorithmic classifications
Pattern recognition training through historical scrollback
Identifying whether stop hunts were inducements or legitimate breaks
Comparing your real-time read versus what the algorithm detected
⚠️ Limitations
Designed for historical analysis only, not live trade signals
Classification accuracy depends on appropriate pivot length for the timeframe
FVG detection uses simple gap logic without mitigation tracking
State classification is based on window data only, not broader context
Requires manual scrolling or date input to review different periods
💡 What Makes This Unique
Purpose-Built for Review: Unlike most indicators focused on live signals, this is designed specifically for post-trade analysis
Expansion-Aware Logic: Algorithm weighs both position in range AND directional efficiency for accurate state detection
Interactive Date Control: Click the dashboard table to reveal draggable anchors for window adjustment directly on chart
🔬 How It Works
1. Window Definition:
User selects either Sliding Window or Date Range mode
System calculates which bars fall within the active analysis zone
Active zone receives blue background highlighting
2. Data Collection:
Algorithm captures window open, running high, running low, and current close
Structure breaks are detected when price crosses above last pivot high or below last pivot low
Bullish and bearish events are counted separately
3. State Classification:
Range Position calculates where close sits as percentage of high-low range
Efficiency calculates net move divided by total range
Hierarchical logic applies priority rules from Parabolic states down to Consolidation
4. Output Rendering:
Dashboard table updates with State title, Analysis description, and Metrics
Visual elements render within window only to keep chart clean
Colors reflect bullish, bearish, or neutral classification
💡 Note:
This indicator is intended for educational and review purposes. Use it to develop your understanding of Smart Money Concepts by analyzing what institutional order flow looked like during historical periods. Combine insights with your own analysis methodology for best results.
Gaps IdentifierThis indicator identifies up and down Gaps using previous period's close price to the next period's open price. Potentially useful for Gap rebound strategies.
(Will identify gaps 4%–11% by default; can change in settings)
TICK.US Dashboard 5mIt's a very simple script, It displays the TICK.US Timeframe 5 mn on your template
Gemini Smart SMA Pro + Wyckoff V2 (Enhanced Cloud)The Smart SMA Pro + Wyckoff V2 is an advanced trend-following and market-cycle indicator built for traders who utilize Wyckoff Theory and Volume Spread Analysis (VSA). It is specifically designed to identify the transition from "Cause" (Squeeze/Accumulation) to "Effect" (Expansion/Markup).
By analyzing the volatility spread between two customizable Moving Averages and validating movements with relative volume, this tool helps traders stay out of sideways markets and enter only when high-conviction momentum is present.
Key Features
Wyckoff Phase Detection: Automatically detects Squeeze (Accumulation/Distribution) and Expansion (Markup/Markdown) phases.
Intelligent Dynamic Cloud: The cloud between the MAs changes its transparency dynamically based on the Volume Ratio and trend slope. Darker colors indicate high-volume trend confirmation.
Dual-Layered SOS/SOW Signals: * SOS (Sign of Strength): A Yellow Dot appears on a bullish squeeze breakout. A Yellow Arrow is added only if the move is validated by High Relative Volume.
SOW (Sign of Weakness): An Orange Dot appears on a bearish breakout, with an Orange Arrow appearing only if supported by high volume.
Live Multi-Data Dashboard: A real-time table displaying the status of Fast/Slow MAs, the current market cycle stage, and the Volume Ratio.
Professional Alerts: Built-in alerts for Sign of Strength (SOS) and Sign of Weakness (SOW) breakouts.
How to Trade with it
Grey Cloud (Squeeze): Market is building a "Cause." Avoid trading and prepare for a breakout.
Yellow Dot + Arrow: This is a Confirmed SOS. It indicates institutional participation and a high probability of a new Markup phase.
Buy/Sell Labels: Standard trend entries based on price crossing the Signal Line (Fast MA). Use these to join an already established trend.
Dashboard Monitoring: Check the "Vol. Ratio" to see if the current move has enough strength to sustain the expansion.
How this Indicator was Created
This project is the result of a cutting-edge collaborative development process between a human trader and Gemini (Google’s AI).
Logic Synthesis: We combined traditional technical analysis with AI-optimized algorithms to calculate the Volatility Ratio, ensuring the "Squeeze" detection is more accurate than standard Bollinger-based tools.
Conditional Visuals: The logic was refined through multiple iterations to create a "Smart Visual" system. For instance, the Volume-Validated Arrow was an architectural decision to separate minor breakouts from high-conviction institutional moves.
Code Optimization: The entire script was written in Pine Script® V6, ensuring maximum performance, low latency on charts, and a clean, responsive Dashboard interface using advanced table objects.
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The Partnership: This indicator represents the perfect synergy between human market intuition and AI’s computational precision, resulting in a tool that is both mathematically sound and visually intuitive for professional use.
#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.
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
