Value Scanner | QuantEdgeB📡 Value Scanner | QuantEdgeB
🔍 What is the Value Scanner?
The Value Scanner by QuantEdgeB is a volatility-adaptive valuation framework that dynamically evaluates where price sits relative to a custom “Fair Value” zone. It combines your choice of moving average engine (SMA, WMA, VIDYA, etc.) with multi-layered standard deviation or ATR-based bands to highlight extreme conditions, reversal zones, and statistical overextensions in real time.
💡 Think of Value Scanner as a radar grid, continuously scanning market terrain and painting a full spectrum from balance to extreme disequilibrium.
⚙️ Core Components
✅ Customizable Moving Average Core
At the heart of the scanner lies a flexible moving average engine:
• Choose from 12+ advanced types: 𝓦𝓜𝓐, 𝓥𝓦𝓜𝓐, 𝓥𝓘𝓓𝓨𝓐, 𝓢𝓜𝓜𝓐, 𝓐𝓛𝓜𝓐, 𝓛𝓢𝓜𝓐, and more.
• Fair Value is derived from this base and acts as the center of the statistical zones.
✅ Volatility-Driven Band Construction
Two volatility methods power the adaptive zones:
• Average True Range (ATR): Ideal for reactive, price-based spreads.
• Standard Deviation (SD): Better for modeling reversion and deviation symmetry.
The scanner builds up to ±5σ zones, dynamically updating in real time.
🎯 Signal and Zone Identification
🧭 Deviation Labels
The system assigns a statistical label at every candle:
• From +0.5σ to +5σ for increasing levels of overextension upward.
• From -0.5σ to -5σ for oversold and undervalued conditions.
🌐 Market Stage Detection
Each deviation zone is translated into an intuitive market phrase such as:
• “𝓔𝔁𝓽𝓻𝓮𝓶𝓮𝓵𝔂 𝓞𝓿𝓮𝓻𝓫𝓸𝓾𝓰𝓱𝓽”
• “𝓜𝓲𝓭 𝓥𝓪𝓵𝓾𝓮 / 𝓑𝓪𝓵𝓪𝓷𝓬𝓮𝓭”
• “𝓜𝓪𝔁𝓲𝓶𝓾𝓶 𝓔𝔁𝓽𝓮𝓷𝓼𝓲𝓸𝓷 𝓓𝓸𝔀𝓷”
These phrases help you intuitively gauge risk, reward, and imbalance without needing to study a chart for long.
🔺 Signal Mechanics
📌 Reversal Signals (Optional)
• Automatic buy signals when price crosses above key lower deviation levels.
• Sell signals when price crosses below upper deviation bands.
• Ideal for mean-reversion setups or high-probability reversal plays.
🖼️ Visual Overlay Engine
• Beautifully shaded volatility bands with decreasing opacity as they move away from fair value.
• Background coloring highlights extreme price zones for fast visual alerts.
• Built-in "table display" summarizing the current base, volatility method, direction, fair value, and deviation stage.
📊 Table Overlay Features
The live diagnostic table (position adjustable) displays:
• 📈 Current Base MA Type
• 🌡️ Volatility Method in use (ATR or SD)
• 🧭 Trend direction (rising/falling/neutral)
• 🧮 Current Deviation Label (+2σ, -3σ, etc.)
• 🚦 Interpretive Stage Phrase ("Strongly Overbought", etc.)
• 📍 Real-Time Fair Value
• 🚨 Upper & Lower Extremes
🧠 Why Use the Value Scanner?
This tool is designed for traders who want to:
• Identify price extremes relative to statistical norms.
• Time entries and exits based on price's relationship to value zones.
• Visualize volatility structure without clutter.
• Combine trend-following or mean-reversion logic with elegant overlays and table analytics.
💼 Ideal Use Cases
• Swing trading: Spot overextensions or returns to mean.
• Options traders: Gauge volatility compression or expansion.
• Reversion systems: Generate contrarian signals at edge zones.
• Trend continuation: Use +1σ or -1σ as breakout validation levels.
🧬 Default Settings
• Base Type: 𝓦𝓜𝓐
• Length: 21
• Volatility Type: 𝓐𝓿𝓰. 𝓣𝓻𝓾𝓮 𝓡𝓪𝓷𝓰𝓮
•. Volatility Lengths: ATR 14 / Stdev 30
🧬 In Summary
Value Scanner | QuantEdgeB is not just a volatility band indicator — it’s a contextual market scanner that combines price equilibrium theory with precision deviation mapping. It adds statistical insight, color-coded extremes, and narrative stage identification — all in real time.
Whether you’re trend-following or fading extremes, this system helps you locate value, measure dislocation, and trade with mathematical confidence.
📌 Trade with Statistical Precision | Powered by QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Volatilite
Z-Score IndicatorWhat it does:
Calculates the Z-Score: (Current Price - Average Price) / Standard Deviation
Plots the Z-Score in a separate panel below your main chart.
Allows you to customize the Lookback Period (default is 30 bars) to suit your trading style and the asset's characteristics. A shorter period is more sensitive, while a longer period provides a smoother output.
Key Features:
Clear Z-Score Line: Visualizes the current Z-Score value.
Reference Lines:
Zero Line (Gray, Dotted): Indicates the price is at its average for the lookback period.
+2 Standard Deviations (Red, Dotted): Highlights when the price is significantly above its recent average. Often interpreted as potentially overbought.
-2 Standard Deviations (Red, Dotted): Highlights when the price is significantly below its recent average. Often interpreted as potentially oversold.
How to use it:
Look for Z-Score values moving towards or beyond the +2 or -2 standard deviation lines. These extremes can signal that the price has moved unusually far from its mean and might be due for a reversion or a pause.
Use it in conjunction with other indicators and your overall market analysis to make more informed trading decisions.
Experiment with the "Lookback Period" setting to find what works best for different assets and timeframes.
Filtered DTR Table📊 Filtered Daily True Range (DTR) Indicator
This indicator calculates and displays a filtered version of the Daily True Range (DTR) over the last 14 trading days, using high and low prices of each day.
It filters out extreme values by excluding any daily range that is:
Less than 0.5× the average range
Greater than 2× the average range
The indicator shows a table in the bottom-right corner of the main chart, containing:
Filtered ATR – The average of valid (filtered) daily ranges over the past 14 days, based on the high-low difference.
Current Day's Range – The high-low range of the current trading day.
% of ATR – How much of the filtered ATR has been covered by today's range, expressed as a whole number percentage.
PhenLabs - Market Fluid Dynamics📊 Market Fluid Dynamics -
Version: PineScript™ v6
📌 Description
The Market Fluid Dynamics - Phen indicator is a new thinking regarding market analysis by modeling price action, volume, and volatility using a fluid system. It attempts to offer traders control over more profound market forces, such as momentum (speed), resistance (thickness), and buying/selling pressure. By visualizing such dynamics, the script allows the traders to decide on the prevailing market flow, its power, likely continuations, and zones of calmness and chaos, and thereby allows improved decision-making.
This measure avoids the usual difficulty of reconciling multiple, often contradictory, market indications by including them within a single overarching model. It moves beyond traditional binary indicators by providing a multi-dimensional view of market behavior, employing fluid dynamic analogs to describe complex interactions in an accessible manner.
🚀 Points of Innovation
Integrated Fluid Dynamics Model: Combines velocity, viscosity, pressure, and turbulence into a single indicator.
Normalized Metrics: Uses ATR and other normalization techniques for consistent readings across different assets and timeframes.
Dynamic Flow Visualization: Main flow line changes color and intensity based on direction and strength.
Turbulence Background: Visually represents market stability with a gradient background, from calm to turbulent.
Comprehensive Dashboard: Provides an at-a-glance summary of key fluid dynamic metrics.
Multi-Layer Smoothing: Employs several layers of EMA smoothing for a clearer, more responsive main flow line.
🔧 Core Components
Velocity Component: Measures price momentum (first derivative of price), normalized by ATR. It indicates the speed and direction of price changes.
Viscosity Component: Represents market resistance to price changes, derived from ATR relative to its historical average. Higher viscosity suggests it’s harder for prices to move.
Pressure Component: Quantifies the force created by volume and price range (close - open), normalized by ATR. It reflects buying or selling pressure.
Turbulence Detection: Calculates a Reynolds number equivalent to identify market stability, ranging from laminar (stable) to turbulent (chaotic).
Main Flow Indicator: Combines the above components, applying sensitivity and smoothing, to generate a primary signal of market direction and strength.
🔥 Key Features
Advanced Smoothing Algorithm: Utilizes multiple EMA layers on the raw flow calculation for a fluid and responsive main flow line, reducing noise while maintaining sensitivity.
Gradient Flow Coloring: The main flow line dynamically changes color from light to deep blue for bullish flow and light to deep red for bearish flow, with intensity reflecting flow strength. This provides an immediate visual cue of market sentiment and momentum.
Turbulence Level Background: The chart background changes color based on calculated turbulence (from calm gray to vibrant orange), offering an intuitive understanding of market stability and potential for erratic price action.
Informative Dashboard: A customizable on-screen table displays critical metrics like Flow State, Flow Strength, Market Viscosity, Turbulence, Pressure Force, Flow Acceleration, and Flow Continuity, allowing traders to quickly assess current market conditions.
Configurable Lookback and Sensitivity: Users can adjust the base lookback period for calculations and the sensitivity of the flow to viscosity, tailoring the indicator to different trading styles and market conditions.
Alert Conditions: Pre-defined alerts for flow direction changes (positive/negative crossover of zero line) and detection of high turbulence states.
🎨 Visualization
Main Flow Line: A smoothed line plotted below the main chart, colored blue for bullish flow and red for bearish flow. The intensity of the color (light to dark) indicates the strength of the flow. This line crossing the zero line can signal a change in market direction.
Zero Line: A dotted horizontal line at the zero level, serving as a baseline to gauge whether the market flow is positive (bullish) or negative (bearish).
Turbulence Background: The indicator pane’s background color changes based on the calculated turbulence level. A calm, almost transparent gray indicates low turbulence (laminar flow), while a more vibrant, semi-transparent orange signifies high turbulence. This helps traders visually assess market stability.
Dashboard Table: An optional table displayed on the chart, showing key metrics like ‘Flow State’, ‘Flow Strength’, ‘Market Viscosity’, ‘Turbulence’, ‘Pressure Force’, ‘Flow Acceleration’, and ‘Flow Continuity’ with their current values and qualitative descriptions (e.g., ‘Bullish Flow’, ‘Laminar (Stable)’).
📖 Usage Guidelines
Setting Categories
Show Dashboard - Default: true; Range: true/false; Description: Toggles the visibility of the Market Fluid Dynamics dashboard on the chart. Enable to see key metrics at a glance.
Base Lookback Period - Default: 14; Range: 5 - (no upper limit, practical limits apply); Description: Sets the primary lookback period for core calculations like velocity, ATR, and volume SMA. Shorter periods make the indicator more sensitive to recent price action, while longer periods provide a smoother, slower signal.
Flow Sensitivity - Default: 0.5; Range: 0.1 - 1.0 (step 0.1); Description: Adjusts how much the market viscosity dampens the raw flow. A lower value means viscosity has less impact (flow is more sensitive to raw velocity/pressure), while a higher value means viscosity has a greater dampening effect.
Flow Smoothing - Default: 5; Range: 1 - 20; Description: Controls the length of the EMA smoothing applied to the main flow line. Higher values result in a smoother flow line but with more lag; lower values make it more responsive but potentially noisier.
Dashboard Position - Default: ‘Top Right’; Range: ‘Top Right’, ‘Top Left’, ‘Bottom Right’, ‘Bottom Left’, ‘Middle Right’, ‘Middle Left’; Description: Determines the placement of the dashboard on the chart.
Header Size - Default: ‘Normal’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’, ‘Huge’; Description: Sets the text size for the dashboard header.
Values Size - Default: ‘Small’; Range: ‘Tiny’, ‘Small’, ‘Normal’, ‘Large’; Description: Sets the text size for the metric values in the dashboard.
✅ Best Use Cases
Trend Identification: Identifying the dominant market flow (bullish or bearish) and its strength to trade in the direction of the prevailing trend.
Momentum Confirmation: Using the flow strength and acceleration to confirm the conviction behind price movements.
Volatility Assessment: Utilizing the turbulence metric to gauge market stability, helping to adjust position sizing or avoid choppy conditions.
Reversal Spotting: Watching for divergences between price and flow, or crossovers of the main flow line above/below the zero line, as potential reversal signals, especially when combined with changes in pressure or viscosity.
Swing Trading: Leveraging the smoothed flow line to capture medium-term market swings, entering when flow aligns with the desired trade direction and exiting when flow weakens or reverses.
Intraday Scalping: Using shorter lookback periods and higher sensitivity to identify quick shifts in flow and turbulence for short-term trading opportunities, particularly in liquid markets.
⚠️ Limitations
Lagging Nature: Like many indicators based on moving averages and lookback periods, the main flow line can lag behind rapid price changes, potentially leading to delayed signals.
Whipsaws in Ranging Markets: During periods of low volatility or sideways price action (high viscosity, low flow strength), the indicator might produce frequent buy/sell signals (whipsaws) as the flow oscillates around the zero line.
Not a Standalone System: While comprehensive, it should be used in conjunction with other forms of analysis (e.g., price action, support/resistance levels, other indicators) and not as a sole basis for trading decisions.
Subjectivity in Interpretation: While the dashboard provides quantitative values, the interpretation of “strong” flow, “high” turbulence, or “significant” acceleration can still have a subjective element depending on the trader’s strategy and risk tolerance.
💡 What Makes This Unique
Fluid Dynamics Analogy: Its core strength lies in translating complex market interactions into an intuitive fluid dynamics framework, making concepts like momentum, resistance, and pressure easier to visualize and understand.
Market View: Instead of focusing on a single aspect (like just momentum or just volatility), it integrates multiple factors (velocity, viscosity, pressure, turbulence) to provide a more comprehensive picture of market conditions.
Adaptive Visualization: The dynamic coloring of the flow line and the turbulence background provide immediate, adaptive visual feedback that changes with market conditions.
🔬 How It Works
Price Velocity Calculation: The indicator first calculates price velocity by measuring the rate of change of the closing price over a given ‘lookback’ period. The raw velocity is then normalized by the Average True Range (ATR) of the same lookback period. Normalization enables comparison of momentum between assets or timeframes by scaling for volatility. This is the direction and speed of initial price movement.
Viscosity Calculation: Market ‘viscosity’ or resistance to price movement is determined by looking at the current ATR relative to its longer-term average (SMA of ATR over lookback * 2). The further the current ATR is above its average, the lower the viscosity (less resistance to price movement), and vice-versa. The script inverts this relationship and bounds it so that rising viscosity means more resistance.
Pressure Force Measurement: A ‘pressure’ variable is calculated as a function of the ratio of current volume to its simple moving average, multiplied by the price range (close - open) and normalized by ATR. This is designed to measure the force behind price movement created by volume and intraday price thrusts. This pressure is smoothed by an EMA.
Turbulence State Evaluation: A equivalent ‘Reynolds number’ is calculated by dividing the absolute normalized velocity by the viscosity. This is the proclivity of the market to move in a chaotic or orderly fashion. This ‘reynoldsValue’ is smoothed with an EMA to get the ‘turbulenceState’, which indicates if the market is laminar (stable), transitional, or turbulent.
Main Flow Derivation: The ‘rawFlow’ is calculated by taking the normalized velocity, dampening its impact based on the ‘viscosity’ and user-input ‘sensitivity’, and orienting it by the sign of the smoothed ‘pressureSmooth’. The ‘rawFlow’ is then put through multiple layers of exponential moving average (EMA) smoothing (with ‘smoothingLength’ and derived values) to reach the final ‘mainFlow’ line. The extensive smoothing is designed to give a smooth and clear visualization of the overall market direction and magnitude.
Dashboard Metrics Compilation: Additional metrics like flow acceleration (derivative of mainFlow), and flow continuity (correlation between close and volume) are calculated. All primary components (Flow State, Strength, Viscosity, Turbulence, Pressure, Acceleration, Continuity) are then presented in a user-configurable dashboard for ease of monitoring.
💡 Note:
The “Market Fluid Dynamics - Phen” indicator is designed to offer a unique perspective on market behavior by applying principles from fluid dynamics. It’s most effective when used to understand the underlying forces driving price rather than as a direct buy/sell signal generator in isolation. Experiment with the settings, particularly the ‘Base Lookback Period’, ‘Flow Sensitivity’, and ‘Flow Smoothing’, to find what best suits your trading style and the specific asset you are analyzing. Always combine its insights with robust risk management practices.
Filt ADR🟠 Script Name: Filtered Average Daily Range (Filt ADR)
This script calculates a filtered version of the Average Daily Range (ADR) based on the last 14 daily candles. It's designed to reduce the influence of unusually high or low daily ranges (outliers) by applying a filter before calculating the average.
🔧 How It Works — Step by Step
1. Calculate Daily Ranges (High - Low)
It retrieves the daily price ranges (difference between daily high and low) for the last 14 days using request.security() with the "D" (daily) timeframe.
pinescript
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high - low // today's daily range
high - low // yesterday's daily range
...
These values are stored into individual variables dr0 to dr13.
2. Build an Array of Daily Ranges
An array named ranges is used to store the 14 daily ranges, but only if they are not na (missing data). This avoids errors during processing.
3. Calculate the Initial (Unfiltered) Average Range
The script sums all values in the ranges array and calculates their average:
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avg_all = total sum of ranges / number of valid entries
4. Filter Out Outliers
Now it filters the values in ranges:
Only keeps the ranges that are between 0.5×avg_all and 2×avg_all.
This is to remove abnormally small or large daily ranges that could distort the average.
The filtered values are added to a second array called filtered.
5. Calculate the Filtered ADR
Finally, it calculates the average of the filtered daily ranges:
pinescript
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avg_filt = sum of filtered ranges / number of filtered values
This is the Filtered ADR.
6. Plot the Result
The result (avg_filt) is plotted as an orange line on the chart. It updates on each bar (depending on the current timeframe you're viewing) but the underlying data is based on the last 14 daily candles.
pinescript
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plot(avg_filt, title="Filtered ADR", color=color.orange, linewidth=2)
✅ Use Case
This script is useful for traders who use the Average Daily Range (ADR) to:
Estimate expected price movement during a day
Set volatility-based stop-loss or take-profit levels
Identify days with unusually high or low volatility
By filtering out extreme values, it provides a more stable and reliable estimate of daily volatility.
GOYD📊 GOYD (Daily Average Percentage Change) Indicator
Created by: Emre Yavuz - @emreyavuz84
This indicator calculates and displays the average daily percentage change for each day of the week. It helps traders identify which days tend to be more volatile, offering valuable insights for timing strategies and market behavior analysis.
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🔧 How It Works
Daily Percentage Change Calculation:
For each candle, the indicator calculates the percentage change using the formula:
Percentage Change = (High - Low) / Low * 100
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Day-Based Data Collection:
The script stores the daily percentage changes in separate arrays for each day of the week:
Monday → mondayChanges
Tuesday → tuesdayChanges
...
Sunday → sundayChanges
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Average Calculation:
For each day, the script calculates the average of all recorded percentage changes. This gives a historical view of how volatile each weekday tends to be.
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Visual Table Display:
A table is displayed in the top-right corner of the chart, showing:
Column 1: Day of the week
Column 2: Average percentage change for that day
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🎯 Use Cases
This indicator is useful for:
Weekly Volatility Analysis: Identify which days are historically more volatile.
Timing Strategies: Optimize entry/exit points based on day-specific behavior.
Data-Driven Decisions: Make informed choices using historical volatility trends.
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🎨 Customization
The table color can be customized via the _tc input parameter.
The indicator is set to display directly on the chart (overlay=true).
If you find this indicator helpful, feel free to like, comment, or add it to your favorites. Your feedback is always appreciated! 📈
CCT Volatility Index📘 CCT Volatility Index
The CCT Volatility Index is a refined adaptation of the LS Volatility Index , originally presented by Brazilian traders Alexandre Wolwacz (Stormer), Fabrício Lorenz, and Fábio Figueiredo (Vlad) . This implementation respects the core logic of the original concept but introduces two important enhancements:
Bollinger Band Width Percentage (BBWP)
Average True Range (ATR)
These are incorporated into the traditional formula (price deviation from a moving average divided by historical volatility), producing a normalized and responsive oscillator.
🧠 Conceptual Summary
This is a volatility indicator, not a directional trend tool. It measures the degree of price dispersion and tension in the market. It can be applied in two primary contexts:
🔁 Reversal Scenarios
When the index approaches extreme levels (near 100), it may signal exhaustion of volatility and potential mean reversion, especially if price is far from the moving average (SMA21 by default).
📈 Trend Continuation
If price stays near the average and the index maintains an elevated or rising profile, it may suggest trend acceptance with ongoing momentum. In this case, volatility expansion aligns with continuation.
🎯 Strategy Guidelines
Trigger points may come from the index crossing its own moving average (white line), either as a breakout or via retest confirmation.
Overlay colors identify BBWP compression/expansion zones:
- Blue: BBWP is 2% above its historical mean.
- Red: BBWP is 98% above.
These zones can help identify breakout setups or mean-reverting conditions.
📊 Info Panel
The indicator includes a dynamic panel showing:
The current price
The moving average used as reference
The percentage deviation between them
This allows you to evaluate if the asset is currently "stretched" or "fair" under current volatility.
⚠️ Disclaimer
This tool is for educational and informational purposes only. It does not constitute investment advice and should not be used in isolation. Always combine it with other tools, market context, and proper risk management.
Killzones (UTC+3) by Roy⏰ Time-Based Division – Trading Quarters:
The trading day is divided into four main quarters, each reflecting distinct market behaviours:
Opo Finance Blog
Quarter Time (Israel Time) Description
Q1 16:30–18:30 Wall Street opening; highest volatility.
Q2 18:30–20:30 Continuation or correction of the opening move.
Q3 20:30–22:30 Quieter market; often characterized by consolidation.
Q4 22:30–24:00 Preparation for market close; potential breakouts or sharp movements.
This framework assists traders in anticipating market dynamics within each quarter, enhancing decision-making by aligning strategies with typical intraday patterns.
Dynamic Volatility EnvelopeDynamic Volatility Envelope: Indicator Overview
The Dynamic Volatility Envelope is an advanced, multi-faceted technical indicator designed to provide a comprehensive view of market trends, volatility, and potential future price movements. It centers around a customizable linear regression line, enveloped by dynamically adjusting volatility bands. The indicator offers rich visual feedback through gradient coloring, candle heatmaps, a background volatility pulse, and an on-chart trend strength meter.
Core Calculation Mechanism
Linear Regression Core :
-A central linear regression line is calculated based on a user-defined source (e.g., close, hl2) and lookback period.
-The regression line can be optionally smoothed using an Exponential Moving Average (EMA) to reduce noise.
-The slope of this regression line is continuously calculated to determine the current trend direction and strength.
Volatility Channel :
-Dynamic bands are plotted above and below a central basis line. This basis is typically the calculated regression line but shifts to an EMA in Keltner mode.
-The width of these bands is determined by market volatility, using one of three user-selectable modes:
ATR Mode : Bandwidth is a multiple of the Average True Range (ATR).
Standard Deviation Mode : Bandwidth is a multiple of the Standard Deviation of the source data.
Keltner Mode (EMA-based ATR) : ATR-based bands are plotted around a central Keltner EMA line, offering a smoother channel.
The channel helps identify dynamic support and resistance levels and assess market volatility.
Future Projection :
The indicator can project the current regression line and its associated volatility bands into the future for a user-defined number of bars. This provides a visual guide for potential future price pathways based on current trend and volatility characteristics.
Candle Heatmap Coloring :
-Candle bodies and/or wicks/borders can be colored based on the price's position within the upper and lower volatility bands.
-Colors transition in a gradient from bearish (when price is near the lower band) through neutral (mid-channel) to bullish (when price is near the upper band), providing an intuitive visual cue of price action relative to the dynamic envelope.
Background Volatility Pulse :
The chart background color can be set to dynamically shift based on a ratio of short-term to long-term ATR. This creates a "pulse" effect, where the background subtly changes color to indicate rising or falling market volatility.
Trend Strength Meter :
An on-chart text label displays the current trend status (e.g., "Strong Bullish", "Neutral", "Bearish") based on the calculated slope of the regression line relative to user-defined thresholds for normal and strong trends.
Key Features & Components
-Dynamic Linear Regression Line: Core trend indicator with optional smoothing and slope-based gradient coloring.
-Multi-Mode Volatility Channel: Choose between ATR, Standard Deviation, or Keltner (EMA-based ATR) calculations for band width.
-Customizable Vertical Gradient Channel Fills: Visually distinct fills for upper and lower channel segments with user-defined top/bottom colors and gradient spread.
-Future Projection: Extrapolates regression line and volatility bands to forecast potential price paths.
-Price-Action Based Candle Heatmap: Intuitive candle coloring based on position within the volatility channel, with adjustable gradient midpoint.
-Volatility-Reactive Background Gradient: Subtle background color shifts to reflect changes in market volatility.
-On-Chart Trend Strength Meter: Clear textual display of current trend direction and strength.
-Extensive Visual Customization: Fine-tune colors, line styles, widths, and gradient aggressiveness for most visual elements.
-Comprehensive Tooltips: Detailed explanations for every input setting, ensuring ease of use and understanding.
Visual Elements Explained
Regression Line : The primary trend line. Its color dynamically changes (e.g., green for uptrend, red-pink for downtrend, neutral for flat) based on its slope, with smooth gradient transitions.
Volatility Channel :
Upper & Lower Bands : These lines form the outer boundaries of the envelope, acting as dynamic support and resistance levels.
Channel Fill : The area between the band center and the outer bands is filled with a vertical gradient. For example, the upper band fill might transition from a darker green near the center to a lighter green at the upper band.
Band Borders : The lines outlining the upper and lower bands, with customizable color and width.
Future Projection Lines & Fill :
Projected Regression Line : An extension of the current regression line into the future, typically styled differently (e.g., dashed).
Projected Channel Bands : Extensions of the upper and lower volatility bands.
Projected Area Fill : A semi-transparent fill between the projected upper and lower bands.
Candle Heatmap Coloring : When enabled, candles are colored based on their closing price's relative position within the channel. Bullish colors appear when price is in the upper part of the channel, bearish in the lower, and neutral in the middle. Users can choose to color the entire candle body or just the wicks and borders.
Background Volatility Pulse : The chart's background color subtly shifts (e.g., between a calm green and an agitated red-pink) to reflect the current volatility regime.
Trend Strength Meter : A text label (e.g., "TREND: STRONG BULLISH") positioned on the chart, providing an at-a-glance summary of the trend.
Configuration Options
Users can tailor the indicator extensively via the settings panel, with options logically grouped:
Core Analysis Engine : Adjust regression source data, lookback period, and EMA smoothing for the regression line.
Regression Line Visuals : Control visibility, line width, trend-based colors (uptrend, downtrend, flat), slope thresholds for trend definition, strong slope multiplier (for Trend Meter), and color gradient sharpness.
Volatility Channel Configuration : Select band calculation mode (ATR, StdDev, Keltner), set relevant periods and multipliers. Customize colors for vertical gradient fills (upper/lower, top/bottom), border line colors, widths, and the gradient spread factor for fills.
Future Projection Configuration : Toggle visibility, set projection length (number of bars), line style, and colors for projected regression and band areas.
Appearance & Candle Theme : Set default bull/bear candle colors, enable/disable candle heatmap, choose if body color matches heatmap, and configure heatmap gradient target colors (bull, neutral, bear) and the gradient's midpoint.
Background Volatility Pulse : Enable/disable the background effect and configure short/long ATR periods for the volatility calculation.
Trend Strength Meter : Enable/disable the meter, and choose its on-chart position and text size.
Interpretation Notes
-The Regression Line is the primary indicator of trend direction. Its slope and color provide immediate insight.
-The Volatility Bands serve as dynamic support and resistance zones. Price approaching or touching these bands may indicate potential turning points or breakouts. The width of the channel itself reflects market volatility – widening suggests increasing volatility, while narrowing suggests consolidation.
Future Projections are not predictions but rather an extension of current conditions. They can help visualize potential areas where price might interact with projected support/resistance if the current trend and volatility persist.
Candle Heatmap Coloring offers a quick visual assessment of where price is trading within the dynamic envelope, highlighting strength or weakness relative to the channel.
The Background Volatility Pulse gives a contextual feel for overall market agitation or calmness.
This indicator is designed to be a comprehensive analytical tool. Its signals and visualizations are best used in conjunction with other technical analysis techniques, price action study, and robust risk management practices. It is not intended as a standalone trading system.
Risk Disclaimer
Trading and investing in financial markets involve substantial risk of loss and is not suitable for every investor. The Dynamic Volatility Envelope indicator is provided for analytical and educational purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Past performance is not indicative of future results. Always use sound risk management practices and never trade with capital you cannot afford to lose. The developers assume no liability for any financial losses incurred based on the use of this indicator.
MA Thrust Processor | QuantEdgeB⚡MA Thrust Processor | QuantEdgeB
🔭 What is the MA Thrust Processor?
The MA Thrust Processor (MTP) is a dynamic and modular market momentum engine that specializes in thrust-based signal analysis derived from smoothed moving averages. It’s engineered to model directional commitment, detect signal imbalances, and visualize structural momentum in a range of market conditions.
🧬 Think of MTP as a precision-engineered motion sensor — decoding strength, follow-through, and structural imbalance in real time — it detects force, direction, velocity, and alignment, adapting based on your preferred calculation model (Wave, Thrust, Z-Score, or Normalized) and signal mode (Impulse, Trend, or HA Candles).
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1. 🔧 System Core: Customizability and Processing Engine
📊 Moving Average Types
MA Thrust Processor supports a rich menu of 13+ moving average styles:
• Standard: SMA, EMA, WMA
• Advanced: HMA, LSMA, ALMA, JMA, TEMA, DEMA, SMMA
• Volume-Based: VWMA
• Adaptive Models: VIDYA (3 modes), FRAMA
💡 Each MA type acts as the backbone for signal smoothing and thrust deviation modeling, giving the user tight control over behavior and lag tradeoffs.
⚙️ Calculation Methods (MA Derivatives)
You choose how the core value is calculated:
1️⃣ 𝓦𝓪𝓿𝓮
• Sine-wave modeled oscillator
• Combines MA distance with standard deviation normalization
• Ideal for detecting divergences and cyclical structure
• Output includes center, smoothed line , and histogram.
2️⃣ 𝓣𝓱𝓻𝓾𝓼𝓽
• Calculates MA deviation vs. price and midpoint
• Captures aggressive directional pushes relative to range center
• Excellent for breakout/trend force analysis
3️⃣ 𝓩-𝓢𝓬𝓸𝓻𝓮
• Mean-reverting z-score over MA
• Expresses statistical distance from norm
• Used in reversion or probabilistic strategies
4️⃣ 𝓝𝓸𝓻𝓶𝓪𝓵𝓲𝔃𝓮𝓭
• Scales MA output to 0–1 (centered at 0.5)
• Tracks where the signal lies in its own relative range
• Great for flat vs. trending recognition
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2. 🧨 SIGNAL MODES – The Behavioral Core
The system supports 3 powerful signal modes that define how the thrust logic is interpreted and visualized.
1️⃣ 𝓘𝓶𝓹𝓾𝓵𝓼𝓮 Mode
🔥 Use Case: Breakouts, aggressive reversals, divergences
🔍 Logic:
• In Wave mode: compares Wave O (oscillator) and S (smoothed)
• In Thrust/Z-Score/Normalized: applies thresholds (static, SD, or percentile)
• Detects sharp departures or rejections from bounds
🎯 Ideal for:
• Scalp or event trades
• High-velocity moves
• Leading edge of trend or compression breaks
2️⃣ 𝓣𝓻𝓮𝓷𝓭 Mode
🧭 Use Case: Stable continuation and trend following
🔍 Logic:
• Signal triggers when value crosses a calculated midline or long-term average
• Thresholds: midline or 365-SMA of smoothed value
• Acts as a stable “bias direction” for trades
🎯 Ideal for:
• Swing trading
• Portfolio allocations
• Holding directional exposure longer
3️⃣ 𝓗𝓐 𝓒𝓪𝓷𝓭𝓵𝓮𝓼 Mode
🎨 Use Case: Visual clarity + phase detection
🔍 Logic:
• Converts signal to Heikin-Ashi candles
• Adds logic for momentum, reversal, continuation, or chop
• Highly discretionary and pattern-oriented
🎯 Ideal for:
• Visual traders
• Phase-based strategies
• Avoiding false positives in chop
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3. 📊 System Sensor Table (Strength Meter)
MA Thrust Processor includes a sophisticated sensor display with multi-layered insights.
🔁 Signal State
• Long ⟹ bullish conviction or thrust
• Short ⟹ bearish dominance or rejection
• Cash ⟹ neutrality or low conviction
Dynamically generated by logic mode and indicator thresholds.
📊 Strength Bars: Conviction + Potential
Strength output is never binary — instead, it’s expressed via:
1️⃣ Conviction Strength (when signal is active):
• Score from 0% to 100%
• Based on:
o Momentum velocity (Rate of Change)
o Distance from key thresholds
o Divergence signal (Wave mode)
o Flat signal detection (for Normalized)
2️⃣ Potential Strength (when signal = neutral):
• Displays both Bullish and Bearish readiness
• Interprets which side is loading pressure
• Helps traders spot “who has the edge” before breakout
👀 In Wave Mode, potential is calculated from oscillator vs. smoothed
👀 In Impulse/Trend, it blends distance + RoC + signal stability
🔸 HA Candle Phase (HA Mode Only)
When HA mode is active, strength bars are replaced with a live phase classifier:
• Momentum Up/Down: price above/below threshold + same color trend
• Reversal Up/Down: price above/below bounds, opposite signal color
• Continuation Up/Down: following a breakout/confirmation
• Chop: indecision zone
• Neutral: no clear trend
This turns HA mode into a narrative engine, expressing what’s happening, why, and what might come next.
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4. 🧠 Smart Auto-Configuration
Enabling Use Recommended Settings triggers optimized configurations:
• Pre-set thresholds (static, percentile, SD)
• Ideal lengths for each logic type
• Proper bounds scaling
• MA selections that match the logic
For example:
• Impulse + Thrust ⇒ shorter length + SD
• Trend + Z-Score ⇒ long mean-based
• Wave ⇒ balanced smoothing + SD blend
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5. 🧪 Summary of Use Cases
Each mode and calculation method within the MA Thrust Processor is tailored for specific trading styles and market conditions. Here’s how to think about their best applications:
🔹 Signal Modes
Impulse Mode is designed for speed and responsiveness. It excels in fast markets where breakouts or sharp reversals happen quickly. Ideal for scalpers, intraday traders, or anyone looking to catch momentum just as it ignites. It’s particularly effective around high-impact events like economic reports or news catalysts, as it picks up directional shifts rapidly.
Trend Mode focuses on longer-term, stable price action. It identifies directional bias using midline or average-based thresholds, making it best for swing traders and trend followers. Because of its stability, it filters out minor fluctuations and helps you stay in trades longer when the directional move is sustained.
HA Candles Mode is for traders who prefer a visual, phase-based approach. It smooths data using Heikin-Ashi logic and adds interpretive layers like "Momentum," "Reversal," or "Chop" to describe what’s happening structurally. This is excellent for discretionary traders, those who use price rhythm or structure, and those seeking cleaner entry points in noisy environments.
🔹 Calculation Methods
Wave is an oscillator-based model. It detects momentum swings and divergence between price and the smoothed oscillator. Great for spotting early reversals, pullback continuations, or cyclical rhythm patterns. In Impulse mode, it shows histogram shifts that reflect internal thrust dynamics.
Thrust quantifies directional pressure by comparing the signal’s distance from both the midpoint of price range and an SMA. This method is powerful when you want to assess how much true force is behind a move — especially useful during breakout scenarios or strong directional pushes.
Z-Score mode normalizes the signal to its statistical distance from the mean. This makes it ideal for mean reversion strategies or situations where price has deviated too far from historical behavior. Traders can look for exhaustion zones or pullback opportunities with greater confidence.
Normalized rescales the signal within a 0–1 range (centered at 0.5), helping traders understand where the price sits within its own context — whether it’s relatively extended or compressed. It’s great for range traders, flat market identification, or mapping gradual bias accumulation.
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Each mode and method has been thoughtfully designed to align with different strategy frameworks — and switching between them completely reconfigures the way the system operates, giving traders unmatched flexibility across timeframes and asset classes
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🧭 Conclusion
MA Thrust Processor isn’t just a tool - it’s a precision-calibrated thrust engine that gives market context form. It lets you define your logic, style, and MA behavior while delivering rich visual output and conviction-based strength insight.
Whether you're reading momentum waves, modeling thrust deviation, or interpreting candle structure, MTP adapts to your strategy.
🚀 From short-term scalps to long-term rotations, MTP delivers signal clarity with the quantitative conviction needed in modern markets.
📌 Trade with Statistical Precision | Powered by QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
Polarity-VoVix Fusion Index (PVFI) Polarity-VoVix Fusion Index (PVFI) - Order Flow and Volatility Regime Detector
The PVFI is a next-generation indicator that fuses the Order Flow Polarity Index (OFPI) with a proprietary VoVix Volume Delta (VVD) engine. This tool is designed for traders who want to see not just how much volume is trading, but who is in control and how volatility is shifting beneath the surface.
What Makes PVFI Standout from the rest?
- Dual Engine: PVFI combines two advanced signals:
* OFPI: Measures real-time buy/sell pressure using candle body position and volume, then smooths it with a T3 moving average for clarity and responsiveness.
* VVD: Captures the "volatility of volume delta" - a normalized, memory-boosted measure of aggressive buying/selling, with a custom non-linear clamp for organic, non-pegged signals.
- Visual Clarity: Neon-glow OFPI line and shadowed, color-gradient VVD area make regime shifts and momentum instantly visible.
- Adaptive Dashboard: Toggle between a full-featured dashboard (desktop) and a compact info line (mobile) for seamless use on any device.
- Universal: Works on any asset - crypto, stocks, futures, forex - and any timeframe.
- No Chart Clutter: Clean, modern visuals and toggles for a pro look.
Inputs:
OFPI Lookback Length (ofpi_len): Sets the window for order flow pressure calculation. Shorter = more sensitive, longer = smoother. For scalping, try 5-10. For swing trading, 15-30. Crypto often benefits from shorter windows due to volatility.
OFPI T3 Smoothing Length (t3_len): Controls the smoothness of the OFPI line. Lower = more responsive, higher = smoother. Use 3-7 for fast markets, 8-15 for slow or higher timeframes.
OFPI T3 Volume Factor (t3_vf): Adjusts the T3’s sensitivity. Higher = more responsive, lower = more stable. 0.6-0.8 is typical. Raise for more “snappy” signals, lower for less noise.
VVD Delta Lookback (delta_len): Sets the window for VVD’s volume delta calculation. 10-20 for most assets. Shorter for high-volatility, longer for slow markets.
VVD Volatility Normalization Length (vol_norm_len): Normalizes VVD by recent volume. 15-30 is typical. Use higher for assets with wild volume swings.
VVD Momentum Memory (momentum_mem): Adds a “memory” boost to VVD, amplifying persistent buying/selling. 2-5 is common. Lower for choppy markets, higher for trending.
Show Dashboard (showDash): Toggles the full dashboard table (best for desktop). Turn off for a minimalist or mobile setup.
Show Compact Info Line (showInfoLabel): Toggles a single-line info label (best for mobile). Turn on for mobile or minimalist setups.
How PVFI Works:
- OFPI Calculation: Splits each candle’s volume into buy/sell pressure based on where the close is within the range. Aggregates over your chosen lookback, then smooths with a T3 moving average for a neon, lag-minimized signal.
- VVD Calculation: Measures the “aggression” of volume (body-weighted), normalizes by recent volume, and applies a memory boost for persistent trends. Uses a custom tanh clamp for a natural, non-pegged range.
- Visuals: OFPI is plotted as a neon line (with glow). VVD is a color-gradient area with a soft shadow, instantly showing regime shifts.
- Dashboard/Info Line: Desktop: Full dashboard with all key stats, color-coded and branded. Mobile: Compact info line with arrows for quick reads.
How you'll use PVFI:
- Bullish OFPI (Teal Neon, Up Arrow): Buyers are dominating. Look for breakouts, trend continuations, or confirmation with your own system.
- Bearish OFPI (Green Neon, Down Arrow): Sellers are in control. Watch for breakdowns or short setups.
- VVD Positive (Teal Area): Aggressive buying is increasing. Confirm with price action.
- VVD Negative (Purple Area): Aggressive selling is increasing. Use for risk management or short bias.
- Neutral/Flat: Market is balanced or indecisive. Consider waiting for a clear regime shift.
- Dashboard/Info Line: Use the dashboard for full context, or the info line for a quick glance on mobile.
Tips:
- For scalping, use lower lookbacks and smoothing.
- For swing trading, increase lookbacks and smoothing for stability.
- Works on all assets and timeframes - tune to your style.
Why PVFI is Unique:
- Fusion of Order Flow and Volatility: No other indicator combines body-based order flow with a volatility-of-volume delta, both visualized with modern, pro-grade graphics.
- Adaptive, Not Static: PVFI adapts to market regime, not just price movement.
- Mobile-Ready: Dashboard and info line toggles for any device.
- No Chart Clutter: Clean, color-coded, and easy to read.
For Educational Use Only
PVFI is a research and educational tool, not financial advice. Always use proper risk management and combine with your own strategy.
Trade with clarity. Trade with edge.
— Dskyz , for DAFE Trading Systems
50-Week High Entry / 40-Week Low Exit StrategyThis is a simple long term strategy
Entry condition : You will enter the market when the stock’s current high exceeds its 50-week high. This condition enables you to identify upward momentum and capitalize on potential price surges.
Exit condition
Conversely, you will exit the market when the stock’s current low drops below its 40-week low. This exit strategy helps protect your capital by ensuring you withdraw from losing positions before further declines in price occur.
This trading strategy relies on the Donchian Channel indicator to monitor the relevant 50-week high and 40-week low levels. Given that this is a weekly trading strategy, all backtesting will be conducted using weekly timeframes.
Al Brooks Open Quality StatusThis indicator helps traders objectively evaluate the quality of the market open, based on core concepts from Al Brooks’ price action methodology.
It analyzes the most recent bars (default: 18) after the regular session opens at 09:30 ET, to determine whether conditions favor breakout trading or indicate a choppy, range-bound environment that should be avoided.
🔍 How It Works
The algorithm checks:
• ✅ Opening Range Strength – compares price range vs. ATR
• ✅ Small Body Bar % – high % = indecision and poor follow-through
• ✅ Bar Overlap % – tight overlap signals trapped, two-sided price action
• ✅ Optional RTH-only analysis toggle – to focus strictly on the NY session
If all conditions are favorable, the indicator will show:
✅ Good to Trade
If not, it will display:
⚠️ Choppy Conditions or ⏳ Waiting for 09:30 before the session begins.
A color-coded info box in the top-right corner summarizes the current environment.
UT Bot + Hull MA Confirmed Signal DelayOverview
This indicator is designed to detect high-probability reversal entry signals by combining "UT Bot Alerts" (UT Bot Alerts script adapted from QuantNomad - Originally developed by Yo_adriiiiaan and idea of original code for "UT Bot Alerts" from HPotter ) with confirmation from a Hull Moving Average (HMA) Developed by Alan Hull . It focuses on capturing momentum shifts that often precede trend reversals, helping traders identify potential entry points while filtering out false signals.
🔍 How It Works
This strategy operates in two stages:
1. UT Bot Momentum Trigger
The foundation of this script is the "UT Bot Alerts" , which uses an ATR-based trailing stop to detect momentum changes. Specifically:
The script calculates a dynamic stop level based on the Average True Range (ATR) multiplied by a user-defined sensitivity factor (Key Value).
When price closes above this trailing stop and the short-term EMA crosses above the stop, a potential buy setup is triggered.
Conversely, when price closes below the trailing stop and the short-term EMA crosses below, a potential sell setup is triggered.
These UT Bot alerts are designed to identify the initial shift in market direction, acting as the first filter in the signal process.
2. Hull MA Confirmation
To reduce noise and false triggers from the UT Bot alone, this script delays the entry signal until price confirms the move by crossing the Hull Moving Average (or its variants: HMA, THMA, EHMA) in the same direction as the UT Bot trigger:
A Buy Signal is generated only when:
A UT Bot Buy condition is active, and
The price closes above the Hull MA.
Or, if a UT Bot Buy condition was recently triggered but price hadn’t yet crossed above the Hull MA, a delayed buy is signaled when price finally breaks above it.
A Sell Signal is generated only when:
A UT Bot Sell condition is active, and
The price closes below the Hull MA.
Similarly, a delayed sell signal can occur if price breaks below the Hull MA shortly after a UT Bot Sell trigger.
This dual-confirmation process helps traders avoid premature entries and improves the reliability of reversal signals.
📈 Best Use Cases
Reversal Trading: This strategy is particularly well-suited for catching early trend reversals rather than trend continuations. It excels at identifying momentum pivots that occur after pullbacks or exhaustion moves.
Heikin Ashi Charts Recommended: The script offers a Heikin Ashi mode for smoothing out noise and enhancing visual clarity. Using Heikin Ashi candles can further reduce whipsaws and highlight cleaner shifts in trend direction.
MACD Alignment: For best results, trade in the direction of the MACD trend or use it as a filter to avoid counter-trend trades.
⚠️ Important Notes
Entry Signals Only: This indicator only plots entry points (Buy and Sell signals). It does not define exit strategies, so users should manage trades manually using trailing stops, profit targets, or other exit indicators.
No Signal = No Confirmation: You may see a UT Bot trigger without a corresponding Buy/Sell signal. This means the price did not confirm the move by crossing the Hull MA, and therefore the setup was considered too weak or incomplete.
⚙️ Customization
UT Bot Sensitivity: Adjust the “Key Value” and “ATR Period” to make the UT Bot more or less reactive to price action.
Use Heikin Ashi: Toggle between standard candles or Heikin Ashi in the indicator settings for a smoother trading experience.
The HMA length may also be modified in the indicator settings from its standard 55 length to increase or decrease the sensitivity of signal.
This strategy is best used by traders looking for a structured, logic-based way to enter early into reversals with added confirmation to reduce risk. By combining two independent systems—momentum detection (UT Bot) and trend confirmation (Hull MA)—it aims to provide high-confidence entries without overwhelming complexity.
Let the indicator guide your entries—you manage the exits.
Examples of use:
Futures:
Stock:
Crypto:
As shown in the snapshots this strategy, like most, works the best when price action has a sizeable ATR and works the least when price is choppy. Therefore it is always best to use this system when price is coming off known support or resistance levels and when it is seen to respect short term EMA's like the 9 or 15.
My personal preference to use this system is for day trading on a 3 or 5 minute chart. But it is valid for all timeframes and simply marks a high probability for a new trend to form.
Sources:
Quant Nomad - www.tradingview.com
Yo_adriiiiaan - www.tradingview.com
HPotter - www.tradingview.com
Hull Moving Average - alanhull.com
Circuit % Marker w/ Mirrored Arrows📈 Indian Market Circuit Limit Change Tracker
This indicator automatically tracks circuit limit changes (price bands) as applied in NSE/BSE stocks.
🧠 How It Works:
Start from a user-defined initial circuit limit (e.g. 10%)
If the upper or lower limit is hit, the script waits for a user-defined cooling period (e.g. 5 trading days)
After that, it automatically adjusts to the next lower or higher band (e.g. from 10% to 5%)
Shows a visual label with the current circuit % right on the chart — placed above or below candles for better visibility
🔧 Custom Inputs:
Starting Circuit % — choose between standard NSE/BSE values (20%, 10%, 5%, 2%)
Cooling Days — how many days must pass after a circuit hit before it’s allowed to change again
Label Positioning, Color, and Size — fully customizable to suit your chart style
🚫 No Clutter:
Doesn’t draw circuit limit lines
Just clean, small labels at key turning points — as seen in real trading dashboards
🔍 Notes:
NSE and BSE manually assign circuit bands — this script does not fetch live exchange data
Use it as a visual tracker and simulator of how circuit behavior would evolve under fixed rules
Adaptive Pulsar Momentum | QuantEdgeB⚡ Adaptive Pulsar Momentum | QuantEdgeB
🔭 What is Adaptive Pulsar Momentum?
The Adaptive Pulsar Momentum (APM) is a high-performance, modular trading system designed to decode market momentum across a range of conditions. It combines multi-indicator adaptability (RSI, MFI, Z-Score, ROC, and a hybrid AVG mode) with dynamic signal generation using five advanced "modes" of signal logic: Impulse, Trend, Heikin-Ashi Candles, Statistical Deviation, and MACD.
💡 Think of APM as a scientific instrument, scanning, adapting, and broadcasting precision-tuned momentum data in real-time, helping traders eliminate noise, guesswork, and lag.
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1.🔧 System Core: Customizability and Adaptation
📊 Indicator Modes
• 𝓡𝓢𝓘 (Relative Strength Index): Classic oscillator detecting overbought/oversold zones.
• 𝓩-𝓢𝓒𝓞𝓡𝓔: Normalized deviation from mean; ideal for statistical reversion plays.
• 𝓜𝓕𝓘 (Money Flow Index): Volume-weighted RSI-style metric.
• 𝓡𝓞𝓒 (Rate of Change): Measures the velocity of price change.
• 𝓐𝓥𝓖: Combines RSI, MFI, Z-Score, and ROC into a unified signal (normalized to 0–100 scale).
🧠 MA Engine (Smoothing)
Over a dozen moving average types:
• Includes ALMA, TEMA, JMA, SMMA, HMA, LSMA, VWMA, and more.
• Dynamic smoothing makes this system versatile across markets and timeframes.
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2.🧨 SIGNAL MODES – THE ENGINE ROOM
Each mode turns the raw smoothed indicator into a powerful momentum signal with thresholds and logic specific to the use case.
1️⃣ 𝓘𝓶𝓹𝓾𝓵𝓼𝓮 Mode
🚀 Use case:
Best for detecting explosive, fast-moving momentum before the crowd catches on.
🔍 Logic:
• Thresholds can be Static, Percentile-based, or Standard Deviation derived.
• Dynamic signal: +1 for breakout, -1 for breakdown, 0 for neutral.
• Custom threshold percentiles enable precise tuning.
🎯 Ideal for:
• Scalping breakouts
• Event-driven spikes (e.g., CPI, FOMC)
• Early trend initiation
2️⃣ 𝓣𝓻𝓮𝓷𝓭 Mode
🧭 Use case:
Built to identify and follow trends with minimal noise. Stable, low-churn logic for riding moves.
🔍 Logic:
• Signal generated via cross above/below a calculated midline (either fixed or dynamic mean).
• Best paired with SMMA or TEMA smoothing.
🎯 Ideal for:
• Swing traders
• Momentum trend followers
• Portfolio rotation strategies
3️⃣ 𝓗𝓐 𝓒𝓪𝓷𝓭𝓵𝓮𝓼 Mode
🔥 Use case:
Filters volatility while capturing structural momentum shifts using Heikin-Ashi logic on smoothed indicators.
🔍 Logic:
• Converts the smoothed signal into Heikin-Ashi candles.
• Measures close vs open to determine trend direction.
• Thresholds again can be static, percentile, or SD-based.
🎯 Ideal for:
• Visual trend clarity
• Avoiding whipsaws in sideways markets
• Discretionary trading with cleaner structure
• Mean-Reverting
4️⃣ 𝓢𝓽𝓪𝓽𝓲𝓼𝓽𝓲𝓬𝓪𝓵 𝓓𝓮𝓿𝓲𝓪𝓽𝓲𝓸𝓷 Mode
🧪 Use case:
Detects high-volatility expansions before or during major directional surges.
🔍 Logic:
• Calculates absolute deviation using HA open vs close.
• Filters this with a moving average and overlays a volatility cloud.
• Breaks above/below the cloud signal directional surge.
🎯 Ideal for:
• Pre-breakout scanning
• Identifying regime shifts
• Options traders looking for volatility expansions
5️⃣ 𝓜𝓐𝓒𝓓 Mode
🧲 Use case:
Classic MACD principles adapted to smoothed momentum indicators—ideal for trend continuation or crossovers.
🔍 Logic:
• MACD line = Pulsar signal - EMA of signal.
• Thresholds (up/down) define bias.
• Optional extra filter to validate with midline crossing.
🎯 Ideal for:
• Trend confirmation
• Crossover-based entry strategies
• Confluence with higher timeframe bias
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3.📊 System Sensor Table
Adaptive Pulsar Momentum includes a live multi-layered analytics table designed to give traders a complete pulse on current market behavior. Here's what each section reveals:
🔁 System Signal
At any given bar, the algorithm outputs one of three states:
• Long ⟹ Bullish conditions are active and sustained
• Short ⟹ Bearish momentum dominates
• Cash ⟹ Neutral zone — conditions lack a strong directional bias
This is dynamically adjusted based on the selected signal mode (Impulse, Trend, etc.) and adapts in real time to shifts in smoothed oscillator logic or candle structure.
📊 Strength: Conviction & Potential
Unlike binary signals, this table offers graded insights into how strong or fragile the signal actually is, a huge upgrade from traditional systems.
There are two distinct layers:
1. Conviction Strength –> shown when the system is in a full long or short signal.
- A value like “Long Strength: 84%” means there's high confidence in the continuation or follow-through of the current bias.
- It blends distance from threshold, momentum velocity (Rate of Change), and position in range to avoid false positives and overstretched signals.
2. Potential Strength –> shown during neutral (Cash) periods.
- Two bars appear: one for bullish potential, another for bearish potential.
- These answer: “If the market were to move soon, which side has the edge?”
- Example: "↗ 68% / ↘ 32%" means bulls have more pent-up energy or structure.
These bars provide pre-signal tension, helping traders anticipate breakouts or avoid traps during choppy periods.
🔸 HA Candle Phase (When Mode = HA Candles)
Instead of showing strength bars, this mode displays a phase label, interpreting the Heikin-Ashi candle structure in context of momentum and thresholds:
- Momentum Up / Down –> Strong impulse direction confirmed above or below dynamic bounds.
- Reversal Up / Down –> Early signs of potential reversals (price beyond bounds but opposite signal ).
- Continuation Up / Down –> Sustained movement after a signal confirmation (post-threshold cross).
- Chop –> Sideways indecisiveness, often signaling to reduce risk or await clarity.
- Neutral –> No active momentum or pattern signal.
This provides a narrative view of market behavior, ideal for discretionary traders who rely on visual rhythm and pattern recognition.
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5. 🧠 Optional Smart Configuration
Enable “Use Recommended Settings” to auto-configure:
• Optimized lengths
• Best-suited moving averages
• Signal type filters
• Volatility lookbacks
Perfect for those wanting precision without manual tuning.
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6.🧪 Use Cases by Mode Summary
🔹 Impulse Mode
Ideal for traders looking to capitalize on sharp breakouts or high-momentum reversals. This mode is built for speed and sensitivity, making it a go-to for scalping, reacting to news events, or identifying trends at their earliest inflection points.
🔹 Trend Mode
Engineered for longer-term positioning, this mode tracks sustained directional bias over time. Best suited for swing traders or those managing portfolio allocations, it's focused on the midline dynamics that define trend health and commitment.
🔹 HA Candles Mode
This mode filters out noise through smoothed Heikin-Ashi transformations, providing clean visual structure. It's perfect for discretionary traders, pattern recognizers, or those looking to enter pullbacks within broader trends. The phase system (e.g. Momentum, Reversal, Chop) adds narrative context to price action.
🔹 Statistical Deviation Mode
A quantitative engine for traders who thrive on volatility exploitation. By modeling deviations from mean behavior, it's particularly powerful in options strategies, regime detection, or scanning for expansion conditions. This mode excels when price breaks away from standard norms.
🔹 MACD Mode
The classic concept of momentum meets modern smoothing in this variant. Use this for confirmation, spotting divergences, or executing crossover-based strategies. MACD mode gives clarity in ambiguous zones, favoring structured continuation or reversal bias.
Each mode is uniquely crafted for a different style of trader and market environment, and switching between them transforms the entire engine’s behavior
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🧭 Conclusion
Adaptive Pulsar Momentum isn’t just a signal tool, it’s a market intelligence system. Whether you’re scalping volatility, swinging trends, or navigating uncertain chop, APM dynamically adjusts to the rhythm of the market. With precision-tuned signal modes, a smart strength matrix, and plug-and-play configuration, it transforms raw momentum into actionable clarity.
📌 Trade with Statistical Precision | Powered by QuantEdgeB
🔹 Disclaimer: Past performance is not indicative of future results.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
JPMorgan G7 Volatility IndexThe JPMorgan G7 Volatility Index: Scientific Analysis and Professional Applications
Introduction
The JPMorgan G7 Volatility Index (G7VOL) represents a sophisticated metric for monitoring currency market volatility across major developed economies. This indicator functions as an approximation of JPMorgan's proprietary volatility indices, providing traders and investors with a normalized measurement of cross-currency volatility conditions (Clark, 2019).
Theoretical Foundation
Currency volatility is fundamentally defined as "the statistical measure of the dispersion of returns for a given security or market index" (Hull, 2018, p.127). In the context of G7 currencies, this volatility measurement becomes particularly significant due to the economic importance of these nations, which collectively represent more than 50% of global nominal GDP (IMF, 2022).
According to Menkhoff et al. (2012, p.685), "currency volatility serves as a global risk factor that affects expected returns across different asset classes." This finding underscores the importance of monitoring G7 currency volatility as a proxy for global financial conditions.
Methodology
The G7VOL indicator employs a multi-step calculation process:
Individual volatility calculation for seven major currency pairs using standard deviation normalized by price (Lo, 2002)
- Weighted-average combination of these volatilities to form a composite index
- Normalization against historical bands to create a standardized scale
- Visual representation through dynamic coloring that reflects current market conditions
The mathematical foundation follows the volatility calculation methodology proposed by Bollerslev et al. (2018):
Volatility = σ(returns) / price × 100
Where σ represents standard deviation calculated over a specified timeframe, typically 20 periods as recommended by the Bank for International Settlements (BIS, 2020).
Professional Applications
Professional traders and institutional investors employ the G7VOL indicator in several key ways:
1. Risk Management Signaling
According to research by Adrian and Brunnermeier (2016), elevated currency volatility often precedes broader market stress. When the G7VOL breaches its high volatility threshold (typically 1.5 times the 100-period average), portfolio managers frequently reduce risk exposure across asset classes. As noted by Borio (2019, p.17), "currency volatility spikes have historically preceded equity market corrections by 2-7 trading days."
2. Counter-Cyclical Investment Strategy
Low G7 volatility periods (readings below the lower band) tend to coincide with what Shin (2017) describes as "risk-on" environments. Professional investors often use these signals to increase allocations to higher-beta assets and emerging markets. Campbell et al. (2021) found that G7 volatility in the lowest quintile historically preceded emerging market outperformance by an average of 3.7% over subsequent quarters.
3. Regime Identification
The normalized volatility framework enables identification of distinct market regimes:
- Readings above 1.0: Crisis/high volatility regime
- Readings between -0.5 and 0.5: Normal volatility regime
- Readings below -1.0: Unusually calm markets
According to Rey (2015), these regimes have significant implications for global monetary policy transmission mechanisms and cross-border capital flows.
Interpretation and Trading Applications
G7 currency volatility serves as a barometer for global financial conditions due to these currencies' centrality in international trade and reserve status. As noted by Gagnon and Ihrig (2021, p.423), "G7 currency volatility captures both trade-related uncertainty and broader financial market risk appetites."
Professional traders apply this indicator in multiple contexts:
- Leading indicator: Research from the Federal Reserve Board (Powell, 2020) suggests G7 volatility often leads VIX movements by 1-3 days, providing advance warning of broader market volatility.
- Correlation shifts: During periods of elevated G7 volatility, cross-asset correlations typically increase what Brunnermeier and Pedersen (2009) term "correlation breakdown during stress periods." This phenomenon informs portfolio diversification strategies.
- Carry trade timing: Currency carry strategies perform best during low volatility regimes as documented by Lustig et al. (2011). The G7VOL indicator provides objective thresholds for initiating or exiting such positions.
References
Adrian, T. and Brunnermeier, M.K. (2016) 'CoVaR', American Economic Review, 106(7), pp.1705-1741.
Bank for International Settlements (2020) Monitoring Volatility in Foreign Exchange Markets. BIS Quarterly Review, December 2020.
Bollerslev, T., Patton, A.J. and Quaedvlieg, R. (2018) 'Modeling and forecasting (un)reliable realized volatilities', Journal of Econometrics, 204(1), pp.112-130.
Borio, C. (2019) 'Monetary policy in the grip of a pincer movement', BIS Working Papers, No. 706.
Brunnermeier, M.K. and Pedersen, L.H. (2009) 'Market liquidity and funding liquidity', Review of Financial Studies, 22(6), pp.2201-2238.
Campbell, J.Y., Sunderam, A. and Viceira, L.M. (2021) 'Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds', Critical Finance Review, 10(2), pp.303-336.
Clark, J. (2019) 'Currency Volatility and Macro Fundamentals', JPMorgan Global FX Research Quarterly, Fall 2019.
Gagnon, J.E. and Ihrig, J. (2021) 'What drives foreign exchange markets?', International Finance, 24(3), pp.414-428.
Hull, J.C. (2018) Options, Futures, and Other Derivatives. 10th edn. London: Pearson.
International Monetary Fund (2022) World Economic Outlook Database. Washington, DC: IMF.
Lo, A.W. (2002) 'The statistics of Sharpe ratios', Financial Analysts Journal, 58(4), pp.36-52.
Lustig, H., Roussanov, N. and Verdelhan, A. (2011) 'Common risk factors in currency markets', Review of Financial Studies, 24(11), pp.3731-3777.
Menkhoff, L., Sarno, L., Schmeling, M. and Schrimpf, A. (2012) 'Carry trades and global foreign exchange volatility', Journal of Finance, 67(2), pp.681-718.
Powell, J. (2020) Monetary Policy and Price Stability. Speech at Jackson Hole Economic Symposium, August 27, 2020.
Rey, H. (2015) 'Dilemma not trilemma: The global financial cycle and monetary policy independence', NBER Working Paper No. 21162.
Shin, H.S. (2017) 'The bank/capital markets nexus goes global', Bank for International Settlements Speech, January 15, 2017.
ADR & ATR Extension from EMAThis indicator helps identify how extended the current price is from a chosen Exponential Moving Average (EMA) in terms of both Average Daily Range (ADR) and Average True Range (ATR).
It calculates:
ADR Extension = (Price - EMA) / ADR
ATR Extension = (Price - EMA) / ATR
The results are shown in a floating table on the chart.
The ADR line turns red if the price is more than 4 ADRs above the selected EMA
Customization Options:
- Select EMA length
- Choose between close or high as price input
- Set ADR and ATR periods
- Customize the label’s position, color, and transparency
- Use the chart's timeframe or a fixed timeframe
Breakout Core | by Solid#SignalsBreakout Core | by SolidSignals
General Overview
Breakout Core is an advanced breakout trading strategy designed for Bitcoin (BTC). Optimized for the unique market dynamics following the launch of BlackRock’s Spot ETFs in January 2024, it adapts to Bitcoin’s post-ETF volatility patterns. The strategy’s core strength lies in its low drawdown, achieved through a proprietary time-based signal-filtering algorithm that sets it apart from traditional breakout strategies. Breakout Core offers traders a reliable tool for navigating Bitcoin’s evolving market with reduced risk and enhanced precision.
Mechanisms
Breakout Core combines well-known indicators BB, EMAs, MAs with custom-tuned parameters to improve signal accuracy. Its unique feature is a proprietary time-filter algorithm that prioritizes high-probability breakout signals during specific high-volatility trading hours, derived from market analysis post-ETF launch. This algorithm minimizes false positives, particularly in volatile conditions, by integrating time-based volatility patterns with price action. The result is a robust strategy that optimizes entry and exit points for Bitcoin trading.
Objectives
Breakout Core aims to provide steady returns with controlled risk by targeting Bitcoin’s breakout patterns in the post-ETF market. Its low drawdown, achieved through extensive optimization and proprietary logic, makes it suitable for leverage trading (e.g., 3–5x leverage), balancing growth with capital protection. Tailored for BTC, the strategy equips traders with a precise tool to navigate Bitcoin’s transformed market dynamics.
Backtesting and Parameter Notes
Backtesting was performed using a $10,000 USDT account, risking up to 10% of equity per trade, including 0.06% commission fees and 2-tick slippage, aligned with standard exchange conditions. The strategy report details backtesting results from the launch of BlackRock’s Spot ETFs. These settings are the script’s defaults, ensuring transparency. Traders are encouraged to verify results using TradingView’s Deep Backtest feature to adapt to current market conditions.
Please note: Past performance does not guarantee future results.
Chart and Usage
The chart is clean and intuitive, displaying only Breakout Core’s buy and sell signals for easy interpretation. Parameters are pre-optimized for immediate use, with adjustable Take Profit (TP) and Stop Loss (SL) levels. Traders should validate custom settings via TradingView’s backtesting tools to ensure market compatibility. An integrated Alarm Panel supports API connectivity, providing clear Entry/Exit commands for Long and Short positions, enabling seamless automated trading workflows.
Originality Statement
Breakout Core is an original strategy developed by SolidSignals, leveraging standard indicators (Bollinger Bands, EMAs, MAs) combined with a proprietary time-filter algorithm. No third-party or open-source code is used, ensuring full compliance with TradingView’s originality requirements. The time-filter mechanism, based on post-ETF volatility analysis, distinguishes this strategy from conventional breakout approaches.
Important Disclaimer
Market conditions evolve continuously, and past performance is not indicative of future results. Traders are responsible for validating the strategy’s settings and performance under current market conditions before use.
India VIX TableThis indicator gives you the India Vix value in real time on your chart. You can change the position on the chart as per your preference.
ABC Market stage judgmentABC Stage Judgment Indicators · Introduction
Core ideology
The market situation is divided into three stages:
Zone B (Low Volatility Accumulation): Extremely low volatility, no trend, institutions accumulate chips.
Zone A (oscillation zone): The volatility has rebounded but there is no unilateral trend, suitable for short-term high selling and low buying.
Zone C (Trend Explosion): The volatility has significantly expanded and the trend is strong, making it profitable to follow the position.
Core Indicators
Volatility measurement
Bollinger Bands Width (BBWidth): 20 cycle moving average ± 2 σ bandwidth, reflecting relative volatility compression/release;
ATR (Average True Volatility): measures the absolute intensity of price volatility.
Trend Strength
ADX (Average Trend Index): measures the strength of a trend (without distinguishing direction),
ADX<20 → No trend (Zone B/A)
ADX>25 → Significant trend (Zone C)
Stage division logic
Zone B: Both BWidth and ATR are less than the set multiple of their respective historical means, and ADX is less than the threshold → "quiet bottoming out";
Zone C: ADX>threshold, and BBWidth or ATR>set multiple of their respective historical means, trading volume amplification → "trend takeoff";
Zone A: Time periods that do not belong to B/C are all classified as oscillation zones.
Optional enhanced filtering
Direction confirmation (+DI/- DI): avoid going against the trend;
Multi cycle verification (4H): in line with the trend of large-scale;
Momentum filtering (ROC/MACD/RSI): ensuring kinetic energy support;
ATR slope: Confirm the release of fluctuations;
Breakthrough Confirmation: Enter only after the breakthrough is confirmed at the closing level.
These filters are turned off by default and can be selected with one click for different scenarios such as "high-level oscillation", "low-level bottoming", "planting trees in the middle", etc.
usage
Multi cycle switching: Built in "5-minute/1-hour" two main cycles for free switching;
Visualization: The background color and labels display the current Zone at a glance;
Alarm: Stage switching automatically triggers an Alert, which can be pushed through mobile phones/Telegram.
ADX EMA's DistanceIt is well known to technical analysts that the price of the most volatile and traded assets do not tend to stay in the same place for long. A notable observation is the recurring pattern of moving averages that tend to move closer together prior to a strong move in some direction to initiate the trend, it is precisely that distance that is measured by the blue ADX EMA's Distance lines on the chart, normalized and each line being the distance between 2, 3 or all 4 moving averages, with the zero line being the point where the distance between them is zero, but it is also necessary to know the direction of the movement, and that is where the modified ADX will be useful.
This is the well known Directional Movement Indicator (DMI), where the +DI and -DI lines of the ADX will serve to determine the direction of the trend.
Gabriel's Squeeze Momentum PRO“Gabriel’s Squeeze Momentum PRO” is a next-generation evolution of the classic SQZMOM concept. It layers multiple John Ehlers filters, Jurik smoothing, adaptive cycle-detection, and a Cauchy-weighted price filter on top of the familiar Bollinger-Band-inside-Keltner-Channel squeeze logic. The goal is to pinpoint volatility contractions and immediately gauge whether forthcoming expansion is likely to break bullish or bearish—while screening out noise, lag, and regime shifts across any symbol or timeframe.
1 · What the script plots
Plot What it represents Why it matters
Momentum line (teal/red) Price-de-trended linear-regression of a Cauchy-filtered source, optionally normalized. Measures directional thrust during / after a squeeze.
Signal line (white JMA) Jurik moving average of the momentum line. Smooth trigger for crossovers / reversals.
Squeeze dots (blue, black, red, yellow, purple, green) Real-time volatility state: No squeeze → Wide → Normal → Narrow → Very Narrow → Fired. Helps anticipate explosive moves as BB exits KC.
Cyclic RSI bands (cyan / fuchsia) Dynamic overbought / oversold bands derived by MESA dominant-cycle analysis. Contextualizes momentum extremes—no fixed 70/30.
Rate-of-Change (optional) (orange / blue shading) ROC of the momentum-signal spread, scaled. Highlights acceleration / deceleration.
Reversal guide lines (optional colored rays) Drawn when momentum crosses its JMA and reversal-mode is on. Visual confirmation of early trend change.
2 · Key engine components
Cauchy PDF-weighted moving average
Creates a heavy-tailed weighting curve; center bars dominate while still capturing fat-tail outliers—excellent for choppy instruments or volume-weighting (Volume weighted?).
Butterworth High-Pass & Super-Smoother Low-Pass
Strip out drift, then smooth what’s left. This isolates true cyclic motion before momentum is computed.
Fast RMS normalizer
Converts the band-pass output into a unit-scale “power” reading—vital for adaptive thresholds.
Goertzel + MESA dominant-cycle
Auto-detects fast & slow cycles, then blends them to size overbought / oversold bands and to set the adaptiveLength (if Use Adaptive Length? is enabled).
Jurik RSX & JMA
Provide ultra-low-lag smoothing for momentum and for reversal detection.
3 · Input groups and how to tune them
Group Why change it Tips
Normalization (Unbounded / Min-Max / Standard Deviations) Puts momentum & signal on the scale that best suits the asset. Crypto / small-caps: StdDev (handles volatility).
FX / indices: Min-Max or leave unbounded for raw juice.
Cauchy Distribution Tailors the Cauchy filter. Gamma ↓ (0.1-0.4) ⇒ faster / riskier. Use Adaptive Length pairs it with MESA cycle length for auto speed control.
Rate of Change Visual momentum acceleration. Leave off (Show Rate of Change = false) if you want a cleaner pane.
Momentum Colors / Directional Momentum? Switch between classic SQZMOM coloring and trend-biased histogram. Turn on when you prefer “green-gets-greener / red-gets-redder” style signals.
Squeeze Colors & Thresholds Fine-tune what “wide / normal / narrow” mean. Larger assets (SPX, BTC-Perp): raise the thresholds a touch. Thin or low-ATR symbols: lower them.
Multi-Time-frame blocks (1 h, 4 h, D, W, M) Pre-sets for BB/KC length, squeeze thresholds, and reversal MA length per TF. The script auto-detects the chart timeframe and loads the matching row—just adjust each block once.
Reversal Signals Whether to draw vertical rays on momentum crossovers. Use on swing-trading timeframes (≥1 h) to catch early momentum flips.
4 · How to read & trade it
Scan for purple / yellow / red dots
These indicate Very-Narrow, Narrow, and Normal squeezes—markets are coiling.
Wait for a fired squeeze (green dot)
BB has pushed outside KC; volatility is expanding. Momentum direction often dictates breakout bias.
Check momentum relative to zero & signal
Bullish setup: Momentum > 0 and crossing above signal. Bearish setup: Momentum < 0 and crossing below signal. Alerts “Bullish / Bearish Trend Reversal” are raised here if enabled.
Validate with cyclic bands
If momentum launches from near the lower cyan band, bullish moves are higher-probability (symmetrical for upper fuchsia band).
Confirm trend strength
Directional-momentum histogram keeps turning brighter in trend direction; ROC is above zero and rising.
Manage the trade
First target = prior squeeze mid-range or recent swing high/low.
Consider scaling out when momentum weakens (histogram fades) or reverses through signal line.
Optional: draw the reversal rays to highlight exit zones automatically.
5 · Practical workflows
Scalpers (1-5 min)
Uncheck Use Adaptive Length, set main Length to 10-12, Gamma to 0.3.
Use ROC for ultra-fast divergences.
Treat Normal squeezes (red) as tradable; ignore Wide. Healthy Volume is ideal.
Swing traders (1 h – 4 h)
Keep default adaptive length; enable 1-H/4-H reversal blocks.
Trade only after Very-Narrow/Narrow squeezes; ride until weekly/daily reversal ray prints.
Position / Trend followers (Daily+)
Raise Wide/Normal thresholds a bit (e.g., 2.2 / 1.7).
Momentum normalization = Standard Deviations to filter regime shifts.
Combine with higher-timeframe MTF panel or moving-average ribbons.
6 · Built-in alert catalog
Alert name Fires when Typical action
🟢 Fired Squeeze Green dot appears (vol expansion already under way) Stay in trend or add on pullbacks.
🟠 Low / 🔴 Normal / 🟡 Tight / 🟣 Very Tight Respective squeeze engages Get your watch-list ready; plan trades.
🐂 Bullish / 🐻 Bearish Trend Reversal Momentum crosses signal in requested direction Entry / exit / scale adds.
Set alerts on “Once Per Bar Close” for reliable signals.
7 · Best practices & caveats
Context is king – Use higher-timeframe structure (support/resistance, VWAP, market profile) to avoid false breakouts.
Data quality – On illiquid symbols, consider turning volume weighting off (pre-market gaps distort results).
Normalization choice – Mixing different normalizations across charts can confuse muscle memory; pick one style per asset class.
Lag vs. noise – If entries feel late, lower Gamma or disable adaptive length. If too jumpy, increase Length or choose Standard-Deviation normalization.
Not a stand-alone holy grail – Combine with risk management (ATR-based stops, Kelly-fraction sizing) and confirm with price action.
Harness the script’s adaptive filtering, multi-TF presets, and rich alert suite to spot compression, time breakouts, and stay on the right side of momentum—whether you’re scalping ES futures or swing-trading alt-coins.
