Multi Cycles Slope-Fit System MLMulti Cycles Predictive System : A Slope-Adaptive Ensemble
Executive Summary:
The MCPS-Slope (Multi Cycles Slope-Fit System) represents a paradigm shift from static technical analysis to adaptive, probabilistic market modeling. Unlike traditional indicators that rely on a single algorithm with fixed settings, this system deploys a "Mixture of Experts" (MoE) ensemble comprising 13 distinct cycle and trend algorithms.
Using a Gradient-Based Memory (GBM) learning engine, the system dynamically solves the "Cycle Mode" problem by real-time weighting. It aggressively curve-fits the Slope of component cycles to the Slope of the price action, rewarding algorithms that successfully predict direction while suppressing those that fail.
This is a non-repainting, adaptive oscillator designed to identify market regimes, pinpoint high-probability reversals via OB/OS logic, and visualize the aggregate consensus of advanced signal processing mathematics.
1. The Core Philosophy: Why "Slope" Matters:
In technical analysis, most traders focus on Levels (Price is above X) or Values (RSI is at 70). However, the primary driver of price action is Momentum, which is mathematically defined as the Rate of Change, or the Slope.
This script introduces a novel approach: Slope Fitting.
Instead of asking "Is the cycle high or low?", this system asks: "Is the trajectory (Slope) of this cycle matching the trajectory of the price?"
The Dual-Functionality of the Normalized Oscillator
The final output is a normalized oscillator bounded between -1.0 and +1.0. This structure serves two critical functions simultaneously:
Directional Bias (The Slope):
When the Combined Cycle line is rising (Positive Slope), the aggregate consensus of the 13 algorithms suggests bullish momentum. When falling (Negative Slope), it suggests bearish momentum. The script measures how well these slopes correlate with price action over a rolling lookback window to assign confidence weights.
Overbought / Oversold (OB/OS) Identification:
Because the output is mathematically clipped and normalized:
Approaching +1.0 (Overbought): Indicates that the top-weighted algorithms have reached their theoretical maximum amplitude. This is a statistical extreme, often preceding a mean reversion or trend exhaustion.
Approaching -1.0 (Oversold): Indicates the aggregate cycle has reached maximum bearish extension, signaling a potential accumulation zone.
Zero Line (0.0): The equilibrium point. A cross of the Zero Line is the most traditional signal of a trend shift.
2. The "Mixture of Experts" (MoE) Architecture:
Markets are dynamic. Sometimes they trend (Trend Following works), sometimes they chop (Mean Reversion works), and sometimes they cycle cleanly (Signal Processing works). No single indicator works in all regimes.
This system solves that problem by running 13 Algorithms simultaneously and voting on the outcome.
The 13 "Experts" Inside the Code:
All algorithms have been engineered to be Non-Repainting.
Ehlers Bandpass Filter: Extracts cycle components within a specific frequency bandwidth.
Schaff Trend Cycle: A double-smoothed stochastic of the MACD, excellent for cycle turning points.
Fisher Transform: Normalizes prices into a Gaussian distribution to pinpoint turning points.
Zero-Lag EMA (ZLEMA): Reduces lag to track price changes faster than standard MAs.
Coppock Curve: A momentum indicator originally designed for long-term market bottoms.
Detrended Price Oscillator (DPO): Removes trend to isolate short-term cycles.
MESA Adaptive (Sine Wave): Uses Phase accumulation to detect cycle turns.
Goertzel Algorithm: Uses Digital Signal Processing (DSP) to detect the magnitude of specific frequencies.
Hilbert Transform: Measures the instantaneous position of the cycle.
Autocorrelation: measures the correlation of the current price series with a lagged version of itself.
SSA (Simplified): Singular Spectrum Analysis approximation (Lag-compensated, non-repainting).
Wavelet (Simplified): Decomposes price into approximation and detail coefficients.
EMD (Simplified): Empirical Mode Decomposition approximation using envelope theory.
3. The Adaptive "GBM" Learning Engine
This is the "Machine Learning" component of the script. It does not use pre-trained weights; it learns live on your chart.
How it works:
Fitting Window: On every bar, the system looks back 20 days (configurable).
Slope Correlation: It calculates the correlation between the Slope of each of the 13 algorithms and the Slope of the Price.
Directional Bonus: It checks if the algorithm is pointing in the same direction as the price.
Weight Optimization:
Algorithms that match the price direction and correlation receive a higher "Fit Score."
Algorithms that diverge from price action are penalized.
A "Softmax" style temperature function and memory decay allow the weights to shift smoothly but aggressively.
The Result: If the market enters a clean sine-wave cycle, the Ehlers and Goertzel weights will spike. If the market explodes into a linear trend, ZLEMA and Schaff will take over, suppressing the cycle indicators that would otherwise call for a premature top.
4. How to Read the Interface:
The visual interface is designed for maximum information density without clutter.
The Dashboard (Bottom Left - GBM Stats)
Combined Fit: A percentage score (0-100%). High values (>70%) mean the system is "Locked In" and tracking price accurately. Low values suggest market chaos/noise.
Entropy: A measure of disorder. High entropy means the algorithms disagree (Neutral/Chop). Low entropy means the algorithms are unanimous (Strong Trend).
Top 1 / Top 3 Weight: Shows how concentrated the decision is. If Top 1 Weight is 50%, one algorithm is dominating the decision.
The Matrix (Bottom Right - Weight Table)
This table lifts the hood on the engine.
Fit Score: How well this specific algo is performing right now.
Corr/Dir: Raw correlation and Direction Match stats.
Weight: The actual percentage influence this algorithm has on the final line.
Cycle: The current value of that specific algorithm.
Regime: Identifies if the consensus is Bullish, Bearish, or Neutral.
The Chart Overlay
The Line: The Gradient-Colored line is the Weighted Ensemble Prediction.
Green: Bullish Slope.
Red: Bearish Slope.
Triangles: Zero-Cross signals (Bullish/Bearish).
"STRONG" Labels: Appears when the cycle sustains a value above +0.5 or below -0.5, indicating strong momentum.
Background Color: Changes subtly to reflect the aggregate Regime (Strong Up, Bullish, Neutral, Bearish, Strong Down).
5. Trading Strategies:
A. The Slope Reversal (OB/OS Fade)
Concept: Catching tops and bottoms using the -1/+1 normalization.
Signal: Wait for the Combined Cycle to reach extreme values (>0.8 or <-0.8).
Trigger: The entry is taken not when it hits the level, but when the Slope flips.
Short: Cycle hits +0.9, color turns from Green to Red (Slope becomes negative).
Long: Cycle hits -0.9, color turns from Red to Green (Slope becomes positive).
B. The Zero-Line Trend Join
Concept: Joining an established trend after a correction.
Signal: Price is trending, but the Cycle pulls back to the Zero line.
Trigger: A "Triangle" signal appears as the cycle crosses Zero in the direction of the higher timeframe trend.
C. Divergence Analysis
Concept: Using the "Fit Score" to identify weak moves.
Signal: Price makes a Higher High, but the Combined Cycle makes a Lower High.
Confirmation: Check the GBM Stats table. If "Combined Fit" is dropping while price is rising, the trend is decoupling from the cycle logic. This is a high-probability reversal warning.
6. Technical Configuration:
Fitting Window (Default: 20): The number of bars the ML engine looks back to judge algorithm performance. Lower (10-15) for scalping/quick adaptation. Higher (30-50) for swing trading and stability.
GBM Learning Rate (Default: 0.25): Controls how fast weights change.
High (>0.3): The system reacts instantly to new behaviors but may be "jumpy."
Low (<0.15): The system is very smooth but may lag in regime changes.
Max Single Weight (Default: 0.55): Prevents one single algorithm from completely hijacking the system, ensuring an ensemble effect remains.
Slope Lookback: The period over which the slope (velocity) is calculated.
7. Disclaimer & Notes:
Repainting: This indicator utilizes closed bar data for calculations and employs non-repainting approximations of SSA, EMD, and Wavelets. It does not repaint historical signals.
Calculations: The "ML" label refers to the adaptive weighting algorithm (Gradient-based optimization), not a neural network black box.
Risk: No indicator guarantees future performance. The "Fit Score" is a backward-looking metric of recent performance; market regimes can shift instantly. Always use proper risk management.
Author's Note
The MCPS-Slope was built to solve the frustration of "indicator shopping." Instead of switching between an RSI, a MACD, and a Stochastic depending on the day, this system mathematically determines which one is working best right now and presents you with a single, synthesized data stream.
If you find this tool useful, please leave a Boost and a Comment below!
Adaptive
Adaptive Log Trend Zones + Retest SignalsAdaptive Log Trend Zones + Retest Signals
Adaptive Log Trend Zones is a trend-following overlay built to identify high-probability breakout retests in strong market conditions. It combines logarithmic regression , volatility-adaptive behavior , and ATR-based trend zones to help traders stay aligned with dominant momentum while avoiding chop.
🔹 Core Features
Logarithmic Regression Midline
Uses linear regression on log price to better handle exponential market moves
Produces smoother, more realistic trend structure on higher timeframes
Volatility-Adaptive Lookback
Automatically expands or contracts the regression length based on ATR volatility
Reacts faster in high volatility, smoother in consolidation
Dynamic Trend Zones
Upper and lower bands are ATR-adjusted and trend-colored
Optional future projection for visual trend guidance
Breakout → Retest Signal Logic
Detects clean breakouts beyond the trend zone
Waits for a controlled pullback (retest) before signaling
Signals only trigger when trend strength is confirmed
Trend Quality Filter
Internal regime detection filters out low-quality, sideways conditions
Uses slope strength and volatility compression to validate entries
🔹 Signals
BUY : Bullish breakout followed by a valid retest in a trending regime
SELL : Bearish breakout followed by a valid retest in a trending regime
Signals are designed for trend continuation , not mean reversion.
🔹 Best Use Cases
Crypto, Forex, and Index markets
Higher timeframes (15m+ recommended)
Trend continuation and pullback strategies
⚠️ Notes
This indicator is not a standalone trading system . Always use proper risk management and confirm signals with structure, volume, or higher-timeframe context.
Designed for traders who prefer structure, patience, and momentum alignment.
Volatility Trend Score [BackQuant]Volatility Trend Score
Overview
Volatility Trend Score is a trend-strength and regime-evaluation indicator built to measure directional persistence, not just direction. Most trend tools answer “up or down” using slope, crossovers, or a single condition. This indicator answers a more useful question for real trading: “How consistently is trend structure holding up once volatility is accounted for?”
It does this by building a volatility-scaled trailing structure (ATR-based) and then scoring how that structure evolves over a configurable lookback range. The output is a continuous score that rises when trend is persistent and decays when price action becomes noisy, mean-reverting, or unstable.
What it is measuring (the real goal)
This indicator is not trying to predict reversals. It is trying to quantify whether the market is behaving like a trend market or a chop market. It focuses on:
Persistence: does structure keep pushing in one direction bar after bar?
Stability: are pullbacks being absorbed without breaking the trailing structure?
Regime: is the market trending strongly enough to justify directional bias?
If you already have entries from other systems, this becomes a high-quality trend filter and trade management layer.
Core idea
At its foundation, the indicator combines two parts:
A volatility-adjusted trailing level derived from ATR and a user-defined factor.
A rolling persistence score that compares the current trail to prior trail values over a configurable loop window.
The trailing structure adapts to volatility and enforces one-sided movement, while the scoring logic converts that behavior into a numeric measure of trend quality.
Inputs and what they actually control
Average True Range Period (calc_p)
Defines the ATR window used to estimate volatility. A higher value smooths the volatility estimate and makes the trailing structure less reactive.
Factor (atr_factor)
Scales the ATR band size. Higher values widen the trailing band, filtering more noise, reducing flip frequency, and generally producing slower but more stable regimes.
For Loop Start/End (start/end)
Defines the comparison window used to build the score. It effectively sets how many historical trail values the current trail is compared against.
Shorter ranges produce a faster, more responsive score.
Longer ranges produce a slower, more “confidence-based” score that only climbs when trend persistence is sustained.
Long/Short Thresholds (thresL/thresS)
Convert a continuous score into regime thresholds.
Long threshold is a “trend quality requirement” for bullish bias.
Short threshold is used as a deterioration / breakdown trigger via crossunder logic.
Volatility-adjusted trailing structure
The trailing line is built from ATR bands around price:
up = close + ATR * factor
dn = close - ATR * factor
Then a trailing value is maintained with one-sided ratcheting behavior:
If dn rises above the previous trail, the trail steps up (ratchets upward).
If up drops below the previous trail, the trail steps down (ratchets downward).
This “ratchet” behavior is important. It prevents the trail from oscillating with small countertrend moves, forcing the trail to represent meaningful structure rather than micro-noise. On-chart, this trail often behaves like dynamic support/resistance in trends.
Why the trail is a better base than raw price
Price itself is noisy, and volatility changes the meaning of “big move” vs “small move.” By anchoring structure to ATR:
A move is interpreted relative to current volatility, not in absolute points.
High-volatility chop is less likely to be misread as a trend.
Trend structure is normalized across assets and timeframes more reliably.
This is why the score remains usable even when switching from low-vol assets to high-vol crypto pairs.
Trend scoring logic
The score is built by repeatedly comparing the current trailing value to trailing values from prior bars across a loop window:
If current trail > trail , add +1
If current trail < trail , add -1
This is a persistence test, not a momentum calculation. In a strong trend, the trail should generally keep stepping in the trend direction, so current values will be greater than many past values (bullish) or lower than many past values (bearish). In chop, the trail fails to progress meaningfully, so the score compresses, oscillates, or bleeds out.
How to interpret the score
Think of the score as a “trend conviction meter”:
High positive values: bullish persistence, structure is advancing consistently.
Low positive values: bullish bias may exist, but trend quality is weak or unstable.
Near zero: indecision, range behavior, or frequent structure challenges.
Negative values: bearish dominance or sustained deterioration in structure.
The speed of score change matters too:
Fast expansion suggests a fresh regime gaining traction.
Slow grind suggests mature trend continuation.
Rapid compression often signals consolidation, exhaustion, or a transition phase.
Signals and regime transitions
This script uses two different styles of conditions (important detail):
Long condition: score > long threshold (state-based, persistent while true).
Short condition: crossunder(score, short threshold) (event-based trigger).
That means:
Long bias can remain active as long as score stays above the long threshold.
Short regime flips are triggered at the moment the score breaks down through the short threshold.
On the chart, long/short shapes are only plotted when the regime flips (first bar of the change), not on every bar, using:
Long shape when signal becomes 1 and previous signal was -1
Short shape when signal becomes -1 and previous signal was 1
This keeps signals clean and avoids spam, making it usable for alerts and regime tagging.
Visual presentation
The indicator is designed to work both as a panel oscillator and as an on-chart overlay:
Score plot (oscillator): color reflects active regime state.
Optional trail on price: volatility-scaled structure line on chart.
Optional threshold reference lines: clear regime boundaries.
Optional candle coloring: makes regime obvious without reading the panel.
Optional background shading: useful for quick scanning and backtesting visually.
You can use only the score, only the trail, or both together depending on your workflow.
Practical use cases
1) Trend filter for systems
Use the score as a regime gate:
Allow long entries only when score is above the long threshold.
Avoid longs when score compresses toward zero or loses the threshold.
Treat the short threshold break as “trend is no longer healthy.”
This often improves system expectancy by reducing exposure during low-conviction conditions.
2) Trend quality grading
Instead of treating all uptrends as equal:
Higher score = higher persistence, better continuation odds.
Score plateau = trend losing pressure, continuation becomes less reliable.
Score decay while price rises = trend is getting weaker under the hood.
This is useful for position sizing or deciding whether to add to winners.
3) Trade management and exits
Two complementary tools exist here:
Trail line can act as a dynamic stop reference or structure invalidation level.
Score behavior can be used to scale out when persistence fades (before a full flip).
Many traders use the trail for “hard structure” and the score for “soft deterioration.”
4) Breakout confirmation vs fakeouts
A breakout that immediately fails to build score is often low quality.
Healthy breakouts usually come with score expansion as structure advances.
Fakeouts often revert quickly, score fails to climb, and regime stays unstable.
Tuning guidelines
These are general behaviors you can expect when adjusting settings:
Higher ATR period and factor: slower regimes, fewer flips, cleaner structure.
Lower ATR period and factor: faster reaction, more sensitivity, more noise risk.
Longer loop range: score becomes more “confidence-based,” slower to change.
Shorter loop range: score becomes more “tactical,” faster but more jittery.
A good way to tune is to pick the trail behavior first (ATR period and factor), then tune the score window (loop) to match how quickly you want “trend conviction” to build.
Market behavior focus
Volatility Trend Score is most valuable in markets where volatility shifts frequently and fake trends are common, especially crypto. It is designed to:
Stay out of low-quality chop where most indicators whipsaw.
Quantify when volatility is being expressed directionally (constructive trend).
Provide a clean regime framework for filtering, alignment, and management.
Summary
Volatility Trend Score converts volatility-adjusted structure into a quantified measure of trend persistence. By combining an ATR-based trailing mechanism with a rolling comparison score, it provides a more reliable read on trend quality than single-condition indicators. It is best used as a regime filter, a trend strength gauge, and a trade management layer, helping you stay aligned with strong directional phases while avoiding low-conviction envir
Apex Adaptive Trend Navigator [Pineify]Apex Adaptive Trend Navigator
The Apex Adaptive Trend Navigator is a comprehensive trend-following indicator that combines adaptive moving average technology, dynamic volatility bands, and market structure analysis into a single, cohesive trading tool. Designed for traders who want to identify trend direction with precision while filtering out market noise, this indicator adapts its sensitivity based on real-time market efficiency calculations.
Key Features
Adaptive Moving Average with efficiency-based smoothing factor
Dynamic ATR-based volatility bands that expand and contract with market conditions
Market Structure detection including BOS (Break of Structure) and CHoCH (Change of Character)
Real-time performance dashboard displaying trend status and efficiency metrics
Color-coded cloud visualization for intuitive trend identification
How It Works
The core of this indicator is built on an Adaptive Moving Average that uses a unique efficiency-based calculation method inspired by the Kaufman Adaptive Moving Average (KAMA) and TRAMA concepts. The efficiency ratio measures the directional movement of price relative to total price movement over the lookback period:
Efficiency = |Price Change over N periods| / Sum of |Individual Bar Changes|
This ratio ranges from 0 to 1, where values closer to 1 indicate a strong trending market with minimal noise, and values closer to 0 indicate choppy, sideways conditions. The smoothing factor is then squared to penalize noisy markets more aggressively, causing the adaptive line to flatten during consolidation and respond quickly during strong trends.
The Dynamic Volatility Bands are calculated using the Average True Range (ATR) multiplied by a user-defined factor. These bands create a channel around the adaptive moving average, helping traders visualize the current volatility regime and potential support/resistance zones.
Trading Ideas and Insights
When price stays above the adaptive line with the bullish cloud forming, consider this a confirmation of uptrend strength
The efficiency percentage in the dashboard indicates trend quality - higher values suggest more reliable trends
Watch for price interactions with the upper and lower bands as potential reversal or continuation zones
A flat adaptive line indicates consolidation - wait for a clear directional break before entering trades
How Multiple Indicators Work Together
This indicator integrates three complementary analytical approaches:
The Adaptive Moving Average serves as the trend backbone, providing a dynamic centerline that automatically adjusts to market conditions. Unlike fixed-period moving averages, it reduces lag during trends while minimizing whipsaws during ranging markets.
The ATR Volatility Bands work in conjunction with the adaptive MA to create a volatility envelope. When the adaptive line is trending and price remains within the cloud (between the MA and outer band), this confirms trend strength. Price breaking through the opposite band may signal exhaustion or reversal.
The Market Structure Analysis using swing point detection adds a Smart Money Concepts (SMC) layer. BOS signals indicate trend continuation when price breaks previous swing highs in uptrends or swing lows in downtrends. CHoCH signals warn of potential reversals when the structure shifts against the prevailing trend.
Unique Aspects
The squared efficiency factor creates a non-linear response that dramatically reduces noise sensitivity
Cloud fills only appear on the trend side, providing clear visual distinction between bullish and bearish regimes
The integrated dashboard eliminates the need to switch between multiple indicators for trend assessment
Pivot-based swing detection ensures accurate market structure identification
How to Use
Add the indicator to your chart and adjust the Lookback Period based on your trading timeframe (shorter for scalping, longer for swing trading)
Monitor the cloud color - green clouds indicate bullish conditions, red clouds indicate bearish conditions
Use the efficiency reading in the dashboard to gauge trend reliability before entering positions
Consider entries when price pulls back to the adaptive line during strong trends (high efficiency)
Use the volatility bands as dynamic take-profit or stop-loss reference levels
Customization
Lookback Period : Controls the sensitivity of trend detection and swing point identification (default: 20)
Volatility Multiplier : Adjusts the width of the ATR bands (default: 2.0)
Show Market Structure : Toggle visibility of BOS and CHoCH labels
Show Performance Dashboard : Toggle the trend status table
Color Settings : Customize bullish, bearish, and neutral colors to match your chart theme
Conclusion
The Apex Adaptive Trend Navigator offers traders a sophisticated yet intuitive approach to trend analysis. By combining adaptive smoothing technology with volatility measurement and market structure concepts, it provides multiple layers of confirmation for trading decisions. Whether you are a day trader seeking quick trend identification or a swing trader looking for reliable trend-following signals, this indicator adapts to your market conditions and trading style. The efficiency-based calculations ensure you always know not just the trend direction, but also the quality and reliability of that trend.
ML-Inspired Adaptive Momentum Strategy (TradingView v6)This strategy demonstrates an adaptive momentum approach using volatility-normalized trend strength. It is designed for educational and analytical purposes and uses deterministic, fully transparent logic compatible with Pine Script v6.
ML-Inspired Concept (Educational Context)
Pine Script cannot train or execute real machine-learning models.
Instead, this strategy demonstrates ML-style thinking by:
Converting price data into features
Normalizing features to account for volatility differences
Producing a bounded confidence score
Applying thresholds for decision making
This is not predictive AI and does not claim forecasting capability.
Strategy Logic
EMA is used to measure directional bias
EMA slope represents momentum change
ATR normalizes the slope (feature scaling)
A clamped score between −1 and +1 is generated
Trades trigger only when the score exceeds defined thresholds
Risk & Execution
Position size capped at 5% equity
Commission and slippage included for realistic testing
Signals are calculated on closed bars only
Purpose
This script is intended to help traders explore adaptive momentum concepts and understand how feature normalization can be applied in systematic trading strategies.
Adaptive RSIThe Adaptive RSI is a new version of the famous RSI that can adapt to environments and produce both Mean Reverting & Trend Following signals.
The Benefits
- Adaptive behaviour can allow fast entries while also filtering false signals
- Provides signals for both catching high/low value zones and trends
- Very good trend catching in trending environments
- Visualization provides Overbought/Oversold signal highlighting of more restrictive (diamonds) and less restrictive type (background), divergence between smoothed and basic RSI, Adaptive RSI values and bar coloring.
- Works well on BINANCE:BNBUSD
The Idea
The main idea is to give the RSI a more adaptive approach to do the market, so it can speed it up during potential oppurtunities and slow down during more dangerous environments.
This would theoreticly allow it to be a lot more versatile and provide a more accurate set of signals. On top of that, the adaptive approach could not only provide great entries but also exits when following the indicator mean-reverting style.
How it works
The indicator sets up 3 conditions, the more of them are true, the more aggressive approach will be chosen. This allows the indicator to shift speed, adapt to any environment and avoid too many false signals.
Then it uses a smoothing to improve accuracy, that is adaptive in the same way as the RSI itself.
It also has a option for a special ROC-weighted source, which however I do not recommend using unless you understand coding & know how it works.
Hope you enjoy Gs!
Please keep in mind no indicator is perfect and that every indicator has flaws
Adaptive MA SuperTrend 3.0The Adaptive MA SuperTrend 3.0 is a 3rd Generation of the SuperTrend indicator focused on improving accuracy while maintaining high speeds to capture ANY trend the market has to offer and allow investors/traders from beginner to advanced and beyond to gain a unique insight on what is happening with the markets.
How does it work?
The indicator uses a Moving Average as a base for the SuperTrend and adapts it to market environments.
It uses averages to find if short-term, medium-term or long-term have the highest avg. volume/ATR/Standard Deviation. Whichever period has the highest avg. is the length that will be used for the moving average.
Then it smooths it slightly to give a smoother result to finish the job.
That leaves us with high speed & accurate signals that adapt to any environment.
Enjoy!
AMS Adaptive MACDAMS Adaptive MACD
A regime-aware MACD built to show when momentum matters and when it doesn’t.
Most MACDs react the same way in every environment. AMS Adaptive MACD does not.
It dynamically adjusts itself to market conditions so momentum expansions stand out clearly, while chop, compression, and late-stage fades are intentionally muted.
This indicator is designed for traders who want cleaner momentum context, not constant crossover noise.
What it shows (at a glance)
Adaptive MACD lines that automatically adjust to current market conditions
A non-repainting momentum state:
BULL / BEAR PUSH – momentum is pressing
BULL / BEAR FADE – momentum is cooling
NEUTRAL / COIL – compression / low-quality conditions
Optional Trader HUD that summarizes the recent regime in plain language:
Market control (Bull / Bear / Range / Transition)
Dominance strength over a lookback window
Tape quality (Clean vs Choppy)
Volatility regime (Compressed / Normal / Elevated)
A simple context cue (not trade signals)
How traders typically use it
Filter out neutral or choppy conditions
Focus only on higher-quality momentum pushes
Stay aligned with the dominant regime instead of reacting to every wiggle
Add structure and patience to discretionary decision-making
This tool is contextual, not predictive. It helps frame what phase the market is in, not where to click buy or sell.
Technical overview (high-level)
AMS Adaptive MACD uses dynamic fast, slow, and signal lengths that respond to market regime rather than remaining fixed.
Without exposing proprietary logic, the engine accounts for:
Broader trend persistence and volatility conditions
Current timeframe efficiency (trend vs chop)
Stability controls to prevent over-reaction or parameter thrashing
All higher-timeframe inputs are handled in a non-repainting manner, and state labeling is locked on confirmed bars.
Important notes
This is an analytical and educational tool, not financial advice - A standalone educational engine inspired by the same design philosophy as the Atmos Suite.
No entries, exits, or alerts are generated by default
Best used as a context filter alongside price, structure, and risk management
AMS Adaptive MACD is built for traders who care less about more signals and more about better conditions.
Adaptive MA SuperTrend 2.0The Adaptive MA SuperTrend 2.0 is a new cutting edge SuperTrend that adapts to the environment and provides users with fast, smooth signals that can enhance the strategies of any user.
How does it work?
This indicator combines the classic ATR with Moving Average of users choice, and filters the data. It uses a condition, that flips the Moving Average between the past and current value, adapting and trying to enhance the accuracy of the indicator
Adaptive MA SuperTrendAdaptive MA SuperTrend is a new trend following tool designed for more responsive & smoother signal production from the classical SuperTrend indicator.
It works by picking two Moving Averages, that are swapped in their function between being used for the upper base or the lower base, based on the circumstances.
Then it applies either SD or ATR (based on the users preference) to the bases.
This provides smooth, fast trend signals that users can use to enhance their trading/investing strategies.
Enjoy!
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.
Market Divergence Index (MDI)MDI - Specialized indicator for BTC, ETH and dominance analysis.
⚠️ FREE BETA - Временный открытый доступ для тестирования
Recommended pairs:
• BTC/USDT or ETH/USDT → Benchmark: USDT.D
• USDT.D → Benchmark: BTC
Adjust Quality Threshold (1-10) for signal filtering.
📱 Telegram: @belfort94
Adaptive Volume Profile [by Oberlunar]Adaptive Volume Profile of Oberlunar is built to solve a practical limitation I’ve found in many volume profile scripts: they don’t truly adapt to the chart’s visible range, so you lose readability when you zoom in for microstructure or zoom out for macro context.
This indicator stays usable across zoom levels, keeping the profile informative and visually consistent whether you’re studying fine detail or the bigger picture.
On top of that, it highlights something I’ve always wanted to read at a glance: how bullish vs bearish pressure behaves inside convex and concave volumetric structures — the bumps (high participation nodes - yellow area) and the bottlenecks (low participation nodes where price often travels fast - violet area).
You can quickly spot whether a bump is dominated by positive or negative flow, then zoom in to validate if the pressure is confirmed by subsequent price action. Missing this kind of clarity can easily lead to wrong assumptions and bad decisions — this tool is designed to make that read immediate and attractive.
Zoom In - Zoom Out example
For example, this is a "zoom in":
It looks bearish...
yeah... let's see the whole picture by a zoom out:
The bearish volumetric pressure is evident in the last bottleneck.
Bearish setup
Before
After
Bullish setup
Before
After
— Oberlunar 👁★
Options Gamma Flip Zones [BackQuant]Options Gamma Flip Zones
A market-structure style “gamma flip” mapper that builds adaptive strike-like zones, scores how price interacts with them, then promotes the strongest candidates into confirmed flip zones. Designed to highlight pinning, failed breaks, and rotational behavior without needing live options chain data.
What this indicator does
This script identifies price levels that behave like “strike magnets” during conditions that resemble options pinning, then draws dynamic zones around those levels.
Instead of assuming every round number matters, it:
Creates a strike ladder (auto or manual step).
Applies a regime filter that looks for “pin-friendly” market conditions.
Tracks and scores repeated interactions with the level.
Upgrades a zone from candidate to confirmed when enough evidence accumulates.
Invalidates zones when price achieves sustained acceptance away from them.
The output is a set of shaded boxes (zones) centered on strike-like levels, with text readouts that show the current state of each zone.
Key concept: “Gamma proxy”
A true gamma flip requires options positioning data. This indicator does not use options chain gamma.
Instead, it uses a proxy approach:
When markets have elevated volatility relative to their recent baseline AND trend strength is weak, price often behaves “sticky” around key levels.
In those conditions, repeated touches and failed escapes around a level behave similarly to pinning around strikes.
So this tool is best read as:
“Where would a strike-like magnet likely exist right now, based on price behavior and regime conditions?”
How zones are created
Zones only start forming when the script detects a pin-friendly regime.
1) Strike Ladder (level selection)
Auto Strike Step selects a step size based on current price magnitude (bigger price, bigger step).
Manual Strike Step lets you force a fixed increment.
The current “active level” is the nearest rounded level to price.
Major Level Every optionally marks major ladder levels (multiples of step).
2) Band construction (zone thickness)
Each zone is a symmetric band around the level, using one of two modes:
ATR mode scales thickness with volatility.
Percent mode scales thickness as a fraction of price.
This matters because “pin behavior” is not a single tick. It’s a region where price repeatedly probes and rejects.
Regime filter (when the script is allowed to believe in pinning)
A zone is only eligible to form and strengthen when Pin Regime is active. Pin Regime is a conjunction of:
1) IV proxy (ATR z-score)
Uses ATR as a volatility proxy.
Converts ATR% into a z-score relative to a long lookback.
IV Proxy Threshold controls how elevated volatility must be before the script considers pinning likely.
2) Weak trend requirement
The script also requires price action to be non-trending:
EMA spread must be small (fast vs slow EMA not diverging strongly).
ADX must be below a ceiling, confirming weak directional trend strength.
Interpretation:
High “IV proxy” + weak trend is where pin-like behavior is most common.
If trend is strong, zones are less meaningful because price is more likely to accept away from levels.
Flip confirmation logic (what upgrades a zone)
A zone is not “confirmed” just because price is near it once. The script builds conviction via evidence accumulation.
Evidence types:
Touches : price comes close to the level within tolerance.
Failed escapes : price pushes outside the band but closes back inside (rejection).
Acceptance run : consecutive closes outside the band, suggesting price is accepting away from the zone.
Protections:
Touch Cooldown prevents counting the same micro-chop as multiple touches.
Acceptance Bars defines what “real acceptance” means, so the zone does not get invalidated by one noisy bar.
A zone becomes confirmed when:
Touches meet the “evidence” requirement.
Failed escapes meet the “rejection” requirement.
The regime filter still says the market is pin-friendly.
That is important, it avoids promoting levels that only worked briefly in a trending tape.
Zone scoring and lifecycle
Each zone maintains a score that evolves over time. Think of score as “how much this level has recently behaved like a magnet.”
Score dynamics:
Decay per bar : score fades over time if price stops respecting the zone.
+ per touch : repeated proximity increases score.
+ per failed escape : rejections add stronger reinforcement.
- per acceptance bar : sustained trading outside reduces score.
Min score to draw : prevents clutter from weak, low-confidence zones.
Invalidation:
If the score becomes very weak AND price achieves sustained acceptance away from the zone, the zone is deleted.
This keeps the chart clean and ensures zones represent current market behavior, not ancient levels.
How to read the plot on chart
1) Zone fill and border
Each zone is drawn as a box extended to the right.
Fill opacity adapts to zone strength, strong zones are visually more prominent.
Border color encodes the current directional context and special events.
2) Bullish vs bearish coloring
A zone is colored bullish when price is currently trading above the zone’s mid-level.
A zone is colored bearish when price is currently trading below it.
This is not a trade signal by itself, it is a state cue for “which side is in control around the level.”
3) Failed escape highlighting
If price attempts to break above the band and fails, the border temporarily highlights as a failed up escape.
If price attempts to break below the band and fails, the border temporarily highlights as a failed down escape.
These are the moments where pin behavior is most visible:
Break attempt.
Immediate rejection.
Return to the band.
4) Midline (optional)
The zone midline is the strike-like level itself.
It is dotted to distinguish it from price structure lines.
5) Optional strike ladder overlay
When enabled, the script draws major and minor ladder lines near current price.
Major levels are thicker and less transparent.
This is a visualization aid for “where the algorithm is rounding,” not a prediction tool.
On-chart text readout (what the box text means)
Each box prints a compact state summary, designed for fast scanning:
Γ CANDIDATE means the zone is being tracked but not yet validated.
Γ FLIP (PROXY) means the zone has met confirmation requirements.
BULL/BEAR indicates which side price is on relative to the mid-level.
L prints the level value.
T is touch count, repeated proximity events.
F is fail count, rejected escape attempts.
IVz is the volatility proxy z-score at the moment.
ADX is the trend strength context.
Practical use cases
1) Pinning and range trading context
Confirmed zones often act like gravity wells in sideways or rotational regimes.
When price repeatedly fails to escape, fading outer edges can be reasonable context for mean reversion workflows.
2) Breakout validation
If price achieves acceptance outside the band for multiple bars, that is stronger breakout context than a single wick.
Zones that invalidate cleanly can mark transitions from pinning to directional move.
3) Time your “do nothing” periods
When Pin Regime is active and a zone is confirmed, the tape often becomes sticky and inefficient for trend chasing.
This helps avoid taking trend entries into a pin environment.
Alerts
Standalone alertconditions are included:
Zone Confirmed : a candidate becomes confirmed.
Zone Touch : price touches an active zone within tolerance.
Zone Invalidated : the zone loses relevance and is removed.
Tuning guidelines
Sensitivity vs quality
Lower Touches Needed and Failed Escapes Needed creates more zones faster, but with lower quality.
Higher values create fewer zones, but the ones that remain are more behaviorally “proven.”
Band width
ATR mode adapts to volatility and is typically safer across assets.
Percent mode is consistent visually but can feel too tight in high vol or too wide in low vol if not tuned.
Regime thresholds
If you want fewer zones, raise IV proxy threshold and tighten weak-trend filters.
If you want more zones, lower IV proxy threshold and loosen weak-trend filters.
Limitations
This is a proxy model, not live options gamma.
In strong trends, pinning assumptions can break, the regime filter is there to reduce that risk, but not eliminate it.
Auto strike step is designed for typical market ranges, manual step is recommended for niche tick sizes or custom markets.
Disclaimer
Educational and informational only, not financial advice.
Not a complete trading system.
Always validate settings per asset and timeframe.
Equilibrium Reversal Channel [BOSWaves]Equilibrium Reversal Channel - Volatility-Based Risk Geometry for Mean Reversion Scenarios
Overview
The Equilibrium Reversal Channel is a volatility-weighted price channel designed to highlight statistically stretched price conditions and assist traders in identifying mean-reversion opportunities within broader market structure. The indicator is not intended to predict market direction in isolation, but rather to contextualize price movement relative to volatility, trend balance, and exhaustion zones.
At its foundation, this tool operates on the assumption that price oscillates around a dynamic equilibrium. When price deviates too far from that equilibrium - particularly under expanding volatility - the probability of a reaction, pause, or reversal increases. The Reversal Channel visualizes these deviations clearly, continuously, and without relying on fixed thresholds or static support/resistance levels.
This indicator is best used as a contextual framework, not as a standalone trading system. Its strength lies in defining where reactions are statistically more likely to occur and when price has moved far enough to warrant caution or contrarian attention.
Use Cases
Primary Use Case 1: Volatility-Anchored Trade Framing (TP / SL Construction)
The Equilibrium Reversal Channel is used to construct trade reference levels directly from live market structure and volatility behavior, rather than from arbitrary price distances.
Stop invalidation is framed around the outer displacement boundary. This boundary represents the point at which price is no longer statistically stretched but instead entering a new volatility regime, invalidating the original mean-reversion premise. In other words, if price accepts beyond this zone, the imbalance thesis is structurally broken.
Take-profit projections are derived from measured rebalancing paths back toward equilibrium, scaled using configurable payoff ratios. These projections reflect how far price typically resolves once imbalance conditions unwind, rather than relying on fixed targets or discretionary exits.
This use case turns the channel into a risk geometry tool — defining where a trade idea is wrong, where resolution is likely to occur, and whether the opportunity offers asymmetric payoff before capital is committed.
Primary Use Case 2: Identifying Statistically Stretched Price Conditions
The second core function of the Reversal Channel is identifying when price is operating far enough from its volatility-adjusted balance state to justify contrarian attention.
Sustained interaction with the outer displacement zones signals that price has entered a statistically inefficient regime. Continuation may still occur, but the marginal return on momentum decreases while reaction probability increases. The channel highlights these conditions in real time, without relying on fixed thresholds or static reference levels.
Rather than predicting reversals, this framework defines where continuation becomes fragile and where rebalancing pressure historically emerges - particularly when reinforced by higher-timeframe structure or liquidity context.
Central Basis Line (Market Equilibrium)
At the core of the Reversal Channel is a dynamically adaptive balance line derived from recent price behavior. This line represents the market’s evolving equilibrium - the point around which price naturally oscillates under normal conditions.
The balance calculation prioritizes recent market information while maintaining smooth continuity, allowing it to adjust efficiently as conditions change without overreacting to short-term noise. Rather than acting as a directional signal, this axis serves as a reference framework for measuring price displacement, volatility expansion, and rebalancing pressure.
Extended acceptance above the equilibrium suggests sustained bullish pressure, while prolonged activity below reflects bearish dominance. However, the Reversal Channel is intentionally agnostic to directional bias - its focus is on distance from balance, not trend prediction.
Volatility-Weighted Channel Construction
Surrounding the equilibrium line are three upper and three lower displacement bands, each derived from a real-time volatility normalization process. This process measures actual market expansion and contraction rather than relying on static price offsets, allowing the channel to adapt fluidly across assets, sessions, and regime shifts.
Each successive band represents an increasing degree of statistical displacement from equilibrium:
The first tier reflects mild volatility expansion
The second tier captures elevated deviation
The outer tier represents extreme statistical stretch
Because the channel geometry is volatility-responsive, it expands during high-energy conditions and contracts during quieter phases. This prevents structural distortion - avoiding channels that are either too restrictive in low volatility or meaningless during aggressive expansion.
To maintain visual coherence and structural continuity, displacement boundaries are processed through a secondary smoothing mechanism. This refinement preserves volatility information while ensuring the channel flows naturally with price action instead of reacting mechanically to isolated candles.
Zone Interpretation (Green, Yellow, Red)
The channel is visually segmented into three color-coded zones on both the upper and lower side of the basis. These zones are not signals - they are probability regions.
The green zone, closest to the basis, represents normal price fluctuation. Price entering this area does not imply exhaustion or reversal; it simply reflects routine movement around equilibrium.
The yellow zone indicates price is becoming extended. Momentum may still continue, but risk increases. This zone often corresponds with late-trend behavior, reduced reward-to-risk for continuation trades, and early contrarian interest.
The red zone represents extreme deviation relative to recent volatility. Price reaching this area suggests the market is operating far from equilibrium. While reversals are not guaranteed, this zone statistically favors slowing momentum, rejection, or reversion, especially when combined with structural or higher-timeframe confluence.
Importantly, these zones are symmetrical. Extreme conditions exist on both the upside and downside, allowing the channel to function in bullish, bearish, and ranging markets.
Reversal Sensitivity Logic
Rather than generating signals immediately when price enters a zone, the indicator uses a confirmation counter mechanism. This means price must remain beyond the first volatility boundary for a user-defined number of consecutive bars before a reversal signal is allowed.
This approach reduces false positives caused by single-candle spikes or transient wicks. By requiring persistence, the indicator attempts to confirm that price is genuinely operating in an extended state rather than momentarily probing it.
Sensitivity inputs allow traders to control how strict this confirmation process is. Lower sensitivity values produce faster signals with higher frequency but lower confirmation. Higher values demand more sustained extension, reducing signal count but increasing contextual reliability.
Buy and Sell Signal Logic
A buy signal is generated only after price has remained below the lower volatility boundary for the required number of consecutive bars and no active trade condition is present. Conceptually, this reflects downside exhaustion relative to volatility.
A sell signal follows the same logic on the upper side, triggering only after sustained price extension above the upper volatility boundary.
These signals are contrarian by design. They are not trend continuation entries. They assume that when price stretches too far, too quickly, the probability of reaction increases - particularly in markets that oscillate rather than trend cleanly.
Trade State Awareness and Exit Logic
The indicator internally tracks whether a trade condition is active. This prevents repeated signals from firing continuously while price remains extended.
Once a trade condition is active, the indicator monitors price relative to the basis line. The basis acts as a logical exit reference, representing a return toward equilibrium. When price crosses back through the basis in the direction of the trade, the condition is reset.
This design reinforces the indicator’s purpose: capturing mean reversion back toward balance, not trend continuation beyond it.
Risk Reference Levels (TP / SL Framework)
Optional take-profit and stop-loss reference levels are derived directly from channel structure rather than arbitrary values. Stop placement is anchored near the outermost volatility band, reflecting the point at which the statistical premise of the trade is invalidated.
Multiple take-profit projections are calculated using configurable risk-to-reward ratios. These levels are not recommendations; they exist to provide structure, visual planning, and consistency when evaluating potential trades.
The indicator does not manage trades. It provides spatial context so the trader can make informed decisions.
Practical Use & Context
The Equilibrium Reversal Channel performs best in markets that exhibit rotational behavior or frequent volatility expansion and contraction. In strong, one-directional trends, extreme zones may persist longer than expected. For this reason, the indicator should always be used alongside higher-timeframe structure, trend context, or directional filters.
Its purpose is not to outperform trend systems, but to define statistical stretch clearly and consistently across assets and timeframes.
Final Notes
Equilibrium Reversal Channel is designed as a contextual decision-support framework rather than a predictive system. It visualizes price behavior relative to dynamically adjusted equilibrium and volatility boundaries, offering insight into statistically stretched conditions and potential mean-reversion opportunities. Its outputs are guidance-oriented, not guarantees, and should be interpreted alongside broader market structure, higher-timeframe context, and sound risk management practices. Every visual element, zone, and signal is intended to enhance situational awareness, empower disciplined decision-making, and provide probabilistic insight into market behavior, not dictate outcomes. Traders are strongly encouraged to combine this framework with their own strategy execution and capital management protocols.
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.
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.
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.
Flux Momentum Oscillator[BullByte]Flux Momentum Oscillator is a professional-grade momentum analysis system built on an original methodology called Momentum Flux Bars (MFB). Unlike conventional oscillators that measure momentum over fixed time periods, this indicator constructs synthetic momentum bars based on actual price movement, creating a pure representation of directional pressure independent of time-based noise.
This is NOT a mashup or combination of existing indicators. The entire system is built from the ground up around a single cohesive concept: measuring momentum through price-triggered synthetic bars rather than time-triggered calculations.
CORE INNOVATION: MOMENTUM FLUX BARS (MFB)
Traditional momentum indicators calculate values at fixed time intervals, which means a slow, grinding move receives the same measurement weight as a fast, explosive move occurring over the same number of bars. This creates distortion in momentum readings.
Momentum Flux Bars solve this problem by forming only when price travels a volatility-adjusted distance. Each MFB represents genuine directional commitment from market participants.
Key Properties of Momentum Flux Bars:
- Form based on price movement, not time passage
- Automatically adjust their formation threshold based on current volatility
- Capture the velocity of price movement (how quickly each bar forms)
- Record volume participation during formation
- Create a noise-filtered view of true market momentum
The oscillator then analyzes the pattern, velocity, and characteristics of recent MFB formations to produce its readings.
WHY THIS APPROACH MATTERS FOR TRADERS
Time-Based Problem: A 14-period RSI on a choppy day produces the same calculation structure as on a trending day, even though market behavior differs completely. The indicator cannot distinguish between meaningful moves and noise.
Flux-Based Solution: When price chops sideways, fewer MFBs form because price fails to travel the required distance. When price trends strongly, MFBs form rapidly in sequence. The oscillator inherently adapts to actual market behavior.
Practical Benefits:
- Cleaner signals during trending conditions
- Automatic noise reduction during consolidation
- Earlier detection of momentum shifts through velocity analysis
- Reduced false signals in choppy markets
- No manual adjustment needed across different market conditions
COMPLETE FEATURE BREAKDOWN
FEATURE 1: AUTO-OPTIMIZATION ENGINE
The indicator includes an optional auto-optimization system that continuously evaluates different sensitivity parameters and selects the configuration producing the cleanest momentum measurement for current conditions.
How It Works:
- Tests multiple ATR multiplier values against recent price history
- Scores each configuration based on trend capture efficiency
- Automatically applies the optimal setting
- Re-evaluates periodically to adapt to changing conditions
Trader Benefit: Eliminates the guesswork of parameter tuning. The indicator finds its own optimal settings.
FEATURE 2: MARKET REGIME CLASSIFICATION
The system classifies current market conditions into four distinct regimes based on MFB formation patterns:
EXPLOSIVE: Rapid MFB formation with strong directional bias and high volume participation. Indicates powerful trending conditions with high momentum.
STEADY: Consistent MFB formation in a primary direction with normal velocity. Represents healthy, sustainable trends suitable for trend-following approaches.
CONSOLIDATING: Mixed direction MFB formation with decreasing velocity. Suggests range-bound conditions where breakout strategies may be appropriate.
DEAD: Minimal MFB formation activity. Indicates extremely low volatility or market indecision. Often precedes significant moves.
Trader Benefit: Instantly understand current market character and adjust strategy accordingly.
FEATURE 3: VELOCITY DIVERGENCE DETECTION
This advanced feature monitors the formation speed of Momentum Flux Bars and compares it against price direction.
Velocity Divergence Bearish: Price making higher highs but MFBs forming progressively slower. Suggests buying pressure is weakening despite higher prices.
Velocity Divergence Bullish: Price making lower lows but MFBs forming progressively slower. Suggests selling pressure is weakening despite lower prices.
Trader Benefit: Early warning system for potential reversals before they appear on price charts.
FEATURE 4: MOMENTUM EXHAUSTION DETECTION
The system identifies when a trending move may be running out of energy by analyzing the duration pattern of consecutive same-direction MFBs.
Exhaustion Pattern: When each successive MFB in a trend takes progressively longer to form, it indicates diminishing momentum even though direction remains unchanged.
States Displayed:
- BUILDING: Momentum is increasing or stable
- PEAK: Maximum momentum velocity reached
- EXHAUSTING: Progressive slowdown detected
Trader Benefit: Know when a trend is losing steam before price reverses.
FEATURE 5: HIGHER TIMEFRAME ALIGNMENT
The indicator checks whether higher timeframe MFB direction supports or conflicts with current timeframe momentum.
ALIGNED BULL: Both timeframes showing bullish MFB direction
ALIGNED BEAR: Both timeframes showing bearish MFB direction
DIVERGENT: Timeframes showing opposing directions
NEUTRAL: Higher timeframe direction unclear
Trader Benefit: Trade with higher timeframe support for higher probability setups.
FEATURE 6: CHOPPY MARKET DETECTION
A dedicated algorithm analyzes recent MFB patterns to determine if the market is in a choppy, directionless state.
Detection Factors:
- Frequency of direction changes in recent MFBs
- Lack of consecutive same-direction formations
- Weak directional bias in the MFB sequence
Trader Benefit: Avoid trend-following strategies when market conditions do not support them.
FEATURE 7: TREND STRENGTH MEASUREMENT
A percentage-based strength reading derived from MFB pattern analysis.
Flux Momentum Oscillator Chart Example
Chart Overview: Bitcoin 15-Minute Chart (Dec 21, 2025)
BTCUSD Market Snapshot
Price: $88,854.53 | Oscillator: 77.38 | Direction: BULLISH | Regime: EXPLOSIVE
1. EXPLOSIVE REGIME DETECTION (Current State - Right Side)
2. MOMENTUM EXHAUSTION ZONE (Mid-Chart)
3. CHOP/CONSOLIDATION PERIOD (Before Breakout)
4. VELOCITY DIVERGENCE (Around 21:00 the previous day)
5. BULLISH MOMENTUM SHIFT (Around 09:00)
6. FORMATION PROGRESS BAR (Bottom of Oscillator)
7. TREND STRENGTH INDICATOR (Bottom Bar)
8. EXTREME ZONES (Top and Bottom Boundaries)
Reading Interpretation:
- Above 70%: Strong trending conditions
- 40% to 70%: Moderate trend or developing move
- Below 40%: Weak trend or choppy conditions
Visual representation provided via the strength bar at the bottom of the indicator panel.
HOW TO READ THE OSCILLATOR PLOT
OSCILLATOR LINE (Main Line):
- Ranges from -100 to +100
- Above zero indicates bullish momentum
- Below zero indicates bearish momentum
- Color intensity reflects momentum direction and strength
- Glow effect (optional) enhances visibility of the main reading
SIGNAL LINE (Secondary Line):
- Smoothed version of the oscillator
- Crossovers indicate momentum shifts
- Purple/accent colored for visual distinction
HISTOGRAM BARS:
- Represent the difference between oscillator and signal line
- Increasing histogram in direction of oscillator confirms momentum
- Decreasing histogram warns of potential momentum shift
- Bright colors indicate increasing momentum
- Faded colors indicate decreasing momentum
ZONE INTERPRETATION:
+75 to +100 (Extreme Bullish Zone):
Very strong bullish momentum. Price has moved significantly and rapidly. Watch for exhaustion patterns. Not ideal for new long entries. Consider profit-taking on existing longs.
+50 to +75 (Strong Bullish Zone):
Healthy bullish momentum. Good conditions for trend-following long strategies. Pullbacks to signal line often provide continuation opportunities.
0 to +50 (Mild Bullish Zone):
Positive but moderate momentum. Trend may be developing or maturing. Watch for strength building or fading.
0 to -50 (Mild Bearish Zone):
Negative but moderate momentum. Downtrend may be developing or maturing. Watch for weakness building or recovering.
-50 to -75 (Strong Bearish Zone):
Healthy bearish momentum. Good conditions for trend-following short strategies. Rallies to signal line often provide continuation opportunities.
-75 to -100 (Extreme Bearish Zone):
Very strong bearish momentum. Price has moved significantly and rapidly to downside. Watch for exhaustion patterns. Not ideal for new short entries. Consider profit-taking on existing shorts.
HOW TO READ THE DASHBOARD
The dashboard provides comprehensive market analysis at a glance. Each row displays specific information:
OSCILLATOR ROW:
Shows current oscillator value with directional icon.
indicates reading above +50 (High)
indicates reading below -50 (Low)
DIRECTION ROW:
Current MFB direction.
BULLISH: Recent MFB formed upward
BEARISH: Recent MFB formed downward
NEUTRAL: No recent MFB or unclear
REGIME ROW:
Current market regime classification.
EXPLOSIVE / STEADY / CONSOLIDATING / DEAD
Color coded for quick recognition.
MARKET ROW:
Trend state assessment.
TRENDING UP: Confirmed uptrend in progress
TRENDING DN: Confirmed downtrend in progress
CHOPPY: No clear trend, high direction changes
MIXED: Partial trend characteristics
STRENGTH ROW:
Visual bar showing trend strength percentage.
More filled bars indicate stronger trend.
Color shifts from red (weak) to yellow (moderate) to green (strong).
VELOCITY ROW:
MFB formation speed status.
ACCELERATING: MFBs forming faster over time
STEADY: Consistent formation speed
DECELERATING: MFBs forming slower over time
MOMENTUM ROW:
Momentum development status.
BUILDING: Momentum increasing
PEAK: Maximum momentum reached
EXHAUSTING: Momentum declining despite same direction
HTF ALIGN ROW:
Higher timeframe alignment status.
BULL: HTF supports bullish bias
BEAR: HTF supports bearish bias
DIVERGENT: HTF opposes current direction
NEUTRAL: HTF unclear
FORMING ROW:
Progress toward next MFB formation.
Visual bar fills as price approaches formation threshold.
Helps anticipate when next MFB will complete.
Additional rows (when not in Compact Mode):
- Flux Size: Current MFB formation threshold value
- ATR Mult: Current optimized ATR multiplier (when auto-optimization enabled)
- Regime %: Numerical regime score
FORMATION PROGRESS INDICATOR
The horizontal line near the bottom of the indicator panel shows progress toward the next MFB formation.
Reading the Progress Line:
- Starts at baseline after each MFB completion
- Rises as price moves toward formation threshold
- Higher position indicates imminent MFB formation
- Color changes from neutral to accent to warning as formation approaches
Practical Use:
- Anticipate when new momentum data will become available
- Gauge intra-bar momentum development
- Understand why signals occur when they do
TREND STRENGTH BAR
The horizontal bar at the very bottom of the indicator displays trend strength visually.
Components:
- Gray background bar represents full scale (0-100%)
- Colored fill represents current strength reading
- Label displays exact percentage value
Color Interpretation:
- Green fill: Strong trend (above 70%)
- Yellow fill: Moderate trend (40-70%)
- Red fill: Weak trend (below 40%)
RECOMMENDED USAGE GUIDELINES
TIMEFRAME RECOMMENDATIONS:
Scalping (1m to 5m):
- Use lower Flux Period (8-10) for faster response
- Focus on oscillator crossovers and histogram momentum
- Regime should be STEADY or EXPLOSIVE for best results
Day Trading (5m to 30m):
- Default settings work well
- Use HTF alignment with 1H or 4H for confirmation
- Avoid trading when regime shows DEAD
Swing Trading (1H to 4H):
- Consider higher Flux Period (18-21) for smoother signals
- Regime classification becomes very valuable
- Velocity divergence provides excellent early warnings
Position Trading (Daily and above):
- Higher Flux Period (21-30) recommended
- Focus on regime changes and exhaustion patterns
- HTF alignment less relevant, oscillator zones more important
ASSET CLASS NOTES:
Forex: Works well on major pairs. Consider slightly higher sensitivity on less volatile pairs.
Crypto: Higher volatility may require lower sensitivity multiplier. Regime detection particularly useful.
Stocks: Excellent for liquid stocks. Less effective on illiquid names due to gappy price action.
Indices: Very effective. Clean price action produces clean MFB patterns.
Commodities: Works well, especially on gold and oil. Adjust sensitivity for different volatility profiles.
SETTINGS OVERVIEW
MODE AND THEME:
- Trading Mode: Simple (clean), Pro (full data), Hybrid (balanced)
- Visual Theme: Dark, Light, Neon, Stealth
- Compact Dashboard: Reduces dashboard rows
FLUX ENGINE:
- Flux Calculation Method: Choose optimization approach
- Enable Auto-Optimization: Let indicator find optimal parameters
- Flux Period: Base volatility calculation period
- Sensitivity Multiplier: Adjust MFB formation threshold
- Optimization Lookback: Bars analyzed for optimization
- Optimization Frequency: How often to re-optimize
OSCILLATOR:
- Oscillator Smoothing: Main line smoothness
- Signal Line Length: Signal line responsiveness
- Momentum Depth: MFBs analyzed for oscillator
- Histogram Scale: Visual scaling of histogram
MARKET STATE:
- Chop Detection Window: MFBs analyzed for chop detection
- Chop Threshold: Sensitivity of chop classification
- Min Trend Confirmation: Consecutive bars for trend confirmation
ADVANCED ANALYSIS:
- Enable Regime Classification: Market regime detection
- Enable Velocity Divergence: Formation speed analysis
- Enable Exhaustion Detection: Trend exhaustion warnings
- Enable HTF Alignment: Higher timeframe checking
- Higher Timeframe: Which timeframe to check
VISUALS:
- Glow Effect: Visual enhancement on oscillator
- Show Zone Fills: Background zone coloring
- Show Formation Progress: Progress indicator display
- Show Trend Strength Bar: Bottom strength bar
- Show Dashboard: Information panel display
- Dashboard Position: Corner placement
SIGNAL INTERPRETATION GUIDELINES
BULLISH MOMENTUM SHIFT:
Oscillator crosses above signal line while not in extreme bearish territory.
Suggests emerging bullish momentum.
Stronger when occurring near zero line or in mild bearish zone.
BEARISH MOMENTUM SHIFT:
Oscillator crosses below signal line while not in extreme bullish territory.
Suggests emerging bearish momentum.
Stronger when occurring near zero line or in mild bullish zone.
STRONG TREND CONDITIONS:
Oscillator beyond +/-55, in direction of signal line, trend strength above 55%, not choppy.
Indicates conditions favorable for trend-following approaches.
EXTREME ZONES:
Oscillator beyond +/-75.
Diamond markers appear.
Exercise caution with new positions in trend direction.
Watch for exhaustion and divergence signals.
ALERT SYSTEM
The indicator includes comprehensive alerts for automated monitoring:
Momentum Alerts:
- Bullish Momentum Shift
- Bearish Momentum Shift
- Strong Uptrend Initiated
- Strong Downtrend Initiated
Zone Alerts:
- Extreme Bullish Zone Reached
- Extreme Bearish Zone Reached
Market State Alerts:
- Choppy Conditions Detected
- Choppy Conditions Cleared
- Explosive Regime Entered
- Dead Regime Entered
Advanced Alerts:
- Velocity Divergence Detected
- Exhaustion Warning Triggered
- HTF Aligned Bullish
- HTF Aligned Bearish
- HTF Divergence Detected
MFB Alerts:
- Bullish MFB Formed
- Bearish MFB Formed
WHAT THIS INDICATOR IS NOT
This indicator is NOT:
- A buy/sell signal generator (it provides momentum context, not trade signals)
- A standalone trading system (combine with price action and other analysis)
- A guarantee of profitability (no indicator can guarantee results)
- A replacement for risk management (always use proper position sizing and stops)
- A mashup of existing indicators (this is original methodology)
ORIGINALITY STATEMENT
The Momentum Flux Bars concept was designed specifically to address limitations of time-based momentum calculations.
Every component of this system serves the central MFB methodology:
- The oscillator measures MFB directional weight
- The regime classifier interprets MFB patterns
- The velocity analysis tracks MFB formation speed
- The exhaustion detector monitors MFB duration progression
- The HTF alignment checks MFB direction across timeframes
This is a unified analytical framework, not a collection of separate indicators.
TECHNICAL NOTES
Non-Repainting Confirmation:
All signal generation uses confirmed bar data only. MFB formations occur on bar close. Historical signals will not change after they appear.
Performance Considerations:
Auto-optimization runs periodically, not every bar, to maintain performance.
MFB history is trimmed to prevent memory issues on extended sessions.
Reduce Max MFB History if experiencing performance issues.
Symbol and Timeframe Handling:
The indicator resets its MFB history when symbol or timeframe changes.
This ensures clean analysis without carryover from previous contexts.
DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice and should not be considered as such.
Trading involves substantial risk of loss. Past performance of any trading methodology or indicator does not guarantee future results. The author makes no representations regarding the profitability or suitability of this indicator for any particular purpose.
Users are solely responsible for their own trading decisions. Always use proper risk management, including appropriate position sizing and stop-loss orders. Never risk more than you can afford to lose.
Before using this or any indicator in live trading, thoroughly test it on historical data and in a demo environment. Understand its behavior across different market conditions.
The author is not liable for any losses incurred through the use of this indicator.
Developed by BullByte
Version 1.0.0
Universal Moving Average🙏🏻 UMA (Universal Moving Average) represents the most natural and prolly ‘the’ final general universal entity for calculating rolling typical value for any type of time-series. Simply via different weighting schemes applied together, it encodes:
Location of each datapoint in corresponding fields (price, time, volume)
Informational relevance of each datapoint via using windowing functions that are fundamental in nature and go beyond DSP inventions & approximations
Innovation in state space (in our case = volatility)
The real beauty of this development: being simply a weighting scheme that can be applied to anything: be it weighted median , weighted quantile regression, or weighted KDE , or a simple weighted mean (like in this script). As long as a method accepts weights, you can harness the power of this entity. It means that final algorithmic complexity will match your initial tool.
As a moving ‘average’ it beats ALMA, KAMA, MAMA, VIDYA and all others because it is a simple and general entity, and all it does is encoding ‘all’ available information. I think that post might anger a lot of people, because lotta things will be realized as legacy and many paywalls gonna be ignored, specially for the followers of DSP cult, the ones who yet don’t understand that aggregated tick data is not a signal omg, it’s a completely different type of time series where your methods simply don’t fit even closely. I am also sorry to inform y’all, that spectral analysis is much closer to state-space methods in spirit than to DSP. But in fact DSP is cool and I love it, well for actual signals xD
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Weights explained & how to use them: as I already said, the whole thing is based on combining different set of weights, and you can turn them on/off in script settings. Btw I've set em up defaults so you can use the thing on price data out of the box right away.
Price, Time, Volume weights: encode location of every datapoint in Price & TIme & Volume field
Howtouse: u have to disable one weight that corresponds to the field you apply UMA to. E.g if you apply UMA to prices, you turn off price weighting And turn on time and volume weighting. Or if you apply UMA to volume delta, you turn off volume weighting And turn on price and time weighting.
Higher prices are more important, this asymmetry is confirmed and even proved by the fact that prices can’t be negative (don’t even mention that incorrect rollover on CL contract in 2k20...).
Signal weights: encode actuality/importance/relevance of datapoints.
Howtouse: in DSP terms, it provides smoothing, but also compensates for the lag it introduces. This smoothness is useful if you use slope reversals for signal generation aka watching peaks and valleys in a moving average shape. It's also better to perturb smoothed outputs with this , this way you inject high freq content back, But in controlled way!
Signal = information.
The fundamental universal entity behind so-called “smoothing” in DSP has nothing to do with signals and goes eons beyond DSP. This is simply about measuring the relevance of data in time.
First, new datapoints need some time to be “embedded” into the timeline, you can think of it as time proof, kinda stuff needs time to be proved, accepted; while earliest datapoints lose relevance in time.
Second, along with the first notion, at the same time there’s the counter notion that simply weights new data more, acting as a counterweight from the down-weighting of the latest datapoints introduced by the first notion.
The first part can be represented as PDF of beta(2, 2) window (a set of weights in our case). It’s actually well known as the Welch window, that lives in between so called statistical and DSP worlds, emerges in multiple contexts. Mainstream DSP users tho mostly don’t use this one, they use primitive legacy windowing function, you can find all kinds on this wiki page.
Now the second part, where DSP adepts usually stop, is to introduce the second compensating windowing function. Instead they try to reduce window size, or introduce other kinds of volatility weights, do some tricks, but it ain’t provides obviously. The natural step here is to simply use the integral of the initial window; if the initial window is beta(2, 2) then what we simply need is CDF of beta(2, 2), in fact the vertically inverted shape of it aka survival function . That’s it bros. Simply as that.
When both of these are applied you have smth magical, your output becomes smooth and yet not lagging. No arbitrary windowing functions, tricks with data modification etc
Why beta(2, 2)? It naturally arises in many contexts, it’s based on one of the most fundamental functions in the universe: x^2. It has finite support. I can talk more bout it on request, but I am absolutely sure this is it.
^^ impulse response of the resulting weighs together (green) compared with uniform weights aka boxcar (red). Made with this script .
Weighing by state: encodes state-space innovation of each datapoint, basically magnitude of changes, strength of these changes, aka volatility.
Howtouse: this makes your moving average volatility aware in proper math ways. The influence of datapoints will be stronger when changes are stronger. This is weighting by innovations, or weighting by volatility by using squared returns.
Why squared returns? They encode state‑space innovations properly because the innovation of any continuous‑time semimartingale is about its quadratic variation, and quadratic variation is built from squared increments, not absolute increments.
Adaptive length is not the right way to introduce adaptivity by volatility xD. When you weight datapoints by squared returns you’re already dynamically varying ‘effective’ data size, you don’t need anything else.
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It’s all good, progress happens, that’s how the Universe works, that's how Universal Moving Average works. Time to evolve. I might update other scripts with this complete weighting scheme, either by my own desire or your request.
...
∞
Ultimate RSI [captainua]Ultimate RSI
Overview
This indicator combines multiple RSI calculations with volume analysis, divergence detection, and trend filtering to provide a comprehensive RSI-based trading system. The script calculates RSI using three different periods (6, 14, 24) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
The script includes optimized configuration presets for instant setup: Scalping, Day Trading, Swing Trading, and Position Trading. Simply select a preset to instantly configure all settings for your trading style, or use Custom mode for full manual control. All settings include automatic input validation to prevent configuration errors and ensure optimal performance.
Configuration Presets
The script includes preset configurations optimized for different trading styles, allowing you to instantly configure the indicator for your preferred trading approach. Simply select a preset from the "Configuration Preset" dropdown menu:
- Scalping: Optimized for fast-paced trading with shorter RSI periods (4, 7, 9) and minimal smoothing. Noise reduction is automatically disabled, and momentum confirmation is disabled to allow faster signal generation. Designed for quick entries and exits in volatile markets.
- Day Trading: Balanced configuration for intraday trading with moderate RSI periods (6, 9, 14) and light smoothing. Momentum confirmation is enabled for better signal quality. Ideal for day trading strategies requiring timely but accurate signals.
- Swing Trading: Configured for medium-term positions with standard RSI periods (14, 14, 21) and moderate smoothing. Provides smoother signals suitable for swing trading timeframes. All noise reduction features remain active.
- Position Trading: Optimized for longer-term trades with extended RSI periods (24, 21, 28) and heavier smoothing. Filters are configured for highest-quality signals. Best for position traders holding trades over multiple days or weeks.
- Custom: Full manual control over all settings. All input parameters are available for complete customization. This is the default mode and maintains full backward compatibility with previous versions.
When a preset is selected, it automatically adjusts RSI periods, smoothing lengths, and filter settings to match the trading style. The preset configurations ensure optimal settings are applied instantly, eliminating the need for manual configuration. All settings can still be manually overridden if needed, providing flexibility while maintaining ease of use.
Input Validation and Error Prevention
The script includes comprehensive input validation to prevent configuration errors:
- Cross-Input Validation: Smoothing lengths are automatically validated to ensure they are always less than their corresponding RSI period length. If you set a smoothing length greater than or equal to the RSI length, the script automatically adjusts it to (RSI Length - 1). This prevents logical errors and ensures valid configurations.
- Input Range Validation: All numeric inputs have minimum and maximum value constraints enforced by TradingView's input system, preventing invalid parameter values.
- Smart Defaults: Preset configurations use validated default values that are tested and optimized for each trading style. When switching between presets, all related settings are automatically updated to maintain consistency.
Core Calculations
Multi-Period RSI:
The script calculates RSI using the standard Wilder's RSI formula: RSI = 100 - (100 / (1 + RS)), where RS = Average Gain / Average Loss over the specified period. Three separate RSI calculations run simultaneously:
- RSI(6): Uses 6-period lookback for high sensitivity to recent price changes, useful for scalping and early signal detection
- RSI(14): Standard 14-period RSI for balanced analysis, the most commonly used RSI period
- RSI(24): Longer 24-period RSI for trend confirmation, provides smoother signals with less noise
Each RSI can be smoothed using EMA, SMA, RMA (Wilder's smoothing), WMA, or Zero-Lag smoothing. Zero-Lag smoothing uses the formula: ZL-RSI = RSI + (RSI - RSI ) to reduce lag while maintaining signal quality. You can apply individual smoothing lengths to each RSI period, or use global smoothing where all three RSIs share the same smoothing length.
Dynamic Overbought/Oversold Thresholds:
Static thresholds (default 70/30) are adjusted based on market volatility using ATR. The formula: Dynamic OB = Base OB + (ATR × Volatility Multiplier × Base Percentage / 100), Dynamic OS = Base OS - (ATR × Volatility Multiplier × Base Percentage / 100). This adapts to volatile markets where traditional 70/30 levels may be too restrictive. During high volatility, the dynamic thresholds widen, and during low volatility, they narrow. The thresholds are clamped between 0-100 to remain within RSI bounds. The ATR is cached for performance optimization, updating on confirmed bars and real-time bars.
Adaptive RSI Calculation:
An adaptive RSI adjusts the standard RSI(14) based on current volatility relative to average volatility. The calculation: Adaptive Factor = (Current ATR / SMA of ATR over 20 periods) × Volatility Multiplier. If SMA of ATR is zero (edge case), the adaptive factor defaults to 0. The adaptive RSI = Base RSI × (1 + Adaptive Factor), clamped to 0-100. This makes the indicator more responsive during high volatility periods when traditional RSI may lag. The adaptive RSI is used for signal generation (buy/sell signals) but is not plotted on the chart.
Overbought/Oversold Fill Zones:
The script provides visual fill zones between the RSI line and the threshold lines when RSI is in overbought or oversold territory. The fill logic uses inclusive conditions: fills are shown when RSI is currently in the zone OR was in the zone on the previous bar. This ensures complete coverage of entry and exit boundaries. A minimum gap of 0.1 RSI points is maintained between the RSI plot and threshold line to ensure reliable polygon rendering in TradingView. The fill uses invisible plots at the threshold levels and the RSI value, with the fill color applied between them. You can select which RSI (6, 14, or 24) to use for the fill zones.
Divergence Detection
Regular Divergence:
Bullish divergence: Price makes a lower low (current low < lowest low from previous lookback period) while RSI makes a higher low (current RSI > lowest RSI from previous lookback period). Bearish divergence: Price makes a higher high (current high > highest high from previous lookback period) while RSI makes a lower high (current RSI < highest RSI from previous lookback period). The script compares current price/RSI values to the lowest/highest values from the previous lookback period using ta.lowest() and ta.highest() functions with index to reference the previous period's extreme.
Pivot-Based Divergence:
An enhanced divergence detection method that uses actual pivot points instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and RSI. The pivot-based method uses a tolerance-based approach with configurable constants: 1% tolerance for price comparisons (priceTolerancePercent = 0.01) and 1.0 RSI point absolute tolerance for RSI comparisons (pivotTolerance = 1.0). Minimum divergence threshold is 1.0 RSI point (minDivergenceThreshold = 1.0). It looks for two recent pivot points and compares them: for bullish divergence, price makes a lower low (at least 1% lower) while RSI makes a higher low (at least 1.0 point higher). This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period. When enabled, pivot-based divergence replaces the traditional method for more accurate signal generation.
Strong Divergence:
Regular divergence is confirmed by an engulfing candle pattern. Bullish engulfing requires: (1) Previous candle is bearish (close < open ), (2) Current candle is bullish (close > open), (3) Current close > previous open, (4) Current open < previous close. Bearish engulfing is the inverse: previous bullish, current bearish, current close < previous open, current open > previous close. Strong divergence signals are marked with visual indicators (🐂 for bullish, 🐻 for bearish) and have separate alert conditions.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low (current low > lowest low from previous period) but RSI makes a lower low (current RSI < lowest RSI from previous period). Bearish hidden divergence: Price makes a lower high (current high < highest high from previous period) but RSI makes a higher high (current RSI > highest RSI from previous period). These patterns indicate the trend is likely to continue in the current direction.
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 0.1 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired.
Volume Climax is detected when volume exceeds: Volume SMA + (Volume StdDev × Multiplier). This indicates potential capitulation moments where extreme volume accompanies price movements. Volume Dry-Up is detected when volume falls below: Volume SMA - (Volume StdDev × Multiplier), indicating low participation periods that may produce unreliable signals. The volume SMA is cached for performance, updating on confirmed and real-time bars.
Multi-RSI Synergy
The script generates signals when multiple RSI periods align in overbought or oversold zones. This creates a confirmation system that reduces false signals. In "ALL" mode, all three RSIs (6, 14, 24) must be simultaneously above the overbought threshold OR all three must be below the oversold threshold. In "2-of-3" mode, any two of the three RSIs must align in the same direction. The script counts how many RSIs are in each zone: twoOfThreeOB = ((rsi6OB ? 1 : 0) + (rsi14OB ? 1 : 0) + (rsi24OB ? 1 : 0)) >= 2.
Synergy signals require: (1) Multi-RSI alignment (ALL or 2-of-3), (2) Volume confirmation, (3) Reset condition satisfied (enough bars since last synergy signal), (4) Additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance). Separate reset conditions track buy and sell signals independently. The reset condition uses ta.barssince() to count bars since the last trigger, returning true if the condition never occurred (allowing first signal) or if enough bars have passed.
Regression Forecasting
The script uses historical RSI values to forecast future RSI direction using four methods. The forecast horizon is configurable (1-50 bars ahead). Historical data is collected into an array, and regression coefficients are calculated based on the selected method.
Linear Regression: Calculates the least-squares fit line (y = mx + b) through the last N RSI values. The calculation: meanX = sumX / horizon, meanY = sumY / horizon, denominator = sumX² - horizon × meanX², m = (sumXY - horizon × meanX × meanY) / denominator, b = meanY - m × meanX. The forecast projects this line forward: forecast = b + m × i for i = 1 to horizon.
Polynomial Regression: Fits a quadratic curve (y = ax² + bx + c) to capture non-linear trends. The system of equations is solved using Cramer's rule with a 3×3 determinant. If the determinant is too small (< 0.0001), the system falls back to linear regression. Coefficients are calculated by solving: n×c + sumX×b + sumX²×a = sumY, sumX×c + sumX²×b + sumX³×a = sumXY, sumX²×c + sumX³×b + sumX⁴×a = sumX²Y. Note: Due to the O(n³) computational complexity of polynomial regression, the forecast horizon is automatically limited to a maximum of 20 bars when using polynomial regression to maintain optimal performance. If you set a horizon greater than 20 bars with polynomial regression, it will be automatically capped at 20 bars.
Exponential Smoothing: Applies exponential smoothing with adaptive alpha = 2/(horizon+1). The smoothing iterates from oldest to newest value: smoothed = alpha × series + (1 - alpha) × smoothed. Trend is calculated by comparing current smoothed value to an earlier smoothed value (at 60% of horizon): trend = (smoothed - earlierSmoothed) / (horizon - earlierIdx). Forecast: forecast = base + trend × i.
Moving Average: Uses the difference between short MA (horizon/2) and long MA (horizon) to estimate trend direction. Trend = (maShort - maLong) / (longLen - shortLen). Forecast: forecast = maShort + trend × i.
Confidence bands are calculated using RMSE (Root Mean Squared Error) of historical forecast accuracy. The error calculation compares historical values with forecast values: RMSE = sqrt(sumSquaredError / count). If insufficient data exists, it falls back to calculating standard deviation of recent RSI values. Confidence bands = forecast ± (RMSE × confidenceLevel). All forecast values and confidence bands are clamped to 0-100 to remain within RSI bounds. The regression functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, division-by-zero protection, and bounds checking for all array access operations to prevent runtime errors.
Strong Top/Bottom Detection
Strong buy signals require three conditions: (1) RSI is at its lowest point within the bottom period: rsiVal <= ta.lowest(rsiVal, bottomPeriod), (2) RSI is below the oversold threshold minus a buffer: rsiVal < (oversoldThreshold - rsiTopBottomBuffer), where rsiTopBottomBuffer = 2.0 RSI points, (3) The absolute difference between current RSI and the lowest RSI exceeds the threshold value: abs(rsiVal - ta.lowest(rsiVal, bottomPeriod)) > threshold. This indicates a bounce from extreme levels with sufficient distance from the absolute low.
Strong sell signals use the inverse logic: RSI at highest point, above overbought threshold + rsiTopBottomBuffer (2.0 RSI points), and difference from highest exceeds threshold. Both signals also require: volume confirmation, reset condition satisfied (separate reset for buy vs sell), and all additional filters passed (RSI50, Trend, ADX, Volume Dry-Up avoidance).
The reset condition uses separate logic for buy and sell: resetCondBuy checks bars since isRSIAtBottom, resetCondSell checks bars since isRSIAtTop. This ensures buy signals reset based on bottom conditions and sell signals reset based on top conditions, preventing incorrect signal blocking.
Filtering System
RSI(50) Filter: Only allows buy signals when RSI(14) > 50 (bullish momentum) and sell signals when RSI(14) < 50 (bearish momentum). This filter ensures you're buying in uptrends and selling in downtrends from a momentum perspective. The filter is optional and can be disabled. Recommended to enable for noise reduction.
Trend Filter: Uses a long-term EMA (default 200) to determine trend direction. Buy signals require price above EMA, sell signals require price below EMA. The EMA slope is calculated as: emaSlope = ema - ema . Optional EMA slope filter additionally requires the EMA to be rising (slope > 0) for buy signals or falling (slope < 0) for sell signals. This provides stronger trend confirmation by requiring both price position and EMA direction.
ADX Filter: Uses the Directional Movement Index (calculated via ta.dmi()) to measure trend strength. Signals only fire when ADX exceeds the threshold (default 20), indicating a strong trend rather than choppy markets. The ADX calculation uses separate length and smoothing parameters. This filter helps avoid signals during sideways/consolidation periods.
Volume Dry-Up Avoidance: Prevents signals during periods of extremely low volume relative to average. If volume dry-up is detected and the filter is enabled, signals are blocked. This helps avoid unreliable signals that occur during low participation periods.
RSI Momentum Confirmation: Requires RSI to be accelerating in the signal direction before confirming signals. For buy signals, RSI must be consistently rising (recovering from oversold) over the lookback period. For sell signals, RSI must be consistently falling (declining from overbought) over the lookback period. The momentum check verifies that all consecutive changes are in the correct direction AND the cumulative change is significant. This filter ensures signals only fire when RSI momentum aligns with the signal direction, reducing false signals from weak momentum.
Multi-Timeframe Confirmation: Requires higher timeframe RSI to align with the signal direction. For buy signals, current RSI must be below the higher timeframe RSI by at least the confirmation threshold. For sell signals, current RSI must be above the higher timeframe RSI by at least the confirmation threshold. This ensures signals align with the larger trend context, reducing counter-trend trades. The higher timeframe RSI is fetched using request.security() from the selected timeframe.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
RSI Centerline and Period Crossovers
RSI(50) Centerline Crossovers: Detects when the selected RSI source crosses above or below the 50 centerline. Bullish crossover: ta.crossover(rsiSource, 50), bearish crossover: ta.crossunder(rsiSource, 50). You can select which RSI (6, 14, or 24) to use for these crossovers. These signals indicate momentum shifts from bearish to bullish (above 50) or bullish to bearish (below 50).
RSI Period Crossovers: Detects when different RSI periods cross each other. Available pairs: RSI(6) × RSI(14), RSI(14) × RSI(24), or RSI(6) × RSI(24). Bullish crossover: fast RSI crosses above slow RSI (ta.crossover(rsiFast, rsiSlow)), indicating momentum acceleration. Bearish crossover: fast RSI crosses below slow RSI (ta.crossunder(rsiFast, rsiSlow)), indicating momentum deceleration. These crossovers can signal shifts in momentum before price moves.
StochRSI Calculation
Stochastic RSI applies the Stochastic oscillator formula to RSI values instead of price. The calculation: %K = ((RSI - Lowest RSI) / (Highest RSI - Lowest RSI)) × 100, where the lookback is the StochRSI length. If the range is zero, %K defaults to 50.0. %K is then smoothed using SMA with the %K smoothing length. %D is calculated as SMA of smoothed %K with the %D smoothing length. All values are clamped to 0-100. You can select which RSI (6, 14, or 24) to use as the source for StochRSI calculation.
RSI Bollinger Bands
Bollinger Bands are applied to RSI(14) instead of price. The calculation: Basis = SMA(RSI(14), BB Period), StdDev = stdev(RSI(14), BB Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around RSI that adapt to RSI volatility. When RSI touches or exceeds the bands, it indicates extreme conditions relative to recent RSI behavior.
Noise Reduction System
The script includes a comprehensive noise reduction system to filter false signals and improve accuracy. When enabled, signals must pass multiple quality checks:
Signal Strength Requirement: RSI must be at least X points away from the centerline (50). For buy signals, RSI must be at least X points below 50. For sell signals, RSI must be at least X points above 50. This ensures signals only trigger when RSI is significantly in oversold/overbought territory, not just near neutral.
Extreme Zone Requirement: RSI must be deep in the OB/OS zone. For buy signals, RSI must be at least X points below the oversold threshold. For sell signals, RSI must be at least X points above the overbought threshold. This ensures signals only fire in extreme conditions where reversals are more likely.
Consecutive Bar Confirmation: The signal condition must persist for N consecutive bars before triggering. This reduces false signals from single-bar spikes or noise. The confirmation checks that the signal condition was true for all bars in the lookback period.
Zone Persistence (Optional): Requires RSI to remain in the OB/OS zone for N consecutive bars, not just touch it. This ensures RSI is truly in an extreme state rather than just briefly touching the threshold. When enabled, this provides stricter filtering for higher-quality signals.
RSI Slope Confirmation (Optional): Requires RSI to be moving in the expected signal direction. For buy signals, RSI should be rising (recovering from oversold). For sell signals, RSI should be falling (declining from overbought). This ensures momentum is aligned with the signal direction. The slope is calculated by comparing current RSI to RSI N bars ago.
All noise reduction filters can be enabled/disabled independently, allowing you to customize the balance between signal frequency and accuracy. The default settings provide a good balance, but you can adjust them based on your trading style and market conditions.
Alert System
The script includes separate alert conditions for each signal type: buy/sell (adaptive RSI crossovers), divergence (regular, strong, hidden), crossovers (RSI50 centerline, RSI period crossovers), synergy signals, and trend breaks. Each alert type has its own alertcondition() declaration with a unique title and message.
An optional cooldown system prevents alert spam by requiring a minimum number of bars between alerts of the same type. The cooldown check: canAlert = na(lastAlertBar) OR (bar_index - lastAlertBar >= cooldownBars). If the last alert bar is na (first alert), it always allows the alert. Each alert type maintains its own lastAlertBar variable, so cooldowns are independent per signal type. The default cooldown is 10 bars, which is recommended for noise reduction.
Higher Timeframe RSI
The script can display RSI from a higher timeframe using request.security(). This allows you to see the RSI context from a larger timeframe (e.g., daily RSI on an hourly chart). The higher timeframe RSI uses RSI(14) calculation from the selected timeframe. This provides context for the current timeframe's RSI position relative to the larger trend.
RSI Pivot Trendlines
The script can draw trendlines connecting pivot highs and lows on RSI(6). This feature helps visualize RSI trends and identify potential trend breaks.
Pivot Detection: Pivots are detected using a configurable period. The script can require pivots to have minimum strength (RSI points difference from surrounding bars) to filter out weak pivots. Lower minPivotStrength values detect more pivots (more trendlines), while higher values detect only stronger pivots (fewer but more significant trendlines). Pivot confirmation is optional: when enabled, the script waits N bars to confirm the pivot remains the extreme, reducing repainting. Pivot confirmation functions (f_confirmPivotLow and f_confirmPivotHigh) are always called on every bar for consistency, as recommended by TradingView. When pivot bars are not available (na), safe default values are used, and the results are then used conditionally based on confirmation settings. This ensures consistent calculations and prevents calculation inconsistencies.
Trendline Drawing: Uptrend lines connect confirmed pivot lows (green), and downtrend lines connect confirmed pivot highs (red). By default, only the most recent trendline is shown (old trendlines are deleted when new pivots are confirmed). This keeps the chart clean and uncluttered. If "Keep Historical Trendlines" is enabled, the script preserves up to N historical trendlines (configurable via "Max Trendlines to Keep", default 5). When historical trendlines are enabled, old trendlines are saved to arrays instead of being deleted, allowing you to see multiple trendlines simultaneously for better trend analysis. The arrays are automatically limited to prevent memory accumulation.
Trend Break Detection: Signals are generated when RSI breaks above or below trendlines. Uptrend breaks (RSI crosses below uptrend line) generate buy signals. Downtrend breaks (RSI crosses above downtrend line) generate sell signals. Optional trend break confirmation requires the break to persist for N bars and optionally include volume confirmation. Trendline angle filtering can exclude flat/weak trendlines from generating signals (minTrendlineAngle > 0 filters out weak/flat trendlines).
How Components Work Together
The combination of multiple RSI periods provides confirmation across different timeframes, reducing false signals. RSI(6) catches early moves, RSI(14) provides balanced signals, and RSI(24) confirms longer-term trends. When all three align (synergy), it indicates strong consensus across timeframes.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Volume climax detection identifies potential reversal points, while volume dry-up avoidance prevents signals during unreliable low-volume periods.
Trend filters align signals with the overall market direction. The EMA filter ensures you're trading with the trend, and the EMA slope filter adds an additional layer by requiring the trend to be strengthening (rising EMA for buys, falling EMA for sells).
ADX filter ensures signals only fire during strong trends, avoiding choppy/consolidation periods. RSI(50) filter ensures momentum alignment with the trade direction.
Momentum confirmation requires RSI to be accelerating in the signal direction, ensuring signals only fire when momentum is aligned. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Divergence detection identifies potential reversals before they occur, providing early warning signals. Pivot-based divergence provides more accurate detection by using actual pivot points. Hidden divergence identifies continuation patterns, useful for trend-following strategies.
The noise reduction system combines multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to significantly reduce false signals. These filters work together to ensure only high-quality signals are generated.
The synergy system requires alignment across all RSI periods for highest-quality signals, significantly reducing false positives. Regression forecasting provides forward-looking context, helping anticipate potential RSI direction changes.
Pivot trendlines provide visual trend analysis and can generate signals when RSI breaks trendlines, indicating potential reversals or continuations.
Reset conditions prevent signal spam by requiring a minimum number of bars between signals. Separate reset conditions for buy and sell signals ensure proper signal management.
Usage Instructions
Configuration Presets (Recommended): The script includes optimized preset configurations for instant setup. Simply select your trading style from the "Configuration Preset" dropdown:
- Scalping Preset: RSI(4, 7, 9) with minimal smoothing. Noise reduction disabled, momentum confirmation disabled for fastest signals.
- Day Trading Preset: RSI(6, 9, 14) with light smoothing. Momentum confirmation enabled for better signal quality.
- Swing Trading Preset: RSI(14, 14, 21) with moderate smoothing. Balanced configuration for medium-term trades.
- Position Trading Preset: RSI(24, 21, 28) with heavier smoothing. Optimized for longer-term positions with all filters active.
- Custom Mode: Full manual control over all settings. Default behavior matches previous script versions.
Presets automatically configure RSI periods, smoothing lengths, and filter settings. You can still manually adjust any setting after selecting a preset if needed.
Getting Started: The easiest way to get started is to select a configuration preset matching your trading style (Scalping, Day Trading, Swing Trading, or Position Trading) from the "Configuration Preset" dropdown. This instantly configures all settings for optimal performance. Alternatively, use "Custom" mode for full manual control. The default configuration (Custom mode) shows RSI(6), RSI(14), and RSI(24) with their default smoothing. Overbought/oversold fill zones are enabled by default.
Customizing RSI Periods: Adjust the RSI lengths (6, 14, 24) based on your trading timeframe. Shorter periods (6) for scalping, standard (14) for day trading, longer (24) for swing trading. You can disable any RSI period you don't need.
Smoothing Selection: Choose smoothing method based on your needs. EMA provides balanced smoothing, RMA (Wilder's) is traditional, Zero-Lag reduces lag but may increase noise. Adjust smoothing lengths individually or use global smoothing for consistency. Note: Smoothing lengths are automatically validated to ensure they are always less than the corresponding RSI period length. If you set smoothing >= RSI length, it will be auto-adjusted to prevent invalid configurations.
Dynamic OB/OS: The dynamic thresholds automatically adapt to volatility. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets.
Volume Confirmation: Set volume threshold to 1.2 (default) for standard confirmation, higher for stricter filtering, or 0.1 to disable volume filtering entirely.
Multi-RSI Synergy: Use "ALL" mode for highest-quality signals (all 3 RSIs must align), or "2-of-3" mode for more frequent signals. Adjust the reset period to control signal frequency.
Filters: Enable filters gradually to find your preferred balance. Start with volume confirmation, then add trend filter, then ADX for strongest confirmation. RSI(50) filter is useful for momentum-based strategies and is recommended for noise reduction. Momentum confirmation and multi-timeframe confirmation add additional layers of accuracy but may reduce signal frequency.
Noise Reduction: The noise reduction system is enabled by default with balanced settings. Adjust minSignalStrength (default 3.0) to control how far RSI must be from centerline. Increase requireConsecutiveBars (default 1) to require signals to persist longer. Enable requireZonePersistence and requireRsiSlope for stricter filtering (higher quality but fewer signals). Start with defaults and adjust based on your needs.
Divergence: Enable divergence detection and adjust lookback periods. Strong divergence (with engulfing confirmation) provides higher-quality signals. Hidden divergence is useful for trend-following strategies. Enable pivot-based divergence for more accurate detection using actual pivot points instead of simple lowest/highest comparisons. Pivot-based divergence uses tolerance-based matching (1% for price, 1.0 RSI point for RSI) for better accuracy.
Forecasting: Enable regression forecasting to see potential RSI direction. Linear regression is simplest, polynomial captures curves, exponential smoothing adapts to trends. Adjust horizon based on your trading timeframe. Confidence bands show forecast uncertainty - wider bands indicate less reliable forecasts.
Pivot Trendlines: Enable pivot trendlines to visualize RSI trends and identify trend breaks. Adjust pivot detection period (default 5) - higher values detect fewer but stronger pivots. Enable pivot confirmation (default ON) to reduce repainting. Set minPivotStrength (default 1.0) to filter weak pivots - lower values detect more pivots (more trendlines), higher values detect only stronger pivots (fewer trendlines). Enable "Keep Historical Trendlines" to preserve multiple trendlines instead of just the most recent one. Set "Max Trendlines to Keep" (default 5) to control how many historical trendlines are preserved. Enable trend break confirmation for more reliable break signals. Adjust minTrendlineAngle (default 0.0) to filter flat trendlines - set to 0.1-0.5 to exclude weak trendlines.
Alerts: Set up alerts for your preferred signal types. Enable cooldown to prevent alert spam. Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- "sBottom" label (green): Strong bottom signal - RSI at extreme low with strong buy conditions
- "sTop" label (red): Strong top signal - RSI at extreme high with strong sell conditions
- "SyBuy" label (lime): Multi-RSI synergy buy signal - all RSIs aligned oversold
- "SySell" label (red): Multi-RSI synergy sell signal - all RSIs aligned overbought
- 🐂 emoji (green): Strong bullish divergence detected
- 🐻 emoji (red): Strong bearish divergence detected
- 🔆 emoji: Weak divergence signals (if enabled)
- "H-Bull" label: Hidden bullish divergence
- "H-Bear" label: Hidden bearish divergence
- ⚡ marker (top of pane): Volume climax detected (extreme volume) - positioned at top for visibility
- 💧 marker (top of pane): Volume dry-up detected (very low volume) - positioned at top for visibility
- ↑ triangle (lime): Uptrend break signal - RSI breaks below uptrend line
- ↓ triangle (red): Downtrend break signal - RSI breaks above downtrend line
- Triangle up (lime): RSI(50) bullish crossover
- Triangle down (red): RSI(50) bearish crossover
- Circle markers: RSI period crossovers
All markers are positioned at the RSI value where the signal occurs, using location.absolute for precise placement.
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. Multi-RSI Synergy signals (SyBuy/SySell) - Highest priority: Requires alignment across all RSI periods plus volume and filter confirmation. These are the most reliable signals.
2. Strong Top/Bottom signals (sTop/sBottom) - High priority: Indicates extreme RSI levels with strong bounce conditions. Requires volume confirmation and all filters.
3. Divergence signals - Medium-High priority: Strong divergence (with engulfing) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal.
4. Adaptive RSI crossovers - Medium priority: Buy when adaptive RSI crosses below dynamic oversold, sell when it crosses above dynamic overbought. These use volatility-adjusted RSI for more accurate signals.
5. RSI(50) centerline crossovers - Medium priority: Momentum shift signals. Less reliable alone but useful when combined with other confirmations.
6. RSI period crossovers - Lower priority: Early momentum shift indicators. Can provide early warning but may produce false signals in choppy markets.
Best practice: Wait for multiple confirmations. For example, a synergy signal combined with divergence and volume climax provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate RSI " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- ATR and Volume SMA are cached using var variables, updating only on confirmed and real-time bars to reduce redundant calculations
- Forecast line arrays are dynamically managed: lines are reused when possible, and unused lines are deleted to prevent memory accumulation
- Calculations use efficient Pine Script functions (ta.rsi, ta.ema, etc.) which are optimized by TradingView
- Array operations are minimized where possible, with direct calculations preferred
- Polynomial regression automatically caps the forecast horizon at 20 bars (POLYNOMIAL_MAX_HORIZON constant) to prevent performance degradation, as polynomial regression has O(n³) complexity. This safeguard ensures optimal performance even with large horizon settings
- Pivot detection includes edge case handling to ensure reliable calculations even on early bars with limited historical data. Regression forecasting functions include comprehensive safety checks: horizon validation (must not exceed array size), empty array handling, edge case handling for horizon=1 scenarios, and division-by-zero protection in all mathematical operations
The script should perform well on all timeframes. On very long historical data, forecast lines may accumulate if the horizon is large; consider reducing the forecast horizon if you experience performance issues. The polynomial regression performance safeguard automatically prevents performance issues for that specific regression type.
Known Limitations and Considerations
- Forecast lines are forward-looking projections and should not be used as definitive predictions. They provide context but are not guaranteed to be accurate.
- Dynamic OB/OS thresholds can exceed 100 or go below 0 in extreme volatility scenarios, but are clamped to 0-100 range. This means in very volatile markets, the dynamic thresholds may not widen as much as the raw calculation suggests.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe RSI uses request.security() which may have slight delays on some data feeds.
- Regression forecasting requires at least N bars of history (where N = forecast horizon) before it can generate forecasts. Early bars will not show forecast lines.
- StochRSI calculation requires the selected RSI source to have sufficient history. Very short RSI periods on new charts may produce less reliable StochRSI values initially.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading: Select the "Swing Trading" preset for instant optimal configuration. This preset uses RSI periods (14, 14, 21) with moderate smoothing. Alternatively, manually configure: Use RSI(24) with Multi-RSI Synergy in "ALL" mode, combined with trend filter (EMA 200) and ADX filter. This configuration provides high-probability setups with strong confirmation across multiple RSI periods.
Day Trading: Select the "Day Trading" preset for instant optimal configuration. This preset uses RSI periods (6, 9, 14) with light smoothing and momentum confirmation enabled. Alternatively, manually configure: Use RSI(6) with Zero-Lag smoothing for fast signal detection. Enable volume confirmation with threshold 1.2-1.5 for reliable entries. Combine with RSI(50) filter to ensure momentum alignment. Strong top/bottom signals work well for day trading reversals.
Trend Following: Enable trend filter (EMA) and EMA slope filter for strong trend confirmation. Use RSI(14) or RSI(24) with ADX filter to avoid choppy markets. Hidden divergence signals are useful for trend continuation entries.
Reversal Trading: Focus on divergence detection (regular and strong) combined with strong top/bottom signals. Enable volume climax detection to identify capitulation moments. Use RSI(6) for early reversal signals, confirmed by RSI(14) and RSI(24).
Forecasting and Planning: Enable regression forecasting with polynomial or exponential smoothing methods. Use forecast horizon of 10-20 bars for swing trading, 5-10 bars for day trading. Confidence bands help assess forecast reliability.
Multi-Timeframe Analysis: Enable higher timeframe RSI to see context from larger timeframes. For example, use daily RSI on hourly charts to understand the larger trend context. This helps avoid counter-trend trades.
Scalping: Select the "Scalping" preset for instant optimal configuration. This preset uses RSI periods (4, 7, 9) with minimal smoothing, disables noise reduction, and disables momentum confirmation for faster signals. Alternatively, manually configure: Use RSI(6) with minimal smoothing (or Zero-Lag) for ultra-fast signals. Disable most filters except volume confirmation. Use RSI period crossovers (RSI(6) × RSI(14)) for early momentum shifts. Set volume threshold to 1.0-1.2 for less restrictive filtering.
Position Trading: Select the "Position Trading" preset for instant optimal configuration. This preset uses extended RSI periods (24, 21, 28) with heavier smoothing, optimized for longer-term trades. Alternatively, manually configure: Use RSI(24) with all filters enabled (Trend, ADX, RSI(50), Volume Dry-Up avoidance). Multi-RSI Synergy in "ALL" mode provides highest-quality signals.
Practical Tips and Best Practices
Getting Started: The fastest way to get started is to select a configuration preset that matches your trading style. Simply choose "Scalping", "Day Trading", "Swing Trading", or "Position Trading" from the "Configuration Preset" dropdown to instantly configure all settings optimally. For advanced users, use "Custom" mode for full manual control. The default configuration (Custom mode) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style.
Reducing Repainting: All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality: Multi-RSI Synergy signals in "ALL" mode provide the highest-quality signals because they require alignment across all three RSI periods. These signals have lower frequency but higher reliability. For more frequent signals, use "2-of-3" mode. The noise reduction system further improves signal quality by requiring multiple confirmations (signal strength, extreme zone, consecutive bars, optional zone persistence and RSI slope). Adjust noise reduction settings to balance signal frequency vs. accuracy.
Filter Combinations: Start with volume confirmation, then add trend filter for trend alignment, then ADX filter for trend strength. Combining all three filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering: Set volume threshold to 0.1 or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
RSI Period Selection: RSI(6) is most sensitive and best for scalping or early signal detection. RSI(14) provides balanced signals suitable for day trading. RSI(24) is smoother and better for swing trading and trend confirmation. You can disable any RSI period you don't need to reduce visual clutter.
Smoothing Methods: EMA provides balanced smoothing with moderate lag. RMA (Wilder's smoothing) is traditional and works well for RSI. Zero-Lag reduces lag but may increase noise. WMA gives more weight to recent values. Choose based on your preference for responsiveness vs. smoothness.
Forecasting: Linear regression is simplest and works well for trending markets. Polynomial regression captures curves and works better in ranging markets. Exponential smoothing adapts to trends. Moving average method is most conservative. Use confidence bands to assess forecast reliability.
Divergence: Strong divergence (with engulfing confirmation) is more reliable than regular divergence. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Pivot-based divergence provides more accurate detection by using actual pivot points instead of simple lowest/highest comparisons. Adjust lookback periods based on your timeframe: shorter for day trading, longer for swing trading. Pivot divergence period (default 5) controls the sensitivity of pivot detection.
Dynamic Thresholds: Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the volatility multiplier and base percentage to fine-tune sensitivity. Higher values create wider thresholds in volatile markets.
Alert Management: Enable alert cooldown (default 10 bars, recommended) to prevent alert spam. Each alert type has its own cooldown, so you can set different cooldowns for different signal types. For example, use shorter cooldown for synergy signals (high quality) and longer cooldown for crossovers (more frequent). The cooldown system works independently for each signal type, preventing spam while allowing different signal types to fire when appropriate.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with caching for ATR and volume calculations. Forecast arrays are dynamically managed to prevent memory accumulation.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Reset conditions and alert cooldowns handle edge cases where conditions never occurred or values are NA.
- Reset Logic: Separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) ensure logical correctness.
- Input Parameters: 60+ customizable parameters organized into logical groups for easy configuration. Configuration presets available for instant setup (Scalping, Day Trading, Swing Trading, Position Trading, Custom).
- Noise Reduction: Comprehensive noise reduction system with multiple filters (signal strength, extreme zone, consecutive bars, zone persistence, RSI slope) to reduce false signals.
- Pivot-Based Divergence: Enhanced divergence detection using actual pivot points for improved accuracy.
- Momentum Confirmation: RSI momentum filter ensures signals only fire when RSI is accelerating in the signal direction.
- Multi-Timeframe Confirmation: Optional higher timeframe RSI alignment for trend confirmation.
- Enhanced Pivot Trendlines: Trendline drawing with strength requirements, confirmation, and trend break detection.
Technical Notes
- All RSI values are clamped to 0-100 range to ensure valid oscillator values
- ATR and Volume SMA are cached for performance, updating on confirmed and real-time bars
- Reset conditions handle edge cases: if a condition never occurred, reset returns true (allows first signal)
- Alert cooldown handles na values: if no previous alert, cooldown allows the alert
- Forecast arrays are dynamically sized based on horizon, with unused lines cleaned up
- Fill logic uses a minimum gap (0.1) to ensure reliable polygon rendering in TradingView
- All calculations include safety checks for division by zero and boundary conditions. Regression functions validate that horizon doesn't exceed array size, and all array access operations include bounds checking to prevent out-of-bounds errors
- The script uses separate reset conditions for buy signals (based on bottom conditions) and sell signals (based on top conditions) for logical correctness
- Background coloring uses a fallback system: dynamic color takes priority, then RSI(6) heatmap, then monotone if both are disabled
- Noise reduction filters are applied after accuracy filters, providing multiple layers of signal quality control
- Pivot trendlines use strength requirements to filter weak pivots, reducing noise in trendline drawing. Historical trendlines are stored in arrays and automatically limited to prevent memory accumulation when "Keep Historical Trendlines" is enabled
- Volume climax and dry-up markers are positioned at the top of the pane for better visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Input Validation: Automatic cross-input validation ensures smoothing lengths are always less than RSI period lengths, preventing configuration errors
- Configuration Presets: Four optimized preset configurations (Scalping, Day Trading, Swing Trading, Position Trading) for instant setup, plus Custom mode for full manual control
- Constants Management: Magic numbers extracted to documented constants for improved maintainability and easier tuning (pivot tolerance, divergence thresholds, fill gap, etc.)
- TradingView Function Consistency: All TradingView functions (ta.crossover, ta.crossunder, ta.atr, ta.lowest, ta.highest, ta.lowestbars, ta.highestbars, etc.) and custom functions that depend on historical results (f_consecutiveBarConfirmation, f_rsiSlopeConfirmation, f_rsiZonePersistence, f_applyAllFilters, f_rsiMomentum, f_forecast, f_confirmPivotLow, f_confirmPivotHigh) are called on every bar for consistency, as recommended by TradingView. Results are then used conditionally when needed. This ensures consistent calculations and prevents calculation inconsistencies.
CSI Cycle Swing MomentumAdaptive Ultra-Smooth Momentum (Cycle-Swing Indicator – CSI)
The Cycle-Swing Indicator (CSI) is an advanced, adaptive momentum oscillator designed to extract clean, reliable signals from market data by focusing on the swing of the dominant market cycle rather than raw momentum. By identifying and aligning with the current dominant cycle, the CSI produces a momentum curve that is exceptionally smooth, responsive, and context-aware.
Key Advantages
The CSI offers several improvements over traditional momentum-based indicators:
Ultra-smooth signal line without sacrificing responsiveness
Zero-lag behavior, enabling timely entries and exits
Pronounced turning-point precision, enhancing signal clarity
Adaptive to real market cycles, automatically adjusting to changing conditions
Reliable deviation and divergence detection, even in noisy environments
Why Standard Indicators Fall Short
Conventional oscillators often struggle in real-world market conditions:
Excessive noise leads to frequent false signals.
Added smoothing reduces noise but introduces significant lag, delaying actionable insights.
Fixed-length parameters make indicators highly sensitive to user settings—you never truly know the "right" length.
The CSI solves all these challenges through its adaptive cyclic algorithm, which automatically aligns itself with the market’s dominant cycle—no manual tuning required.
Practical Example
In the example chart, the CSI highlights clear turning points and deviations with far less noise than the standard momentum indicator, demonstrating its superior clarity and responsiveness.
How to Use
The CSI is fully adaptive and requires no parameters. Simply apply it to any symbol and timeframe—the indicator automatically detects the dominant cycle and produces an ultra-smooth, cycle-aligned momentum curve.
Included features:
Adaptive upper and lower bands identifying extreme conditions
Automatic divergence detection (toggle on/off)
Works on any timeframe and any asset
Adaptive length - no input parameter required
How to Read the Indicator
The CSI functions similarly to a traditional momentum oscillator but with enhanced adaptive context:
Look for divergences between price and the CSI signal line — powerful early warnings of weakening trends or impending shifts.
Note on Divergence Signals:
The divergence markers displayed on the chart are generated using embedded pivot-based detection. Because pivots must be confirmed by price action, divergence signals can only be plotted after a pivot forms. For real-time monitoring on the latest bar, users should watch for early-forming divergences as they develop, since confirmed pivot-based divergences will always appear with a slight delay. Script parameters are available for precise adjustment of pivot detection behaviour.
Info: Legacy vs. Pro Version
This is the actively maintained and continuously enhanced edition of my free, open-source indicator “Cycle Swing Momentum”. The Pro Version will remain fully up to date with the latest Pine Script standards and will receive ongoing refinements and feature improvements, all while preserving the core logic and intent of the original tool. The legacy version will continue to be available for code review and educational purposes, but it will no longer receive updates. The legacy open-source version is always available in the public TV indicator repository.
付費腳本
Hurst Flow • @Capital.comDescription
Hurst Flow is a regime-adaptive analytical tool that measures the continuous intention force behind market behavior.
It blends momentum and persistence analysis to quantify how strongly price movement aligns with trend continuation versus mean reversion.
The output is a normalized continuous force line:
Positive values indicate increasing long-side capital exposure — markets showing trend-persistence and momentum alignment.
Negative values reflect strengthening short-side capital exposure — environments favoring mean reversion or fading moves.
Internally, the indicator processes open-price rate-of-change dynamics through adaptive smoothing, persistence estimation, and standardized scaling, producing a stable and comparable signal across time frames and assets.
Use Hurst Flow as a market regime compass — to gauge bias, filter trades, or allocate exposure intensity dynamically.
Input descriptions
TF — Timeframe used to compute the signal. Higher TF = smoother, less whipsaw, but more lag.
ROC length (Open) — Lookback for Open-to-Open rate of change (base momentum horizon).
EMA length — Smoothing for ROC; increases stability at the cost of responsiveness.
Hurst window — Window for Hurst-style persistence estimate; governs regime sensitivity.
Standartizatoin window — Period for standardization; makes values comparable across assets/timeframes.
Scale factor (0..1) — Final gain applied to the standardized signal; use <1 to temper amplitude.
Presets/Backtest
Below is a list of presets that can be used to test indicators. The presets cover various asset classes and time frames, demonstrating versatility and high customizability. To do this, you can use a special strategy Target % Rebalancer Based Strategy on Intention Indicator . The entry signal for the strategy is the output signal of the indicator from the chart, which can be selected from a special drop-down list. A detailed description of the strategy can be found on a special page. The presets presented were created on instruments not included in the sample.
Below are the basic presets for the strategy. Other configuration functions can be used to fine-tune the strategy.
The strategy settings are the same for all of the presets listed. The time interval must be set for both the indicator and the chart.
Strategy fine tuning
Enable Hysteresis + Cooldown : Off
Risk & costs
Enable Max Daily Loss Halt : Off
Commission : 0.1%
============== Pre-Sets for Hurst Flow Indicator =============================
Preset Gold
Chart bar size: 3D
Indicator settings
TF : 3D
ROC : 10
EMA : 22
Hurst : 16
Standardization window length : 8
Scale : 1
====================================================
Preset Crude Oil:USOIL
Chart bar size: 1D
Indicator settings
TF : 1D
ROC : 70
EMA : 6
Hurst : 26
Standardization window length : 16
Scale : 1
Final Weight Cap : 1
====================================================
Preset S&P500 index
Chart bar size: 2D
Indicator settings
TF : 2D
ROC : 26
EMA : 8
Hurst : 33
Standardization window length : 16
Scale : 1
====================================================
Preset MSFT
Chart bar size: 2D
Indicator settings
TF : 2D
ROC : 16
EMA : 50
Hurst : 44
Standardization window length : 32
Scale : 1
QuantMotions - TPR Sentinel LineTPR Sentinel Line is an advanced adaptive Support/Resistance system that combines multi-layered trend analysis with a directional Time-Price Ratio (TPR) engine. The indicator dynamically builds a stabilized support or resistance line that adjusts to market volatility, trend strength, ATR expansion and contraction, and real-time slope changes.
This creates a high-precision, self-adjusting trend barrier that acts as support in uptrends, resistance in downtrends, and a neutral anchor during sideways phases.
Key Features
✔ Adaptive Trend Base
- A composite trend model blending:
- Kijun-style midpoint
- Donchian midline
- SMA & EMA smoothing
This creates a stable baseline that reacts smoothly but reliably to structural trend shifts.
✔ Directional TPR Calculation
The indicator measures slope across short, medium, and long trend windows, normalizes it with ATR, and determines:
- Trend direction
- Trend strength
- Momentum quality
✔ Dynamic Support/Resistance Line
Depending on trend direction:
- In uptrends → the line becomes adaptive support
- In downtrends → the line becomes adaptive resistance
- In neutral phases → the line centers around the smoothed trend base
A built-in lag factor prevents unrealistic jumps and keeps the level stable.
✔ Automatic Support/Resistance Zones
The indicator expands the main line into upper and lower zones based on ATR and trend strength, creating a dynamic volatility envelope around the trend structure.
✔ Signals & Alerts
- Support bounce
- Resistance rejection
- Breakouts above/below the dynamic line
These events help identify high-probability continuation or reversal moments.
✔ Information Panel
A real-time status table displays:
- Trend direction
- Trend strength
- Current S/R level
🎯 Ideal For
- Precision entries on pullbacks
- Detecting trend shifts earlier
- Identifying strong or weak trend phases
- Adaptive take-profit and stop-loss zones
- Filtering false breakouts
💡 Summary
TPR Sentinel Line gives you a living, breathing support/resistance structure that evolves with the market.
Instead of relying on static levels, you get a continuously adapting trend barrier that reflects real strength, real volatility, and real momentum.
A powerful tool for traders who want structure, clarity, and trend confidence.
