Hybrid Smart Money Concepts [MarkitTick]💡This indicator provides a comprehensive technical analysis system that combines Market Structure concepts (Smart Money Concepts) with advanced Gap Analysis and a statistical Stress Model. It is designed to help traders identify trend direction, structural pivot points, potential reversal zones (Order Blocks), significant price gaps, and moments of market exhaustion.
Unlike standard ZigZag or Fractal indicators, this script integrates volume, trend maturity, and statistical volatility (Z-Score) to contextually classify price action. By overlaying these elements with a robust Market Structure engine—which identifies Change of Character (CHoCH) and Order Blocks—the tool provides a confluent view of price action.
It automates the detection of institutional footprints, allowing traders to see the structural trend, momentum drivers, and potential exhaustion points simultaneously.
● METHODOLOGY
The script operates on three distinct but complementary logic engines:
• Gap Analysis Engine
This module detects gaps between the previous high/low and the current open. It classifies them into three specific types based on volume and structural context:
Breakaway Gaps: Identified when a gap creates a breakout above a recent Pivot High or below a Pivot Low. This signals the start of a potential new trend.
Exhaustion Gaps: Identified when a gap occurs with high relative volume and meets the Trend Maturity criteria. This often signals the end of a trend.
Runaway Gaps: Standard continuation gaps that occur within a trend.
• Market Structure Engine
Swings and CHoCH: The script uses a left-and-right bar lookback to identify Pivot Highs and Lows. A Change of Character (CHoCH) is plotted when price closes beyond the most recent major pivot.
Order Blocks (OB): Upon a continuation of the trend, the script scans backward to find the extreme candle (the origin of the move) and highlights this zone as an Order Block.
Dynamic Cleanup: Gaps and Order Blocks are automatically removed (mitigated) when price aggressively crosses through their levels.
• Exhaustion & Stress Model
This statistical engine measures market "Stress" by analyzing the impact of price range relative to volume (True Range / Volume).
Calculation: It calculates a Z-Score (Standard Deviation) of this impact.
Logic: When the Z-Score exceeds a specific threshold (Sigma), it indicates a statistical anomaly or "Stress."
Signal: If high stress occurs while price is significantly above the trend baseline, it signals "Buyer Exhaustion." Conversely, high stress below the baseline signals "Seller Exhaustion."
● VISUALS & LEGEND
Before trading, you need to know what the indicator is drawing on your chart:
• Change of Character (CHoCH)
Green Dashed Line: Indicates a Bullish reversal.
Red Dashed Line: Indicates a Bearish reversal.
• Order Blocks (OB)
Green Boxes: Bullish support zones (Buy interest).
Red Boxes: Bearish resistance zones (Sell interest).
Note: Invalidated boxes are automatically deleted.
• Gaps
Blue Box (Breakaway): Strong momentum gap starting a new trend.
Orange Box (Runaway): Continuation gap.
Red Box (Exhaustion): Warning signal; trend may be ending.
• Stress Model Signals
Label "BE" (Red): Buyer Exhaustion. Suggests the bullish move is overextended relative to volume participation.
Label "SE" (Green): Seller Exhaustion. Suggests the bearish move is overextended.
● TRADING STRATEGY
You can use a "Pullback, Continuation & Exhaustion" strategy with this indicator.
• Scenario A: Long Setup (Buying)
Trend Change: Look for a CHoCH label with a Green Dashed Line.
Entry Zone: Look for a Green Order Block (OB) to form.
Confirmation: A Breakaway Gap (Blue) validates the breakout.
Entry: Enter Long when price pulls back into the Green OB.
Exit Warning: If a "BE" (Buyer Exhaustion) label appears, consider tightening stops or taking profit.
• Scenario B: Short Setup (Selling)
Trend Change: Look for a CHoCH label with a Red Dashed Line.
Entry Zone: Look for a Red Order Block (OB) to form.
Confirmation: A Breakaway Gap downwards validates the move.
Entry: Enter Short when price rallies back into the Red OB.
Exit Warning: If an "SE" (Seller Exhaustion) label appears, consider tightening stops or taking profit.
● SETTINGS
• Date Range Filter
Use Date Filter: Toggle time-based filtering.
Start Date: Timestamp to begin calculations.
• Gap Analysis
Min Gap Size: Minimum points required to register a gap.
Logic Inputs: Configures lookback periods and volume multipliers for gap classification.
Visuals: Customize colors for Breakaway, Runaway, and Exhaustion gaps.
• Market Structure
Swing Detection Length: Lookback period for pivot points.
Show CHoCH: Toggle for Change of Character labels.
Show Order Blocks: Toggle for OB boxes.
• Exhaustion & Stress Model
Trend Filter Length: Baseline length for determining trend direction (EMA).
Statistical Lookback: Length for the Z-Score calculation.
Stress Threshold (Sigma): The standard deviation requirement to trigger an exhaustion signal (Default: 2.0).
● 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.
Analisi trend
Candle 2 Closure [LuxAlgo]The Candle 2 Closure tool detects a specific reversal pattern on the chart spanning four bars. The first bar trades into a key price level. The second bar trades outside the first bar's range, but closes inside, indicating a reversal. The third bar closes outside the second bar's range, in the direction of the reversal, creating a price expansion. The fourth bar is a continuation of prices in that same direction.
This tool features key levels, equilibrium zones, and real-time alarms upon confirmation of the second and third candles of the pattern.
This specific part of the more complete Fractal model by TTrades was requested by a lot of you. We are happy to bring it to you and wish you a merry Christmas!
🔶 USAGE
This pattern is a TTrades concept: a reversal setup that is very easy to understand. It occurs when the current bar trades outside of the previous bar's range, but closes inside it. In other words, traders try to push prices outside of the previous bar's range, but fail. This is considered a reversal, meaning that traders encountered opposing forces that overwhelmed them. Thus, the expectation is that prices will trade in the new direction, changing the market bias from bullish to bearish, or vice versa.
Let's look at the example in the chart, where the four candles of this setup are marked. Note that we have selected a perfect setup, where all conditions are met.
Candle 1: This bar traded into a key price area at the top of the range, spanning several months.
Candle 2: This bar traded outside the range of Candle 1, but failed to close outside. This is the reversal.
Candle 3: The wick of this bar formed at or below the equilibrium zone of Candle 2, and it closed outside the range of Candle 2. This is the expansion.
Candle 4: At this point, the setup is complete, and the expectation for this candle is that it will trade in the same direction. The top of the candle is at or below the equilibrium zone of Candle 3. This is the continuation.
In a strong setup, the top or bottom of the next bar will form inside the equilibrium zone defined by the highlighted areas on candles 2 and 3.
This is a perfect bearish setup, featuring all elements. Not all setups will be like this, but when this setup occurs, it is important for traders to be aware of it.
The tool is highly customizable from the settings panel and features real-time alerts at candle 2 and 3 confirmations.
Now, let's take a broader view of the same chart. We have disabled the display of candle 2 and filtered the setups with a length of 50.
As we can see, most of the last 17 setups found on the EUR/USD daily chart lead to multi-day or multi-month price movements.
🔹 Filtering Reversals
The tool features a reversals filter that is disabled by default. This filter allows us to filter out minor reversals and display only those that are important.
Traders can adjust the length parameter to display reversals only at the top or bottom of the last N specified bars. We can see some examples in the chart.
🔹 Wick Threshold
From the settings panel, traders can fine-tune the equilibrium zone for candle 2.
If the wick exceeds the threshold expressed as a percentage of the total bar range, the equilibrium zone will be calculated based only on the wick. In all other cases, the full bar range will be used.
🔶 SETTINGS
Candle 2 (Reversal): Enable or disable Candle 2 reversals.
Candle 3 (Expansion): Enable or disable Candle 3 expansions.
Reversals Filter: Filter reversals as the highest or lowest of the last N bars.
Wick Threshold %: Filter wicks as percentage of total bar range.
🔹 Style
Bullish Color: Select bullish color.
Bearish Color: Select bearish color.
Transparency: Select the transparency level. 0 is solid and 100 is fully transparent.
Levels: Enable or disable the horizontal levels.
Candle 2 Zone: Enable or disable the Candle 2 equilibrium zones.
Candle 3 Zone: Enable or disable the Candle 3 equilibrium zones.
🔹 Alerts
Candle 2 Alerts: Enable or disable Candle 2 alerts.
Candle 3 Alerts: Enable or disable Candle 3 alerts.
TradingView Alert Adapter for AlgoWayTRALADAL is a universal TradingView alert adapter designed for traders who work with indicators and want to test and automate indicator-based signals in a structured way.
It allows users to convert indicator outputs into a TradingView strategy and forward the same logic through alerts for multi-platform execution via AlgoWay.
This script can be used as TradingView indicator automation, enabling traders to build a TradingView strategy from indicators and route TradingView alerts through an AlgoWay connector TradingView workflow for multi-platform execution.
Why this adapter is needed
Most TradingView indicators are not available as strategies.
Traders often receive visual signals or alerts but have no access to objective statistics such as win rate, drawdown, or profit factor.
This adapter solves that problem by providing a generic framework that transforms indicator signals into a backtestable strategy — without modifying indicator code and without requiring Pine Script knowledge.
Input source–based design (including closed indicators)
All conditions in TRALADAL are built using input sources, which means you can connect:
Event-based signals (1 / non-zero values, arrows, shapes)
Indicator lines and values (EMA, VWAP, RSI, MACD, etc.)
Outputs from invite-only or closed-source indicators
If an indicator produces a visible signal or alert-compatible output, it can be evaluated and tested using this adapter, even when the source code is locked.
Three-level signal logic
The strategy uses a three-layer condition model commonly applied in discretionary and systematic trading:
Signal — primary entry trigger
Confirmation — directional validation
Filter — additional noise reduction
Each level can be enabled independently and combined using AND / OR logic, allowing traders to test multi-indicator systems without writing complex scripts.
Risk management and alert execution
The adapter supports practical risk parameters:
Stop Loss (pips)
Take Profit (pips)
Trailing Stop (pips)
Two execution modes are available:
Strategy Mode — risk rules are applied inside the TradingView Strategy Tester
Alert Mode — risk parameters are embedded into structured TradingView alerts and handled by AlgoWay during execution
Position sizing follows TradingView conventions (percent of equity, cash, or contracts) to keep strategy results and alerts aligned.
Typical use cases
This TradingView alert adapter is intended for:
Indicator-based trading systems
Backtesting signals from closed or invite-only scripts
Comparing multiple indicators within a single strategy
Sending TradingView alerts to external trading platforms via AlgoWay
The adapter does not generate signals or trading recommendations.
Its purpose is to provide a transparent and testable workflow from indicator signals to TradingView alerts and automated execution.
Fractal Swing Levels📊 Fractal Swing Levels — Indicator Description
Fractal Swing Levels is a lightweight, visual indicator that plots historical swing high and swing low reference levels using Williams Fractal logic. The indicator helps traders visually identify areas where price previously formed confirmed pivots. These levels can be used as contextual reference zones when analyzing price structure and market behavior.
🔍 What the Indicator Does
Detects confirmed swing highs and swing lows using a configurable fractal length. Draws horizontal levels at those swing points. Extends the levels to the right for ongoing visual reference. Limits the number of displayed levels to keep the chart clean
🎨 Visual Elements
Red lines represent historical swing high levels
Green lines represent historical swing low levels
These lines are drawn only after fractal confirmation and represent past price structure, not future projections.
⚙️ Settings Explained
Fractal Length : Controls how significant a swing must be to qualify as a level.
Higher values → fewer, more prominent levels
Lower values → more frequent levels
Max Levels Per Side : Limits how many swing high and swing low levels are displayed at one time, helping reduce chart clutter.
📈 How to Use
Use the levels as visual reference points for structure analysis. Combine with trend tools, moving averages, or other technical indicators. Useful across intraday, swing, and positional timeframes. This indicator is best used as a contextual aid, not as a standalone decision tool.
⚠️ Important Notes
This is a visual analysis tool only. It does not generate buy or sell signals. It does not predict future price movement. Levels are based solely on confirmed historical price data
🎯 Summary
Fractal Swing Levels provides a clean and minimal way to visualize historical swing structure on the chart, helping traders better understand where price has previously reacted.
Trend Regime Bands (EMA 50 / 150 / 200)📘 Trend Regime Bands – EMA 50·150·200
Overview
Trend Regime Bands is a visual trend-context indicator designed to help users quickly understand whether the market is in a bullish or bearish regime. The indicator uses the alignment of EMA 50, EMA 150, and EMA 200 to determine overall trend direction, while additional EMAs are used only to create color-based bands for visual context. No buy or sell signals are generated.
How Trend Direction Is Determined
Trend direction is derived exclusively from the relative positioning of: EMA 50 (short-term trend) , EMA 150 (medium-term trend) , EMA 200 (long-term trend) . Bullish regime: EMA 50 ≥ EMA 150 ≥ EMA 200 . Bearish regime: EMA 50 < EMA 150 < EMA 200. These three EMAs act as the decision framework for the indicator.
What the Color Bands Represent : The indicator displays two visual bands on the chart:
Fast Band (Momentum Context) - Built using faster EMAs, Represents short-term momentum and pullback behavior. Brighter color intensity reflects stronger momentum
Slow Band (Regime Context) - Built using slower EMAs. Represents broader trend structure and regime stability.Deeper color intensity reflects stronger trend alignment
The color of both bands follows the trend direction determined by EMA 50/150/200:
Green shades indicate a bullish regime. Red shades indicate a bearish regime. Color intensity increases or decreases smoothly based on trend strength.
How to Use This Indicator
Use the bands to understand market context, not as entry or exit signals. Strong, bright bands suggest a well-established trend. Lighter bands indicate weaker or transitioning trends. The indicator works across intraday, swing, and higher timeframes. This tool is best used alongside price action, support/resistance, or other confirmation methods.
Important Notes
This indicator does not provide buy or sell signals. It does not predict future price movement. It is intended solely as a visual trend-regime and context tool
Summary
Trend Regime Bands offers a clean, distraction-free way to visualize bullish and bearish market regimes using EMA structure and color intensity, helping traders maintain directional awareness and discipline.
Supply & Demand Zones (Volume-Based)📌 Supply & Demand Zones (Volume-Based) — Indicator Description
Overview
This indicator visually highlights potential supply and demand price zones using historical candle structure combined with relative volume behavior.The zones are intended to help users observe areas of increased market activity where price has previously reacted. This tool is designed for visual analysis only.
How the Zones Are Identified
Demand zones are highlighted when price shows a strong bullish reaction following a bearish candle.Supply zones are highlighted when price shows a strong bearish reaction following a bullish candle.Relative volume is used as context, not as a predictive input, to classify zones into higher or lower activity levels.Zones automatically invalidate when price structurally breaks them.
About the Percentage Display
The percentage shown on a zone represents normalized relative volume strength at the time the zone was formed.This value is not a probability, not a success rate, and not a performance metric.It should not be interpreted as a prediction or trading signal.Percentages are displayed only for active zones and are removed once a zone is invalidated.
How This Indicator Is Intended to Be Used
As a visual reference tool for identifying historical supply and demand areas.As a contextual overlay alongside other forms of technical analysis.To observe how price behaves when revisiting previously active zones.This indicator does not suggest trade direction, entry timing, or exit levels.
Important Notes & Limitations
All zones are derived from historical price and volume data.Market conditions change, and historical zones may lose relevance over time.No trading decisions should be made based solely on this indicator.Users are encouraged to apply their own analysis and risk management.
Disclaimer
This indicator is provided for educational and informational purposes only.It does not constitute trading, investment, or financial advice.The author assumes no responsibility for decisions made using this tool.
Custom Psych Levels V1.0 Theo SignalDesigned for Index Traders (US30, NAS100, SPX, etc.)
This script is especially effective on indices such as US30, where price reacts strongly to round numbers and psychological zones. By default, levels adapt to index volatility and scale, making them ideal for:
intraday bias
pullback reactions
breakout continuation
mean reversion back to balance
Key Features
Rolling 5-Level Structure: Always centered on current price, no chart clutter.
Market- Aware Magnitude: Automatically adjusts spacing for indices, forex, and crypto.
Higher- Timeframe Anchoring: Optionally anchor levels to 1H, 4H, or Daily closes while trading lower timeframes like 5m.
Session & Daily Resets: Re-anchor levels at New York session open or new trading day.
Center Line Emphasis: Highlight the equilibrium level with custom color, thickness, and style for balance or decision-making.
Clean Professional Display: Only relevant levels near price are shown.
Trading Use Cases
This indicator is best used as a framework, not a signal generator. It excels when combined with:
momentum confirmation
liquidity sweeps
volume expansion
break-and-retest structures
session highs/lows
Traders can use the center line as balance, outer levels as reaction or target zones, and band shifts as confirmation of expanding price acceptance.
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.
Buying Opportunity Score V2.2Buying Opportunity Indicator V2.2
What This Indicator Does
This indicator identifies potential buying opportunities during market fear and pullbacks by combining multiple technical signals into a single composite score (0-100). Higher scores indicate more fear/oversold conditions are present simultaneously.
Why These Components?
Market bottoms typically occur when multiple fear signals align. This indicator combines five complementary measurements that each capture different aspects of market stress:
1. VIX Level (30 points) - Measures implied volatility/fear. VIX spikes during selloffs as traders buy protection. Thresholds based on historical percentiles (VIX 25+ is ~85th percentile historically).
2. Price Drawdown (30 points) - Distance from 52-week high. Larger drawdowns create better risk/reward for mean reversion entries. A 10%+ drawdown from highs historically presents better entry points than buying at all-time highs.
3. RSI 14 (12 points) - Classic momentum oscillator measuring oversold conditions. RSI below 30 indicates short-term selling exhaustion.
4. Bollinger Band Position (13 points) - Statistical measure of price extension. Price below the lower band (2 standard deviations) indicates statistically unusual weakness.
5. VIX Timing (15 points) - Bonus points when VIX is declining from a recent peak. This helps avoid catching falling knives by waiting for fear to subside.
How The Score Works
- Each component contributes points based on severity
- Components are weighted by predictive value from historical analysis
- Score of 70+ means multiple fear signals are present
- Score of 80+ means extreme fear across most components
How To Use
1. Apply to SPY, QQQ, or IWM on daily timeframe
2. Monitor the Current Score in the statistics table
3. Scores below 50 = normal conditions, no action needed
4. Scores 60-69 = elevated fear, monitor closely
5. Scores 70+ = consider entering long positions
6. Scores 80+ = strongest historical entry points
Important Limitations
- This is a research tool, not financial advice
- Past patterns may not repeat in the future
- Signals are infrequent (typically 2-4 per year reaching 70+)
- Works best on broad market ETFs; not validated for individual stocks
- Always use proper position sizing and risk management
- The indicator identifies conditions that have historically been favorable, but cannot predict future returns
Statistics Table
The table shows:
- Current Score with context message
- Chart Results: Rolling 1Y/3Y/5Y statistics from your loaded chart data
Alerts
Multiple alert options available for different score thresholds.
Open Source
Code is fully visible for review and educational purposes.
QuantLabs MASM Correlation TableThe Market is a graph. See the flows:
The QuantLabs MASM is not a standard correlation table. It is an Alpha-Grade Scanner architected to reveal the hidden "hydraulic" relationships between global macro assets in real-time.
Rebuilt from the ground up for Version 3, this engine pushes the absolute limits of the Pine Script™ runtime. It utilizes a proprietary Logarithmic Math Engine, Symmetric Compute Optimization, and a futuristic "Ghost Mode" interface to deliver a 15x15 real-time correlation matrix with zero lag.
Under the Hood: The Quant Architecture
We stripped away standard libraries to build a lean, high-performance engine designed for institutional-grade accuracy.
1. Alpha Math Engine (Logarithmic Returns) Most tools calculate correlation based on Price, which generates spurious signals (e.g., "Everything is correlated in a bull run").
The Solution: Our engine computes Logarithmic Returns (log(close/close )) by default. This measures the correlation of change (Velocity & Vector), not price levels.
The Result: A mathematically rigorous view of statistical relationships that filters out the noise of general market drift.
Dual-Core: Toggle seamlessly between "Alpha Mode" (Log Returns) for verified stats and "Visual Mode" (Price) for trend alignment.
Calculation Modes: Pearson (Standard), Euclidean (Distance), Cosine (Vector), Manhattan (Grid).
2. Symmetric Compute Optimization Calculating a 15x15 matrix requires evaluating 225 unique relationships per bar, which often crashes memory limits.
The Fix: The V3 Engine utilizes Symmetric Logic, recognizing that Correlation(A, B) == Correlation(B, A).
The Gain: By computing only the lower triangle of the matrix and mirroring pointers to the upper triangle, we reduced computational load by 50%, ensuring a lightning-fast data feed even on lower timeframes.
3. Context-Aware "Ghost Mode" The UI is designed for professional traders who need focus, not clutter.
Smart Detection: The matrix automatically detects your current chart's Ticker ID. If you are trading QQQ, the matrix will visually highlight the Nas100 row and column, making them opaque and bright while dimming the rest.
Dynamic Transparency: Irrelevant data ("Noise" < 0.3 correlation) fades into the background. Only significant "Alpha Signals" (> 0.7) glow with full Neon Saturation.
Key Features
Dominant Flow Scanner: The matrix scans all 105 unique pairs every tick and prints the #1 Strongest Correlation at the bottom of the pane (e.g., DOMINANT FLOW: Bitcoin ↔ Nas100 ).
Streak Counter: A "Stubbornness" metric that tracks how many consecutive days a strong correlation has persisted. Instantly identify if a move is a "flash event" or a "structural trend."
Neon Palette: Proprietary color mapping using Electric Blue (+1.0) for lockstep correlation and Deep Red (-1.0) for inverse hedging.
Usage Guide
Placement: Best viewed in a bottom pane (Footer).
Assets: Pre-loaded with the Essential 15 Macro Drivers (Indices, BTC, Gold, Oil, Rates, FX, Key Sectors). Fully editable via settings (Ticker|Name).
Reading the Grid:
🔵 Bright Blue: Assets moving in lockstep (Risk-On).
🔴 Bright Red: Assets moving perfectly opposite (Hedge/Risk-Off).
⚫ Faded/Black: No statistical relationship (Decoupled).
Key Improvements Made:
Formatting: Added clear bullet points and bolding to make it scannable.
Clarity: Clarified the "Logarithmic Returns" section to explain why it matters (Velocity vs. Price Levels).
Tone: Maintained the "high-tech/quant" vibe but removed slightly clunky phrases like "spurious signals" (unless you prefer that academic tone, in which case I left it in as it fits the persona).
Structure: Grouped the "Modes" under the Math Engine for better logic.
Created and designed by QuantLabs
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.
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.
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.
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.
ICT ORB Killzones by MaxN (15 / 30m)Trading session London, Asia, New York
orb 15/30 min selectable breakout zones with buy/sell signals
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
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.
Market Acceptance Zones [Interakktive]Market Acceptance Zones (MAZ) identifies statistical price acceptance — areas where the market reaches agreement and price rotates rather than trends.
Unlike traditional support/resistance tools, MAZ does not assume where price "should" react. Instead, it highlights regions where multiple internal conditions confirm balance: directional efficiency drops, effort approximately equals result, volatility contracts, and participation remains stable.
This is a market-state diagnostic tool, not a signal generator.
█ WHAT THE ZONES REPRESENT
MAZ (ATF) — Chart Timeframe Acceptance
A MAZ marks an area where price displayed rotational behaviour and the auction temporarily agreed on value. These zones often act as compression regions, fair-price areas, or boundaries of consolidation where impulsive follow-through is less likely.
Use ATF MAZs to:
- Identify rotational environments
- Avoid chasing price inside balance
- Frame consolidation prior to expansion
MAZ • HTF / MAZ • 2/3 — Multi-Timeframe Acceptance (AMTF)
When Multi-Timeframe mode is enabled, MAZ evaluates acceptance on:
- The chart timeframe
- Two higher structural timeframes
If the minimum consensus threshold is met (default: 2 of 3), the zone is classified as AMTF. These zones represent stronger agreement and typically decay more slowly than single-timeframe acceptance.
AMTF zones are structurally stronger and are useful for:
- Higher-quality rotation areas
- Pullback framing within trends
- Context alignment across timeframes
H • MAZ — Historic Acceptance Zones
Historic MAZs represent older acceptance that has transitioned out of active relevance. These zones are hidden by default and can be enabled to provide long-term memory context.
█ AUTO MULTI-TIMEFRAME LOGIC
When MTF Mode is set to Auto, MAZ uses a deterministic structural mapping based on the current chart timeframe:
- 5m → 15m + 1H
- 15m → 1H + 4H
- 1H → 4H + 1D
- 4H → 1D + 1W
- 1D → 1W + 1M
This ensures consistent higher-timeframe context without manual configuration. Advanced users may switch to Manual mode to define custom timeframes.
█ ZONE LIFECYCLE
MAZ zones are dynamic and maintain an internal lifecycle:
- Active — Acceptance remains relevant
- Aging — Acceptance quality is degrading
- Historic — Retained only for memory context
Zones track price interaction and re-acceptance, which can stabilise or strengthen them. Weak or stale zones are automatically removed to keep the chart clean.
█ HOW TRADERS USE MAZ
MAZ is designed to provide structure, not entries.
Common applications include:
- Avoiding chop when price is inside acceptance
- Framing expansion after clean breaks from MAZ
- Identifying higher-quality rotational pullbacks (AMTF zones)
- Defining objective invalidation using zone boundaries
█ SETTINGS OVERVIEW
Market Acceptance Zones — Core
- Acceptance Lookback
- ATR Length
- Zone Frequency (Conservative / Balanced / Aggressive)
Market Acceptance Zones — Zones
- Maximum Zones
- Fade & Stale Bars
- Historic Zone Visibility (default OFF)
Market Acceptance Zones — Timeframes
- MTF Mode (Off / Auto / Manual)
- Manual Higher Timeframes
- Minimum Consensus Requirement
Market Acceptance Zones — Visuals
- Neon / Muted Theme
- Zone Labels & Consensus Detail
- Optional Midline Display
█ DISCLAIMER
This indicator is a market context and diagnostic tool only.
It does not generate trade signals, entries, or exits.
Past acceptance behaviour does not guarantee future price action.
Always combine with independent analysis and proper risk management.
Dragon Flow Arrows (LITE)🚀 DRAGON FLOW ARROWS | Smart Trend Engine + Clean Reversal Arrows
A lightweight but highly-optimized trend system designed for clean charts, powerful visual signals, and no-noise directional flow. Built for traders who want simplicity, clarity, and professional-level momentum-filtered signals without over-complication.
🔥 Dragon Channel (Clean 3-Line Ribbon)
A smooth adaptive channel formed from ATR + EMA, giving you structural trend zones without clutter.
✅ Dragon Flow Gradient
A horizontal, color-shifted flow:
🟢 Bull flow → green glow
🔴 Bear flow → red glow
Automatic blend based on trend direction
Smooth visual transitions (no vertical stripes)
✅ Momentum-Filtered Arrows
BUY/SELL arrows only print when:
Price breaks outside the Dragon Channel
Momentum confirms (RSI + MACD filters)
Trend flips → one clean arrow per direction
✅ Smart Header Panel
At the top of your chart:
📌 Trend: Uptrend / Downtrend / Neutral
⚡ Impulse Strength: Weak / Normal / Strong
📊 How to Use
Entry:
- BUY Setup
Price moving above baseline
Dragon Flow turns bullish (cyan side)
Arrow appears below channel
- SELL Setup
Price breaks below baseline
Dragon Flow turns bearish (magenta side)
Arrow pops above channel
Exit / Filter:
Opposite arrow
Flow color shift
Trend panel flips
Works on Forex, Crypto, Stocks, Indices — all timeframes (just adjust the channel length).
Happy trading!
DDDDD : EMA Pack (Matched Colors + MTF)📌 DDDDD : EMA Pack (Matched Colors + MTF)
🔹 Concept
DDDDD : EMA Pack is a clean and minimal Exponential Moving Average (EMA) overlay designed for trend structure analysis and multi-timeframe context.
This indicator focuses on visual clarity, consistent color mapping, and optional MTF EMA projection, allowing traders to read market structure without clutter or signal noise.
It is not an entry or signal generator, but a trend and regime visualization tool.
🔹 Logic
The script plots a fixed set of EMAs commonly used to define short-term momentum, intermediate trend, and long-term bias:
EMA 5
EMA 10
EMA 25
EMA 50
EMA 75
EMA 200
Each EMA is calculated using the standard exponential moving average formula.
If a higher timeframe is selected, the EMA is calculated on that timeframe and projected onto the current chart using request.security().
🔹 Methodology
Users may select:
Source price (default: close)
EMA timeframe
Empty = current chart timeframe
Any higher timeframe = true MTF EMA projection
All EMA colors are manually matched and fixed to maintain visual consistency across markets and timeframes.
Line thickness is kept uniform to avoid visual hierarchy bias.
This design ensures the indicator remains purely structural, without repainting logic, smoothing tricks, or adaptive parameters.
🔹 How to Use
Use EMA alignment and spacing to assess:
Trend direction
Trend strength
Compression vs expansion
Higher-timeframe EMA projection can be used as:
Dynamic support/resistance
Trend filter
Regime context for lower-timeframe execution
This indicator works best when combined with:
Price action
Market structure
Separate entry/exit logic of your own system
⚠️ This indicator does not provide buy/sell signals and should not be used alone for trade execution.
🔹 Notes
No repainting beyond standard MTF behavior
No performance or profitability claims
Designed for discretionary and systematic traders
Suitable for stocks, crypto, forex, and indices
RSI Dashboard Multi-TF This script displays RSI values from multiple timeframes in a compact dashboard directly on the chart.
It is designed for traders who want to quickly identify whether the market is overbought, oversold, or neutral across different timeframes, without constantly switching chart intervals.
The dashboard shows the RSI simultaneously for the following timeframes:
- 1 minute
- 3 minutes
- 5 minutes
- 15 minutes
- 1 hour
- 4 hours
- Daily
Typical use cases:
- Scalping & intraday trading
- Multi-timeframe analysis at a glance
- Entry confirmation (e.g. pullbacks, breakouts)
- Avoiding trades against overbought or oversold market conditions
- Complementing EMA, VWAP, or price action strategies
⚙️ Notes
This dashboard is an analysis tool, not an automated trading system.
No repainting (uses request.security).
Suitable for indices, forex, crypto, and commodities.
This RSI dashboard provides a fast, clear, and visually clean market overview across multiple timeframes, making it an ideal tool for active traders who want to make efficient and well-structured trading decisions.
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.
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.
