TradersAID / Adaptive Smoothing Channel (use on 1W chart)TradersAID – Adaptive Smoothing Channel (use on 1-Week chart)
Overview
TradersAID – Adaptive Smoothing Channel is a two-line price overlay designed to help traders interpret trend structure and shifting momentum zones on the 1-week chart only.
Unlike traditional moving averages or fixed smoothing methods, this tool uses an adaptive approach inspired by Kalman filtering — a concept widely used in robotics and control systems to track signals in noisy environments. Applied to price, this allows the band to adapt to directional flow and volatility while filtering out distracting short-term fluctuations.
1.What It Does
This tool builds a dynamic corridor around price using:
• A faster line that follows near-term directional movement
• A slower line that anchors broader market structure
Together, they form a responsive band that:
• Tilts with trend direction (via slope)
• Expands or contracts with volatility
• Fills the space between to show directional rhythm
It’s especially useful for observing how price moves within sustained trends or compression zones, helping traders visually interpret market structure with more clarity.
2. How to Use It
• Trend Structure:
Follow the slope of the band to understand overall direction. A narrowing band may indicate consolidation; a widening band may reflect strong follow-through.
• Momentum Compression Zones:
Watch for tightening distance between the lines — this may signal the market is preparing for a structural transition or breakout.
• Clarity Layer:
Overlay this tool with others (e.g. TradersAID Warning Dots) to reduce noise and improve decision context.
3. Key Features
• Dual Adaptive Lines: One fast, one slow — capturing different time dynamics
• Shaded Fill Zone: Highlights directional bias and rhythm
• 3 Reaction Modes: Slow / Regular / Fast for different sensitivities
• Overlay Style: Plots directly on price
• Minimalist Layout: Clean visual language
4. Technical Basis (Why It’s Closed Source)
This tool is based on a custom smoothing logic inspired by Kalman filtering, adapted specifically for charting market structure.
While it does not replicate a full Kalman system, it borrows key principles: dynamically adjusting to noisy input while maintaining structural clarity.
The algorithm was developed internally to provide a visual layer that integrates into the broader TradersAID analysis system — offering something distinct from public indicators. Its behavior, flexibility, and integration were designed to serve advanced structural analysis, and as such, the script is closed to protect proprietary logic and intellectual property.
5. Settings
• Mode Selector: Fast / Regular / Slow
• Color Fill Toggle & Styling
• Frame Lock:
✅ This script is built to work exclusively on the 1-week timeframe.
6. Disclaimer
This tool is for educational and informational purposes only. It does not offer financial advice or generate trading signals. Always use with your own strategy and discretion.
Trendfollowing
RSI-Adaptive T3 + Squeeze Momentum Strategy✅ Strategy Guide: RSI-Adaptive T3 + Squeeze Momentum Strategy
📌 Overview
The RSI-Adaptive T3 + Squeeze Momentum Strategy is a dynamic trend-following strategy based on an RSI-responsive T3 moving average and Squeeze Momentum detection .
It adapts in real-time to market volatility to enhance entry precision and optimize risk.
⚠️ This strategy is provided for educational and research purposes only.
Past performance does not guarantee future results.
🎯 Strategy Objectives
The main objective of this strategy is to catch the early phase of a trend and generate consistent entry signals.
Designed to be intuitive and accessible for traders from beginner to advanced levels.
✨ Key Features
RSI-Responsive T3: T3 length dynamically adjusts according to RSI values for adaptive trend detection
Squeeze Momentum: Combines Bollinger Bands and Keltner Channels to identify trend buildup phases
Visual Triggers: Entry signals are generated from T3 crossovers and momentum strength after squeeze release
📊 Trading Rules
Long Entry:
When T3 crosses upward, momentum is positive, and the squeeze has just been released.
Short Entry:
When T3 crosses downward, momentum is negative, and the squeeze has just been released.
Exit (Reversal):
When the opposite condition to the entry is triggered, the position is reversed.
💰 Risk Management Parameters
Pair & Timeframe: BTC/USD (30-minute chart)
Capital (simulated): $30,00
Order size: `$100` per trade (realistic, low-risk sizing)
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 5%
Number of Trades (backtest period): 181
📊 Performance Overview
Symbol: BTC/USD
Timeframe: 30-minute chart
Date Range: January 1, 2024 – July 3, 2025
Win Rate: 47.8%
Profit Factor: 2.01
Net Profit: 173.16 (units not specified)
Max Drawdown: 5.77% or 24.91 (0.79%)
⚙️ Indicator Parameters
Indicator Name: RSI-Adaptive T3 + Squeeze Momentum
RSI Length: 14
T3 Min Length: 5
T3 Max Length: 50
T3 Volume Factor: 0.7
BB Length: 27 (Multiplier: 2.0)
KC Length: 20 (Multiplier: 1.5, TrueRange enabled)
🖼 Visual Support
T3 slope direction, squeeze status, and momentum bars are visually plotted on the chart,
providing high clarity for quick trend analysis and execution.
🔧 Strategy Improvements & Uniqueness
Inspired by the RSI Adaptive T3 by ChartPrime and Squeeze Momentum Indicator by LazyBear ,
this strategy fuses both into a hybrid trend-reversal and momentum breakout detection system .
Compared to traditional trend-following methods, it excels at capturing early trend signals with greater sensitivity .
✅ Summary
The RSI-Adaptive T3 + Squeeze Momentum Strategy combines momentum detection with volatility-responsive risk management.
With a strong balance between visual clarity and practicality, it serves as a powerful tool for traders seeking high repeatability.
⚠️ This strategy is based on historical data and does not guarantee future profits.
Always use appropriate risk management when applying it.
Logarithmic Moving Average (LMA) [QuantAlgo]🟢 Overview
The Logarithmic Moving Average (LMA) uses advanced logarithmic weighting to create a dynamic trend-following indicator that prioritizes recent price action while maintaining statistical significance. Unlike traditional moving averages that use linear or exponential weights, this indicator employs logarithmic decay functions to create a more sophisticated price averaging system that adapts to market volatility and momentum conditions.
The indicator displays a smoothed signal line that oscillates around zero, with positive values indicating bullish momentum and negative values indicating bearish momentum. The signal incorporates trend quality assessment, momentum confirmation, and multiple filtering mechanisms to help traders and investors identify trend continuation and reversal opportunities across different timeframes and asset classes.
🟢 How It Works
The indicator's core innovation lies in its logarithmic weighting system, where weights are calculated using the formula: w = 1.0 / math.pow(math.log(i + steepness), 2) The steepness parameter controls how aggressively recent data is prioritized over historical data, creating a dynamic weight decay that can be fine-tuned for different trading styles. This logarithmic approach provides more nuanced weight distribution compared to exponential moving averages, offering better responsiveness while maintaining stability.
The LMA calculation combines multiple sophisticated components. First, it calculates the logarithmic weighted average of closing prices. Then it measures the slope of this average over a 10-period lookback: lmaSlope = (lma - lma ) / lma * 100 The system also incorporates trend quality assessment using R-squared correlation analysis of log-transformed prices, measuring how well the price data fits a linear trend model over the specified period.
The final signal generation uses the formula: signal = lmaSlope * (0.5 + rSquared * 0.5) which combines the LMA slope with trend quality weighting. When momentum confirmation is enabled, the indicator calculates annualized log-return momentum and applies a multiplier when the momentum direction aligns with the signal direction, strengthening confirmed signals while filtering out weak or counter-trend movements.
🟢 How to Use
1. Signal Interpretation and Threshold Zones
Positive Values (Above Zero): LMA slope indicating bullish momentum with upward price trajectory relative to logarithmic baseline
Negative Values (Below Zero): LMA slope indicating bearish momentum with downward price trajectory relative to logarithmic baseline
Zero Line Crosses: Signal transitions between bullish and bearish regimes, indicating potential trend changes
Long Entry Threshold Zone: Area above positive threshold (default 0.5) indicating confirmed bullish signals suitable for long positions
Short Entry Threshold Zone: Area below negative threshold (default -0.5) indicating confirmed bearish signals suitable for short positions
Extreme Values: Signals exceeding ±1.0 represent strong momentum conditions with higher probability of continuation
2. Momentum Confirmation and Visual Analysis
Signal Color Intensity: Gradient coloring shows signal strength, with brighter colors indicating stronger momentum
Bar Coloring: Optional price bar coloring matches signal direction for quick visual trend identification
Position Labels: Real-time position classification (Bullish/Bearish/Neutral) displayed on the latest bar
Momentum Weight Factor: When short-term log-return momentum aligns with LMA signal direction, the signal receives additional weight confirmation
Trend Quality Component: R-squared values weight the signal strength, with higher correlation indicating more reliable trend conditions
3. Examples: Preconfigured Settings
Default: Universally applicable configuration balanced for medium-term investing and general trading across multiple timeframes and asset classes.
Scalping: Highly responsive setup with shorter period and higher steepness for ultra-short-term trades on 1-15 minute charts, optimized for quick momentum shifts.
Swing Trading: Extended period with moderate steepness and increased smoothing for multi-day positions, designed to filter noise while capturing larger price swings on 1-4 hour and daily charts.
Trend Following: Maximum smoothing with lower steepness for established trend identification, generating fewer but more reliable signals optimal for daily and weekly timeframes.
Mean Reversion: Shorter period with high steepness for counter-trend strategies, more sensitive to extreme moves and reversal opportunities in ranging market conditions.
Xcalibur Signals & Alerts [AlgoXcalibur]An advanced trend-following algorithm forged to empower retail traders with an edge.
Xcalibur Signals & Alerts is a sophisticated, multi-layered algorithm designed to consistently deliver real-time trend signals—without clutter or unnecessary complexity. The system combines refined trend-following logic with breakout detection, flat-market filtration, false signal failsafes, take profit cues, live alerts, and more — all in a visually simple, easy-to-use indicator built for all assets, timeframes, and market conditions.
🧠 Algorithm Logic
Xcalibur Signals & Alerts operates on a systematic framework that evaluates multiple technical dimensions in harmony—directional alignment, momentum confirmation, relative strength, volume bias, breakout detection, Fibonacci calculations, and more. Rather than reacting to isolated triggers, it filters every opportunity through a multi-layered confirmation engine. It doesn’t just react to every move—it evaluates them. This cohesive approach ensures that each signal results from aligned conditions—not arbitrary thresholds. By combining structural awareness with adaptive filtering, Xcalibur maintains clarity and consistency across a wide range of market environments—delivering actionable signals without unnecessary noise or lag.
⚙️ User-Adjustable Features
• Adjustable Sensitivity:
Choose from 5 pre-tuned Signal Trigger Settings and 3 dynamic Confirmation Filter Modes to tailor the system to your trading style, asset, and timeframe. Candle color reflects the active trigger condition, while an adaptive cyan line displays the selected Confirmation Filter—blocking signals until the filter threshold is crossed.
• Directional Stability Filter: When enabled, this filter uses mean-reversion calculations to determine directional bias and block unreliable signals during choppy, indecisive price action. A magenta line represents this filter threshold and provides higher-confidence signals during periods of low directional conviction.
• Pullback Allowance Filter:
When enabled, this unique filter uses Fibonacci ratios to deliberately block signals from temporary pullbacks during strong trend periods. A green (uptrend) or red (downtrend) line marks the active pullback allowance zone.
• False Signal Failsafe
:
Two selectable modes:
Simple — Cancels the signal if price breaks the signal candle’s high or low.
Advanced — Requires both a price break and opposing momentum confirmation.
When triggered, the system plots a white “X” signal, turns candles gray, disables the background color, sends an alert (if enabled), and enters standby mode until a valid trend condition re-emerges.
• Reaction Zones:
Identifies probable reversal or breakout zones based on recent price action patterns. A yellow line appears when active, with a yellow caution flag plotted if the price reaches this critical area.
• Take-Profit Cues
: Automatically detects potential trend exhaustion using price action structure and momentum shifts. When triggered, a visual “TP” marker is plotted—advising traders to manage profits or prepare for a possible reversal.
• Trailing Stop:
Plots a dynamic, percentage-based trailing stop or trailing take-profit using your selected input. Adjust it to suit your risk tolerance and asset.
• Multi-Timeframe Monitor
: Displays real-time trend direction across 1m, 2m, 5m, 15m, 1H, 4H, and 1D timeframes in a compact, easy-to-read table.
• Alert System
:
Receive desktop and/or mobile alerts for:
* New trend signals
* Failsafe triggers
* 9:00 AM Morning Greeting messages with auto re-arming confirmation
(Alerts are limited to 9:00 AM – 4:00 PM Eastern Time)
• SuperCandles
: Highlights strong momentum moves with a stunning and easily recognizable glow effect.
• Color-Coded Candles & Background
: Candles reflect the current trigger condition, while the background tint tracks the most recent trend—enhancing situational awareness.
*All input settings include tooltips to guide users through setup and interpretation.
⚔️ Not Just Another Signal Tool
Xcalibur Signals & Alerts was built from the ground up to empower retail traders with access to a cohesive, structured algorithmic system—one that reflects the kind of awareness, discipline, and market adaptability found in professional-grade algorithms.
This is not another oversensitive or under-responsive signal indicator that is limited to one specific type of market condition or trader. It does not utilize hyperactive triggers, rely on lagging crossover logic, or need infinitely adjustable and complex sensitivity settings. Instead of cluttered visuals to interpret, this indicator delivers a simple, easy-to-use tool—prioritizing clarity and usability without compromising on depth and sophistication.
Whether the market is trending, breaking out, or moving sideways, Xcalibur adapts—prioritizing trend stability, directional integrity, and visual clarity from one signal to the next.
⚠️ While the Xcalibur Signals & Alerts algorithm is immune to human emotion, you are not. Be mindful not to fall victim to costly emotions that can manipulate your judgment, and understand the unpredictable and complex nature of trading. No algorithm, strategy, or technique can deliver perfect accuracy, and Xcalibur Signals & Alerts is no exception. While AlgoXcalibur strives to be as accurate as possible, incorrect signals can and will occur. Xcalibur Signals & Alerts is a tool, not a guarantee. Users are fully responsible for making their own trading decisions, implementing proper risk management, and always trading responsibly.
🛡️ Wield Xcalibur as a standalone weapon or use it alongside other tools.
🔐 To get access or learn more, visit the Author’s Instructions section.
Momentum Trail Oscillator [AlgoAlpha]🟠 OVERVIEW
This script builds a Momentum Trail Oscillator designed to measure directional momentum strength and dynamically track shifts in trend bias using a combination of smoothed price change calculations and adaptive trailing bands. The oscillator aims to help traders visualize when momentum is expanding or contracting and to identify transitions between bullish and bearish conditions.
🟠 CONCEPTS
The core idea combines two methods. First, the script calculates a normalized momentum measure by smoothing price changes relative to their absolute values, which creates a bounded oscillator that highlights whether moves are directional or choppy. Second, it uses a trailing band mechanism inspired by volatility stops, where bands adapt to the oscillator’s volatility, adjusting the thresholds that define a shift in directional bias. This dual approach seeks to address both the magnitude and persistence of momentum, reducing false signals in ranging markets.
🟠 FEATURES
The momentum calculation applies Hull Moving Averages and double EMA smoothing to price changes, producing a smooth, responsive oscillator.
The trailing bands are derived by offsetting a weighted moving average of the oscillator by a multiple of recent momentum volatility. A directional state variable tracks whether the oscillator is above or below the bands, updating when the momentum crosses these dynamic thresholds.
Overbought and oversold zones are visually marked between fixed levels (+30/+40 and -30/-40), with color fills to highlight when momentum is in extreme areas. The script plots signals on both the oscillator pane and optionally overlays markers on the main price chart for clarity.
🟠 USAGE
To use the indicator, apply it to any symbol and timeframe. The “Oscillator Length” controls how sensitive the momentum line is to recent price changes—lower values react faster, higher values smooth out noise. The “Trail Multiplier” sets how far the adaptive bands sit from the oscillator mid-line, which affects how often trend state changes occur. When the momentum line rises into the upper filled area and then crosses back below +40, it signals potential overbought exhaustion. The opposite applies for the oversold zone below -40. The plotted trailing bands switch visibility depending on the current directional state: when momentum is trending up, the lower band acts as the active trailing stop, and when trending down, the upper band becomes active. Trend changes are marked with circular symbols when the direction variable flips, and optional overlay arrows appear on the price chart to highlight overbought or oversold reversals. Traders can combine these signals with their own price action or volume analysis to confirm entries or exits.
Volatility-Adjusted Momentum Score (VAMS) [QuantAlgo]🟢 Overview
The Volatility-Adjusted Momentum Score (VAMS) measures price momentum relative to current volatility conditions, creating a normalized indicator that identifies significant directional moves while filtering out market noise. It divides annualized momentum by annualized volatility to produce scores that remain comparable across different market environments and asset classes.
The indicator displays a smoothed VAMS Z-Score line with adaptive standard deviation bands and an information table showing real-time metrics. This dual-purpose design enables traders and investors to identify strong trend continuation signals when momentum persistently exceeds normal levels, while also spotting potential mean reversion opportunities when readings reach statistical extremes.
🟢 How It Works
The indicator calculates annualized momentum using a simple moving average of logarithmic returns over a specified period, then measures annualized volatility through the standard deviation of those same returns over a longer timeframe. The raw VAMS score divides momentum by volatility, creating a risk-adjusted measure where high volatility reduces scores and low volatility amplifies them.
This raw VAMS value undergoes Z-Score normalization using rolling statistical parameters, converting absolute readings into standardized deviations that show how current conditions compare to recent history. The normalized Z-Score receives exponential moving average smoothing to create the final VAMS line, reducing false signals while preserving sensitivity to meaningful momentum changes.
The visualization includes dynamically calculated standard deviation bands that adjust to recent VAMS behavior, creating statistical reference zones. The information table provides real-time numerical values for VAMS Z-Score, underlying momentum percentages, and current volatility readings with trend indicators.
🟢 How to Use
1. VAMS Z-Score Bands and Signal Interpretation
Above Mean Line: Momentum exceeds historical averages adjusted for volatility, indicating bullish conditions suitable for trend following
Below Mean Line: Momentum falls below statistical norms, suggesting bearish conditions or downward pressure
Mean Line Crossovers: Primary transition signals between bullish and bearish momentum regimes
1 Standard Deviation Breaks: Strong momentum conditions indicating statistically significant directional moves worth following
2 Standard Deviation Extremes: Rare momentum readings that often signal either powerful breakouts or exhaustion points
2. Information Table and Market Context
Z-Score Values: Current VAMS reading displayed in standard deviations (σ), showing how far momentum deviates from its statistical norm
Momentum Percentage: Underlying annualized momentum displayed as percentage return, quantifying the directional strength
Volatility Context: Current annualized volatility levels help interpret whether VAMS readings occur in high or low volatility environments
Trend Indicators: Directional arrows and change values provide immediate feedback on momentum shifts and market transitions
3. Strategy Applications and Alert System
Trend Following: Use sustained readings beyond the mean line and 1σ band penetrations for directional trades, especially when VAMS maintains position in upper or lower statistical zones
Mean Reversion: Focus on 2σ extreme readings for contrarian opportunities, particularly effective in sideways markets where momentum tends to revert to statistical norms
Alert Notifications: Built-in alerts for mean crossovers (regime changes), 1σ breaks (strong signals), and 2σ touches (extreme conditions) help monitor multiple instruments for both continuation and reversal setups
Wavelet-Trend ML Integration [Alpha Extract]Alpha-Extract Volatility Quality Indicator
The Alpha-Extract Volatility Quality (AVQ) Indicator provides traders with deep insights into market volatility by measuring the directional strength of price movements. This sophisticated momentum-based tool helps identify overbought and oversold conditions, offering actionable buy and sell signals based on volatility trends and standard deviation bands.
🔶 CALCULATION
The indicator processes volatility quality data through a series of analytical steps:
Bar Range Calculation: Measures true range (TR) to capture price volatility.
Directional Weighting: Applies directional bias (positive for bullish candles, negative for bearish) to the true range.
VQI Computation: Uses an exponential moving average (EMA) of weighted volatility to derive the Volatility Quality Index (VQI).
Smoothing: Applies an additional EMA to smooth the VQI for clearer signals.
Normalization: Optionally normalizes VQI to a -100/+100 scale based on historical highs and lows.
Standard Deviation Bands: Calculates three upper and lower bands using standard deviation multipliers for volatility thresholds.
Signal Generation: Produces overbought/oversold signals when VQI reaches extreme levels (±200 in normalized mode).
Formula:
Bar Range = True Range (TR)
Weighted Volatility = Bar Range × (Close > Open ? 1 : Close < Open ? -1 : 0)
VQI Raw = EMA(Weighted Volatility, VQI Length)
VQI Smoothed = EMA(VQI Raw, Smoothing Length)
VQI Normalized = ((VQI Smoothed - Lowest VQI) / (Highest VQI - Lowest VQI) - 0.5) × 200
Upper Band N = VQI Smoothed + (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
Lower Band N = VQI Smoothed - (StdDev(VQI Smoothed, VQI Length) × Multiplier N)
🔶 DETAILS
Visual Features:
VQI Plot: Displays VQI as a line or histogram (lime for positive, red for negative).
Standard Deviation Bands: Plots three upper and lower bands (teal for upper, grayscale for lower) to indicate volatility thresholds.
Reference Levels: Horizontal lines at 0 (neutral), +100, and -100 (in normalized mode) for context.
Zone Highlighting: Overbought (⋎ above bars) and oversold (⋏ below bars) signals for extreme VQI levels (±200 in normalized mode).
Candle Coloring: Optional candle overlay colored by VQI direction (lime for positive, red for negative).
Interpretation:
VQI ≥ 200 (Normalized): Overbought condition, strong sell signal.
VQI 100–200: High volatility, potential selling opportunity.
VQI 0–100: Neutral bullish momentum.
VQI 0 to -100: Neutral bearish momentum.
VQI -100 to -200: High volatility, strong bearish momentum.
VQI ≤ -200 (Normalized): Oversold condition, strong buy signal.
🔶 EXAMPLES
Overbought Signal Detection: When VQI exceeds 200 (normalized), the indicator flags potential market tops with a red ⋎ symbol.
Example: During strong uptrends, VQI reaching 200 has historically preceded corrections, allowing traders to secure profits.
Oversold Signal Detection: When VQI falls below -200 (normalized), a lime ⋏ symbol highlights potential buying opportunities.
Example: In bearish markets, VQI dropping below -200 has marked reversal points for profitable long entries.
Volatility Trend Tracking: The VQI plot and bands help traders visualize shifts in market momentum.
Example: A rising VQI crossing above zero with widening bands indicates strengthening bullish momentum, guiding traders to hold or enter long positions.
Dynamic Support/Resistance: Standard deviation bands act as dynamic volatility thresholds during price movements.
Example: Price reversals often occur near the third standard deviation bands, providing reliable entry/exit points during volatile periods.
🔶 SETTINGS
Customization Options:
VQI Length: Adjust the EMA period for VQI calculation (default: 14, range: 1–50).
Smoothing Length: Set the EMA period for smoothing (default: 5, range: 1–50).
Standard Deviation Multipliers: Customize multipliers for bands (defaults: 1.0, 2.0, 3.0).
Normalization: Toggle normalization to -100/+100 scale and adjust lookback period (default: 200, min: 50).
Display Style: Switch between line or histogram plot for VQI.
Candle Overlay: Enable/disable VQI-colored candles (lime for positive, red for negative).
The Alpha-Extract Volatility Quality Indicator empowers traders with a robust tool to navigate market volatility. By combining directional price range analysis with smoothed volatility metrics, it identifies overbought and oversold conditions, offering clear buy and sell signals. The customizable standard deviation bands and optional normalization provide precise context for market conditions, enabling traders to make informed decisions across various market cycles.
Rolling Z-Score Trend [QuantAlgo]🟢 Overview
The Rolling Z-Score Trend measures how far the current price deviates from its rolling mean in terms of standard deviations. It transforms price data into standardized scores to identify overbought and oversold conditions while tracking momentum shifts.
The indicator displays a Z-Score line showing price deviation from statistical norms, with background momentum columns showing the rate of change in these deviations. This helps traders and investors identify mean reversion opportunities and momentum shifts across different asset classes and timeframes.
🟢 How It Works
The indicator uses the Z-Score formula: Z = (X - μ) / σ, where X is the current closing price, μ is the rolling mean, and σ is the rolling standard deviation over a user-defined lookback period. This creates a dynamic baseline that adapts to changing market conditions and standardizes price movements for interpretation across different assets and volatility conditions. The raw Z-Score undergoes 3-period EMA smoothing to reduce noise while maintaining responsiveness to market signals.
Beyond the basic Z-Score calculation, the indicator measures the rate of change in Z-Score values between successive bars, displayed as background momentum columns. This momentum component shows acceleration and deceleration of statistical deviations. All calculations are processed through confirmation filters, displaying signals only on confirmed bars to reduce premature signals based on incomplete price action.
🟢 How to Use
1. Z-Score Interpretation and Threshold Zones
Positive Values (Above Zero) : Price trading above statistical mean, suggesting bullish momentum or potential overbought conditions
Negative Values (Below Zero) : Price trading below statistical mean, suggesting bearish momentum or potential oversold conditions
Zero Line Crosses : Signal transitions between statistical regimes and potential trend changes
Upper Threshold Zone : Area above entry threshold (default 1.5) indicating potential overbought conditions
Lower Threshold Zone : Area below negative entry threshold (default -1.5) indicating potential oversold conditions
Extreme Values (±2.0 or higher) : Statistically significant deviations that may indicate reversal opportunities
2. Momentum Background Analysis and Info Table
Green Columns : Accelerating positive momentum in Z-Score values
Red Columns : Accelerating negative momentum in Z-Score values
Column Height : Magnitude of momentum change between bars
Momentum Divergence : When columns contradict primary Z-Score direction, often signals impending reversals
Info Table : Displays real-time numerical values for both Z-Score and momentum, including trend direction indicators and bar-to-bar change calculations for position management
3. Preconfigured Settings
Default : Balanced performance across multiple timeframes and asset classes for general trading and medium-term position management.
Scalping : Responsive setup for ultra-short-term trading on 1-15 minute charts with frequent signals and increased sensitivity to quick price movements.
Swing Trading : Optimized for multi-day positions with noise filtering, focusing on larger price swings. Most effective on 1-4 hour and daily timeframes.
Trend Following : Maximum smoothing that prioritizes established trends over short-term volatility. Generates fewer signals for daily and weekly charts.
Trend Flow Trail [AlgoAlpha]OVERVIEW
This script overlays a custom hybrid indicator called the Money Flow Trail which combines a volatility-based trend-following trail with a volume-weighted momentum oscillator. It’s built around two core components: the AlphaTrail—a dynamic band system influenced by Hull MA and volatility—and a smoothed Money Flow Index (MFI) that provides insights into buying or selling pressure. Together, these tools are used to color bars, generate potential reversal markers, and assist traders in identifying trend continuation or exhaustion phases in any market or timeframe.
CONCEPTS
The AlphaTrail calculates a volatility-adjusted channel around price using the Hull Moving Average as the base and an EMA of range as the spread. It adaptively shifts based on price interaction to capture trend reversals while avoiding whipsaws. The direction (bullish or bearish) determines both the band being tracked and how the trail locks in. The Money Flow Index (MFI) is derived from hlc3 and volume, measuring buying vs selling pressure, and is further smoothed with a short Hull MA to reduce noise while preserving structure. These two systems work in tandem: AlphaTrail governs directional context, while MFI refines the timing.
FEATURES
Dynamic AlphaTrail line with regime switching logic that controls directional bias and bar coloring.
Smoothed MFI with gradient coloring to visually communicate pressure and exhaustion levels.
Overbought/oversold thresholds (80/20), mid-level (50), and custom extreme zones (90/10) for deeper signal granularity.
Built-in take-profit signal logic: crossover of MFI into overbought with bullish AlphaTrail, or into oversold with bearish AlphaTrail.
Visual fills between price and AlphaTrail for clearer confirmation during trend phases.
Alerts for regime shifts, MFI crossovers, trail interactions, and bar color regime changes.
USAGE
Add the indicator to any chart. Use the AlphaTrail plot to define trend context: bullish (trailing below price) or bearish (trailing above). MFI values give supporting confirmation—favor long setups when MFI is rising and above 50 in a bullish regime, and shorts when MFI is falling and below 50 in a bearish regime. The colored fills help visually track strength; sharp changes in MFI crossing 80/20 or 90/10 zones often precede pullbacks or reversals. Use the plotted circles as optional take-profit signals when MFI and trend are extended. Adjust AlphaTrail length/multiplier and MFI smoothing to better match the asset’s volatility profile.
Dynamic Flow Ribbons [BigBeluga]🔵 OVERVIEW
A dynamic multi-band trend visualization system that adapts to market volatility and reveals trend momentum with layered ribbon channels.
Dynamic Flow Ribbons transforms price action into flowing trend bands that expand and contract with volatility. It not only shows the active directional bias but also visualizes how strong or weak the trend is through layered ribbons, making it easier to assess trend quality and structure.
🔵 CONCEPTS
Uses an adaptive trend detection system built on a volatility envelope derived from an EMA of the average price (HLC3).
Measures volatility using a long-period average of the high-low range, which scales the envelope width dynamically.
Trend direction flips when the average price crosses above or below these envelopes.
Ribbons form around the trend line to show how far price is stretching or compressing relative to the mean.
🔵 FEATURES
Volatility-Based Trend Line:
A thick, color-coded line tracks the current trend with smoother transitions between phases.
Multi-Layered Flow Ribbons:
Up to 10 bands (5 above and 5 below) radiate outward from the upper and lower envelopes, reflecting volatility strength and direction.
Trend Coloring & Transitions:
Ribbons and candles are dynamically colored based on trend direction— green for bullish , orange for bearish . Transparency fades with distance from the core trend band.
Real-Time Responsiveness:
Ribbon structure and trend shifts update in real time, adapting instantly to fast market changes.
🔵 HOW TO USE
Use the color and thickness of the core trend line to follow directional bias.
When ribbons widen symmetrically, it signals strong trend momentum .
Narrowing or overlapping ribbons can suggest consolidation or transition zones .
Combine with breakout systems or volume tools to confirm impulsive or corrective phases .
Adjust the “Length” (factor) input to tune sensitivity—higher values smooth trends more.
🔵 CONCLUSION
Dynamic Flow Ribbons offers a sleek and insightful view into trend strength and structure. By visualizing volatility expansion with directional flow, it becomes a powerful overlay for momentum traders, swing strategists, and trend followers who want to stay ahead of evolving market flows
Fibonacci Entry Bands [AlgoAlpha]OVERVIEW
This script plots Fibonacci Entry Bands, a trend-following and mean-reversion hybrid system built around dynamic volatility-adjusted bands scaled using key Fibonacci levels. It calculates a smoothed basis line and overlays multiple bands at fixed Fibonacci multipliers of either ATR or standard deviation. Depending on the trend direction, specific upper or lower bands become active, offering a clear framework for entry timing, trend identification, and profit-taking zones.
CONCEPTS
The core idea is to use Fibonacci levels—0.618, 1.0, 1.618, and 2.618—as multipliers on a volatility measure to form layered price bands around a trend-following moving average. Trends are defined by whether the basis is rising or falling. The trend determines which side of the bands is emphasized: upper bands for downtrends, lower bands for uptrends. This approach captures both directional bias and extreme price extensions. Take-profit logic is built in via crossovers relative to the outermost bands, scaled by user-selected aggressiveness.
FEATURES
Basis Line – A double EMA smoothing of the source defines trend direction and acts as the central mean.
Volatility Bands – Four levels per side (based on selected ATR or stdev) mark the Fibonacci bands. These become visible only when trend direction matches the side (e.g., only lower bands plot in an uptrend).
Bar Coloring – Bars are shaded with adjustable transparency depending on distance from the basis, with color intensity helping gauge overextension.
Entry Arrows – A trend shift triggers either a long or short signal, with a marker at the outermost band with ▲/▼ signs.
Take-Profit Crosses – If price rejects near the outer band (based on aggressiveness setting), a cross appears marking potential profit-taking.
Bounce Signals – Minor pullbacks that respect the basis line are marked with triangle arrows, hinting at continuation setups.
Customization – Users can toggle bar coloring, signal markers, and select between ATR/stdev as well as take-profit aggressiveness.
Alerts – All major signals, including entries, take-profits, and bounces, are available as alert conditions.
USAGE
To use this tool, load it on your chart, adjust the inputs for volatility method and aggressiveness, and wait for entries to form on trend changes. Use TP crosses and bounce arrows as potential exit or scale-in signals.
Intra_Candle_Welding by Chaitu50cIntra Candle Welding by Chaitu50c
This is a professional price action–based indicator designed to automatically detect and visualize *intra-candle reversal zones* using simple yet powerful logic. It highlights price levels where two consecutive opposite candles meet with a high probability of short-term market reaction.
Concept
The indicator identifies potential intraday support and resistance levels based on the "Intra Candle Welding" concept: when the close of one candle is very close to the open of the next candle, and the two candles have opposite directions (bullish followed by bearish, or bearish followed by bullish). These levels often attract market attention due to order flow imbalance created during such transitions.
How It Works
1. The indicator continuously monitors each new candle and checks if the current open is approximately equal to the previous close, within a configurable buffer.
2. It further ensures that the two candles form an opposite pair (green→red or red→green).
3. When a valid pair is detected, the indicator checks for existing active lines near this level. If no active line exists within the defined tolerance, it draws a new horizontal line at the detected level.
4. Each line is classified as either a potential resistance (from green→red pair) or support (from red→green pair).
5. Lines automatically extend rightward and update with each bar. If price breaks through the line beyond a configurable break buffer, the line stops extending and is visually marked as "broken."
6. The indicator intelligently manages the maximum number of lines on the chart by deleting the oldest ones when the limit is exceeded.
Use Case
Traders can use this tool to identify short-term reaction zones and potential intraday turning points. The highlighted levels act as temporary support and resistance areas where price frequently reacts. It is especially useful in fast-moving or volatile markets such as index futures or liquid stocks.
Features
* Automatically detects intra-candle reversal zones.
* Classifies zones as support (bottom) or resistance (top).
* Automatically updates and breaks lines when invalidated by price action.
* Adjustable parameters for flexibility:
* Equality Buffer
* Max Lines to Keep
* Line Suppression Tolerance
* Initial Extend Bars
* Break Buffer
* Line colors, widths, and styles (active and broken states)
* Efficient memory handling with capped line count.
* Minimalist and clean visual representation, suitable for overlay on any chart.
Recommended Settings
* Works best on intraday timeframes (1 min to 15 min).
* Tune the Equality Buffer and Tolerance parameters based on instrument volatility.
* Use conservative Break Buffer to avoid premature line invalidation.
Disclaimer
This is a tool to support discretionary trading decisions. It is not a standalone buy/sell signal generator. Users are advised to combine it with their own market context and risk management framework.
This indicator is released for the TradingView community for educational and practical trading use.
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Adaptive MACD Deluxe [AlgoAlpha]OVERVIEW
This script is an advanced rework of the classic MACD indicator, designed to be more adaptive, visually informative, and customizable. It enhances the original MACD formula using a dynamic feedback loop and a correlation-based weighting system that adjusts in real-time based on how deterministic recent price action is. The signal line is flexible, offering several smoothing types including Heiken Ashi, while the histogram is color-coded with gradients to help users visually identify momentum shifts. It also includes optional normalization by volatility, allowing MACD values to be interpreted as relative percentage moves, making the indicator more consistent across different assets and timeframes.
CONCEPTS
This version of MACD introduces a deterministic weight based on R-squared correlation with time, which modulates how fast or slow the MACD adapts to price changes. Higher correlation means smoother, slower MACD responses, and low correlation leads to quicker reaction. The momentum calculation blends traditional EMA math with feedback and damping components to create a smoother, less noisy series. Heiken Ashi is optionally used for signal smoothing to better visualize short-term trend bias. When normalization is enabled, the MACD is scaled by an EMA of the high-low range, converting it into a bounded, volatility-relative indicator. This makes extreme readings more meaningful across markets.
FEATURES
The script offers six distinct options for signal line smoothing: EMA, SMA, SMMA (RMA), WMA, VWMA, and a custom Heiken Ashi mode based on the MACD series. Each option provides a different response speed and smoothing behavior, allowing traders to match the indicator’s behavior to their strategy—whether it's faster reaction or reduced noise.
Normalization is another key feature. When enabled, MACD values are scaled by a volatility proxy, converting the indicator into a relative percentage. This helps standardize the MACD across different assets and timeframes, making overbought and oversold readings more consistent and easier to interpret.
Threshold zones can be customized using upper and lower boundaries, with inner zones for early warnings. These zones are highlighted on the chart with subtle background fills and directional arrows when MACD enters or exits key levels. This makes it easier to spot strong or weak reversals at a glance.
Lastly, the script includes multiple built-in alerts. Users can set alerts for MACD crossovers, histogram flips above or below zero, and MACD entries into strong or weak reversal zones. This allows for hands-free monitoring and quick decision-making without staring at the chart.
USAGE
To use this script, choose your preferred signal smoothing type, enable normalization if you want MACD values relative to volatility, and adjust the threshold zones to fit your asset or timeframe. Use the colored histogram to detect changes in momentum strength—brighter colors indicate rising strength, while faded colors imply weakening. Heiken Ashi mode smooths out noise and provides clearer signals, especially useful in choppy conditions. Use alert conditions for crossover and reversal detection, or monitor the arrow markers for entries into potential exhaustion zones. This setup works well for trend following, momentum trading, and reversal spotting across all market types.
SMEMA Trend CoreSMEMA Trend Core is a multi-timeframe trend analysis tool designed to provide a clean, adaptive and structured view of the market’s directional bias. It can be used in short term, swing or long term contexts. The internal calculation adjusts automatically based on the selected trading style, while always combining data from six timeframes.
At its core, the indicator uses a SMEMA, which is a Simple Moving Average applied to an EMA. This combination improves smoothness without losing reactivity. The SMEMA is calculated separately on 1H, 4H, 1D, 3D, 1W and 1M timeframes. These six values are then combined using dynamic weights that depend on the trading mode:
Short Term mode gives more influence to 1H and 4H
Swing Trading mode gives more influence to 1D, 3D and 1W
Long Term mode gives more influence to 1W and 1M
However, all six timeframes are always included in the final result. This avoids the tunnel vision of relying on a single resolution and ensures that the indicator captures both local and structural movements.
The result is a synthetic trend line, called Global SMEMA, that adapts to market conditions and offers a realistic view of the ongoing trend. To enhance the reading, the indicator calculates a Trend Score. This score reflects the position of price relative to the Global SMEMA, scaled by a long-term ATR, and adjusted by the slope of the trend line. A hyperbolic tangent function is used to normalize values and reduce distortion from outliers.
The final score is capped between -10 and +10, and used to define the trend state:
Green when the trend is bullish (score > +1.5)
Red when the trend is bearish (score < -1.5)
Brown when the trend is neutral (score between -1.5 and +1.5)
Optional Deviation Bands can be displayed at ±1, ±2 and ±3 ATR distances around the central line. These dynamic zones help identify extended price movements or potential support and resistance areas, depending on the current trend bias.
Main features:
A single, stable trend line based on six timeframes
Automatic rebalancing depending on trading mode
Quantified score integrating distance and slope
No overreaction to short-term noise
Deviation zones for advanced market context
No repainting, no lookahead, 100% real-time
SMEMA Trend Core is not a signal tool. It is a directional framework that helps you stay aligned with the real structure of the market. Use it to confirm setups, filter trades or simply understand where the market stands in its trend cycle.
Kaufman Trend Strength Signal█ Overview
Kaufman Trend Strength Signal is an advanced trend detection tool that decomposes price action into its underlying directional trend and localized oscillation using a vector-based Kalman Filter.
By integrating adaptive smoothing and dynamic weighting via a weighted moving average (WMA), this indicator provides real-time insight into both trend direction and trend strength — something standard moving averages often fail to capture.
The core model assumes that observed price consists of two components:
(1) a directional trend, and
(2) localized noise or oscillation.
Using a two-step Predict & Update cycle, the filter continuously refines its trend estimate as new market data becomes available.
█ How It Works
This indicator employs a Kalman Filter model that separates the trend from short-term fluctuations in a price series.
Predict & Update Cycle : With each new bar, the filter predicts the price state and updates that prediction using the latest observed price, producing a smooth but adaptive trend line.
Trend Strength Normalization : Internally, the oscillator component is normalized against recent values (N periods) to calculate a trend strength score between -100 and +100.
(Note: The oscillator is not plotted on the chart but is used for signal generation.)
Filtered MA Line : The trend component is plotted as a smooth Kalman Filter-based moving average (MA) line on the main chart.
Threshold Cross Signals : When the internal trend strength crosses a user-defined threshold (default: ±60), visual entry arrows are displayed to signal momentum shifts.
█ Key Features
Adaptive Trend Estimation : Real-time filtering that adjusts dynamically to market changes.
Visual Buy/Sell Signals : Entry arrows appear when the trend strength crosses above or below the configured threshold.
Built-in Range Filter : The MA line turns blue when trend strength is weak (|value| < 10), helping you filter out choppy, sideways conditions.
█ How to Use
Trend Detection :
• Green MA = bullish trend
• Red MA = bearish trend
• Blue MA = no trend / ranging market
Entry Signals :
• Green triangle = trend strength crossed above +Threshold → potential bullish entry
• Red triangle = trend strength crossed below -Threshold → potential bearish entry
█ Settings
Entry Threshold : Level at which the trend strength triggers entry signals (default: 60)
Process Noise 1 & 2 : Control the filter’s responsiveness to recent price action. Higher = more reactive; lower = smoother.
Measurement Noise : Sets how much the filter "trusts" price data. High = smoother MA, low = faster response but more noise.
Trend Lookback (N2) : Number of bars used to normalize trend strength. Lower = more sensitive; higher = more stable.
Trend Smoothness (R2) : WMA smoothing applied to the trend strength calculation.
█ Visual Guide
Green MA Line → Bullish trend
Red MA Line → Bearish trend
Blue MA Line → Sideways/range
Green Triangle → Entry signal (trend strengthening)
Red Triangle → Entry signal (trend weakening)
█ Best Practices
In high-volatility conditions, increase Measurement Noise to reduce false signals.
Combine with other indicators (e.g., RSI, MACD, EMA) for confirmation and filtering.
Adjust "Entry Threshold" and noise settings depending on your timeframe and trading style.
❗ Disclaimer
This script is provided for educational purposes only and should not be considered financial advice or a recommendation to buy/sell any asset.
Trading involves risk. Past performance does not guarantee future results.
Always perform your own analysis and use proper risk management when trading.
Kaufman Trend Strategy# ✅ Kaufman Trend Strategy – Full Description (Script Publishing Version)
**Kaufman Trend Strategy** is a dynamic trend-following strategy based on Kaufman Filter theory.
It detects real-time trend momentum, reduces noise, and aims to enhance entry accuracy while optimizing risk.
⚠️ _For educational and research purposes only. Past performance does not guarantee future results._
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## 🎯 Strategy Objective
- Smooth price noise using Kaufman Filter smoothing
- Detect the strength and direction of trends with a normalized oscillator
- Manage profits using multi-stage take-profits and adaptive ATR stop-loss logic
---
## ✨ Key Features
- **Kaufman Filter Trend Detection**
Extracts directional signal using a state space model.
- **Multi-Stage Profit-Taking**
Automatically takes partial profits based on color changes and zero-cross events.
- **ATR-Based Volatility Stops**
Stops adjust based on swing highs/lows and current market volatility.
---
## 📊 Entry & Exit Logic
**Long Entry**
- `trend_strength ≥ 60`
- Green trend signal
- Price above the Kaufman average
**Short Entry**
- `trend_strength ≤ -60`
- Red trend signal
- Price below the Kaufman average
**Exit (Long/Short)**
- Blue trend color → TP1 (50%)
- Oscillator crosses 0 → TP2 (25%)
- Trend weakens → Final exit (25%)
- ATR + swing-based stop loss
---
## 💰 Risk Management
- Initial capital: `$3,000`
- Order size: `$100` per trade (realistic, low-risk sizing)
- Commission: `0.002%`
- Slippage: `2 ticks`
- Pyramiding: `1` max position
- Estimated risk/trade: `~0.1–0.5%` of equity
> ⚠️ _No trade risks more than 5% of equity. This strategy follows TradingView script publishing rules._
---
## ⚙️ Default Parameters
- **1st Take Profit**: 50%
- **2nd Take Profit**: 25%
- **Final Exit**: 25%
- **ATR Period**: 14
- **Swing Lookback**: 10
- **Entry Threshold**: ±60
- **Exit Threshold**: ±40
---
## 📅 Backtest Summary
- **Symbol**: USD/JPY
- **Timeframe**: 1H
- **Date Range**: Jan 3, 2022 – Jun 4, 2025
- **Trades**: 924
- **Win Rate**: 41.67%
- **Profit Factor**: 1.108
- **Net Profit**: +$1,659.29 (+54.56%)
- **Max Drawdown**: -$1,419.73 (-31.87%)
---
## ✅ Summary
This strategy uses Kaufman filtering to detect market direction with reduced lag and increased smoothness.
It’s built with visual clarity and strong trade management, making it practical for both beginners and advanced users.
---
## 📌 Disclaimer
This script is for educational and informational purposes only and should not be considered financial advice.
Use with proper risk controls and always test in a demo environment before live trading.
Trend Scanner ProTrend Scanner Pro, Robust Trend Direction and Strength Estimator
Trend Scanner Pro is designed to evaluate the current market trend with maximum robustness, providing both direction and strength based on statistically reliable data.
This indicator builds upon the core logic of a previous script I developed, called Best SMA Finder. While the original script focused on identifying the most profitable SMA length based on backtested trade performance, Trend Scanner Pro takes that foundation further to serve a different purpose: analyzing and quantifying the actual trend state in real time.
It begins by testing hundreds of SMA lengths, from 10 to 1000 periods. Each one is scored using a custom robustness formula that combines profit factor, number of trades, and win rate. Only SMAs with a sufficient number of trades are retained, ensuring statistical validity and avoiding curve fitting.
The SMA with the highest robustness score is selected as the dynamic reference point. The script then calculates how far the price deviates from it using rolling standard deviation, assigning a trend strength score from -5 (strong bearish) to +5 (strong bullish), with 0 as neutral.
Two detection modes are available:
Slope mode, based on SMA slope reversals
Bias mode, based on directional shifts relative to deviation zones
Optional features:
Deviation bands for visual structure
Candle coloring to reflect trend strength
Compact table showing real-time trend status
This tool is intended for traders who want an adaptive, objective, and statistically grounded assessment of market trend conditions.
Laplace Momentum Percentile ║ BullVision 🔬 Overview
Laplace Momentum Percentile ║ BullVision is a custom-built trend analysis tool that applies Laplace-inspired smoothing to price action and maps the result to a historical percentile scale. This provides a contextual view of trend intensity, with optional signal refinement using a Kalman filter.
This indicator is designed for traders and analysts seeking a normalized, scale-independent perspective on market behavior. It does not attempt to predict price but instead helps interpret the relative strength or weakness of recent movements.
⚙️ Key Concepts
📉 Laplace-Based Smoothing
The core signal is built using a Laplace-style weighted average, applying an exponential decay to price values over a specified length. This emphasizes recent movements while still accounting for historical context.
🎯 Percentile Mapping
Rather than displaying the raw output, the filtered signal is converted into a percentile rank based on its position within a historical lookback window. This helps normalize interpretation across different assets and timeframes.
🧠 Optional Kalman Filter
For users seeking additional smoothing, a Kalman filter is included. This statistical method updates signal estimates dynamically, helping reduce short-term fluctuations without introducing significant lag.
🔧 User Settings
🔁 Transform Parameters
Transform Parameter (s): Controls the decay rate for Laplace weighting.
Calculation Length: Sets how many candles are used for smoothing.
📊 Percentile Settings
Lookback Period: Defines how far back to calculate the historical percentile ranking.
🧠 Kalman Filter Controls
Enable Kalman Filter: Optional toggle.
Process Noise / Measurement Noise: Adjust the filter’s responsiveness and tolerance to volatility.
🎨 Visual Settings
Show Raw Signal: Optionally display the pre-smoothed percentile value.
Thresholds: Customize upper and lower trend zone boundaries.
📈 Visual Output
Main Line: Smoothed percentile rank, color-coded based on strength.
Raw Line (Optional): The unsmoothed percentile value for comparison.
Trend Zones: Background shading highlights strong upward or downward regimes.
Live Label: Displays current percentile value and trend classification.
🧩 Trend Classification Logic
The indicator segments percentile values into five zones:
Above 80: Strong upward trend
50–80: Mild upward trend
20–50: Neutral zone
0–20: Mild downward trend
Below 0: Strong downward trend
🔍 Use Cases
This tool is intended as a visual and contextual aid for identifying trend regimes, assessing historical momentum strength, or supporting broader confluence-based analysis. It can be used in combination with other tools or frameworks at the discretion of the trader.
⚠️ Important Notes
This script does not provide buy or sell signals.
It is intended for educational and analytical purposes only.
It should be used as part of a broader decision-making process.
Past signal behavior should not be interpreted as indicative of future results.
SuperTrend Confluence Signals [AlgoAlpha]OVERVIEW
This script enhances the classic SuperTrend indicator by integrating volume dynamics, retracement detection, and a multi-asset trend matrix—alongside an automatic mitigation-level drawing system. It's designed for traders who want to see not just trend direction, but the confluence of trend strength, volatility-adjusted retracements, and capital flow through volume pressure. It visually maps key transitions in market structure while offering a clean, color-coded overview of multiple symbols and timeframes in a single chart.
CONCEPTS
At the core is the traditional SuperTrend , which determines directional bias using Average True Range (ATR) with a volatility multiplier. This script overlays that with a dynamic volume histogram that scales relative to recent volume standard deviation, coloring volume bursts within the trend. Retracement signals are triggered when price pulls back toward the SuperTrend level but respects it—quantified through normalized distance sensitivity. On top of that, the indicator automatically draws and manages horizontal support/resistance zones that appear at key trend shifts. These levels persist and are cleared based on configurable rules such as wick/body sweeps or consecutive candle closes. A multi-asset, multi-timeframe table then gives an instant snapshot of trend status across five user-defined symbols and timeframes.
FEATURES
SuperTrend : Configurable ATR length and multiplier for flexible trend sensitivity.
Volumetric Histogram : Gradient-filled candles anchored to SuperTrend bands, scaled by relative volume to indicate activity intensity during trends.
Retracement Arrows : Signals printed when price nears the SuperTrend level without breaking it, allowing identification of high-probability continuation zones.
Volume TP Markers : Diamond markers flag high-volume events, contextualizing price moves with liquidity bursts.
Automatic Structure Levels : Draws clean horizontal lines at significant trend transitions, with optional volatility-based band fills. These levels self-update and clear based on price interaction logic.
Trend Table : Displays trend direction (▲/▼) across five assets and five timeframes. Each cell is colored according to trend bias, providing a compact overview for multi-market confluence.
USAGE
Start by loading the indicator on your main chart and adjusting the ATR Length and Multiplier to match your strategy timeframe. Use lower values for scalping and higher values for swing trading. The histogram bars will appear as colored candles above or below the SuperTrend level, indicating how strong volume is within that trend. Arrow signals suggest minor pullbacks within the trend, which can act as entry opportunities. The level system will automatically plot key price zones during trend flips; if "Body" is selected for mitigation, price must close through the level to invalidate it. If "Wick" is chosen, a single wick breach is enough. Adjust expiry and rejection settings to fine-tune how long levels stay on chart. Finally, enable the Multi-Asset Table to view live trend signals across popular symbols like AAPL or NVDA in different timeframes, helping spot macro-to-micro alignment for higher-confidence trades.
SOXL Trend Surge v3.0.2 – Profit-Only RunnerSOXL Trend Surge v3.0.2 – Profit-Only Runner
This is a trend-following strategy built for leveraged ETFs like SOXL, designed to ride high-momentum waves with minimal interference. Unlike most short-term scalping scripts, this model allows trades to develop over multiple days to even several months, capitalizing on the full power of extended directional moves — all without using a stop-loss.
🔍 How It Works
Entry Logic:
Price is above the 200 EMA (long-term trend confirmation)
Supertrend is bullish (momentum confirmation)
ATR is rising (volatility expansion)
Volume is above its 20-bar average (liquidity filter)
Price is outside a small buffer zone from the 200 EMA (to avoid whipsaws)
Trades are restricted to market hours only (9 AM to 2 PM EST)
Cooldown of 15 bars after each exit to prevent overtrading
Exit Strategy:
Takes partial profit at +2× ATR if held for at least 2 bars
Rides the remaining position with a trailing stop at 1.5× ATR
No hard stop-loss — giving space for volatile pullbacks
⚙️ Strategy Settings
Initial Capital: $500
Risk per Trade: 100% of equity (fully allocated per entry)
Commission: 0.1%
Slippage: 1 tick
Recalculate after order is filled
Fill orders on bar close
Timeframe Optimized For: 45-minute chart
These parameters simulate an aggressive, high-volatility trading model meant for forward-testing compounding potential under realistic trading costs.
✅ What Makes This Unique
No stop-loss = fewer premature exits
Partial profit-taking helps lock in early wins
Trailing logic gives room to ride large multi-week moves
Uses strict filters (volume, ATR, EMA bias) to enter only during high-probability windows
Ideal for leveraged ETF swing or position traders looking to hold longer than the typical intraday or 2–3 day strategies
⚠️ Important Note
This is a high-risk, high-reward strategy meant for educational and testing purposes. Without a stop-loss, trades can experience deep drawdowns that may take weeks or even months to recover. Always test thoroughly and adjust position sizing to suit your risk tolerance. Past results do not guarantee future returns. Backtest range: May 8, 2020 – May 23, 2025
Turbo Market Regime Detector [QuantAlgo]The Turbo Market Regime Detector is a market state classification system that combines volatility-adaptive filtering with slope analysis to identify and categorize market regimes. It helps traders and investors distinguish between trending and ranging market conditions across different timeframes and asset classes.
🟢 Technical Foundation
The Turbo Market Regime Detector employs a multi-layered analytical approach to market regime identification, incorporating:
Volatility-Adaptive Regime Filter (VARF) : Uses dynamic alpha calculation based on price volatility and range to create an adaptive filter that responds to changing market conditions
Slope Analysis : Calculates the absolute slope of the VARF curve and applies customizable moving average smoothing to determine trend strength and market regime classification
Normalized Histogram : Transforms raw slope data into percentage-based metrics (0-100%) for interpretation of market conditions
Multi-Threshold Classification System : Implements user-defined thresholds to categorize markets into Strong Trend, Weak Trend, and Ranging regimes
The indicator processes price data through mathematical operations including volatility adjustment, slope normalization, and statistical range analysis. This creates a regime detection system that adapts to market volatility while maintaining classification consistency across different timeframes and asset classes.
🟢 Key Features & Signals
1. Market Regime Classification
The indicator presents market conditions through a normalized histogram that distinguishes between three distinct market states:
1/ Strong Trend Regime: When the histogram exceeds the strong trend threshold (default 30%), indicating directional market movement with sustained momentum
2/ Weak Trend Regime: When the histogram falls between weak trend (default 10%) and strong trend thresholds, representing transitional market conditions with moderate directional bias
3/ Ranging Regime: When the histogram remains below the weak trend threshold, signaling consolidation periods with limited directional movement
This classification system provides insights into:
→ Current market state with percentage-based quantification
→ Regime transitions and their timing
→ Market momentum strength across different timeframes
2. Visual Feedback System
The indicator features multiple visualization options for market analysis:
Background Coloring: Optional chart background coloring that applies regime-based colors to both the indicator pane and main price chart for visual context
Bar Coloring: Price bar coloring based on current market regime, providing visual feedback on market conditions
Reference Lines: Horizontal reference lines at 25%, 50%, 75%, and 100% levels for percentage assessment and historical comparison
Information Table: Real-time status display showing current market state and trend strength percentage with customizable positioning and sizing options
3. Alert and Notification System
The indicator generates alerts for regime transitions:
State Change Alerts: Notifications triggered when the market transitions between regime states (Strong Trend ↔ Weak Trend ↔ Ranging)
Specific Regime Entry Alerts: Individual alert conditions for entering Strong Trend, Weak Trend, or Ranging regimes for targeted trading strategies
Customizable Alert Messages: Pre-formatted alert messages including exchange and ticker information for context and decision-making
🟢 Practical Usage Guidelines
→ Regime-Based Strategy Selection: Use the indicator to identify potential trading strategies - trend-following during Strong Trend regimes, mean-reversion during Ranging periods, and adjusted position sizing during Weak Trend transitions
→ Multi-Timeframe Analysis: Apply the indicator across different timeframes to understand market regime hierarchy and identify confluence between short-term and long-term market states
→ Threshold Optimization: Adjust regime thresholds based on market volatility and asset characteristics - lower thresholds for more sensitive regime detection, higher thresholds for more definitive regime changes
🟢 Configuration Tips
VARF settings optimization:
→ Lower thresholds (-0.3 to -0.5) for more responsive regime detection in volatile markets
→ Higher thresholds (-0.1 to 0.1) for smoother signals in stable market conditions
→ Enable adaptive VARF for automatic volatility adjustment across different market cycles
Slope analysis parameter tuning:
→ Shorter MA lengths (100-200) for faster regime transition signals
→ Longer MA lengths (300-500) for more stable regime identification
→ Adjust sensitivity multiplier based on desired responsiveness vs. stability balance
Regime interpretation framework:
→ Strong Trend regimes for momentum-based strategies and trend following
→ Ranging regimes for mean-reversion and support/resistance trading
→ Weak Trend periods for reduced position sizing and cautious market approach
Complementary analysis integration:
→ Volume analysis for regime change confirmation
→ Support/resistance levels for entry/exit timing within regime contexts
→ Price action patterns for validation of regime-based trading decisions
→ Economic calendar events that may influence regime transitions
EMA 12/26 With ATR Volatility StoplossThe EMA 12/26 With ATR Volatility Stoploss
The EMA 12/26 With ATR Volatility Stoploss strategy is a meticulously designed systematic trading approach tailored for navigating financial markets through technical analysis. By integrating the Exponential Moving Average (EMA) and Average True Range (ATR) indicators, the strategy aims to identify optimal entry and exit points for trades while prioritizing disciplined risk management. At its core, it is a trend-following system that seeks to capitalize on price momentum, employing volatility-adjusted stop-loss mechanisms and dynamic position sizing to align with predefined risk parameters. Additionally, it offers traders the flexibility to manage profits either by compounding returns or preserving initial capital, making it adaptable to diverse trading philosophies. This essay provides a comprehensive exploration of the strategy’s underlying concepts, key components, strengths, limitations, and practical applications, without delving into its technical code.
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Core Philosophy and Objectives
The EMA 12/26 With ATR Volatility Stoploss strategy is built on the premise of capturing short- to medium-term price trends with a high degree of automation and consistency. It leverages the crossover of two EMAs—a fast EMA (12-period) and a slow EMA (26-period)—to generate buy and sell signals, which indicate potential trend reversals or continuations. To mitigate the inherent risks of trading, the strategy incorporates the ATR indicator to set stop-loss levels that adapt to market volatility, ensuring that losses remain within acceptable bounds. Furthermore, it calculates position sizes based on a user-defined risk percentage, safeguarding capital while optimizing trade exposure.
A distinctive feature of the strategy is its dual profit management modes:
SnowBall (Compound Profit): Profits from successful trades are reinvested into the capital base, allowing for progressively larger position sizes and potential exponential portfolio growth.
ZeroRisk (Fixed Equity): Profits are withdrawn, and trades are executed using only the initial capital, prioritizing capital preservation and minimizing exposure to market downturns.
This duality caters to both aggressive traders seeking growth and conservative traders focused on stability, positioning the strategy as a versatile tool for various market environments.
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Key Components of the Strategy
1. EMA-Based Signal Generation
The strategy’s trend-following mechanism hinges on the interaction between the Fast EMA (12-period) and Slow EMA (26-period). EMAs are preferred over simple moving averages because they assign greater weight to recent price data, enabling quicker responses to market shifts. The key signals are:
Buy Signal: Triggered when the Fast EMA crosses above the Slow EMA, suggesting the onset of an uptrend or bullish momentum.
Sell Signal: Occurs when the Fast EMA crosses below the Slow EMA, indicating a potential downtrend or the end of a bullish phase.
To enhance signal reliability, the strategy employs an Anchor Point EMA (AP EMA), a short-period EMA (e.g., 2 days) that smooths the input price data before calculating the primary EMAs. This preprocessing reduces noise from short-term price fluctuations, improving the accuracy of trend detection. Additionally, users can opt for a Consolidated EMA (e.g., 18-period) to display a single trend line instead of both EMAs, simplifying chart analysis while retaining trend insights.
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2. Volatility-Adjusted Risk Management with ATR
Risk management is a cornerstone of the strategy, achieved through the use of the Average True Range (ATR), which quantifies market volatility by measuring the average price range over a specified period (e.g., 10 days). The ATR informs the placement of stop-loss levels, which are set at a multiple of the ATR (e.g., 2x ATR) below the entry price for long positions. This approach ensures that stop losses are proportionate to current market conditions—wider during high volatility to avoid premature exits, and narrower during low volatility to protect profits.
For example, if a stock’s ATR is $1 and the multiplier is 2, the stop loss for a buy at $100 would be set at $98. This dynamic adjustment enhances the strategy’s adaptability, preventing stop-outs from normal market noise while capping potential losses.
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3. Dynamic Position Sizing
The strategy calculates position sizes to align with a user-defined Risk Per Trade, typically expressed as a percentage of capital (e.g., 2%). The position size is determined by:
The available capital, which varies depending on whether SnowBall or ZeroRisk mode is selected.
The distance between the entry price and the ATR-based stop-loss level, which represents the per-unit risk.
The desired risk percentage, ensuring that the maximum loss per trade does not exceed the specified threshold.
For instance, with a $1,000 capital, a 2% risk per trade ($20), and a stop-loss distance equivalent to 5% of the entry price, the strategy computes the number of units (shares or contracts) to ensure the total loss, if the stop loss is hit, equals $20. To prevent over-leveraging, the strategy includes checks to ensure that the position’s dollar value does not exceed available capital. If it does, the position size is scaled down to fit within the capital constraints, maintaining financial discipline.
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4. Flexible Capital Management
The strategy’s dual profit management modes—SnowBall and ZeroRisk—offer traders strategic flexibility:
SnowBall Mode: By compounding profits, traders can increase their capital base, leading to larger position sizes over time. This is ideal for those with a long-term growth mindset, as it harnesses the power of exponential returns.
ZeroRisk Mode: By withdrawing profits and trading solely with the initial capital, traders protect their gains and limit exposure to market volatility. This conservative approach suits those prioritizing stability over aggressive growth.
These options allow traders to tailor the strategy to their risk tolerance, financial goals, and market outlook, enhancing its applicability across different trading styles.
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5. Time-Based Trade Filtering
To optimize performance and relevance, the strategy includes an option to restrict trading to a specific time range (e.g., from 2018 onward). This feature enables traders to focus on periods with favorable market conditions, avoid historically volatile or unreliable data, or align the strategy with their backtesting objectives. By confining trades to a defined timeframe, the strategy ensures that performance metrics reflect the intended market context.
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Strengths of the Strategy
The EMA 12/26 With ATR Volatility Stoploss strategy offers several compelling advantages:
Systematic and Objective: By adhering to predefined rules, the strategy eliminates emotional biases, ensuring consistent execution across market conditions.
Robust Risk Controls: The combination of ATR-based stop losses and risk-based position sizing caps losses at user-defined levels, fostering capital preservation.
Customizability: Traders can adjust parameters such as EMA periods, ATR multipliers, and risk percentages, tailoring the strategy to specific markets or preferences.
Volatility Adaptation: Stop losses that scale with market volatility enhance the strategy’s resilience, accommodating both calm and turbulent market phases.
Enhanced Visualization: The use of color-coded EMAs (green for bullish, red for bearish) and background shading provides intuitive visual cues, simplifying trend and trade status identification.
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Limitations and Considerations
Despite its strengths, the strategy has inherent limitations that traders must address:
False Signals in Range-Bound Markets: EMA crossovers may generate misleading signals in sideways or choppy markets, leading to whipsaws and unprofitable trades.
Signal Lag: As lagging indicators, EMAs may delay entry or exit signals, causing traders to miss rapid trend shifts or enter trades late.
Overfitting Risk: Excessive optimization of parameters to fit historical data can impair the strategy’s performance in live markets, as past patterns may not persist.
Impact of High Volatility: In extremely volatile markets, wider stop losses may result in larger losses than anticipated, challenging risk management assumptions.
Data Reliability: The strategy’s effectiveness depends on accurate, continuous price data, and discrepancies or gaps can undermine signal accuracy.
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Practical Applications
The EMA 12/26 With ATR Volatility Stoploss strategy is versatile, applicable to diverse markets such as stocks, forex, commodities, and cryptocurrencies, particularly in trending environments. To maximize its potential, traders should adopt a rigorous implementation process:
Backtesting: Evaluate the strategy’s historical performance across various market conditions to assess its robustness and identify optimal parameter settings.
Forward Testing: Deploy the strategy in a demo account to validate its real-time performance, ensuring it aligns with live market dynamics before risking capital.
Ongoing Monitoring: Continuously track trade outcomes, analyze performance metrics, and refine parameters to adapt to evolving market conditions.
Additionally, traders should consider market-specific factors, such as liquidity and volatility, when applying the strategy. For instance, highly liquid markets like forex may require tighter ATR multipliers, while less liquid markets like small-cap stocks may benefit from wider stop losses.
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Conclusion
The EMA 12/26 With ATR Volatility Stoploss strategy is a sophisticated, systematic trading framework that blends trend-following precision with disciplined risk management. By leveraging EMA crossovers for signal generation, ATR-based stop losses for volatility adjustment, and dynamic position sizing for risk control, it offers a balanced approach to capturing market trends while safeguarding capital. Its flexibility—evident in customizable parameters and dual profit management modes—makes it suitable for traders with varying risk appetites and objectives. However, its limitations, such as susceptibility to false signals and signal lag, necessitate thorough testing and prudent application. Through rigorous backtesting, forward testing, and continuous refinement, traders can harness this strategy to achieve consistent, risk-adjusted returns in trending markets, establishing it as a valuable tool in the arsenal of systematic trading.
Disparity Index with Volatility ZonesDisparity Index with Volatility Zones
is a momentum oscillator that measures the percentage difference between the current price and its simple moving average (SMA). This allows traders to identify overbought/oversold conditions, assess momentum strength, and detect potential trend reversals or continuations.
🔍 Core Concept:
The Disparity Index (DI) is calculated as:
DI = 100 × (Price − SMA) / SMA
A positive DI indicates the price is trading above its moving average (potential bullish sentiment), while a negative DI suggests the price is below the average (potential bearish sentiment).
This version of the Disparity Index introduces a dual-zone volatility framework, offering deeper insight into the market's current state.
🧠 What Makes This Version Unique?
1. High Volatility Zones
When DI crosses above +1.0% or below –1.0%, it often indicates the start or continuation of a strong trend.
Sustained readings beyond these thresholds typically align with trending phases, offering opportunities for momentum-based entries.
A reversal back within ±1.0% after exceeding these levels can suggest a shift in momentum — similar to how RSI exits the overbought/oversold zones before reversals.
These thresholds act as dynamic markers for breakout confirmation and potential trend exhaustion.
2. Low Volatility Zones
DI values between –0.5% and +0.5% define the low-volatility zone, shaded for visual clarity.
This area typically indicates market indecision, sideways price action, or consolidation.
Trading within this range may favor range-bound or mean-reversion strategies, as trend momentum is likely limited.
The logic is similar to interpreting a flat ADX, tight Bollinger Bands, or contracting Keltner Channels — all suggesting consolidation.
⚙️ Features:
Customizable moving average length and input source
Adjustable thresholds for overbought/oversold and low-volatility zones
Optional visual fill between low-volatility bounds
Clean and minimal chart footprint (non-essential plots hidden by default)
📈 How to Use:
1. Trend Confirmation:
A break above +1.0% can be used as a bullish continuation signal.
A break below –1.0% may confirm bearish strength.
Long periods above/below these thresholds support trend-following entries.
2. Reversal Detection:
If DI returns below +1.0% after exceeding it, bullish momentum may be fading.
If DI rises above –1.0% after falling below, bearish pressure may be weakening.
These shifts resemble overbought/oversold transitions in oscillators like RSI or Stochastic, and can be paired with divergence, volume, or price structure analysis for higher reliability.
3. Sideways Market Detection:
DI values within ±0.5% indicate low volatility or a non-trending environment.
Traders may avoid breakout entries during these periods or apply range-trading tactics instead.
Observing transitions out of the low-volatility zone can help anticipate breakouts.
4. Combine with Other Indicators:
DI signals can be enhanced using tools like MACD, Volume Oscillators, or Moving Averages.
For example, a DI breakout beyond ±1.0% supported by a MACD crossover or volume spike can help validate trend initiation.
This indicator is especially powerful when paired with Bollinger Bands:
A simultaneous price breakout from the Bollinger Band and DI moving beyond ±1.0% can help identify early trend inflection points.
This combination supports entering positions early in a developing trend, improving the efficiency of trend-following strategies and enhancing decision-making precision.
It also helps filter false breakouts when DI fails to confirm the move outside the band.
This indicator is designed for educational and analytical purposes and works across all timeframes and asset classes.
It is particularly useful for traders seeking a clear framework to identify momentum strength, filter sideways markets, and improve entry timing within a larger trading system.
