QuantRX Trendlines v1QuantRX Trendlines v1 is a visual market structure indicator designed to automatically draw trendlines and channels based on recent swing highs and lows.
The tool focuses on clean chart structure by dynamically updating trendlines as price evolves, helping users visualize support, resistance, and directional bias across any market or timeframe.
Key characteristics:
Automatic detection of swing-based trendlines
Optional channel mode with adjustable thickness
Wick or body anchoring for different structure interpretations
Visual differentiation between active and broken lines
Designed to reduce chart clutter and improve readability
This indicator is intended as a visual analysis aid only.
It does not generate trade signals, predictions, or risk management instructions.
Users are encouraged to combine it with their own analysis and decision-making process.
⚠️ Disclaimer
This script is provided for educational and visual charting purposes only and does not constitute financial, investment, or trading advice.
M-trend
Vdubus Momentum Lock (Overlay)The Top Indicator: "Vdubus Momentum Lock (Overlay)"
The Bottom Indicator: "Vdubus TrixStoch HMA"
Purpose: Precision timing. It shows you exactly when the pullbacks happen.
The Trigger Zones (48 / 52):
Buy Zone (Below 48): When the Blue line dips into this zone, the market is "reloading" for a buy.
Sell Zone (Above 52): When the Blue line pops into this zone, the market is "reloading" for a sell.
The Confluence Circles:
Green Dot ("Dip"): Appears only if HMA is Green AND Trix is Rising. This filters out bad buy signals during downtrends.
Red Dot ("Rally"): Appears only if HMA is Red AND Trix is Falling. This filters out bad sell signals during uptrends.
3. The Strategy:
A. Entry Logic (The Sniper)
Trend Check: Is HMA 100 Green or Red?
Momentum Check: Is TRIX 34 agreeing with the HMA?
Trigger:
Buy: Stoch K crosses under 48.
Sell: Stoch K crosses over 52.
Pulse Re-Entry: If Trix momentum was lost briefly but snaps back into alignment, re-enter immediately (even without a Stoch signal).
B. Exit Logic (The Safety)
Momentum Exit: If the TRIX slope flips against you (e.g., you are Long, but Trix turns down), CLOSE IMMEDIATELY.
Hard Deck (HMA Flip): If the HMA line changes color, CLOSE EVERYTHING. This is the emergency brake.
Adaptive Trend Envelope [BackQuant]Adaptive Trend Envelope
Overview
Adaptive Trend Envelope is a volatility-aware trend-following overlay designed to stay responsive in fast markets while remaining stable during slower conditions. It builds a dynamic trend spine from two exponential moving averages and surrounds it with an adaptive envelope whose width expands and contracts based on realized return volatility. The result is a clean, self-adjusting trend structure that reacts to market conditions instead of relying on fixed parameters.
This indicator is built to answer three core questions directly on the chart:
Is the market trending or neutral?
If trending, in which direction is the dominant pressure?
Where is the dynamic trend boundary that price should respect?
Core trend spine
At the heart of the indicator is a blended trend spine:
A fast EMA captures short-term responsiveness.
A slow EMA captures structural direction.
A volatility-based blend weight dynamically shifts influence between the two.
When short-term volatility is low relative to long-term volatility, the fast EMA has more influence, keeping the trend responsive. When volatility rises, the blend shifts toward the slow EMA, reducing noise and preventing overreaction. This blended output is then smoothed again to form the final trend spine, which acts as the structural backbone of the system.
Volatility-adaptive envelope
The envelope surrounding the trend spine is not based on ATR or fixed percentages. Instead, it is derived from:
Log returns of price.
An exponentially weighted variance estimate.
A configurable multiplier that scales envelope width.
This creates bands that automatically widen during volatile expansions and tighten during compression. The envelope therefore reflects the true statistical behavior of price rather than an arbitrary distance.
Inner hysteresis band
Inside the main envelope, an inner band is constructed using a hysteresis fraction. This inner zone is used to stabilize regime transitions:
It prevents rapid flipping between bullish and bearish states.
It allows trends to persist unless price meaningfully invalidates them.
It reduces whipsaws in sideways conditions.
Trend regime logic
The indicator operates with three regime states:
Bullish
Bearish
Neutral
Regime changes are confirmed using a configurable number of bars outside the adaptive envelope:
A bullish regime is confirmed when price closes above the upper envelope for the required number of bars.
A bearish regime is confirmed when price closes below the lower envelope for the required number of bars.
A trend exits back to neutral when price reverts through the trend spine.
This structure ensures that trends are confirmed by sustained pressure rather than single-bar spikes.
Active trend line
Once a regime is active, the indicator plots a single dominant trend line:
In a bullish regime, the lower envelope becomes the active trend support.
In a bearish regime, the upper envelope becomes the active trend resistance.
In neutral conditions, price itself is used as a placeholder.
This creates a simple, actionable visual reference for trend-following decisions.
Directional energy visualization
The indicator uses layered fills to visualize directional pressure:
Bullish energy fills appear when price holds above the active trend line.
Bearish energy fills appear when price holds below the active trend line.
Opacity gradients communicate strength and persistence rather than binary states.
A subtle “rim” effect is added using ATR-based offsets to give depth and reinforce the active side of the trend without cluttering the chart.
Signals and trend starts
Discrete signals are generated only when a new trend regime begins:
Buy signals appear at the first confirmed transition into a bullish regime.
Sell signals appear at the first confirmed transition into a bearish regime.
Signals are intentionally sparse. They are designed to mark regime shifts, not every pullback or continuation, making them suitable for higher-quality trend entries rather than frequent trading.
Candle coloring
Optional candle coloring reinforces regime context:
Bullish regimes tint candles toward the bullish color.
Bearish regimes tint candles toward the bearish color.
Neutral states remain visually muted.
This allows the chart to communicate trend state even when the envelope itself is partially hidden or de-emphasized.
Alerts
Built-in alerts are provided for key trend events:
Bull trend start.
Bear trend start.
Transition from trend to neutral.
Price crossing the trend spine.
These alerts support hands-off trend monitoring across multiple instruments and timeframes.
How to use it for trend following
Trend identification
Only trade in the direction of the active regime.
Ignore counter-trend signals during confirmed trends.
Entry alignment
Use the first regime signal as a structural entry.
Use pullbacks toward the active trend line as continuation opportunities.
Trend management
As long as price respects the active envelope boundary, the trend remains valid.
A move back through the spine signals loss of trend structure.
Market filtering
Periods where the indicator remains neutral highlight non-trending environments.
This helps avoid forcing trades during chop or compression.
Adaptive Trend Envelope is designed to behave like a living trend structure. Instead of forcing price into static rules, it adapts to volatility, confirms direction through sustained pressure, and presents trend information in a clean, readable form that supports disciplined trend-following workflows.
Volatility Regimes | GainzAlgo📊 OVERVIEW:
=========
This is a comprehensive ATR-based trading system designed for professional
traders who need advanced volatility analysis, precise trade management, and
intelligent market regime detection. The indicator combines multiple proven
volatility concepts into one powerful, customizable tool.
⭐ WHY THIS SYSTEM IS UNIQUE AND WORTHY OF PUBLICATION:
====================================================
This is not simply a collection of ATR-based indicators placed together.
It represents a unified volatility analysis framework where each component
is specifically designed to work in concert with the others, creating a
complete trading workflow that cannot be replicated by using multiple
separate indicators.
🔗 SYNERGISTIC INTEGRATION - How Components Work Together:
🧠 1. CONTEXT-AWARE ANALYSIS
The Volatility Regime Detection acts as the "brain" of the system,
classifying market conditions into 4 distinct phases. Every other
component then adapts its behavior based on this regime classification:
- ATR Bands expand/contract with regime changes
- Stop Loss distances automatically adjust (tighter in compression,
wider in high volatility)
- Take Profit targets scale proportionally to current regime
- Signal sensitivity filters itself based on market phase
📐 2. UNIFIED VOLATILITY FOUNDATION
All calculations share a single ATR baseline calculation, ensuring
internal consistency across the entire system. When ATR changes, every
element updates in perfect synchronization:
- Bands recalculate from the same ATR value
- Risk management levels use the same volatility measurement
- Regime classification and signals reference identical data
🛡️ 3. INTEGRATED RISK MANAGEMENT
The system doesn't just show WHERE to enter - it calculates HOW MUCH
to risk:
- Dynamic Stop Loss adapts to current ATR automatically
- Position Size Calculator uses the dynamic stop to compute exact quantities
- Take Profit levels scale proportionally, maintaining optimal risk:reward
✅ 4. TWO-STAGE SIGNAL CONFIRMATION
The alert system creates a logical progression:
Step 1: Volatility Breakout → Market energy is building
Step 2: Trend Confirmation → Direction confirmed with volatility support
This prevents false breakouts by requiring both volatility AND direction.
🏦 5. PROFESSIONAL WORKFLOW INTEGRATION
The system mirrors how institutional traders analyze markets:
Phase 1: Assess regime → What's the market doing?
Phase 2: Identify setup → Where's the opportunity?
Phase 3: Calculate risk → What's my exposure?
Phase 4: Set targets → Where do I take profit?
Phase 5: Monitor regime → When do conditions change?
❌ WHY NOT USE SEPARATE INDICATORS?
- Separate ATR Bands: Don't know about regime changes, remain static
- Separate Regime Indicator: Doesn't automatically adjust stop/targets
- Separate Position Calculator: Doesn't know your actual ATR-based stop
- Manual Integration: Requires constant mental calculation and cross-referencing
🧮 DETAILED CALCULATION METHODOLOGY:
=================================
📏 ATR (AVERAGE TRUE RANGE) CALCULATION:
- True Range = Maximum of:
1. Current High - Current Low
2. Absolute value of (Current High - Previous Close)
3. Absolute value of (Current Low - Previous Close)
- ATR = Simple Moving Average of True Range over specified period (default: 14)
📊 DYNAMIC ATR BANDS:
- Upper Band = Current Close + (ATR × Band Multiplier)
- Lower Band = Current Close - (ATR × Band Multiplier)
- Band 1: 1.0× ATR (closest support/resistance)
- Band 2: 2.0× ATR (intermediate zone)
- Band 3: 3.0× ATR (extended zone)
🌡️ VOLATILITY REGIME CLASSIFICATION:
Step 1: Calculate ATR Baseline
- Baseline ATR = SMA or EMA of ATR over long period (default: 50 bars)
- This represents "normal" volatility for the instrument
Step 2: Calculate ATR Ratio
- ATR Ratio = Current ATR ÷ Baseline ATR
- Example: If current ATR = 70 and baseline = 50, ratio = 1.40
Step 3: Classify Regime Based on Ratio
- COMPRESSION: Ratio < 0.70 (ATR is 30% below normal)
Market consolidating, volatility contracting, energy building
- EXPANSION: Ratio between 1.15 and 1.40 (ATR is 15-40% above normal)
Volatility breaking out, early phase of directional movement
- HIGH VOLATILITY: Ratio > 1.40 (ATR is 40%+ above normal)
Strong sustained trend with high participation
- EXHAUSTION: ATR declining after high volatility period
Requires: Previous high ratio + declining ATR over X bars (default: 5)
Trend maturity, potential reversal or consolidation approaching
🛑 DYNAMIC STOP LOSS CALCULATION:
- For Long Positions: Stop Loss = Entry Price - (ATR × SL Multiplier)
- For Short Positions: Stop Loss = Entry Price + (ATR × SL Multiplier)
- Default Multiplier: 2.0× ATR
- Adjusts automatically: Wider in high volatility, tighter in compression
🎯 TAKE PROFIT LEVELS:
- TP1 = Entry Price ± (ATR × TP1 Multiplier)
- TP2 = Entry Price ± (ATR × TP2 Multiplier)
- TP3 = Entry Price ± (ATR × TP3 Multiplier)
- Direction (+ or -) depends on trade direction
📦 POSITION SIZE CALCULATION:
Formula: Position Size = Account Risk Amount ÷ Stop Loss Distance
Step-by-step:
1. Risk Amount = Account Size × (Risk Percentage ÷ 100)
2. Stop Distance = |Entry Price - Stop Loss Price|
3. Position Size = Risk Amount ÷ Stop Distance
📈 ATR PERCENTILE RANKING:
- >80% = Extremely high volatility
- 20-80% = Normal volatility range
- <20% = Extremely low volatility
🌀 VOLATILITY CONTRACTION PATTERN:
Detects extended low-volatility periods indicating imminent breakout.
🧭 TREND DETECTION SIGNALS:
Bullish: Price > MA AND Current ATR > ATR MA
Bearish: Price < MA AND Current ATR > ATR MA
⚡ VOLATILITY BREAKOUT SIGNALS:
Triggered when ATR exceeds its moving average by a defined threshold.
🧩 CORE FEATURES:
==============
1. ATR BANDS (Dynamic Support/Resistance)
2. VOLATILITY REGIME DETECTION
3. DYNAMIC STOP LOSS SYSTEM
4. MULTIPLE TAKE PROFIT LEVELS
5. SUPPORT & RESISTANCE LEVELS
6. RISK MANAGEMENT CALCULATOR
7. ATR PERCENTILE RANKING
8. VOLATILITY CONTRACTION PATTERN
9. TREND DETECTION SIGNALS
10. VOLATILITY BREAKOUT SIGNALS
⚙️ RECOMMENDED SETTINGS BY TRADING STYLE:
======================================
DAY TRADING • SWING TRADING • POSITION TRADING • SCALPING
📘 HOW TO USE THIS INDICATOR:
==========================
STEP 1: Identify Market Regime
STEP 2: Wait for Entry Signal
STEP 3: Set Stop Loss
STEP 4: Set Take Profits
STEP 5: Position Sizing
STEP 6: Monitor & Manage
🔔 ALERT SYSTEM:
=============
Alerts for volatility breakouts, trend changes, regime transitions,
ATR band crossings, contraction completion, and percentile extremes.
🎨 CUSTOMIZATION:
==============
All visuals, thresholds, multipliers, colors, alerts, and risk parameters
can be fully customized.
⚠️ IMPORTANT DISCLAIMER:
=====================
This indicator is a volatility analysis tool and does NOT provide financial advice.
Past performance does not guarantee future results.
All trading involves substantial risk.
All trading decisions are the sole responsibility of the user.
Adaptive Strength Overlay (MTF) [BackQuant]Adaptive Strength Overlay (MTF)
A multi-timeframe RSI strength visualizer that projects oscillator “pressure” directly onto price using adaptive gradient fills between percent bands. Built to make strength, exhaustion, and regime context readable at a glance, without needing to stare at a separate oscillator panel.
Mean-Reversion mode example
What this indicator does
This indicator converts RSI strength into a chart overlay that reacts to momentum and extremes, then visualizes it as colored “pressure zones” around price.
Instead of plotting RSI in a sub-window, it:
Builds 1 to 3 symmetric percent bands above and below price.
Computes RSI strength on up to 3 different timeframes (MTF).
Smooths RSI with your selected moving average type.
Maps RSI values into discrete transparency “buckets”.
Fills between the bands with a gradient whose opacity reflects strength or exhaustion.
Displays a compact RSI table for all enabled timeframes.
Provides alert conditions for extremes and midline shifts on each timeframe.
The result is an overlay that looks like a dynamic envelope. When strength rises, the envelope “lights up” in the direction of the move. When strength becomes stretched, the outer zones become visually prominent.
Core idea: “Strength as an overlay”
RSI is normally interpreted in a separate oscillator panel. That makes context-switching slow:
You check price action.
You look down at RSI.
You mentally translate RSI into risk or trend bias.
This script removes that translation step by projecting strength directly onto the price area, using band fills as a visual language:
More visible fill = stronger strength or more extreme condition (depending on mode).
Less visible fill = weak strength or neutral state.
Two operating modes
1) Trend mode
Trend mode emphasizes strength aligned with direction:
When RSI is strong on the upside, upper bands become more visible.
When RSI is strong on the downside, lower bands become more visible.
Neutral RSI fades, so the chart de-clutters during chop.
Use Trend mode when:
You want a clean trend-following overlay.
You want to quickly see which timeframe(s) are powering the move.
You want to filter entries to moments when strength confirms direction.
2) Mean-Reversion mode
Mean-Reversion mode flips the emphasis to highlight exhaustion against the move :
Upper extremes become a “potential exhaustion” cue.
Lower extremes become a “potential exhaustion” cue.
The overlay is tuned to make stretched conditions obvious.
This is not an automatic “short overbought / long oversold” system. It is a visualization mode that makes “extended” conditions stand out faster, especially when multiple timeframes align.
How the bands work (Percent Bands)
The indicator constructs up to three symmetric envelopes around price:
Band 1: percent1 scaled by scale
Band 2: percent2 scaled by scale (optional)
Band 3: percent3 scaled by scale (optional)
The percent bands are simple deviations from the selected price source:
Upper = price * (1 + (percent * scaling)/100)
Lower = price * (1 - (percent * scaling)/100)
Why this matters:
It anchors “strength visualization” to meaningful price distance.
It makes the overlay comparable across assets because it’s percent-based.
It gives you a consistent spatial frame for reading momentum versus extension.
Multi-timeframe engine (MTF)
The script runs the same strength calculation on up to three timeframes:
Timeframe 1 uses the chart timeframe by default (empty string input).
Timeframe 2 is optional and defaults to Daily.
Timeframe 3 is optional and defaults to Weekly.
Each timeframe has:
Its own RSI period (len, len2, len3).
Its own smoothing length (slen, slen2, slen3).
The same smoothing type selection (EMA, HMA, etc).
This creates a layered view:
TF1 often reflects tactical pressure (entries/exits).
TF2 reflects structural pressure (swing context).
TF3 reflects macro bias (regime context).
When multiple timeframes agree, the fills stack and the overlay becomes visually louder. When they disagree, the overlay looks mixed or muted, which is exactly the point.
Smoothing options (why so many)
Raw RSI can be noisy. This script lets you smooth RSI with multiple MA types, which changes how “responsive” the overlay feels:
EMA/RMA smooth without lagging as hard as SMA.
HMA responds faster but can be twitchy.
LINREG can feel more “structural”.
ALMA and T3/TEMA provide heavier smoothing profiles with different lag characteristics.
This isn’t cosmetic. Your smoothing choice affects:
How early the overlay “lights up” in Trend mode.
How long extremes remain highlighted in Mean-Reversion mode.
How often fills flicker in chop.
Strength mapping (the transparency buckets)
Instead of mapping RSI to a continuous color scale, the script uses a discrete transparency ladder. That creates a clean, readable visual that avoids constant flickering.
The logic assigns two transparency values per timeframe:
Upper-side transparency responds to lower RSI zones (weak upside strength).
Lower-side transparency responds to higher RSI zones (strong upside strength).
Then the script uses those transparencies differently depending on mode:
Trend mode shows “strength aligned with direction”.
Mean-Reversion mode swaps the emphasis so “extremes” stand out as potential stretch.
You can think of it as:
Trend mode highlights continuation strength.
Mean-Reversion mode highlights potential exhaustion.
Fill stacking (how the overlay is built)
The overlay uses layered fills:
Fill from price to Band 1
Fill from Band 1 to Band 2 (if enabled)
Fill from Band 2 to Band 3 (if enabled)
Upper side uses the negative color (typically red) and lower side uses the positive color (typically green), because upper bands represent “above price” space and lower bands represent “below price” space. The intensity is controlled by the computed transparency per timeframe and selected mode.
Important behavior:
Disabling Band 2 or Band 3 can change how the stacked fills look, because you are removing fill segments.
If you want a clean look, run only Band 1.
If you want a “regime heat” look, run Bands 1–3 with higher scaling.
Table (MTF RSI dashboard)
A compact table prints RSI values for each configured timeframe:
Row labels show TF.
Values show the smoothed RSI output that drives the overlay.
Use it for quick confirmation:
If overlay looks strong but table RSI is neutral, your band settings might be too tight.
If TF3 RSI is extreme while TF1 is neutral, you are likely in a macro stretched regime with local consolidation.
Alerts (built-in)
Alerts are provided for each timeframe separately, covering:
Entering upper extreme (cross above 70)
Exiting upper extreme (cross below 70)
Entering lower extreme (cross below 30)
Exiting lower extreme (cross above 30)
Bullish midline cross (cross above 50)
Bearish midline cross (cross below 50)
This enables workflows like:
Notify when TF2 enters extreme, then wait for TF1 mean-reversion confirmation.
Notify when TF3 crosses midline, then only take TF1 trend setups in that direction.
How to use it (practical reads)
Trend mode reads
Strong continuation: TF1 and TF2 fills become clearly visible on the same side.
Healthy pullback: TF1 fades but TF2 stays visible, suggesting underlying structure remains strong.
Chop warning: fills alternate or remain mostly invisible, indicating neutral strength.
Mean-Reversion mode reads
Exhaustion zones: outer fills become prominent near the extremes, signaling stretched conditions.
Compression after extreme: fill fades while price stabilizes, suggesting “cooling off” rather than immediate reversal.
Multi-TF stretch: TF2 and TF3 extremes together often mark higher significance zones.
Recommended setup presets
Preset A: Clean trend overlay
Mode: Trend
Bands: only Band 1
Scale: 1–2
Smoothing: EMA, moderate slen (6–10)
TF2: Daily on intraday charts
Preset B: Regime and exhaustion mapper
Mode: Mean-Reversion
Bands: Bands 1–3
Scale: 2–4
Smoothing: T3 or RMA, slightly higher slen
TF2: Daily, TF3: Weekly
Limitations
This is a strength visualization tool, not a full entry/exit system.
Percent bands are not volatility-adjusted, they are distance frames. In very high vol conditions, you may need higher band percentages or higher scaling.
MTF values update on their own timeframe closes, so higher timeframes will step rather than update every bar.
Tabla de EMA's y TimeframesGraphic and permanent representation of the trend of an action/CFD/stock/crypto, directly related to the technical analysis of its EMA's.
Polynomial Regression Channel [ChartPrime]⯁ OVERVIEW
The Polynomial Regression Channel fits price action using advanced polynomial regression, extending beyond simple linear or logarithmic models. By leveraging matrix calculations, it builds a curved regression line that adapts to swings more naturally. The channel includes extrapolated forward projections, helping traders visualize where price may gravitate in the near future. Midline color shifts reflect directional bias, while prediction ranges are marked with dashed extensions, labeled prices, and a live table for clarity.
⯁ KEY FEATURES
Polynomial Regression Core:
Uses matrix algebra to calculate a polynomial fit of customizable degree, adapting to complex, non-linear market structures.
polyreg(source, length, degree, extrapolate) =>
total = length + extrapolate
X_all = matrix.new(total, degree + 1, 0.0)
for i = 0 to total - 1
for j = 0 to degree
matrix.set(X_all, i, j, math.pow(i, j))
// y (length × 1), oldest→newest over the fit window
y = matrix.new(length, 1, 0.0)
for i = 0 to length - 1
matrix.set(y, i, 0, source )
// X_train (first `length` rows of X_all)
X_tr = matrix.new(length, degree + 1, 0.0)
for i = 0 to length - 1
for j = 0 to degree
matrix.set(X_tr, i, j, matrix.get(X_all, i, j))
// OLS via normal equations: (X'X)^(-1)b = X'y ⇒ b = (X'X)^(-1) X'y
Xt = matrix.transpose(X_tr) // X'
XtX = matrix.mult(Xt, X_tr) // (X'X)
Xty = matrix.mult(Xt, y) // X'y
XtX_inv = matrix.inv(XtX) // (X'X)^(-1)
b = matrix.mult(XtX_inv, Xty) // b = (X'X)^(-1) X'y
// Predictions for all rows (fit + extrap)
preds = matrix.mult(X_all, matrix.col(b,0))
preds
Extrapolated Future Projections:
Forward-looking range (dashed lines + circular markers) shows where the fitted polynomial suggests price may move.
Dynamic Midline Coloring:
Regression midline shifts green when slope turns upward and magenta when slope turns downward, giving instant directional context.
Channel Boundaries:
Upper and lower levels expand from the midline using a volatility-based offset, framing potential overbought and oversold conditions.
Top-Right Data Table:
A live table displays Upper, Middle, and Lower Prediction values, updating in real time for quick reference without scanning the chart.
⯁ USAGE
Use the regression midline to gauge underlying market bias; green slopes suggest continuation, magenta slopes caution for weakness.
Watch dashed extrapolated ranges as potential targets or reaction zones during upcoming sessions.
Price labels and table values act as precise reference levels for planning entries, exits, or stop placement.
Increase Degree for more curve-fitting on choppy markets, or keep it low for broader trend approximation.
Adjust Period and Extrapolate length to balance stability vs. responsiveness.
⯁ CONCLUSION
The Polynomial Regression Channel offers a mathematically advanced way to visualize price trends and anticipate future paths. With matrix-driven polynomial fitting, extrapolated projections, and integrated live labels, it combines statistical rigor with practical trading visuals — a robust upgrade over standard regression channels.
Quality-Controlled Trend Strategy v2 (Expectancy Focused)This script focuses on quality control rather than curve-fitting.
No repainting, no intrabar tricks, no fake equity curves.
It uses confirmed-bar entries, ATR-based risk, and clean trend logic so backtests reflect what could actually be traded live.
If you publish scripts, this is the minimum structure worth sharing.
Why this script exists
TradingView’s public scripts are flooded with:
repainting indicators
no stop-loss logic
curve-fit entries that collapse live
strategies that look good only in hindsight
This script is intentionally boring but honest.
No repainting.
No intrabar tricks.
No fake equity curves
The goal is quality control, not hype.
What this strategy enforces
✔ Confirmed bars only
✔ Single source of truth for indicators
✔ Fixed risk structure
✔ No signal repainting
✔ Clean exits with unique IDs
✔ Works on any liquid market
Trading Logic (simple & auditable)
Trend filter
EMA 50 vs EMA 200
Entry
Pullback to EMA 50
RSI confirms momentum (not oversold/overbought)
Risk
ATR-based stop
Fixed R:R
One position at a time
This is the minimum bar for a strategy to be considered publish-worthy.
Why this helps TradingView quality
Most low-value scripts fail because they:
hide repainting logic
skip exits entirely
use inconsistent calculations
rely on hindsight candles
This strategy forces discipline:
every signal is confirmed
every trade has defined risk
behavior is repeatable across symbols & timeframes
If more scripts followed this baseline, TradingView’s public library would be far more usable.
Cyber Pips Wave & Momentum SuiteCyber Pips Wave & Momentum Suite is an oscillator-based analysis indicator that combines WaveTrend-style momentum with divergence highlighting and additional momentum context.
It includes:
• Oscillator lines with customizable overbought/oversold zones
• Optional cross-based markers for momentum shifts
• Regular and hidden divergence detection (with optional strength filtering)
• Trend and volume confirmation filters to reduce low-quality signals
• Informational momentum labels for context
Notes:
• Outputs can update on the currently forming candle.
• Any display offsets (if enabled) affect visualization only and do not predict future bars.
This script is provided for charting and educational purposes only. It does not provide financial advice or performance guarantees.
Opening Path Selector (EMA200 Context Tool)📝 Description
Opening Path Selector is a context-based indicator designed to help traders quickly identify which asset may offer the cleanest directional path at the market open.
This tool does not generate entry or exit signals.
Its purpose is to reduce decision fatigue during the first minutes of the session by ranking a small set of high-liquidity assets based on higher-timeframe EMA200 structure.
🔍 What this indicator evaluates
The dashboard compares a predefined group of major symbols and ranks them according to:
• Proximity to the nearest EMA200
• Relative position versus higher-timeframe EMA200 levels
• Directional context inferred from EMA structure
The result is a priority-based list that highlights which asset may present:
• Less immediate EMA resistance
• Clearer directional context
• Lower probability of early-session chop
📊 How to read the dashboard
• Priority – Ranking based on opening context
• Symbol – Evaluated instrument
• Nearest EMA200 – Distance and side relative to price
• Possible Path – Direction with less immediate EMA resistance
• Bias – Strength of the higher-timeframe context
Colored markers are used to provide fast visual identification of the highest-priority assets.
⚠️ Important notes
• This is a context and selection tool, NOT a trading system
• No buy/sell signals, alerts, TP, or SL logic are included
• Designed to be used alongside your own execution methodology
🔧 Compatibility
Due to Pine Script multi-symbol and multi-timeframe constraints, this public version is intentionally limited to a small set of symbols.
TradingView Pro / Premium or higher is recommended for consistent performance.
🔗 Complementary tools
This indicator can be complemented with Multi-Tool VWAP + EMAs (Multi-Timeframe) + Key Levels , which provides detailed visibility of multiple EMA levels, VWAP structure, and higher-timeframe reference zones directly on the chart.
While Opening Path Selector helps decide which asset to focus on at the open, the complementary tool can assist with in-chart context and confirmation once an asset has been selected.
Both tools are designed to serve different stages of the decision process and can be used independently.
Liquidity Strain Detector [MarkitTick]💡 This indicator provides a specialized method for detecting market anomalies where price movement becomes disconnected from typical volume profiles, signaling potential exhaustion events. By combining statistical analysis of liquidity (price impact) with a directional trend filter, the tool aims to highlight moments of extreme market stress, such as panic selling or euphoric buying, that often precede mean reversions or trend pauses.
● Originality and Utility
Standard volume indicators often look at raw volume levels, which can be misleading during different times of the day or across different assets. This script calculates the efficiency of moving price (Illiquidity) and normalizes it statistically. This allows the trader to see when the market is becoming thin or stressed relative to recent history. It is particularly useful for contrarian traders looking for capitulation points within established trends, offering a unique perspective beyond standard RSI or MACD divergence.
● Methodology
The core mechanism drives a custom Liquidity Engine that performs the following steps:
Price Impact Calculation: It computes the ratio of the True Range to Volume. High values indicate that price is moving significant distances on relatively low volume or that volatility is extreme relative to participation.
Normalization: The raw impact data is smoothed using a logarithmic scale to handle the wide variance in volume data.
Statistical Scoring (Z-Score): The script calculates the Z-Score of this normalized data over a user-defined lookback period. This determines how many standard deviations the current liquidity stress is away from the mean.
Trend Filtering: A standard Exponential Moving Average (EMA) determines the dominant market direction to contextualize the stress signal.
● How to Use
The indicator plots labels on the chart when specific High Stress conditions are met during a trend:
SE (Seller Exhaustion - Green Label): Appears when the market is in a downtrend (price below EMA), the current candle is bearish, and the liquidity stress Z-Score breaches the upper threshold. This suggests panic selling or a liquidity gap down, often marking a temporary bottom or reversal point.
BE (Buyer Exhaustion - Red Label): Appears when the market is in an uptrend (price above EMA), the current candle is bullish, and the liquidity stress Z-Score breaches the upper threshold. This suggests a melt-up or buying climax into thin liquidity, often preceding a pullback.
● Inputs
Trend Filter Length: The period for the EMA used to determine the baseline trend direction.
Statistical Lookback: The number of bars used to calculate the mean and standard deviation for the Z-Score.
Stress Threshold (Sigma): The Z-Score value required to trigger a high-stress signal. Higher values result in fewer, more extreme signals.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
LTF Distribution Analyzer█ OVERVIEW
LTF Distribution Analyzer reveals the hidden price distribution and order flow within each candle by sampling lower timeframe data. It visualizes where prices concentrated, how volume was distributed between buyers and sellers, and identifies divergences between price action and actual market participation.
Unlike traditional candlesticks showing only OHLC, this indicator exposes the statistical structure of price movement using quartile-based visualization combined with delta analysis.
█ CONCEPTS
The indicator is built on two core concepts:
1 — Statistical Price Distribution
Each candle contains many lower timeframe bars. By analyzing these bars, we calculate:
• Q1 (25th percentile) - 25% of prices traded below this level
• Q3 (75th percentile) - 75% of prices traded below this level
• Median - The middle price value
• IQR (Interquartile Range) - The Q3-Q1 spread containing 50% of all prices
2 — Volume Delta Analysis
Delta measures buying vs selling pressure:
• Delta = Buy Volume − Sell Volume
• Positive delta = More aggressive buying
• Negative delta = More aggressive selling
• Delta Ratio normalizes this as a percentage
█ HOW IT WORKS
The indicator fetches lower timeframe data using request.security_lower_tf() and processes it to create a statistical summary:
Step 1: Timeframe Calculation
• Auto mode: Chart timeframe ÷ Auto Divisor = LTF
• Example: 1H chart ÷ 1000 = ~3.6 second sampling
• Manual mode: User-specified timeframe
Step 2: Data Collection
• Collects all close prices from LTF bars within current candle
• Aggregates volume by candle direction (bullish/bearish)
Step 3: Statistical Analysis
• Calculates quartiles (Q1, Q3), median, and boundaries
• Identifies outliers using 1.5× and 3× IQR fences
• Finds Volume POC (price with highest volume)
Step 4: Delta Calculation
• Sums buy volume (from bullish LTF bars)
• Sums sell volume (from bearish LTF bars)
• Computes delta ratio for color determination
█ VISUAL ELEMENTS
┌─────────────────────────────────────────┐
│ ▲ Extreme outlier (3× IQR) │
│ △ Mild outlier (1.5× IQR) │
│ ─ Upper whisker cap │
│ ┊ Whisker line (dashed) │
│ ▄ IQR Box (Q1 to Q3 range) │
│ ━ Volume POC (highest volume) │
│ ● Median (green=bull, red=bear) │
│ ┊ Whisker line (dashed) │
│ ─ Lower whisker cap │
│ ▽ Mild outlier │
│ ▼ Extreme outlier │
└─────────────────────────────────────────┘
█ COLOR SYSTEM
Colors indicate the relationship between candle direction and order flow:
🟢 TEAL (Positive Flow)
Bullish candle + Positive delta
→ Strong buying confirmation
→ Trend continuation signal
🔴 RED (Negative Flow)
Bearish candle + Negative delta
→ Strong selling confirmation
→ Trend continuation signal
🟠 ORANGE (Mixed Signal A)
Bullish candle + Negative delta
→ Price up but sellers dominated
→ Potential weakness/reversal warning
🔵 BLUE (Mixed Signal B)
Bearish candle + Positive delta
→ Price down but buyers dominated
→ Potential accumulation/reversal signal
█ SETTINGS
Timeframe Settings
• LTF Mode — Auto or Manual selection
• Manual Timeframe — Specific LTF when in Manual mode
• Auto Divisor — Higher = finer granularity (default: 1000)
• Allow Sub-Minute — Requires Premium subscription
Visual Style
• Positive/Negative Flow colors — Customize the 4 flow colors
• Box Transparency — Opacity of the quartile box (0-100%)
Statistics Display
• Show Statistics Panel — Toggle on-chart stats table
• Show Timeframe Badge — Toggle LTF indicator badge
• Panel Position — Choose corner placement
• Panel Size — Text size selection
█ HOW TO USE
1. Divergence Detection
Look for color mismatches:
• Orange bars in uptrend = weakness, potential reversal
• Blue bars in downtrend = strength, potential reversal
• Multiple consecutive divergent bars strengthen signal
• Wait for confirmation before entry
2. Volume POC Trading
• POC marks where most volume traded
• POC clusters at similar levels = strong S/R zone
• Price often returns to POC before continuing
• Use POC for entry/exit targeting
3. Trend Confirmation
• Consecutive teal = strong uptrend
• Consecutive red = strong downtrend
• Median position shows intrabar momentum
• Wide boxes indicate high volatility
4. Outlier Analysis
• Extreme markers (▲▼) often mark stop hunts
• Consider fading extremes at key levels
• Mild markers (△▽) = areas to watch
█ RECOMMENDED SETTINGS
For different chart timeframes:
│ Chart TF │ Auto Divisor │ Resulting LTF │
├──────────┼──────────────┼───────────────┤
│ 15M │ 1500 │ ~1M │
│ 1H │ 1000 │ ~3-4s │
│ 4H │ 600 │ ~24s │
│ Daily │ 500 │ ~2-3M │
Tip: Check the TF badge to confirm active sampling timeframe.
█ BEST PRACTICES
Do:
✓ Use "Bars" chart style for cleanest display
✓ Combine with support/resistance analysis
✓ Wait for confirmation bars
✓ Note POC clusters across multiple bars
✓ Adjust divisor based on your timeframe
Avoid:
✗ Trading single bar signals alone
✗ Using during low volume periods
✗ Trading immediately after news releases
✗ Ignoring overall market context
█ LIMITATIONS
• Requires adequate market liquidity for reliable signals
• Sub-minute timeframes need Premium subscription
• Historical data depth depends on TradingView's data availability
• Delta calculation assumes volume direction matches candle direction
█ NOTES
This indicator works best on liquid markets (forex majors, major indices, popular stocks/crypto) where volume data is meaningful.
The gray dotted vertical line marks where LTF data becomes available - bars before this line won't display the indicator.
For questions or suggestions, leave a comment below.
SCOTTGO - MOMO RVOL Trend Painter V2 (Elite Pro)SCOTTGO - MOMO RVOL Trend Painter V2 (Elite Pro)
This professional-grade trend-following indicator identifies high-probability "Elite" entry points by combining Relative Volume (RVOL) with strict trend alignment and momentum filters. It is designed to filter out market noise and highlight only the most significant institutional moves.
Core Features
Elite Signal Logic: Triggers only when high RVOL (default >2.0x) aligns with a confirmed trend (Price vs. VWAP & 9EMA) and positive momentum (RSI & MACD).
Dynamic Bar Coloring: Instantly paints bars Green (Bullish) or Red (Bearish) when all "Elite" criteria are met.
Smart Labeling: Labels are corner-anchored to the left of the signal bar. This prevents visual clutter and ensures labels never obstruct new price action.
Detailed Tooltips: Hover over any "Elite" flag to see a comprehensive breakdown of the specific metrics (RVOL value, Trend status, RSI, and MACD) that triggered the signal.
Key Components
RVOL Threshold: Adjustable sensitivity to volume spikes.
Trend Filter: Optional requirement for price to stay above/below VWAP and the 9EMA.
Momentum Filters: Integrated RSI and MACD confirmation to avoid "exhaustion" trades.
Visual Customization: Full control over label spacing, colors, and opacity.
How to use: Look for the ⭐ ELITE flags as confirmation for trend continuation or high-volume breakouts. Use the triangles for precise candle entry points.
Disclaimer: Technical analysis tools are for informational purposes only. Trading involves significant financial risk.
Smart Impulse PRO v1.0Smart Impulse PRO (Invite‑Only) — Comprehensive Guide for TradingView
***
## English Version
Smart Impulse PRO (Invite‑Only) — Comprehensive Guide for TradingView
Strategy Concept & Uniqueness
Smart Impulse PRO is a trend‑following impulse continuation strategy built specifically for volatile crypto pairs . It uses a custom price×volume impulse signal normalized with Z‑score , then filters these impulses through multi‑timeframe trend conditions and a layered guard system that blocks structurally weak trades (flat, overextension, exhaustion).
Backtest Summary (Crypto Pairs)
Smart Impulse PRO was backtested on several volatile crypto perpetual pairs (including ETHUSDT, BTCUSDT and other majors/alts) on 1h charts in the period 01 Jan 2023 – 26 Dec 2025. On this sample, typical results were:
- Total trades per pair : ≈100–130
- Win rate range : ≈ 90–94%
- Profit factor range : ≈ 3.0–3.9
These values are historical backtest metrics on specific symbols and settings and do not guarantee similar performance in the future .
Why It’s Special
✅ Custom price×volume impulse model (Z‑score‑based) : Measures how unusual each bar’s move is in its recent context, not just simple MA/RSI crossovers
✅ 15+ Exhaustion & Structure Guards : Automatically block bad contexts (flat, low vol, overextended candles, climax volume)
✅ Dynamic TP Grid : Take‑profit levels adapt to current impulse strength |Z|
✅ Visual Transparency : Bubbles show exactly why signals were blocked
✅ Invite‑Only Logic : The concrete impulse model and guard interactions are proprietary and therefore published as invite‑only with protected source, as allowed by TradingView’s script rules.
***
### 1. What the Script Does (User View)
Smart Impulse PRO acts as an automated decision engine for volatile crypto pairs (e.g., ETHUSDT, BTCUSDT) on intraday and swing timeframes (15m–4h). It:
- Generates Long/Short entries only when both trend and impulse conditions align.
- Manages exits with a multi‑level TP grid, breakeven logic, optional trailing stop and time‑based exit.
- Visually shows both taken trades and blocked signals , including a short text reason for rejection.
This lets users trade crypto trends with a clear explanation of when and why the strategy chooses to act or stay out.
***
Entry Rules
Long (Buy):
Price is above EMA200 (long‑term trend is up)
Z‑score impulse > Z_threshold (e.g., 1.5)
Volume above recent average
ADX > Min ADX (e.g., 25)
ATR regime OK (ATR > ATR_floor and not in volatility squeeze)
All active guards pass (no overextended candle, no extreme wick against direction, no climax volume lock, no distance violation vs EMA200/VWAP, no Z‑streak lock)
Short (Sell):
Price is below EMA200 (long‑term trend is down)
Z‑score impulse > Z_threshold
Volume above recent average
ADX > Min ADX
ATR regime OK
All active guards pass (same checks, mirrored for shorts)
Logic:
The script first checks that the market is trending (EMA200 side + ADX + volatility filters), then validates that the current bar is a statistically strong price×volume impulse, and finally makes sure the bar is not an exhaustion spike or overextended move according to the guard system. Only if all three layers agree, a trade is opened.
Exit Rules
Stop‑Loss:
Initial stop‑loss is placed at a user‑defined distance (percent or ATR‑based), and position size is calculated so that a full stop equals Max Risk per Trade (%).
Take‑Profit grid:
Up to 10 TP levels.
Step type: Percent, ATR% or Hybrid.
Optional “Breathing grid”: TP distances are increased in proportion to |Z‑score| at entry (capped), so stronger impulses receive wider, more ambitious targets.
TP Profile (Equal / Aggressive / Balanced / Defensive) decides how much size is closed at each level.
Breakeven and Trailing:
Optional breakeven: after TP1 is hit, stop can be moved to entry price plus a small offset.
Optional ATR‑based trailing stop activates only after TP3 to avoid being shaken out too early by noise.
Time‑based Exit:
If enabled, any open trade that does not hit TP or SL within the chosen time limit (bars or minutes) is closed at market, to avoid very long, stagnant positions.
### 2. How the Script Works (Internals)
2.1 Impulse Engine (Custom Z‑Score Model)
At the core is a price×volume impulse series with Z‑score normalisation:
- Raw impulse:
`delta_impulse = (close - close ) * volume`
- Normalisation over N bars (default N = 20):
`zscore = (delta_impulse - avg(delta_impulse, N)) / stdev(delta_impulse, N)`
A bar becomes an impulse candidate only when:
- `abs(zscore) > Z_threshold` (default 1.5), and
- volume is above its recent average.
This is a custom implementation of a price×volume impulse model based on Z‑score; the exact combination of inputs, window, thresholds and how this signal feeds guards and exits is part of the proprietary logic.
2.2 Trend & Volatility Context — Why the Mashup Exists
The strategy combines several classic tools, but each covers a specific failure mode. The mashup is intentional:
| Component | What it checks | Why it is needed |
|----------|----------------|------------------|
| EMA200 | Long‑term bias (price above/below) | Prevents counter‑trend trading |
| EMA200 slope | Steepness of EMA over K bars | Filters flat/ranging phases even above/below EMA |
| VWAP | Distance of price from volume‑weighted fair value | Avoids entering when price is far from value (overextension) |
| ADX | Trend strength | Disables signals in low‑trend, choppy markets |
| ATR vs AvgATR50 | Current volatility vs recent average | Detects volatility squeezes and abnormally calm regimes |
| ATR% floor (Anti‑Flat Gate) | ATR as % of price | Hard “no‑trade” mode in ultra‑tight ranges |
An impulse alone is not sufficient in crypto; only impulses inside a suitable trend and volatility context are allowed to become trades.
2.3 Guard System (Exhaustion & Overextension)
Above trend filters, Smart Impulse PRO adds a guard layer designed from typical crypto problems (late entries, news spikes, “buying the top”):
- Max body / ATR : Rejects abnormally large real bodies (e.g., body > 3× ATR), often at the end of a move.
- Max range / ATR : Blocks extremely long high‑low bars.
- Upper/lower wick filters :
- Longs blocked when upper wick dominates (rejection from above).
- Shorts blocked when lower wick dominates (rejection from below).
- Z‑streak guard : After several consecutive impulse bars in the same direction, new entries in that direction are disabled to avoid chasing.
- Climax volume + cool‑off : When volume spikes above a multiple of its recent average, new trades are paused for N bars.
- Distance guards : Excessive distance (in ATR multiples) from EMA200 and VWAP can block trades.
These checks interact with the impulse model so that the final decision reflects a coherent risk framework rather than a loose collection of filters.
2.4 Dynamic TP Grid (Exit Logic)
- Up to 10 TP levels; step type: Percent, ATR% or Hybrid.
- With Breathing grid , TP spacing is increased by a factor of `k * abs(zscore)` (capped) at entry.
- Stronger impulses (higher |z|) → wider distances between TP levels; weaker impulses → tighter TP spacing.
- TP profiles (Equal / Aggressive / Balanced / Defensive) control how much position size is allocated to early vs late targets.
- Optional breakeven: move SL to entry (plus offset) after TP1.
- Optional trailing: ATR‑based trailing stop activates after TP3.
This links entry strength and exit geometry using the same impulse signal.
***
### 3. How to Use the Script (Practical Guide)
3.1 Quick Start
1. Add Smart Impulse PRO to a volatile crypto pair (e.g., ETHUSDT, BTCUSDT) on 15m–4h.
2. Keep the default preset and observe executed trades and blocked bubbles.
3. Use the dashboard to see which filters are active and which ones are blocking most trades (e.g., ADX, Flat, Exhaust).
4. If there are too few trades, gradually lower Z_threshold or Min ADX , or slightly relax guard limits — change one parameter at a time .
5. Set Max Risk per Trade (%) , stop distance, TP count/profile and optional trailing in line with your risk tolerance.
3.2 Example Profiles
- Aggressive intraday (15m)
- Z‑threshold 1.2
- Min ADX 20
- ATR% floor 0.2%
- Some exhaustion guards disabled (e.g., less strict wick limits).
- Conservative swing (1h–4h)
- Z‑threshold 1.5
- Min ADX 25–30
- ATR% floor 0.3–0.4%
- All guards enabled, higher‑timeframe filters ON.
3.3 Risk Management & Position Sizing
- Max Risk per Trade (%) — percentage of equity at risk if the full stop‑loss is hit.
- Position size is computed automatically from Max Risk %, stop distance and instrument price.
- Breakeven and trailing can be enabled to reduce open risk after partial profit is taken.
- Time‑based exit closes trades that stay open beyond a user‑defined duration without reaching TP or SL.
3.4 Alerts
Alerts use `strategy.order.alert_message` to send JSON containing side (long/short), entry, stop and TP levels. This allows users to connect the strategy with external bots or dashboards without exposing internal code.
***
### 4. Why This Script Is Invite‑Only (Originality Justification)
TradingView asks invite‑only scripts to explain why their logic is original and why source protection is justified. Smart Impulse PRO does that by:
- Implementing a custom price×volume impulse model based on Z‑score normalisation and integrating it with exits through the breathing TP grid.
- Using a coordinated guard framework that explicitly targets typical crypto issues (late chase entries, overextension vs VWAP/EMA200, volatility squeezes, volume spikes).
- Providing a structured indicator mashup where EMA200, VWAP, ADX, ATR and Anti‑Flat Gate each address different dimensions (trend, volatility, structure) and are designed to work together as a context gate for the impulse signal.
On ETHUSDT, BTCUSDT and a group of other volatile crypto pairs, Smart Impulse PRO showed approximately 90–94% win rate and profit factor above 3.0 in 2023–2025 backtests under default risk and filter settings. These numbers are illustrative only and do not promise or guarantee similar live results.
Risk Disclaimer
Trading cryptocurrencies involves substantial risk. Backtests are hypothetical and assume perfect execution without additional slippage, liquidity constraints or exchange issues. Always test the strategy on your own symbols and timeframes and keep risk per trade at a level you are comfortable with.
FAQ
Q: Does the strategy guarantee profit?
A: No. It is a rule‑based decision engine; all results depend on market conditions, parameters and execution, and backtests do not guarantee future performance.
Q: Can I use it on any crypto pair?
A: The logic is designed for volatile crypto pairs. It has been backtested on ETHUSDT, BTCUSDT and several other majors/alts, but each symbol should be tested and, if needed, re‑tuned by the user.
Q: Which timeframe is best?
A: The engine is intended for intraday and swing charts between 15m and 4h. Lower timeframes will generally produce more signals and more noise; higher ones will produce fewer, slower signals.
Q: Can I disable some filters or guards?
A: Yes. Trend filters, the Anti‑Flat Gate and most exhaustion guards can be turned on or off. It is recommended to change one setting at a time and monitor how it affects blocked signals and the equity curve.
Q: How are alerts meant to be used?
A: Alerts send a JSON payload with side, entry, stop and TP levels via strategy.order.alert_message, so users can connect the strategy to external bots or dashboards if they wish.
***
## Русская версия
Smart Impulse PRO (по приглашению) — Полное руководство для TradingView
Концепция и уникальность
Smart Impulse PRO — стратегия продолжения импульсов, разработанная под волатильные криптовалютные пары . В ней используется пользовательская модель импульса “цена×объём”, нормализованная через Z‑score , после чего такие импульсы проходят фильтрацию по тренду на разных таймфреймах и через каскад гардов, блокирующих слабые и рискованные сетапы (флэт, перетянутость, истощение).
Сводка тестов (крипто‑пары)
Стратегия тестировалась на нескольких волатильных крипто‑парах (перпетуальные контракты, включая ETHUSDT, BTCUSDT и ряд других мейджоров/альтов) на часовом таймфрейме за период 01.01.2023 – 26.12.2025. Типичные значения по этим тестам:
- Количество сделок на пару : ≈100–130
- Диапазон винрейта : ≈ 90–94%
- Диапазон фактора прибыли : ≈ 3.0–3.9
Это результаты тестов на истории по конкретным инструментам и настройкам и не гарантируют такой же доходности в будущем .
Почему она оригинальная
✅ Пользовательская модель импульса цена×объём (Z‑score) : измеряет “редкость” бара в его статистическом окружении, а не просто пересечение стандартных индикаторов
✅ 15+ гардов : системно защищают от догоняния, пампов, торговли в “пиле” и на перетянутых уровнях
✅ “Дышащая” TP‑сетка : цели автоматически подстраиваются под силу текущего импульса |Z|
✅ Прозрачность : пузырьки показывают причины каждого отказа от сделки
✅ Формат по приглашению : логика импульса и взаимодействие гардов публикуются как закрытый скрипт с Invite‑Only доступом, что соответствует правилам TradingView.
***
### 1. Что делает скрипт (для пользователя)
Smart Impulse PRO выступает как движок принятия решений для торговли волатильными крипто‑парами (ETHUSDT, BTCUSDT и др.) на таймфреймах от 15 минут до 4 часов:
- Открывает лонги/шорты только при одновременном совпадении трендовых и импульсных условий.
- Управляет выходом через многоуровневую сетку TP, безубыток, по желанию — трейлинг‑стоп и тайм‑стоп.
- Отображает как реальные сделки , так и отклонённые сигналы с короткой подписью причины блокировки.
Задача — структурировать трендовую торговлю криптой и сделать логику решений максимально понятной.
***
### 2. Как работает скрипт (внутренняя логика)
2.1 Импульсное ядро (кастомная модель на Z‑score)
В основе лежит ряд дельта×объём :
- Сырой импульс:
`delta_impulse = (close - close ) * volume`
- Нормализация по окну N баров (по умолчанию 20):
`zscore = (delta_impulse - среднее(delta_impulse, N)) / стд(delta_impulse, N)`
Бар считается кандидатом на импульс , только если:
- `abs(zscore) > Z_threshold` (по умолчанию 1.5);
- объём выше своей недавней средней.
Это собственная реализация импульсного сигнала цена×объём , нормализованного по Z‑score; выбор входных данных, окна, порогов и связка с гардами и выходами формируют проприетарную часть стратегии.
2.2 Зачем нужен “мэшап” индикаторов (тренд и волатильность)
Комбинация EMA200, VWAP, ADX, ATR и Anti‑Flat Gate собрана так, чтобы каждый компонент покрывал отдельный вид риска:
| Компонент | Что проверяет | Зачем нужен |
|----------|---------------|------------|
| EMA200 | Долгосрочный уклон (цена выше/ниже) | Защита от контртрендовых входов |
| Наклон EMA200 | Наклон за K баров | Отсекает участки со слабым трендом (флэт) |
| VWAP | Удалённость цены от “центра объёма” | Не даёт входить в явной перетянутости от справедливой цены |
| ADX | Силу тренда | Запрещает торговлю в пиле и боковике |
| ATR vs AvgATR50 | Текущую волатильность к средней | Находит режимы сжатия и аномально низкой волатильности |
| ATR% пол (Anti‑Flat Gate) | ATR в % от цены | Жёсткий запрет торговли в очень узком диапазоне |
Импульс может быть сильным, но без нормального тренда и адекватной волатильности сделка не допускается.
2.3 Система гардов (истощение, перетянутость)
- Макс тело/ATR : слишком большая свеча относительно ATR трактуется как возможное окончание движения.
- Макс диапазон/ATR : блокирует экстремальные по размеру бары.
- Фильтры по хвостам :
- Лонги блокируются при доминирующем верхнем хвосте (отторжение сверху).
- Шорты — при доминирующем нижнем хвосте.
- Z‑streak : после серии импульсных баров в одну сторону новые входы по этому направлению отключаются.
- Climax‑объём + пауза : при объёме выше кратности к средней входы на несколько баров ставятся на паузу.
- Дистанционные гарды : чрезмерное удаление цены от EMA200 и VWAP в ATR‑мультипликаторах может блокировать вход.
Эти условия работают совместно с импульсным ядром и трендовыми фильтрами, формируя связанную модель риска.
2.4 Динамическая TP‑сетка
- До 10 тейк‑профитов; шаг — в %, ATR% или гибридный.
- При включённой опции “Breathing grid” шаг между TP увеличивается пропорционально `|zscore|` (в пределах лимита).
- Сильные импульсы → более широкая сетка и шанс забрать длинное движение, слабые → более плотная сетка.
- Профили TP (равный / агрессивный / сбалансированный / защитный) задают распределение объёма между ближними и дальними целями.
- Можно включить перевод стопа в безубыток после TP1 и трейлинг‑стоп по ATR после TP3.
***
### 3. Как использовать стратегию (практика)
3.1 Быстрый старт
1. Откройте график волатильной крипто‑пары (ETHUSDT, BTCUSDT и т.п.) на ТФ 15m–4h и добавьте стратегию.
2. Оставьте настройки по умолчанию и наблюдайте маркеры сделок и пузырьки отклонённых сигналов.
3. Через дашборд смотрите, какие фильтры чаще всего блокируют сделки (ADX, Flat, Exhaust и др.).
4. Если сделок мало, по шагу снижайте порог Z‑score или ADX либо ослабляйте некоторые гарды — всегда меняйте только один параметр за раз.
5. Настройте Max Risk per Trade , размер стопа, количество и профиль TP, а также при необходимости безубыток и трейлинг‑стоп.
3.2 Типовые профили
- Агрессивный скальпинг (15m)
- Z‑порог 1.2
- ADX min 20
- ATR% пол 0.2%
- Несколько гардов истощения отключены.
- Консервативный свинг (1h–4h)
- Z‑порог 1.5
- ADX min 25–30
- ATR% пол 0.3–0.4%
- Все гарды включены, HTF‑фильтры активны.
3.3 Риск и размер позиции
- Max Risk per Trade (%) задаёт долю капитала, которую допускается потерять при полном срабатывании стоп‑лосса.
- Стратегия рассчитывает размер позиции из риска, стопа и цены инструмента.
- Можно включить перевод стопа в безубыток после TP1 и трейлинг‑стоп после TP3.
- Тайм‑стоп закрывает сделки, которые слишком долго остаются открытыми без достижения TP/SL.
3.4 Алерты
Алерты формируют JSON‑строку с направлением, ценой входа, стопом и всеми TP‑уровнями через `strategy.order.alert_message`. Это позволяет подключать внешние боты и панели без раскрытия кода.
***
### 4. Почему скрипт по приглашению (обоснование оригинальности)
Стратегия не сводится к “набору индикаторов на графике”. Формат Invite‑Only обоснован тем, что в коде реализованы:
- Пользовательская модель импульса цена×объём на базе Z‑score и использование этого же сигнала для адаптивной TP‑геометрии.
- Связанный набор гардов , построенный вокруг реальных проблем крипто‑торговли (поздние входы после пампов, перетянутость от VWAP/EMA200, режимы сжатия, всплески объёма).
- Логика мэшапа : EMA200, VWAP, ADX, ATR и Anti‑Flat Gate работают согласованно как фильтр контекста для импульса, а не как независимые визуальные индикаторы.
На ETHUSDT, BTCUSDT и ряде других крипто‑пар Smart Impulse PRO показывала ≈90–94% винрейт и фактор прибыли выше 3.0 в тестах 2023–2025 годов при стандартных настройках фильтров и риска. Эти значения служат иллюстрацией поведения стратегии в прошлом и не являются обещанием аналогичных результатов в реальной торговле.
Предупреждение о рисках
Торговля криптовалютами связана с повышенным риском. Результаты бэктестов гипотетичны и предполагают идеальное исполнение без дополнительного проскальзывания и проблем с ликвидностью. Перед использованием стратегии на реальном счёте протестируйте её на своих инструментах и выбирайте риск на сделку в соответствии с личной толерантностью к убыткам.
FAQ
В: Гарантирует ли стратегия прибыль?
О: Нет. Это набор правил для принятия решений; результат зависит от рынка, настроек и исполнения. Любые бэктесты не гарантируют такую же доходность в будущем.
В: Можно ли использовать её на любой крипто‑паре?
О: Логика рассчитана на волатильные криптовалютные пары. Стратегия тестировалась на ETHUSDT, BTCUSDT и нескольких других мейджорах/альтах, но для каждого инструмента параметры желательно проверить и при необходимости подстроить.
В: Какой таймфрейм предпочтителен?
О: Стратегия рассчитана на внутридневную и свинговую торговлю в диапазоне 15m–4h. На младших ТФ сигналов больше и шума выше; на старших — сигналов меньше, но они формируются медленнее.
В: Можно ли отключать отдельные фильтры и гарды?
О: Можно. Трендовые фильтры, Anti‑Flat Gate и большинство гардов истощения включаются и выключаются отдельно. Рекомендуется менять настройки по одной и смотреть, как это влияет на заблокированные сигналы и кривую капитала.
В: Для чего нужны алерты?
О: Алерты отправляют JSON‑сообщение с направлением, ценой входа, стопом и уровнями TP через strategy.order.alert_message, что позволяет при желании подключать внешних ботов и панели управления риском.
ThaiRiches Predictor [AI Premium]ThaiRiches Predictor is a comprehensive trend-following system designed to help traders identify high-probability entries while managing risk effectively. This script combines Zero-Lag technology (ZLEMA) with volatility filters and an intelligent AI Dashboard to analyze market conditions in real-time.
Key Features:
Zero-Lag Trend Engine: Uses a custom Zero-Lag EMA (ZLEMA) logic combined with volatility bands to detect trend changes earlier than traditional Moving Averages.
AI Analysis Dashboard: A real-time monitor panel that evaluates Trend, Momentum (RSI), and Volatility to provide actionable advice (e.g., "Strong Uptrend", "Overbought - Wait for Pullback", or "Low Volatility - Caution").
Auto TP & SL System: Automatically calculates and displays Stop Loss (SL), Take Profit 1 (TP1), and Take Profit 2 (TP2) based on ATR, adapting to the current market volatility.
Improved Safety: SL is calculated from the High/Low of the signal candle to prevent premature stop-outs.
Visual Alerts: Clear BUY/SELL labels with price targets and color-coded candlesticks for easy visual confirmation.
How to Use:
BUY Signal: Look for the Green Label and Green Trend Line. Confirm with the Dashboard (Status: BULLISH).
S ELL Signal: Look for the Red Label and Red Trend Line. Confirm with the Dashboard (Status: BEARISH).
Risk Management: Use the provided SL levels. It is recommended to take partial profit at TP1 and trail your stop to entry.
Caution: Avoid trading when the Dashboard shows "Low Volatility" or "Choppy" warnings.
Settings:
You can adjust the Trend Sensitivity and RSI Period.
TP/SL Multipliers are fully customizable to fit different assets (Gold, Forex, Crypto).
Next Candle PredictorAdvanced TradingView Indicator for Precise Buy and Sell Signals
Overview:
The Predicta Futures - Next Candle Predictor is a cutting-edge TradingView indicator designed to forecast the next candle's direction in futures and cryptocurrency markets. Leveraging a multi-indicator confluence strategy, this tool provides traders with actionable long and short prediction percentages, enhanced by dynamic ADX-based thresholds and visual projection candles. Ideal for scalping, day trading, or swing trading on platforms like MEXC or Binance futures, it combines Supertrend, MACD, RSI, Stochastic, ADX, and volume analysis to deliver high-probability buy and sell signals while minimizing false positives.
Key Features:
• Multi-Indicator Confluence Scoring:
Integrates Supertrend for trend direction, EMAs (8, 21, 50) for alignment, MACD for momentum crossovers, RSI for overbought/oversold conditions, Stochastic for divergence detection, ADX for trend strength, and volume ratios for confirmation. A customizable confluence score (0-6) ensures signals meet user-defined criteria, reducing whipsaws in volatile markets.
• Dynamic Prediction Thresholds:
ADX-driven adjustments lower the required prediction percentage (e.g., 60% in strong trends) for "PERFECT TIME" entries, adapting to market conditions like ranging or trending phases.
• Visual Analysis Table:
A sleek, color-coded dashboard displays progress bars for each indicator, prediction percentages, and status (e.g., "PERFECT TIME" or "WAIT"). Supports long and short analyses with intuitive ASCII bars for quick scans.
• Projection Candles:
Simulates potential next-candle outcomes with volatility-scaled (via Bollinger Bands width) green long and red short candles, aiding in visualizing price targets.
• Buy/Sell Signals and Alerts:
Generates labeled "BUY" and "SELL" arrows on EMA crossovers within confirmed trends, with separate alerts for basic signals and high-confluence "PERFECT TIME" opportunities.
• Customizable Inputs:
Adjust ATR periods, Supertrend factors, minimum confluence scores, and volume ratios to tailor the indicator for stocks, forex, or crypto perpetual futures.
How It Works:
This TradingView script calculates long and short scores using weighted contributions from key indicators, normalizing them into prediction percentages. A confluence check—factoring trend, EMA alignment, MACD, Stochastic, volume, and ADX—triggers "PERFECT TIME" only when conditions align robustly. For example:
• In a downtrend (Supertrend red), with bearish MACD and Stochastic, and sufficient volume, the indicator highlights short opportunities.
• Dynamic thresholds ensure aggressive entries in strong trends (ADX >25) and conservative ones in weak trends.
• Backtested for reliability, it excels in identifying reversals and continuations, making it a must-have for traders seeking an edge in futures trading strategies.
Usage Instructions:
1. Add the indicator to your TradingView chart. (Search: Next Candle Predictor)
2. Customize settings via the inputs panel (e.g., set minConfluence to 5 for stricter signals).
3. Monitor the analysis table for predictions and confluence scores.
4. Act on "BUY/SELL" labels or "PERFECT TIME" alerts, combining with your risk management.
5. Enable projection candles for visual forecasting of the next bar.
Compatible with all timeframes, from 1-minute scalping to daily swings. Note: This is not financial advice; always verify signals with additional analysis.
Join thousands of traders enhancing their strategies—add it to your charts today and elevate your trading performance!
Please rate and review if it boosts your trades!
Thank you!
BUY/SELL Multi-Factor Decision Engine (v8) WebhookBUY / SELL Multi-Factor Decision Engine (v8) — Webhook
Important Notice
This indicator is not financial advice, does not guarantee results, and does not eliminate losses.
It is not a bot, not an oracle, and does not replace experience, risk management, or human judgment.
It is a tool for reading, filtering, and organizing market information.
1. What is this indicator?
BUY / SELL Multi-Factor Decision Engine (v8) — Webhook is a technical analysis indicator that:
analyzes multiple indicators at the same time,
evaluates structure, momentum, pressure, and context,
generates BUY / SELL signals when sufficient intent exists,
displays two state semaphores (BAS and CTX),
concentrates complex information into a compact panel,
is highly configurable from the settings panel (almost the entire indicator is configurable, including parameters, thresholds, profiles, and tolerances, allowing significant modification of the indicator’s behavior),
can generate alerts and signals via Webhook.
It does not execute trades.
It does not promise consistent wins.
It does not eliminate risk.
2. What does it actually do?
This indicator does NOT work with simple rules such as:
“RSI above X = buy”
“Moving average crossover = entry”
It also does not wait for everything to be perfect at the same time.
It works as follows:
It evaluates market intent using several indicators simultaneously.
It builds a LONG probability and a SHORT probability.
Intent may exist even if some indicators are neutral.
When intent exceeds a minimum configurable threshold, a BUY or SELL is generated internally.
That signal is only shown if the market is moving enough (ATR filter).
Important note:
ATR does NOT participate in the BUY / SELL decision.
ATR only decides whether existing intent:
is shown on screen,
triggers an alert,
or is sent via Webhook.
In parallel, risk context (CTX) is evaluated and displayed as a warning.
CTX does not participate in the BUY / SELL decision; it only informs about risk.
All analyzed information (EMAs, MACD, RSI, CMF, ADX/DI, BBP, SMC, candles, patterns, sweeps, EQs) is displayed in a compact panel, including the direction they appear to indicate.
BUY / SELL is not an order; it is a visual synthesis of a complex reading.
3. Market Intent (main engine)
This is where BUY or SELL is born.
Intent is calculated using classic indicators, but they are not read as textbook values, rather as behavior.
The engine does not ask:
“Is it above or below X?”
It asks things like:
Is the market pushing or losing strength?
Is momentum accelerating or exhausting?
Is there real pressure or just a bounce?
Does structure support or contradict the move?
Because of this, the indicator may:
anticipate classic signals,
maintain intent while something is neutral,
fail,
arrive early or late.
This is normal in any probabilistic system.
Nothing in the market is certain.
BUY and SELL signals:
are not orders,
are not imperative instructions,
must not be interpreted as mandatory entries or exits,
and do not replace market reading or the trader’s own analysis.
BUY / SELL is:
a visual synthesis of a complex reading,
a probabilistic representation of intent,
a decision-support tool,
not a mandate or a guarantee.
4. Indicators that form intent (interpretation and weight)
The intent engine works on an accumulated score.
Each indicator adds evidence, not orders.
EMAs — weight: 2 points
Measure structure and dynamic direction.
Evaluates:
slope,
speed,
relationship between them.
LONG intent may exist before a classic crossover.
MACD — weight: 2 points
Measures momentum and acceleration.
Not used as a “magic crossover”.
Evaluates:
whether momentum accelerates or weakens,
whether it accompanies price.
RSI — weight: 1 point
Not used as overbought/oversold.
Interpreted as:
direction of pressure,
gain or loss of relative strength.
CMF (Chaikin Money Flow) — weight: 1 point
Evaluates money flow.
Helps distinguish:
supported moves,
empty moves.
ADX + DI — weight: 2 points
Evaluates:
whether there is real trend,
who dominates (buyers or sellers),
whether the move has a foundation.
BBP (Bull/Bear Power) — weight: 1 point
Evaluates buying vs selling pressure.
Helps detect:
control,
exhaustion.
SMC (BOS / CHOCH) — weight: 3 points
Evaluates market structure:
continuity (BOS),
change of character (CHOCH).
Not decorative.
It has the highest individual weight in the engine.
Important:
Bias does not have a 3-point weight.
SMC only adds 3 points when a BOS or CHOCH event appears in the panel.
While only Bias is present, it adds 0 points, because there is no event.
Therefore, the intent threshold depends on the other indicators until a BOS or CHOCH occurs.
Important
The engine does not require unanimity.
It requires sufficient intent (sum of points ≥ configured threshold).
5. BAS Semaphore (intent state)
The BAS semaphore summarizes the state of the intent engine:
🟢 Green → solid intent
🟡 Yellow → weak or transitioning intent
🔴 Red → deteriorated or risky intent
BAS:
is linked to BUY / SELL,
reflects intent quality,
does not automatically cancel a signal.
It helps evaluate trade health, not blind obedience.
6. Operability (ATR Gates)
ATR:
does NOT generate BUY or SELL,
does NOT decide direction.
ATR only answers:
Is the market moving enough for this intent to be operational?
Therefore intent may:
exist,
but not be shown,
not trigger alerts,
not be sent via Webhook.
This avoids:
trading dead ranges,
signal spam,
micro-moves without continuity.
ATR Profiles (timeframe)
Included ATR profiles:
Scalp (2m / 5m)
Intraday (15m / 30m)
Swing (1H – 4H)
Position (1D / 1W / 1M / 3M)
STANDARD (editable)
Profiles only adjust operability filtering.
They do not change direction or the intent engine.
Recommendation:
Use the profile matching your timeframe or edit STANDARD according to your criteria.
7. Engine Profiles
The indicator also includes Engine profiles.
The Engine STANDARD is editable by the user.
Predefined Engine profiles are NOT editable.
They are calibrated as coherent parameter sets.
This avoids common mistakes such as:
scalping EMAs with swing RSI,
mixing incompatible indicator ranges.
Modifying fixed profiles breaks internal coherence.
8. Context (CTX)
Context does NOT participate in BUY / SELL decisions.
It adds no points.
It subtracts no points.
It does not block signals.
It warns about risk.
Evaluates, among other things:
liquidity sweeps,
Equal Highs / Equal Lows (EQ),
candle types,
chart patterns (forming or confirmed).
CTX semaphore:
🟢 relatively clean environment
🟡 transition / caution
🔴 high-risk environment
A BUY with red CTX is not invalid, but riskier.
In CTX, fewer marks is generally better.
9. What is shown on screen
The indicator can show:
BUY / SELL
Compact panel with:
BAS
CTX
indicator readings
L / S labels on the chart
Labels:
L → Long
S → Short
10. Abbreviations (panel key)
Candles
Doji → Doji
LLDoji → Long-legged Doji
Eng → Engulfing
Maru → Dominant no-wick candle
Hammer → Hammer
InvHam → Inverted Hammer
Shoot → Shooting Star
Hang → Hanging Man
BD Slot (strength / indecision)
DD → strong indecision
D → indecision
BE↑ / BE↓ → bullish / bearish engulfing
B↑ / B↓ → dominant candle
Chart Patterns
H&S → Head & Shoulders
iH&S → Inverse H&S
DT / DB → Double Top / Bottom
RWdg / FWdg → Rising / Falling Wedge
RChnl / FChnl → Rising / Falling Channel
SymTri / AscTri / DescTri → Triangles
Comp → Compression
Stage:
F → Forming
C → Confirmed
11. Configuration (very important)
Parameters are not decorative.
Modifying:
EMAs
RSI
MACD
CMF
ADX / DI
BBP
ATR
intent threshold
profiles
context tolerances
changes the real behavior of the engine.
Important:
Adjusting a single parameter in isolation is generally not recommended.
If one value changes, the set should usually be adjusted to avoid incompatible ranges.
Example:
EMA 10/20 ≠ EMA 15/30 ≠ EMA 10/50
Same applies to all indicators.
12. BUY / SELL, Alerts and Webhook
The indicator does not execute trades.
It is used to:
trade manually,
receive alerts,
send signals to Telegram or other systems,
automate only if the user builds their own bot.
The indicator only sends structured information.
Execution is:
external,
user-decided,
user-responsibility.
13. How I use it (creator’s criteria)
I do not rely solely on the indicator, and no one should.
I still read:
each individual indicator,
candle patterns,
chart patterns,
sweeps,
EQs,
structure and overall context.
The indicator does not replace my reading — it confirms it.
I use it to:
consolidate scattered information,
decide faster,
reduce visual noise,
avoid impulsive entries.
It is support, not a substitute for judgment.
DISCLAIMER
Important Notice – read carefully
As stated throughout this document, BUY / SELL Multi-Factor Decision Engine (v8) — Webhook is a technical analysis tool and does not constitute financial advice, investment recommendations, or a guarantee of results.
This indicator:
does not predict the future,
does not guarantee profits,
does not eliminate losses,
does not reduce market risk,
and does not replace experience, human judgment, risk management, or the learning curve required to trade.
BUY / SELL Multi-Factor Decision Engine:
is not a bot,
is not an automated system,
is not an oracle,
does not execute trades,
and does not make decisions for the user.
BUY and SELL signals:
are not orders,
are not imperative instructions,
must not be interpreted as mandatory entries or exits,
and do not replace market reading or personal analysis.
BUY / SELL is:
a visual synthesis of a complex reading,
a probabilistic representation of intent,
a decision-support tool,
not a mandate or a guarantee.
Nature of the indicator and the market
This indicator reads information, not outcomes.
It interprets what the market — and specifically TradingView — shows at each moment: indicators, structure, patterns, candles, sweeps, EQs, momentum, and context.
That a LONG or SHORT intent forms, a BUY or SELL signal triggers, and the market later does not move in that direction does not mean the indicator failed.
This happens because:
the market may show intent and later invalidate it,
new orders may enter,
liquidity may change,
context may deteriorate.
This is exactly why even very experienced traders lose trades.
The indicator always interprets information the same way, but it has no more information than what is publicly available.
It does not see the future, hidden orders, or external events.
A failed signal is not an indicator error — it is the probabilistic and uncertain nature of the market.
Parameter configuration
Users may modify parameters, thresholds, profiles, and tolerances.
Doing so changes the actual behavior of the engine, not just appearance.
Modifying a single parameter in isolation is generally not recommended.
Changing one value often requires adjusting the whole set to avoid incoherent ranges.
The intent-based logic does not change, but results can be altered if ranges are modified inconsistently.
Alerts and Webhook usage
This indicator can generate alerts and send signals via Webhook to external systems (bots, servers, messaging platforms, execution systems).
The Webhook only transmits information generated when internal conditions are met.
The indicator does not execute trades, control external systems, or validate user actions.
Any automation, bot, script, server, or system receiving these signals:
is external to the indicator,
is built, configured, and operated by the user,
and operates under the user’s full responsibility.
The creator is not responsible for:
automated executions,
programming errors in external bots or scripts,
connectivity failures,
duplicate orders,
delays,
losses derived from automation,
or decisions made from Webhook signals.
Using Webhook does not turn this indicator into a bot or automated system.
Webhook is only a communication channel.
Final Statement
Neither this indicator, nor any other indicator, nor any bot:
predicts the future,
guarantees profits,
or prevents losses.
Anyone claiming otherwise is lying.
This indicator is designed as a support tool to:
organize information,
reduce noise,
improve market reading,
and help make more conscious decisions,
not to eliminate risk or replace human judgment.
The creator of BUY / SELL Multi-Factor Decision Engine (v8) — Webhook assumes no responsibility for any loss, economic damage, financial harm, or negative consequence resulting from the use of this indicator.
This includes, but is not limited to, use:
manual,
semi-automated,
automated,
via alerts,
via Webhook,
via bots, scripts, servers, APIs, or any external system.
Any decision made using this indicator:
is solely the user’s responsibility,
made under their own judgment,
and at their own risk.
Using this indicator implies explicit acceptance that:
trading involves risk,
losses are possible,
and the creator assumes no direct or indirect liability for adverse results, misinterpretation, incorrect execution, faulty automation, or trading decisions.
tncylyv - Improved Delta Volume BubbleThis script is a specialized modification and structural upgrade of the excellent "Delta Volume Bubble " by tncylyv.
While the original tool provided a fantastic foundation for statistical volume analysis, this "Zero Float" Edition was built to solve specific visual challenges faced by active traders—specifically the issue of indicators "floating" or disconnecting from price when zooming in on lower timeframes.
The Straight Improvements
This version turns a "Signal Indicator" into a complete "Trading System" with five specific upgrades:
1. Visual Stability (The "Zero Float" Fix)
Original: Used complex coordinates that could desynchronize, causing bubbles to drift or float away from candles on fast charts (1m/5m).
My Upgrade: Implemented "Magnetic Anchoring." Labels and bubbles are now physically locked to the candle wicks. They never drift, overlap, or float, no matter how much you zoom or resize the chart.
2. Cognitive Load (The HUD)
Original: Displayed raw numbers inside colored circles, requiring you to memorize color codes.
My Upgrade: Replaced numbers with Semantic Text Labels (e.g., "ABSORB", "SQUEEZE", "MOMENTUM"). You can read the market intent instantly without decoding it.
3. Regime Adaptation (AI Engine)
Original: Used a fixed threshold (e.g., Z-Score > 2.0).
My Upgrade: Added an Adaptive Learning Window. The script scans recent volatility to automatically raise the threshold during choppy markets (filtering noise) and lower it during quiet sessions (catching subtle entries).
4. Market Memory (Smart Structure)
Original: Signals disappeared into history.
My Upgrade: Draws Support/Resistance Rails extending from major volume events. This helps you visualize exactly where institutions are defending their positions.
5. Robust Data Handling
My Upgrade: Added a Hybrid Fallback Engine. If granular 1-minute data isn't available (e.g., on historical charts), the script seamlessly switches to an estimation model so the indicator never "breaks" or disappears.
Core Logic
Z-Score Normalization: We don't look at raw volume; we look at statistical anomalies (Standard Deviations).
Absorption: Detects "Effort vs. Result"—high volume with tiny price movement (Trapped Traders).
Squeeze: Highlights areas where a breakout is imminent due to volatility compression.
Credits
Original Concept & Code: tncylyv (Delta Volume Bubble ). This script would not exist without his brilliant groundwork.
Modifications: Visual Anchoring, HUD Text System, AI Thresholding, and Structure Rails added in this edition.
This script is open-source to keep the spirit of the original author alive. Use it to understand the "Why" behind the move.
Kalman Hull Kijun [BackQuant]Kalman Hull Kijun
A trend baseline that merges three ideas into one clean overlay, Kalman filtering for noise control, Hull-style responsiveness, and a Kijun-like Donchian midline for structure and bias.
Context and lineage
This indicator sits in the same family as two related scripts:
Kalman Price Filter
This is the foundational building block. It introduces the Kalman filter concept, a state-estimation algorithm designed to infer an underlying “true” signal from noisy measurements, originally used in aerospace guidance and later adopted across robotics, economics, and markets.
Kalman Hull Supertrend
This is the original script made, which people loved. So it inspired me to create this one.
Kalman Hull Kijun uses the same core philosophy as the Supertrend variant, but instead of building a Supertrend band system, it produces a single structural baseline that behaves like a Kijun-style reference line.
What this indicator is trying to solve
Most trend baselines sit on a bad trade-off curve:
If you smooth hard, the line reacts late and misses turns.
If you react fast, the line whipsaws and tracks noise.
Kalman Hull Kijun is designed to land closer to the middle:
Cleaner than typical fast moving averages in chop.
More responsive than slow averages in directional phases.
More “structure aware” than pure averages because the baseline is range-derived (Kijun-like) after filtering.
Core idea in plain language
The plotted line is a Kijun-like baseline, but it is not built from raw candles directly.
High level flow:
Start with a chosen price stream (source input).
Reduce measurement noise using Kalman-style state estimation.
Add Hull-style responsiveness so the filtered stream stays usable for trend work.
Build a Kijun-like baseline by taking a Donchian midpoint of that filtered stream over the base period.
So the output is a single baseline that is intended to be:
Less jittery than a simple fast MA.
Less laggy than a slow MA.
More “range anchored” than standard smoothing lines.
How to read it
1) Trend and bias (the primary use)
Price above the baseline, bullish bias.
Price below the baseline, bearish bias.
Clean flips across the baseline are regime changes, especially when followed by a hold or retest.
2) Retests and dynamic structure
Treat the baseline like dynamic S/R rather than a signal generator:
In uptrends, pullbacks that respect the baseline can act as continuation context.
In downtrends, reclaim failures around the baseline can act as continuation context.
Repeated back-and-forth around the line usually means compression or chop, not clean trend.
3) Extension vs compression (using the fill)
The fill is meant to communicate “distance” and “pressure” visually:
Large separation between price and baseline suggests expansion.
Price compressing into the baseline suggests rebalancing and decision points.
Inputs and what they change
Kijun Base Period
Controls the structural memory of the baseline.
Higher values track broader swings and reduce flips.
Lower values track tighter swings and react faster.
Kalman Price Source
Defines what data the filter is estimating.
Close is usually the cleanest default.
HL2 often “feels” smoother as an average price.
High/Low sources can become more reactive and less stable depending on the market.
Measurement Noise
Think of this as the main smoothness knob:
Higher values generally produce a calmer filtered stream.
Lower values generally produce a faster, more reactive stream.
Process Noise
Think of this as adaptability:
Higher values adapt faster to changing conditions but can get twitchy.
Lower values adapt slower but stay stable.
Plotting and UI (what you see on chart)
1) Adaptive line coloring
Baseline turns bullish color when price is above it.
Baseline turns bearish color when price is below it.
This makes the state readable without extra panels.
2) Gradient “energy” fill
Bull fill appears between price and baseline when above.
Bear fill appears between price and baseline when below.
The goal is clarity on separation and control, not decoration.
3) Rim effect
A subtle band around price that only appears on the active side.
Helps highlight directional control without hiding candles.
4) Candle painting (optional)
Candles can be colored to match the current bias.
Useful for scanning many charts quickly.
Disable if you prefer raw candles.
Alerts
Long state alert when price is above the baseline.
Short state alert when price is below the baseline.
Best used as a bias or regime notification, not a standalone entry trigger.
Where it fits in a workflow
This is a context layer, it pairs well with:
Market structure tools, BOS/MSB, OBs, FVGs.
Momentum triggers that need a regime filter.
Mean reversion tools that need “do not fade trends” context.
Limitations
No baseline eliminates chop whipsaws, tuning only manages the trade-off.
Settings should not be copy pasted across assets without checking behavior.
This does not forecast, it estimates and smooths state, then expresses it as a structural baseline.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
If you use it in any trading workflow, do proper backtesting, forward testing, and risk management before any live execution.
QuantLabs MASM Correlation TableThe Market is a graph. See the flows:
The QuantLabs MASM is not a standard correlation table. It is an Alpha-Grade Scanner architected to reveal the hidden "hydraulic" relationships between global macro assets in real-time.
Rebuilt from the ground up for Version 3, this engine pushes the absolute limits of the Pine Script™ runtime. It utilizes a proprietary Logarithmic Math Engine, Symmetric Compute Optimization, and a futuristic "Ghost Mode" interface to deliver a 15x15 real-time correlation matrix with zero lag.
Under the Hood: The Quant Architecture
We stripped away standard libraries to build a lean, high-performance engine designed for institutional-grade accuracy.
1. Alpha Math Engine (Logarithmic Returns) Most tools calculate correlation based on Price, which generates spurious signals (e.g., "Everything is correlated in a bull run").
The Solution: Our engine computes Logarithmic Returns (log(close/close )) by default. This measures the correlation of change (Velocity & Vector), not price levels.
The Result: A mathematically rigorous view of statistical relationships that filters out the noise of general market drift.
Dual-Core: Toggle seamlessly between "Alpha Mode" (Log Returns) for verified stats and "Visual Mode" (Price) for trend alignment.
Calculation Modes: Pearson (Standard), Euclidean (Distance), Cosine (Vector), Manhattan (Grid).
2. Symmetric Compute Optimization Calculating a 15x15 matrix requires evaluating 225 unique relationships per bar, which often crashes memory limits.
The Fix: The V3 Engine utilizes Symmetric Logic, recognizing that Correlation(A, B) == Correlation(B, A).
The Gain: By computing only the lower triangle of the matrix and mirroring pointers to the upper triangle, we reduced computational load by 50%, ensuring a lightning-fast data feed even on lower timeframes.
3. Context-Aware "Ghost Mode" The UI is designed for professional traders who need focus, not clutter.
Smart Detection: The matrix automatically detects your current chart's Ticker ID. If you are trading QQQ, the matrix will visually highlight the Nas100 row and column, making them opaque and bright while dimming the rest.
Dynamic Transparency: Irrelevant data ("Noise" < 0.3 correlation) fades into the background. Only significant "Alpha Signals" (> 0.7) glow with full Neon Saturation.
Key Features
Dominant Flow Scanner: The matrix scans all 105 unique pairs every tick and prints the #1 Strongest Correlation at the bottom of the pane (e.g., DOMINANT FLOW: Bitcoin ↔ Nas100 ).
Streak Counter: A "Stubbornness" metric that tracks how many consecutive days a strong correlation has persisted. Instantly identify if a move is a "flash event" or a "structural trend."
Neon Palette: Proprietary color mapping using Electric Blue (+1.0) for lockstep correlation and Deep Red (-1.0) for inverse hedging.
Usage Guide
Placement: Best viewed in a bottom pane (Footer).
Assets: Pre-loaded with the Essential 15 Macro Drivers (Indices, BTC, Gold, Oil, Rates, FX, Key Sectors). Fully editable via settings (Ticker|Name).
Reading the Grid:
🔵 Bright Blue: Assets moving in lockstep (Risk-On).
🔴 Bright Red: Assets moving perfectly opposite (Hedge/Risk-Off).
⚫ Faded/Black: No statistical relationship (Decoupled).
Key Improvements Made:
Formatting: Added clear bullet points and bolding to make it scannable.
Clarity: Clarified the "Logarithmic Returns" section to explain why it matters (Velocity vs. Price Levels).
Tone: Maintained the "high-tech/quant" vibe but removed slightly clunky phrases like "spurious signals" (unless you prefer that academic tone, in which case I left it in as it fits the persona).
Structure: Grouped the "Modes" under the Math Engine for better logic.
Created and designed by QuantLabs
Trend Stress Quant [MarkitTick]💡This indicator combines a liquidity-based stress model with a dynamic linear regression channel to identify potential market exhaustion points and assess trend quality. By merging volume impact analysis with statistical deviation, this tool aims to highlight moments where price action may be overextended relative to the underlying liquidity conditions.
● Originality and Utility
Standard volatility indicators often rely solely on price range (like Bollinger Bands). This script introduces a Stress Engine that normalizes the relationship between Price Range (True Range) and Volume. This helps distinguish between healthy price movements and liquidity-stress events (illiquidity). Furthermore, instead of using a fixed-length channel, this tool offers a Dynamic Mode that anchors the regression channel to recent pivot points, ensuring the statistical analysis aligns with the current market structure rather than an arbitrary timeframe.
● Methodology
The script operates on two distinct mathematical models:
• Illiquidity Stress Engine
The core formula calculates a raw illiquidity metric based on the log-normal distribution of the ratio between True Range and Volume. A Z-Score (standard score) is then derived from this data over a specific lookback period. High Z-Scores indicate that price is moving disproportionately fast relative to the available volume, often a signature of panic selling or euphoric buying (exhaustion).
• Linear Regression Channel
The script calculates an Ordinary Least Squares (OLS) regression line (the line of best fit) to determine the mean price trend.
Standard Deviation Bands are plotted parallel to this mean.
Pearson Correlation Coefficient (R) is calculated to quantify the strength of the linear trend. Values closer to 1 or -1 indicate a strong trend, while values near 0 indicate a chaotic or ranging market.
📑 How to Use
Traders can utilize the visual outputs for mean reversion or trend continuation context:
• Exhaustion Signals (SE / BE Labels)
SE (Seller Exhaustion): Appears when the market is in a downtrend, but the Stress Engine detects a statistical anomaly (High Z-Score) on a down candle. This suggests panic selling may be peaking.
BE (Buyer Exhaustion): Appears when the market is in an uptrend, but the Stress Engine detects high stress on an up candle, suggesting a potential blow-off top.
• Regression Channel
The dashed middle line represents the fair value (mean) of the current trend.
The outer bands represent statistical extremes. Price interacting with the outer bands (default 2 Standard Deviations) while coincident with an Exhaustion Signal provides a high-confluence area of interest.
• Metrics Dashboard
A dashboard displays the current Trend Regime, Exhaustion Status, and Channel Width (volatility percentage).
● Settings
• Exhaustion Model
Trend Filter Length: Sets the baseline EMA to determine if the market is bullish or bearish.
Stress Threshold (Sigma): The Z-Score required to trigger an exhaustion signal (default is 2.0).
• Channel Configuration
Dynamic Pivot Mode: If enabled, automatically calculates the channel length based on recent pivots. If disabled, uses the Fixed Length.
Standard Deviations: Controls the width of the inner and outer channel bands.
📖This guide explains how to interpret and utilize signals for trading:
The script is designed primarily for Mean Reversion and Exhaustion trading strategies.
● The Core Strategy: Volatility Exhaustion
The script uses a "Stress Engine" to identify when price movement is statistically overextended relative to the available liquidity (Volume).
• Setup A: The "Seller Exhaustion" (Bullish Bounce)
Look for this setup during a downtrend to catch a temporary bottom or a reversal.
Trend Condition: The dashboard shows Bearish (Price is below the trend filter).
Trigger: The label SE (Seller Exhaustion) appears below a candle.
Why? This indicates that selling pressure was intense but likely panic-driven (High Z-Score/Stress) and may be drying up.
Confluence: Ideally, this signal appears when the price is touching or piercing the Lower Channel Band (dotted or solid lines).
Action: Traders often use this as a signal to close Short positions or enter a speculative Long (counter-trend) targeting the middle line.
• Setup B: The "Buyer Exhaustion" (Bearish Pullback)
Look for this setup during an uptrend to catch a local top.
Trend Condition: The dashboard shows Bullish .
Trigger: The label BE (Buyer Exhaustion) appears above a candle.
Why? This indicates euphoric buying on low liquidity or extreme volatility that is statistically unsustainable.
Confluence: Look for price rejection at the Upper Channel Band.
Action: Traders often use this to close Long positions or enter a Short targeting the mean.
● The Filter: Trend & Correlation
The script includes a Linear Regression Channel that quantifies the quality of the trend.
• Channel Slope
If the channel is angling steeply up or down, the trend is strong.
• Pearson R (Correlation)
The script calculates the Pearson R coefficient.
Weak Correlation: If the channel turns Gray/Neutral (or the fill becomes weak), it means the correlation is below the threshold (default 0.5).
Trading Rule: Avoid trading exhaustion signals when the channel is Gray/Neutral, as the market is likely chopping sideways with no clear direction.
● Risk Management & Targets
• Stop Loss
Since this is a volatility tool, a common technique is to place stops just outside the Outer Deviation Band (the widest line). If price expands beyond the outer band with no exhaustion signal, the trend may be entering a "runaway" phase.
• Take Profit
Target 1: The Middle Regression Line (The dashed center line). Prices tend to revert to this mean after an exhaustion event.
Target 2: The opposite channel band (e.g., if you bought at the bottom, hold until the top).
● Summary of Dashboard Metrics
The table on your chart provides a quick snapshot:
Trend Regime: Tells you if you should fundamentally look for Shorts (Bearish) or Longs (Bullish).
Seller/Buyer Status: Alerts you if the current bar is EXHAUSTED or Normal .
Channel Width %: Indicates volatility. If the width is very low (percentage is small), a breakout might be imminent (squeezing). If high, be careful of chop.
⚙️ Indicator settings
• Signal Parameters
Exhaustion & Stress Model: Controls signal sensitivity.
Trend Filter: Decides if the market is Bullish or Bearish.
Stress Threshold (Sigma): Higher values (e.g., 2.5) make the script stricter, showing fewer but potentially stronger signals.
• Channel Configuration
Dynamic Pivot Mode: If ON, the channel length auto-adjusts to recent market pivots. If OFF, it uses the Fixed Length you set.
Channel Bands: Adjusts the channel width.
Outer Deviation: The boundary for "extreme" moves. Price hitting this often signals a reversal.
• Quality Filter
Filter Weak Correlations: If enabled, the channel turns gray during choppy/sideways markets to warn you not to trust trend signals.
• Visuals
Display Options: Toggles the "Stats" dashboard and adjusts volatility coloring.
● Disclaimer
All provided scripts and indicators are strictly for educational exploration and must not be interpreted as financial advice or a recommendation to execute trades. I expressly disclaim all liability for any financial losses or damages that may result, directly or indirectly, from the reliance on or application of these tools. Market participation carries inherent risk where past performance never guarantees future returns, leaving all investment decisions and due diligence solely at your own discretion.
Adaptive ML Trailing Stop [BOSWaves]Adaptive ML Trailing Stop – Regime-Aware Risk Control with KAMA Adaptation and Pattern-Based Intelligence
Overview
Adaptive ML Trailing Stop is a regime-sensitive trailing stop and risk control system that adjusts stop placement dynamically as market behavior shifts, using efficiency-based smoothing and pattern-informed biasing.
Instead of operating with fixed ATR offsets or rigid trailing rules, stop distance, responsiveness, and directional treatment are continuously recalculated using market efficiency, volatility conditions, and historical pattern resemblance.
This creates a live trailing structure that responds immediately to regime change - contracting during orderly directional movement, relaxing during rotational conditions, and applying probabilistic refinement when pattern confidence is present.
Price is therefore assessed relative to adaptive, condition-aware trailing boundaries rather than static stop levels.
Conceptual Framework
Adaptive ML Trailing Stop is founded on the idea that effective risk control depends on regime context rather than price location alone.
Conventional trailing mechanisms apply constant volatility multipliers, which often results in trend suppression or delayed exits. This framework replaces static logic with adaptive behavior shaped by efficiency state and observed historical outcomes.
Three core principles guide the design:
Stop distance should adjust in proportion to market efficiency.
Smoothing behavior must respond to regime changes.
Trailing logic benefits from probabilistic context instead of fixed rules.
This shifts trailing stops from rigid exit tools into adaptive, regime-responsive risk boundaries.
Theoretical Foundation
The indicator combines adaptive averaging techniques, volatility-based distance modeling, and similarity-weighted pattern analysis.
Kaufman’s Adaptive Moving Average (KAMA) is used to quantify directional efficiency, allowing smoothing intensity and stop behavior to scale with trend quality. Average True Range (ATR) defines the volatility reference, while a K-Nearest Neighbors (KNN) process evaluates historical price patterns to introduce directional weighting when appropriate.
Three internal systems operate in tandem:
KAMA Efficiency Engine : Evaluates directional efficiency to distinguish structured trends from range conditions and modulate smoothing and stop behavior.
Adaptive ATR Stop Engine : Expands or contracts ATR-derived stop distance based on efficiency, tightening during strong trends and widening in low-efficiency environments.
KNN Pattern Influence Layer : Applies distance-weighted historical pattern outcomes to subtly influence stop placement on both sides.
This design allows stop behavior to evolve with market context rather than reacting mechanically to price changes.
How It Works
Adaptive ML Trailing Stop evaluates price through a sequence of adaptive processes:
Efficiency-Based Regime Identification : KAMA efficiency determines whether conditions favor trend continuation or rotational movement, influencing stop sensitivity.
Volatility-Responsive Scaling : ATR-based stop distance adjusts automatically as efficiency rises or falls.
Pattern-Weighted Adjustment : KNN compares recent price sequences to historical analogs, applying confidence-based bias to stop positioning.
Adaptive Stop Smoothing : Long and short stop levels are smoothed using KAMA logic to maintain structural stability while remaining responsive.
Directional Trailing Enforcement : Stops advance only in the direction of the prevailing regime, preserving invalidation structure.
Gradient Distance Visualization : Gradient fills reflect the relative distance between price and the active stop.
Controlled Interaction Markers : Diamond markers highlight meaningful stop interactions, filtered through cooldown logic to reduce clustering.
Together, these elements form a continuously adapting trailing stop system rather than a fixed exit mechanism.
Interpretation
Adaptive ML Trailing Stop should be interpreted as a dynamic risk envelope:
Long Stop (Green) : Acts as the downside invalidation level during bullish regimes, tightening as efficiency improves.
Short Stop (Red) : Serves as the upside invalidation level during bearish regimes, adjusting width based on efficiency and volatility.
Trend State Changes : Regime flips occur only after confirmed stop breaches, filtering temporary price spikes.
Gradient Depth : Deeper gradient penetration indicates increased extension from the stop rather than imminent reversal.
Pattern Influence : KNN weighting affects stop behavior only when historical agreement is strong and remains neutral otherwise.
Distance, efficiency, and context outweigh isolated price interactions.
Signal Logic & Visual Cues
Adaptive ML Trailing Stop presents two primary visual signals:
Trend Transition Circles : Display when price crosses the opposing trailing stop, confirming a regime change rather than anticipating one.
Stop Interaction Diamonds : Indicate controlled contact with the active stop, subject to cooldown filtering to avoid excessive signals.
Alert generation is limited to confirmed trend transitions to maintain clarity.
Strategy Integration
Adaptive ML Trailing Stop fits within trend-following and risk-managed trading approaches:
Dynamic Risk Framing : Use adaptive stops as evolving invalidation levels instead of fixed exits.
Directional Alignment : Base execution on confirmed regime state rather than speculative reversals.
Efficiency-Based Tolerance : Allow greater price fluctuation during inefficient movement while enforcing tighter control during clean trends.
Pattern-Guided Refinement : Let KNN influence adjust sensitivity without overriding core structure.
Multi-Timeframe Context : Apply higher-timeframe efficiency states to inform lower-timeframe stop responsiveness.
Technical Implementation Details
Core Engine : KAMA-based efficiency measurement with adaptive smoothing
Volatility Model : ATR-derived stop distance scaled by regime
Machine Learning Layer : Distance-weighted KNN with confidence modulation
Visualization : Directional trailing stops with layered gradient fills
Signal Logic : Regime-based transitions and controlled interaction markers
Performance Profile : Optimized for real-time chart execution
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Tight adaptive trailing for short-term momentum control
15 - 60 min : Structured intraday trend supervision
4H - Daily : Higher-timeframe regime monitoring
Suggested Baseline Configuration:
KAMA Length : 20
Fast/Slow Periods : 15 / 50
ATR Period : 21
Base ATR Multiplier : 2.5
Adaptive Strength : 1.0
KNN Neighbors : 7
KNN Influence : 0.2
These suggested parameters should be used as a baseline; their effectiveness depends on the asset volatility, liquidity, and preferred entry frequency, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Excessive chop or overreaction : Increase KAMA Length, Slow Period, and ATR Period to reinforce regime filtering.
Stops feel overly permissive : Reduce the Base ATR Multiplier to tighten invalidation boundaries.
Frequent false regime shifts : Increase KNN Neighbors to demand stronger historical agreement.
Delayed adaptation : Decrease KAMA Length and Fast Period to improve responsiveness during regime change.
Adjustments should be incremental and evaluated over multiple market cycles rather than isolated sessions.
Performance Characteristics
High Effectiveness:
Markets exhibiting sustained directional efficiency
Instruments with recurring structural behavior
Trend-oriented, risk-managed strategies
Reduced Effectiveness:
Highly erratic or event-driven price action
Illiquid markets with unreliable volatility readings
Integration Guidelines
Confluence : Combine with BOSWaves structure or trend indicators
Discipline : Follow adaptive stop behavior rather than forcing exits
Risk Framing : Treat stops as adaptive boundaries, not forecasts
Regime Awareness : Always interpret stop behavior within efficiency context
Disclaimer
Adaptive ML Trailing Stop is a professional-grade adaptive risk and regime management tool. It does not forecast price movement and does not guarantee profitability. Results depend on market conditions, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates structure, volatility, and contextual risk management.
PowerWave Oscillator Suite [BOSWaves]PowerWave Oscillator Suite - Multi-Dimensional Momentum & Trend Oscillator with Adaptive Divergence Insight
Overview
PowerWave Oscillator Suite is a cutting-edge analytical toolkit designed to provide traders with a sophisticated understanding of momentum, trend strength, and divergence behavior in financial markets. Unlike conventional oscillators that rely solely on price-based calculations, PowerWave combines adaptive, multi-dimensional computation engines with advanced visualization tools and divergence detection systems. The suite offers a unique blend of trend-following, mean-reversion, and contrarian trading insights, allowing users to analyze markets from multiple angles simultaneously. Each module within the suite has been designed to offer precision, clarity, and adaptability, ensuring that traders of all levels - from novice to professional - can extract actionable intelligence without unnecessary chart clutter or signal ambiguity.
PowerWave Oscillator Suite focuses on three primary trading paradigms: momentum measurement, volume-based filtering, and smoothed trend oscillation. These paradigms are accessible via three core modules - Aroon Oscillator, Adaptive Volume Filter, and HyperSmooth Oscillator - each equipped with advanced smoothing, dynamic source selection, reduced-lag computation, and divergence detection, offering a comprehensive approach to market analysis. By leveraging the full capabilities of this toolkit, traders can identify market turning points, confirm trend strength, detect hidden divergences, and refine entries and exits, all within a single integrated framework.
Configuration Panel and Customization Options
At the heart of PowerWave is a robust configuration panel that allows users to tailor the suite to their individual trading preferences and market conditions. The first level of customization is the Module Selection, allowing users to toggle between the Aroon Oscillator, Adaptive Volume Filter, or HyperSmooth Oscillator. Each module is designed with a distinct analytical purpose:
Aroon Oscillator : Measures trend strength and provides early signals for trend reversals or continuation.
Adaptive Volume Filter : Uses volume-based filtering to highlight momentum shifts, smoothing out noise from price fluctuations.
HyperSmooth Oscillator : Delivers finely smoothed oscillations, designed to capture micro-trend shifts and acceleration patterns.
Users can enhance the responsiveness and filtering behavior of each module via the Enhancement Level setting, a numeric input that applies a series of multi-stage exponential smoothing layers, ensuring signals are robust against market noise without introducing excessive lag. Additionally, the Source Type option allows traders to determine the price input methodology - ranging from adaptive combinations of open, high, low, and close values to more traditional sources - granting flexibility to align the indicator with preferred strategies or asset characteristics.
Engineered Visual Intelligence and Module-Specific Color Systems
PowerWave employs purpose-built, module-specific color systems that are tightly integrated with each oscillator’s underlying computation model. Rather than treating color as a cosmetic layer, the suite uses color as an informational channel, encoding state, momentum bias, and structural context directly into the visual output.
Each module operates with a dedicated color logic aligned to its analytical role:
The Aroon Oscillator uses polarity-driven gradients to express time-based trend dominance and directional strength.
The Adaptive Volume Filter applies contrasting color states to distinguish expanding versus contracting volume pressure.
The HyperSmooth Oscillator utilizes a dynamic HSV-based color spectrum that continuously maps momentum acceleration and deceleration into the oscillator line itself.
These color systems are reinforced through coordinated visual elements, including bar coloring, background state highlighting, histogram fills, and cross-condition shading. Users can further tune visual intensity and emphasis through enhanced mode and opacity controls, allowing the same engineered color logic to be amplified or subdued depending on chart density and personal workflow.
By designing color behavior as an extension of the calculation engine - rather than an arbitrary styling choice - PowerWave ensures that visual cues remain consistent, data-driven, and immediately interpretable across assets, timeframes, and market regimes.
Dynamic Source and Zero-Lag Computation
A defining characteristic of PowerWave Oscillator Suite is its Dynamic Source Calculation engine, which adjusts the input price series according to the trader’s chosen source type and enhancement level. This system ensures that signals are computed from a refined, noise-filtered base, enhancing reliability across asset classes and timeframes. Each stage of the multi-level smoothing hierarchy incrementally reduces erratic price fluctuations while preserving meaningful structural movement, allowing traders to differentiate between minor price noise and genuine momentum shifts.
Complementing this is the Adaptive Reduced-Lag Filter, a highly specialized algorithm that minimizes lag inherent in traditional moving averages or oscillators. This filter uses a gain-optimized EMA structure that continuously self-adjusts based on recent price dynamics, providing traders with fast yet reliable signals. By incorporating zero-lag calculations, PowerWave ensures that trend reversals and momentum inflections are detected in near real-time, allowing for earlier entries, faster confirmations, and more accurate exits. The reduced-lag filter also dynamically adjusts its internal gain coefficients, minimizing error while accounting for varying market volatility.
Aroon Oscillator Module
The Aroon Oscillator module within PowerWave is designed to quantify trend strength and identify emerging directional shifts. Utilizing a dual-period calculation, the module compares the relative timing of recent highs and lows, producing a normalized oscillation that reflects the market’s current momentum. Advanced zero-lag filtering ensures that even minor reversals or trend accelerations are captured with minimal delay, while additional smoothing can be applied via the configuration panel to match the trader’s preferred sensitivity.
The module includes trend and mean-reversion signal detection:
Trend Signals : Generated when the oscillator crosses the zero line, indicating potential trend continuation or initiation.
Reversion Signals : Triggered by crossovers between the oscillator and its internal signal line, highlighting potential pullbacks or temporary counter-trend behavior.
Visual overlays, including bar coloring and gradient plots, highlight bullish and bearish momentum zones, making it immediately apparent whether the market is in a trending or consolidating state. By combining trend and reversion insights with divergence detection, traders gain a multi-layered understanding of market structure, allowing for well-timed entries and exits.
Use Case:
Use the Aroon Oscillator when your primary objective is identifying real trend shifts early and staying aligned with structure. This model excels in markets transitioning from consolidation into expansion, where timing matters more than micro-entries. Zero-line crosses define directional regime changes, while signal-line crossovers expose mean-reversion pullbacks within a dominant trend. Divergences here are high-quality because Aroon measures time-based strength, not just price movement - making this ideal for swing traders and intraday trend followers who want confirmation before committing size.
Adaptive Volume Filter Module
The Adaptive Volume Filter takes a fundamentally different approach, analyzing volume-driven market behavior. By transforming price inputs with volume-weighted calculations and applying an adaptive multi-stage smoothing engine, this module emphasizes genuine buying and selling pressure while suppressing noise caused by small, indecisive bars.
Key features include:
Dynamic Thresholding : Traders can set threshold levels to define oversold or overbought regions based on relative volume patterns.
Multi-tiered Signal Generation : Local trend signals identify moderate momentum shifts, while oversold/overbought conditions trigger stronger trade opportunities.
Volume-Cycle Adaptation : The filter adapts to cyclical volume patterns, ensuring that signals remain valid during periods of high or low market participation.
This module is particularly effective for spotting institutional accumulation/distribution, validating trends, and detecting early inflection points where price action alone might be misleading.
Use Case:
Select the Adaptive Volume Filter when you want to validate price movement with participation, not guess momentum in a vacuum. This oscillator shines during breakouts, distribution phases, and deceptive price moves where volume tells the real story. Overbought and oversold zones highlight statistically stretched volume conditions, while the adaptive smoothing engine filters short-term noise caused by small, indecisive bars. This is the model you use to confirm whether a move is being supported or starved - making it lethal for spotting exhaustion, fake breakouts, and accumulation/distribution zones.
HyperSmooth Oscillator Module
The HyperSmooth Oscillator represents the most sophisticated module in the suite, combining adaptive smoothing, dual-cycle EMA differentiation, and volatility-normalized scaling. It calculates momentum by comparing fast and slow EMA cycles of a dynamically smoothed price series and then normalizes this difference using ATR-based volatility adjustments. This ensures that the oscillator is sensitive to micro-momentum changes while remaining robust against extreme volatility spikes.
Additional innovations in this module include:
Hyper-smoothing and acceleration detection : Captures micro-trend shifts and identifies momentum acceleration or deceleration, providing early insight into potential trend reversals.
Dynamic color mapping : Uses HSV-based gradient calculations to indicate the intensity and direction of momentum, enhancing immediate visual interpretation.
Threshold-based cross-validation : Ensures that only meaningful crossovers are flagged as buy or sell signals, reducing false positives in noisy markets.
Combined, these mechanisms give traders access to both subtle and strong market moves, allowing nuanced position sizing and timing strategies.
Use Case:
Use HyperSmooth when you need speed, sensitivity, and volatility-aware momentum detection. This model is built for fast markets, aggressive entries, and momentum continuation plays where standard oscillators lag. By normalizing momentum with ATR and dynamically adjusting signal thresholds, HyperSmooth filters weak crosses and only reacts when momentum actually matters. Color-shifted acceleration highlights when force is increasing or decaying, making this the go-to mode for scalpers and momentum traders hunting explosive continuation or sharp reversals with minimal delay.
Enhanced Divergence Detection System
PowerWave includes a robust divergence detection engine, capable of identifying regular and hidden bullish and bearish divergences across all modules. Divergences are detected by analyzing oscillator pivots against corresponding price highs and lows, ensuring that traders can spot structural weaknesses or strengths in trend continuation.
Key enhancements include:
Pivot-based analysis with lookback control : Allows customization of sensitivity to short-term vs. long-term divergences.
Priority system : Regular divergences are highlighted first, while hidden divergences are only displayed if no regular divergence is present, reducing chart clutter.
Visual representation : Divergences are drawn on both the oscillator and price chart using solid or dashed lines with opacity gradients, enabling clear interpretation of potential reversal zones.
This system equips traders to anticipate trend exhaustion points, early reversals, and high-probability pullbacks, a critical advantage in both trending and range-bound markets.
Visualization and Chart Interpretation
Every module in PowerWave is accompanied by enhanced visual aids, including histogram fills, line overlays, bar coloring, and shape-based trade markers. These features provide instant clarity on:
Trend direction : Bullish vs. bearish zones are highlighted via gradient fills and bar color overlays.
Signal strength : Minor, regular, and strong trade setups are distinguished using shape markers (triangles, circles, diamonds).
Momentum confirmation : Histogram fills indicate whether the oscillator is accelerating or decelerating relative to its signal line.
By integrating these visualizations, PowerWave transforms complex calculations into immediately actionable chart insights, enabling both manual and automated strategies to be executed with confidence.
General Use Cases and Trading Applications
Trend-following : Combine oscillator zero-line crossovers with divergence confirmation for disciplined entries.
Counter-trend trading : Utilize hidden divergence signals to identify potential reversal points before visible trend exhaustion.
Volume-sensitive trades : Adaptive Volume Filter highlights accumulation/distribution phases, providing context for institutional participation.
Scalping and swing strategies : HyperSmooth Oscillator captures micro-momentum changes, ideal for both short-term scalping and multi-day swing trades.
The suite is designed for flexibility and adaptability, allowing traders to integrate multiple modules, fine-tune parameters, and create customized signals aligned with personal strategies or specific market conditions.
Final Notes
PowerWave Oscillator Suite is designed as an analytical decision-support system. It provides structured market insight based on historical price and volume behavior and does not constitute predictive or outcome-guaranteed functionality. Its core design philosophy emphasizes clarity, adaptability, and risk-aware decision-making. Every calculation, filter, and visual cue is intended to provide insight, not guarantees. Traders are encouraged to combine the suite’s outputs with proper risk management, contextual market awareness, and disciplined strategy execution.
Risk Disclaimer
This indicator is provided for educational and informational purposes only and does not constitute financial advice. Trading involves significant risk, and past performance is not indicative of future results. Users are responsible for their own analysis, risk management, and execution decisions.
