Multi indicators tableThis is a comprehensive trading tool that presents an overview of the market in a tabular format. It consists of five distinct categories of trading indicators : Volatility, Trend, Momentum, Reversal, and Volume. Each category includes a series of indicators that are widely used in the trading communauty.
The Volatility category includes the Average True Range (ATR) and Bollinger Bands indicators. The Trend category comprises the Average Directional Index (ADX), four Exponential Moving Averages (EMAs), Aroon, Parabolic SAR, and the Supertrend. The Momentum category includes the Stochastic Relative Strength Index (StochRSI), Money Flow Index (MFI), Williams %R, Relative Strength Index (RSI), and Commodity Channel Index (CCI). The Reversal category includes Parabolic SAR, Moving Average Convergence Divergence (MACD), and PP Supertrend. Finally, the Volume category includes the Volume Exponential Moving Average (EMA) indicator.
The indicators states are easily readable, the indicator case is colored based on his actual state. A bullish color (green by default), a bearish color (red by default),
a very bullish color (dark green by default), a very bearish color (dark red by default) and a neutral color (gray by default) displayed when the indicator doesn't give us a clear signal. Some indicators do not have a very bullish or very bearish state. Concerning volatility indicators, the bullish color indicates high volatility, the bearish color indicates low volatility, and the neutral color indicates normal volatility.
Most of the indicators displayed in the table are customizable, and traders can choose to hide the categories they don't want to use. The Indicator provides a quick and easily readable view on the market and allows traders to reduce the number of indicators on their chart making it lighter and more readable.
Pesquisar nos scripts por "momentum"
Natural Market River [CC]The Natural Market River was created by Jim Sloman (Ocean Theory pgs 59-62) and this is another momentum indicator that is extremely similar to the previous indicator I published, the Natural Market Mirror . This has almost identical buy and sell signals but different way to handle calculations so I'm going to leave it up to you which one you will prefer. Since this is almost identical, the buy and sell signals work in the same way with both strong signals and normal ones. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like to see me publish!
Natural Market Mirror [CC]The Natural Market Mirror was created by Jim Sloman (Ocean Theory pgs 49-57) and this is a continuation of my series from Jim Sloman's indicators. This indicator is also a momentum indicator and is very similar to the previous indicator I published, the Ocean Indicator and of course this indicator is built using ideas from the Ocean indicator. It may just be my opinion but I feel like this indicator provides better buy and sell signals in comparison. I built this using strong buy and sell indicators in addition to normal ones so darker colors are the strong signals and lighter colors are the normal signals. Buy when the line turns green and sell when it turns red.
Let me know what other indicators you would like me to publish!
MACD Trend Squeezer V2This is a combination of a slightly sped up MACD overlay on top of a modified Bar Trend Squeeze or highly modified Momentum indicator. Helps to see the trend/momentum matched with the characteristics of the MACD and it's historiography. Very user friendly for adjusting color, transparency, depth, lines, size, etc.
MACD is the dark gray line.
Its signal slower line is orange.
Its historiography is the area fill blues and reds
Trend Squeezer / momentum are the Bars in the background.
// Changes from original version \\
Visual depth mostly. Most of the items are adjustable in the settings.
Increased user friendly inputs to adjust colors, lines, data, etc.
(darken / lighten and change background bar colors, increase/decrease line strengths and colors, adjust field data inputs)
Compare - Oscillator vs BTC momentumI've made a simple indicator to compare the momentum of a trading pair against the momentum of BTC to the dollar. I use it to see how a pair is affected by BTC's momentum... I wouldnt use it to trade off alone, but it can be a useful tool alongside other indicators.
The time range can be adjusted, but I wouldnt reccomend setting it to anything over 12M, or under 1W.... as I'm not sure if it would work.
Any feedback is welcome!
This is an idea I had after looking at a wonderful visualisation made by BarclayJames, link below:
www.tradingview.com
Directional Trend Index (DTI) This technique was described by William Blau in his book "Momentum,
Direction and Divergence" (1995). His book focuses on three key aspects
of trading: momentum, direction and divergence. Blau, who was an electrical
engineer before becoming a trader, thoroughly examines the relationship between
price and momentum in step-by-step examples. From this grounding, he then looks
at the deficiencies in other oscillators and introduces some innovative techniques,
including a fresh twist on Stochastics. On directional issues, he analyzes the
intricacies of ADX and offers a unique approach to help define trending and
non-trending periods.
Directional Trend Index is an indicator similar to DM+ developed by Welles Wilder.
The DM+ (a part of Directional Movement System which includes both DM+ and
DM- indicators) indicator helps determine if a security is "trending." William
Blau added to it a zeroline, relative to which the indicator is deemed positive or
negative. A stable uptrend is a period when the DTI value is positive and rising, a
downtrend when it is negative and falling.
VCAI Stochastic RSI+VCAI Stoch RSI+ is a cleaned-up Stochastic RSI built with V-Core colours for faster, clearer momentum reads and more reliable OB/OS signals.
What it shows:
Purple %K line → bearish momentum strengthening
Yellow %D line → bullish momentum building and smoothing
Soft purple/yellow background bands → OB/OS exhaustion zones, not just raw 80/20 triggers
Midline at 50 → balance point where momentum shifts between bull- and bear-side control
Optional HTF mode → run Stoch RSI from any timeframe while viewing it on your current chart
How to read it:
Both lines rising out of OS → early bullish shift; pullbacks that hold direction favour continuation
Both lines falling from OB → early bearish shift; bounces into the purple OB zone can become fade setups
Lines stacked and moving together → strong, cleaner momentum
Lines crossing repeatedly → low-conviction, choppy conditions
OB/OS shading highlights exhaustion so you focus on moves with context, not every 80/20 tick
Why it’s different:
Classic Stoch RSI is hyper-sensitive and mostly noise.
VCAI Stoch RSI+ applies V-Core’s colour-driven regime logic, controlled OB/OS shading, and optional HTF smoothing so you see momentum structure instead of clutter — making it easier to judge when momentum is genuinely shifting and when it’s just another wiggle.
VCAI RSI Divergence +VCAI RSI Divergence+ is an RSI that shows trend, momentum, and divergence using V-CoresAI colour logic instead of a single white line.
What it shows:
Yellow RSI line → bullish momentum (RSI above its MA; buy-side pressure in control)
Purple RSI line → bearish momentum (RSI below its MA; sell-side pressure in control)
Thin blue line → fast RSI moving average that drives the colour flips
Dashed 70/30 lines → classic OB/OS zones
Background bands → soft purple in OB, soft yellow in OS to mark exhaustion areas
How to read it:
Yellow & rising → momentum shifting bullish; pullbacks into yellow OS band can be accumulation zones
Purple & falling → momentum shifting bearish; pushes into purple OB band can be distribution/sell zones
Hard colour flips (yellow ↔ purple) mark trend regime changes, not minor RSI noise
Divergence mode (on/off)
The divergence engine scans RSI and price pivot structure:
Bullish divergence (yellow) → price lower low + RSI higher low
Bearish divergence (purple) → price higher high + RSI lower high
Lines and tags appear only where a meaningful disagreement between price and RSI exists, giving early context for potential reversals or fade setups.
Together, the momentum colours + optional divergence mapping give a far clearer market read than a standard RSI, with zero clutter and no guesswork.
Luminous Glide Momentum Indicator [wjdtks255]This indicator, named "Customized SuperSmoother MA Oscillator," applies a smoothing filter to price data using a SuperSmoother technique to reduce noise and enhance signal clarity. It calculates two moving averages on the smoothed data—a fast and a slow—whose difference forms the oscillator line. A signal line is derived by smoothing the oscillator with another moving average. The histogram visualizes the divergence between the oscillator and signal lines, indicating momentum strength and direction.
How it works
SuperSmoother Filter: Reduces price noise to provide smoother and more reliable signals than raw data.
Fast and Slow Moving Averages: The fast MA reacts quicker to price changes, while the slow MA indicates longer trends.
Oscillator: The difference between the fast and slow MAs signals shifts in momentum.
Signal Line: A smoothed version of the oscillator used to generate crossovers.
Histogram: Displays the distance between the oscillator and signal line, with color changes indicating bullish or bearish momentum.
Trading Strategy
Buy Signal: When the oscillator crosses above the signal line, it suggests increasing upward momentum, signaling a potential buy opportunity.
Sell Signal: When the oscillator crosses below the signal line, it suggests increasing downward momentum, signaling a potential sell opportunity.
Histogram Size and Color: Larger green bars indicate stronger bullish momentum; larger red bars indicate stronger bearish momentum.
Usage Tips
Combine this oscillator with other indicators or price action analysis to confirm trading signals.
Adjust smoothing and moving average lengths according to your trading timeframe and the asset volatility.
Use proper risk management to filter out potential false signals common in oscillators.
[AS] MACD-v & Hist [Alex Spiroglou | S.M.A.R.T. TRADER SYSTEMS] MACD-v & MACD-v Histogram
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Volatility Normalised Momentum 📈
Twice Awarded Indicator 🏆
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✅ 1. INTRODUCTION TO THE MACD-v ✅
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I created the MACD-v in 2015,
as a way to deal with the limitations
of well known indicators like the Stochastic, RSI, MACD.
I decided to publicly share a very small part of my research
in the form of a research paper I wrote in 2022,
titled "MACD-v: Volatility Normalised Momentum".
That paper was awarded twice:
1. The "Charles H. Dow" Award (2022),
for outstanding research in Technical Analysis,
by the Chartered Market Technicians Association (CMTA)
2. The "Founders" Award (2022),
for advances in Active Investment Management,
by the National Association of Active Investment Managers (NAAIM)
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❌ 2. WHY CREATE THE MACD-v ?
THE LIMITATIONS OF CONVENTIONAL MOMENTUM INDICATORS
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Technical Analysis indicators focused on momentum,
come in two general categories,
each with its own set of limitations:
(i) Range Bound Oscillators (RSI, Stochastics, etc)
These usually have a scaling of 0-100,
and thus have the advantage of having normalised readings,
that are comparable across time and securities.
However they have the following limitations (among others):
1. Skewing effect of steep trends
2. Indicator values do not adjust with and reflect true momentum
(indicator values are capped to 100)
(ii) Unbound Oscillators (MACD, RoC, etc)
These are boundless indicators,
and can expand with the market,
without being limited by a 0-100 scaling,
and thus have the advantage of really measuring momentum.
They have the main following limitations (among others):
1. Subjectivity of overbought / oversold levels
2. Not comparable across time
3. Not comparable across securities
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💡 3. THE SOLUTION TO SOLVE THESE LIMITATIONS
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In order to deal with these limitations,
I decided to create an indicator,
that would be the "Best of two worlds".
A unique & hybrid indicator,
that would have objective normalised readings
(similar to Range Bound Oscillators - RSI)
but would also be able to have no upper/lower boundaries
(similar to Unbound Oscillators - MACD).
This would be achieved by "normalising" a boundless oscillator (MACD)
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⛔ 4. DEEP DIVE INTO THE 5 LIMITATIONS OF THE MACD
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A Bloomberg study found that the MACD
is the most popular indicator after the RSI,
but the MACD has 5 BIG limitations.
Limitation 1: MACD values are not comparable across Time
The raw MACD values shift
as the underlying security's absolute value changes across time,
making historical comparisons obsolete
e.g S&P 500 maximum MACD was 1.56 in 1957-1971,
but reached 86.31 in 2019-2021 - not indicating 55x stronger momentum,
but simply different price levels.
Limitation 2: MACD values are not comparable across Assets
Traditional MACD cannot compare momentum between different assets.
S&P 500 MACD of 65 versus EUR/USD MACD of -0.5
reflects absolute price differences, not momentum differences
Limitation 3: MACD values cannot be Systematically Classified
Due to limitations #1 & #2, it is not possible to create
a momentum level classification scale
where one can define "fast", "slow", "overbought", "oversold" momentum
making systematic analysis impossible
Limitation 4: MACD Signal Line gives false crossovers in low-momentum ranges
In range-bound, low momentum environments,
most of the MACD signal line crossovers are false (noise)
Since there is no objective momentum classification system (limitation #3),
it is not possible to filter these signals out,
by avoiding them when momentum is low
Limitation 5: MACD Signal Line gives late crossovers in high momentum regimes.
Signal lag in strong trends not good at timing the turning point
— In high-momentum moves, MACD crossovers may come late.
Since there is no objective momentum classification system (limitation #3),
it is not possible to filter these signals out,
by avoiding them when momentum is high
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🏆 5. MACD-v : THE SOLUTION TO THE LIMITATIONS OF THE MACD , RSI, etc
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MACD-v is a volatility normalised momentum indicator.
It remedies these 5 limitations of the classic MACD,
while creating a tool with unique properties.
Formula: × 100
MACD-V enhances the classic MACD by normalizing for volatility,
transforming price-dependent readings into standardized momentum values.
This resolves key limitations of traditional MACD and adds significant analytical power.
Core Advantages of MACD-V
Advantage 1: Time-Based Stability
MACD-V values are consistent and comparable over time.
A reading of 100 has the same meaning today as it did in the past
(unlike traditional MACD which is influenced by changes in price and volatility over time)
Advantage 2: Cross-Market Comparability
MACD-V provides universal scaling.
Readings (e.g., ±50) apply consistently across all asset classes—stocks,
bonds, commodities, or currencies,
allowing traders to compare momentum across markets reliably.
Advantage 3: Objective Momentum Classification
MACD-V includes a defined 5-range momentum lifecycle
with standardized thresholds (e.g., -150 to +150).
This offers an objective framework for analyzing market conditions
and supports integration with broader models.
Advantage 4: False Signal Reduction in Low-Momentum Regimes
MACD-V introduces a "neutral zone" (typically -50 to +50)
to filter out these low-probability signals.
Advantage 5: Improved Signal Timing in High-Momentum Regimes
MACD-V identifies extremely strong trends,
allowing for more precise entry and exit points.
Advantage 6: Trend-Adaptive Scaling
Unlike bounded oscillators like RSI or Stochastic,
MACD-V dynamically expands with trend strength,
providing clearer momentum insights without artificial limits.
Advantage 7: Enhanced Divergence Detection
MACD-V offers more reliable divergence signals
by avoiding distortion at extreme levels,
a common flaw in bounded indicators (RSI, etc)
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⚒️ 5. HOW TO USE THE MACD-v: 7 CORE PATTERNS
HOW TO USE THE MACD-v Histogram: 2 CORE PATTERNS
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>>>>>> BASIC USE (RANGE RULES) <<<<<<
The MACD-v has 7 Core Patterns (Ranges) :
1. Risk Range (Overbought)
Condition: MACD-V > Signal Line and MACD-V > +150
Interpretation: Extremely strong bullish momentum—potential exhaustion or reversal zone.
2. Retracing
Condition: MACD-V < Signal Line and MACD-V > -50
Interpretation: Mild pullback within a bullish trend.
3. Rundown
Condition: MACD-V < Signal Line and -50 > MACD-V > -150
Interpretation: Momentum is weakening—bearish pressure building.
4. Risk Range (Oversold)
Condition: MACD-V < Signal Line and MACD-V < -150
Interpretation: Extreme bearish momentum—potential for reversal or capitulation.
5. Rebounding
Condition: MACD-V > Signal Line and MACD-V > -150
Interpretation: Bullish recovery from oversold or weak conditions.
6. Rallying
Condition: MACD-V > Signal Line and MACD-V > +50
Interpretation: Strengthening bullish trend—momentum accelerating.
7. Ranging (Neutral Zone)
Condition: MACD-V remains between -50 and +50 for 20+ bars
Interpretation: Sideways market—low conviction and momentum.
The MACD-v Histogram has 2 Core Patterns (Ranges) :
1. Risk (Overbought)
Condition: Histogram > +40
Interpretation: Short-term bullish momentum is stretched—possible overextension or reversal risk.
2. Risk (Oversold)
Condition: Histogram < -40
Interpretation: Short-term bearish momentum is stretched—potential for rebound or reversal.
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📈 6. ADVANCED PATTERNS WITH MACD-v
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Thanks to its volatility normalization,
the MACD-V framework enables the development
of a wide range of advanced pattern recognition setups,
trading signals, and strategic models.
These patterns go beyond basic crossovers,
offering deeper insight into momentum structure,
regime shifts, and high-probability trade setups.
These are not part of this script
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⚙️ 7. FUNCTIONALITY - HOW TO ADD THE INDICATORS TO YOUR CHART
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The script allows you to see :
1. MACD-v
The indicator with the ranges (150,50,0,-50,-150)
and colour coded according to its 7 basic patterns
2. MACD-v Histogram
The indicator The indicator with the ranges (40,0,-40)
and colour coded according to its 2 basic ranges / patterns
3. MACD-v Heatmap
You can see the MACD-v in a Multiple Timeframe basis,
using a colour-coded Heatmap
Note that lowest timeframe in the heatmap must be the one on the chart
i.e. if you see the daily chart, then the Heatmap will be Daily, Weekly, Monthly
4. MACD-v Dashboard
You can see the MACD-v for 7 markets,
in a multiple timeframe basis
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🤝 CONTRIBUTIONS 🤝
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I would like to thank the following people:
1. Mike Christensen for coding the indicator
@TradersPostInc, @Mik3Christ3ns3n,
2. @Indicator-Jones For allowing me to use his Scanner
3. @Daveatt For allowing me to use his heatmap
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⚠️ LEGAL - Usage and Attribution Notice ⚠️
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Use of this Script is permitted
for personal or non-commercial purposes,
including implementation by coders and TradingView users.
However, any form of paid redistribution,
resale, or commercial exploitation is strictly prohibited.
Proper attribution to the original author is expected and appreciated,
in order to acknowledge the source
and maintain the integrity of the original work.
Failure to comply with these terms,
or to take corrective action within 48 hours of notification,
will result in a formal report to TradingView’s moderation team,
and will actively pursue account suspension and removal of the infringing script(s).
Continued violations may result in further legal action, as deemed necessary.
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⚠️ DISCLAIMER ⚠️
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This indicator is For Educational Purposes Only (F.E.P.O.).
I am just Teaching by Example (T.B.E.)
It does not constitute investment advice.
There are no guarantees in trading - except one.
You will have losses in trading.
I can guarantee you that with 100% certainty.
The author is not responsible for any financial losses
or trading decisions made based on this indicator. 🙏
Always perform your own analysis and use proper risk management. 🛡️
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Hello Crypto! Modern Combo Snapshot
Unified long/short analyzer blending EMA structure, SuperTrend, WaveTrend, QQE, and volume pressure.
Background shading flags “watch” and “ready” states; optional long/short modules let you focus on one side.
Alerts fire when every checklist item aligns, while the side-panel table summarizes trend, momentum, liquidity, and overall score in real time.
Indicator → Trend Analysis
Indicator → Momentum Oscillators
Indicator → Volume Indicators
Tags:
cryptocurrency, bitcoin, altcoins, trend-following, momentum, volume, ema, supertrend, intraday, swing-trading, alerts, checklist, trading-strategy, risk-management
Enhanced Holt-Winters RSI [BOSWaves]Enhanced Holt-Winters RSI – Next-Level Momentum Smoothing & Signal Precision
Overview
The Enhanced Holt-Winters RSI transforms the classic Relative Strength Index into a robust, lag-minimized momentum oscillator through Holt-Winters triple exponential smoothing. By modeling the level, trend, and cyclical behavior of the RSI series, this indicator delivers smoother, more responsive signals that highlight overbought/oversold conditions, momentum shifts, and high-conviction trading setups without cluttering the chart with noise.
Unlike traditional RSI, which reacts to historical data and produces frequent whipsaws, the Enhanced Holt-Winters RSI filters transient price fluctuations, enabling traders to detect emerging momentum and potential reversal zones earlier.
Theoretical Foundation
The traditional RSI measures relative strength by comparing average gains and losses, but suffers from:
Lag in trend recognition : Signals often arrive after momentum has shifted.
Noise sensitivity : High-frequency price movements generate unreliable crossovers.
Limited insight into structural market shifts : Standard RSI cannot contextualize cyclical or momentum patterns.
The Enhanced Holt-Winters RSI addresses these limitations by applying triple exponential smoothing directly to the RSI series. This decomposes the series into:
Level (Lₜ) : Represents the smoothed central tendency of RSI.
Trend (Tₜ) : Captures rate-of-change in smoothed momentum.
Seasonal Component (Sₜ) : Models short-term cyclical deviations in momentum.
By incorporating these elements, the oscillator produces smoothed RSI values that react faster to emerging trends while suppressing erratic noise. Its internal forecast is mathematical, influencing the smoothed RSI output and signals, rather than being directly plotted.
How It Works
The Enhanced Holt-Winters RSI builds its signal framework through several layers:
1. Base RSI Calculation
Computes standard RSI over the selected period as the primary momentum input.
2. Triple Exponential Smoothing (Holt-Winters)
The RSI is smoothed recursively to extract underlying momentum structure:
Level, trend, and seasonal components are combined to produce a smoothed RSI.
This internal smoothing reduces lag and enhances signal reliability.
3. Momentum Analysis
Short-term momentum shifts are tracked via a moving average of the smoothed RSI, highlighting acceleration or deceleration in directional strength.
4. Volume Confirmation (Optional)
Buy/sell signals can be filtered through a configurable volume threshold, ensuring only high-conviction moves trigger alerts.
5. Visual Output
Colored Candles : Represent overbought (red), oversold (green), or neutral (yellow) conditions.
Oscillator Panel : Plots the smoothed RSI with dynamic color coding for immediate trend context.
Signals : Triangular markers indicate bullish or bearish setups, with stronger signals flagged in extreme zones.
Interpretation
The Enhanced Holt-Winters RSI provides a multi-dimensional perspective on price action:
Trend Strength : Smoothed RSI slope and color coding reflect the direction and momentum intensity.
Momentum Shifts : Rapid changes in the smoothed RSI indicate emerging strength or weakness.
Overbought/Oversold Zones : Highlight areas where price is stretched relative to recent momentum.
High-Conviction Signals : Combined with volume filtering, markers indicate optimal entries/exits.
Cycle Awareness : Smoothing reveals structural patterns, helping traders avoid reacting to noise.
By combining these elements, traders gain early insight into market structure and momentum without relying on raw, lag-prone RSI data.
Strategy Integration
The Enhanced Holt-Winters RSI can be applied across trading styles:
Trend Following
Enter when RSI is aligned with price momentum and color-coded signals confirm trend direction.
Strong slope in the smoothed RSI signals trend continuation.
Reversal Trading
Look for RSI extremes with momentum shifts and strong signal markers.
Compression in oscillator values often precedes reversal setups.
Breakout Detection
Oscillator flattening in neutral zones followed by directional expansion indicates potential breakout conditions.
Multi-Timeframe Confluence
Higher timeframes provide directional bias; lower timeframes refine entry timing using smoothed RSI dynamics.
Technical Implementation Details
Input Source : Close, open, high, low, or price.
Smoothing : Holt-Winters triple exponential smoothing applied to RSI.
Parameters :
Level (α) : Controls smoothing of RSI.
Trend (β) : Adjusts responsiveness to momentum changes.
Seasonal Length : Defines cycles for short-term adjustments.
Delta Smoothing : Reduces choppiness in smoothed RSI difference.
Outputs :
Smoothed RSI
Colored candles and oscillator panel
Buy/Sell signal markers (with optional strength filtering)
Volume Filtering : Optional threshold to confirm signals.
Optimal Application Parameters
Asset-Specific Guidance:
Forex : Use moderate smoothing (α, β) to capture medium-term momentum swings while filtering minor price noise. Works best when combined with volume or volatility filters.
Equities : Balance responsiveness and smoothness to identify sustained sector momentum or rotational shifts; ideal for capturing clean directional transitions.
Cryptocurrency : Increase smoothing parameters slightly to stabilize RSI during extreme volatility; optional volume confirmation can help filter false signals.
Futures/Indices : Lower smoothing sensitivity emphasizes macro momentum and structural trend durability over short-term fluctuations.
Timeframe Optimization:
Scalping (1-5m) : Use higher sensitivity (lower smoothing factors) to react quickly to micro-momentum reversals.
Intraday (15m-1h) : Balance smoothing and responsiveness for detecting short-term acceleration and exhaustion zones.
Swing (4h-Daily) : Apply moderate smoothing to reveal underlying directional persistence and cyclical reversals.
Position (Daily-Weekly) : Use stronger smoothing to isolate dominant momentum trends and filter temporary pullbacks.
Integration Guidelines
Combine with trend filters (EMAs, SuperSmoother MA, ATR-based tools) for confirmation.
Use volume and signal strength markers to filter low-conviction trades.
Slope, color, and signal alignment can guide entry, stop placement, and scaling.
Disclaimer
The Enhanced Holt-Winters RSI is a technical analysis tool, not a guaranteed profit system. Effectiveness depends on proper settings, market structure, and disciplined risk management. Always backtest before live trading.
Pro Momentum Table + Trade Alerts📊 Indicator Name: Pro Momentum Table – ADX + DI + ATR + Astro Timing
🧠 Concept:
This indicator is designed for professional scalpers and intraday traders who want to capture only strong momentum waves — not noise. It combines trend strength, volatility, directional movement, momentum oscillation, vega divergence, and astrological timing into a single compact table on your chart.
⚙️ Components Explained:
Metric Description
ADX (Average Directional Index) Measures the strength of the trend. Values above 20 indicate that a meaningful move is starting.
+DI / -DI (Directional Indicators) Show whether buyers (+DI) or sellers (-DI) are dominating. Increasing +DI with ADX rising = bullish momentum. Increasing -DI with ADX rising = bearish momentum.
ATR (Average True Range) Shows volatility and expected range. Used for setting realistic stop-loss and multi-level targets (1×, 1.5×, 2×, 2.5× ATR).
Price Displays the current price level for quick reference.
CMO (Chande Momentum Oscillator) Measures short-term momentum direction and strength. Helps identify overbought/oversold conditions in trend continuation.
Vega Divergence Shows a synthetic reading of volatility pressure — "Bullish" when volatility expansion supports upward moves, "Bearish" for downward pressure, and "Neutral" otherwise.
Astro Remark Suggests ideal time windows based on planetary cycles for scalping entries. “Bullish Window” often aligns with high-probability long trades; “Bearish Window” favors shorts.
Trade Signal The core momentum condition: “Bullish Momentum” if ADX > 20 and +DI rising, “Bearish Momentum” if ADX > 20 and -DI rising, else “No Clear Momentum.”
📈 How to Use:
Wait for ADX > 20 – This confirms that the market is entering a strong momentum phase.
Check DI direction:
✅ +DI rising: Buyers gaining strength → look for long setups.
✅ -DI rising: Sellers gaining strength → look for short setups.
Use ATR to plan exits:
🎯 TP1 = Entry ± 1 × ATR
🎯 TP2 = Entry ± 1.5 × ATR
🎯 TP3 = Entry ± 2 × ATR
🎯 TP4 = Entry ± 2.5 × ATR
CMO & Vega Divergence: Confirm momentum direction and volatility expansion before committing.
Astro Remark: Align your scalping activity with the planetary support window for higher probability trades.
🪙 Pro Tips for Scalpers:
Only trade when ADX > 20 and DI is consistently rising. Ignore signals in choppy or sideways phases.
Avoid trades if Vega is neutral and CMO is flat – these usually indicate fake breakouts.
If targets aren’t hit within expected ATR-based time, treat the move as false and exit early.
Combine with 9 EMA and 20 EMA (hidden) for wave structure confirmation without cluttering the chart.
💡 Summary:
This indicator acts as a real-time trade decision dashboard. It removes clutter from the chart and delivers everything a professional scalper needs — strength, direction, volatility, momentum, timing, and actionable trade bias — all in one elegant table.
VWAP Momentum Oscillator How It Works
Core Calculation Method
The oscillator combines four key market measurements into a single, normalized reading:
1. Price-VWAP Deviation: `(Close - VWAP) / VWAP × 100`
2. VWAP-MA Momentum: `(VWAP - MovingAverage) / MovingAverage × 100`
3. Anchored VWAP Strength: Average of high/low anchor deviations from rolling VWAP
4. Range Position: `(Close - PeriodLow) / (PeriodHigh - PeriodLow) × 100 - 50`
Dynamic Signal Line
The signal line uses an EMA that automatically adjusts its length based on your chart timeframe:
- Futures: Always covers 23 hours of trading (1,380 minutes)
- Stocks: Always covers 6.5 hours of trading (390 minutes)
- Examples: 276 periods on 5-min futures chart, 1,380 periods on 1-min futures chart
Trading Signals
🟢 Buy Signals
- Condition: Main oscillator crosses above signal line while below zero
- Logic: Momentum turning bullish from oversold conditions
- Visual: Green "BUY" label below price action
🔴 Sell Signals
- Condition: Main oscillator crosses below signal line while above zero
- Logic: Momentum turning bearish from overbought conditions
- Visual: Red "SELL" label above price action
⚠️ Extreme Warnings
- Extreme Overbought: Red triangle when oscillator crosses above +4.0
- Extreme Oversold: Green triangle when oscillator crosses below -4.0
- Purpose: Risk management alerts, not entry/exit signals
Oscillator Zones
Interpretation Guide
- Above +2.0: Strong bullish momentum zone (green background)
- 0 to +2.0: Mild bullish territory
- 0 to -2.0: Mild bearish territory
- Below -2.0: Strong bearish momentum zone (red background)
- Above +4.0: Extreme overbought (caution advised)
- Below -4.0: Extreme oversold (potential reversal zone)
Customization Options
Moving Average Settings
- EMA/SMA Toggle: Choose between exponential or simple moving average
- Color Customization: Adjust MA line color and width
Visual Controls
- Bullish/Bearish Colors: Customize momentum zone colors
- Signal Line: Toggle visibility and adjust color
- Line Widths: Control thickness of all plot lines
Anchor Modes
- NY Session Only: Anchors reset at NY market open (9:30 AM ET)
- 24H NY Day: Anchors reset at NY calendar day change (midnight ET)
Best Practices
Timeframe Selection
- Scalping: 1-5 minute charts for quick momentum changes
- Day Trading: 5-15 minute charts for clearer trend signals
- Swing Trading: 1-4 hour charts for major momentum shifts
Signal Confirmation
- Wait for crossovers: Don't trade on oscillator position alone
- Respect extreme levels: Exercise caution above +4 or below -4
- Use with price action: Combine with support/resistance levels
Risk Management
- Extreme zones: Reduce position size when oscillator is extended
- Failed signals: Exit quickly if momentum doesn't follow through
- Market context: Consider overall trend direction and market volatility
Technical Specifications
Calculation Components
- Base Length: 1,380 periods (futures) / 390 periods (stocks)
- Signal Line: Dynamic EMA covering one full trading day
- Smoothing: 3-period SMA on raw oscillator (adjustable)
- Update Frequency: Real-time on every price tick
Performance Notes
- Resource Efficient: Optimized calculations minimize CPU usage
- Memory Friendly: Uses incremental VWAP calculations
- Fast Loading: Minimal historical data requirements
Version History & Development
This oscillator evolved from advanced VWAP overlay strategies, transforming complex multi-line analysis into a single, actionable momentum gauge. The indicator maintains the sophistication of institutional VWAP analysis while providing the clarity needed for retail trading decisions.
Core Philosophy
Traditional VWAP indicators show where price is relative to volume-weighted averages, but they don't quantify momentum or provide clear entry/exit signals. This oscillator solves that problem by normalizing all VWAP relationships into a single, bounded indicator that works consistently across all timeframes and asset classes.
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Open Source License: This indicator is provided free for the TradingView community. Feel free to modify and enhance according to your trading needs.
PRO Investing - Apex EnginePRO Investing - Apex Engine
1. Core Concept: Why Does This Indicator Exist?
Traditional momentum oscillators like RSI or Stochastic use a fixed "lookback period" (e.g., 14). This creates a fundamental problem: a 14-period setting that works well in a fast, trending market will generate constant false signals in a slow, choppy market, and vice-versa. The market's character is dynamic, but most tools are static.
The Apex Engine was built to solve this problem. Its primary innovation is a self-optimizing core that continuously adapts to changing market conditions. Instead of relying on one fixed setting, it actively tests three different momentum profiles (Fast, Mid, and Slow) in real-time and selects the one that is most synchronized with the current price action.
This is not just a random combination of indicators; it's a deliberate synthesis designed to create a more robust momentum tool. It combines:
Volatility analysis (ATR) to generate adaptive lookback periods.
Momentum measurement (ROC) to gauge the speed of price changes.
Statistical analysis (Correlation) to validate which momentum measurement is most effective right now.
Classic trend filters (Moving Average, ADX) to ensure signals are only taken in favorable market conditions.
The result is an oscillator that aims to be more responsive in volatile trends and more stable in quiet periods, providing a more intelligent and adaptive signal.
2. How It Works: The Engine's Three-Stage Process
To be transparent, it's important to understand the step-by-step logic the indicator follows on every bar. It's a process of Adapt -> Validate -> Signal.
Stage 1: Adapt (Dynamic Length Calculation)
The engine first measures market volatility using the Average True Range (ATR) relative to its own long-term average. This creates a volatility_factor. In high-volatility environments, this factor causes the base calculation lengths to shorten. In low-volatility, they lengthen. This produces three potential Rate of Change (ROC) lengths: dynamic_fast_len, dynamic_mid_len, and dynamic_slow_len.
Stage 2: Validate (Self-Optimizing Mode Selection)
This is the core of the engine. It calculates the ROC for all three dynamic lengths. To determine which is best, it uses the ta.correlation() function to measure how well each ROC's movement has correlated with the actual bar-to-bar price changes over the "Optimization Lookback" period. The ROC length with the highest correlation score is chosen as the most effective profile for the current moment. This "active" mode is reflected in the oscillator's color and the dashboard.
Stage 3: Signal (Normalized Velocity Oscillator)
The winning ROC series is then normalized into a consistent oscillator (the Velocity line) that ranges from -100 (extreme oversold) to +100 (extreme overbought). This ensures signals are comparable across any asset or timeframe. Signals are only generated when this Velocity line crosses its signal line and the trend filters (explained below) give a green light.
3. How to Use the Indicator: A Practical Guide
Reading the Visuals:
Velocity Line (Blue/Yellow/Pink): The main oscillator line. Its color indicates which mode is active (Fast, Mid, or Slow).
Signal Line (White): A moving average of the Velocity line. Crossovers generate potential signals.
Buy/Sell Triangles (▲ / ▼): These are your primary entry signals. They are intentionally strict and only appear when momentum, trend, and price action align.
Background Color (Green/Red/Gray): This is your trend context.
Green: Bullish trend confirmed (e.g., price above a rising 200 EMA and ADX > 20). Only Buy signals (▲) can appear.
Red: Bearish trend confirmed. Only Sell signals (▼) can appear.
Gray: No clear trend. The market is likely choppy or consolidating. No signals will appear; it is best to stay out.
Trading Strategy Example:
Wait for a colored background. A green or red background indicates the market is in a tradable trend.
Look for a signal. For a green background, wait for a lime Buy triangle (▲) to appear.
Confirm the trade. Before entering, confirm the signal aligns with your own analysis (e.g., support/resistance levels, chart patterns).
Manage the trade. Set a stop-loss according to your risk management rules. An exit can be considered on a fixed target, a trailing stop, or when an opposing signal appears.
4. Settings and Customization
This script is open-source, and its settings are transparent. You are encouraged to understand them.
Synaptic Engine Group:
Volatility Period: The master control for the adaptive engine. Higher values are slower and more stable.
Optimization Lookback: How many bars to use for the correlation check.
Switch Sensitivity: A buffer to prevent frantic switching between modes.
Advanced Configuration & Filters Group:
Price Source: The data source for momentum calculation (default close).
Trend Filter MA Type & Length: Define your long-term trend.
Filter by MA Slope: A key feature. If ON, allows for "buy the dip" entries below a rising MA. If OFF, it's stricter, requiring price to be above the MA.
ADX Length & Threshold: Filters out non-trending, choppy markets. Signals will not fire if the ADX is below this threshold.
5. Important Disclaimer
This indicator is a decision-support tool for discretionary traders, not an automated trading system or financial advice. Past performance is not indicative of future results. All trading involves substantial risk. You should always use proper risk management, including setting stop-losses, and never risk more than you are prepared to lose. The signals generated by this script should be used as one component of a broader trading plan.
Step Channel Momentum Trend [ChartPrime]OVERVIEW
Step Channel Momentum Trend is a momentum-based price filtering system that adapts to market structure using pivot levels and ATR volatility. It builds a dynamic channel around a stepwise midline derived from swing highs and lows. The system colors price candles based on whether price remains inside this channel (low momentum) or breaks out (strong directional flow). This allows traders to clearly distinguish ranging conditions from trending ones and take action accordingly.
⯁ STRUCTURAL MIDLNE (STEP CHANNEL CORE)
The midline acts as the backbone of the trend system and is based on structure rather than smoothing.
Calculated as the average of the most recent confirmed Pivot High and Pivot Low.
The result is a step-like horizontal line that only updates when new pivot points are confirmed.
This design avoids lag and makes the line "snap" to recent structural shifts.
It reflects the equilibrium level between recent bullish and bearish control.
This unique step logic creates clear regime shifts and prevents noise from distorting trend interpretation.
⯁ DYNAMIC VOLATILITY BANDS (ATR FILTERING)
To detect momentum strength, the script constructs upper and lower bands using the ATR (Average True Range):
The distance from the midline is determined by ATR × multiplier (default: 200-period ATR × 0.6).
These bands adjust dynamically to volatility, expanding in high-ATR environments and contracting in calm markets.
The area between upper and lower bands represents a neutral or ranging market state.
Breakouts outside the bands are treated as significant momentum shifts.
This filtering approach ensures that only meaningful breakouts are visually emphasized — not every candle fluctuation.
⯁ MOMENTUM-BASED CANDLE COLORING
The system visually transforms price candles into momentum indicators:
When price (hl2) is above the upper band, candles are green → bullish momentum.
When price is below the lower band, candles are red → bearish momentum.
When price is between the bands, candles are orange → low or no momentum (range).
The candle body, wick, and border are all colored uniformly for visual clarity.
This gives traders instant feedback on when momentum is expanding or fading — ideal for breakout, pullback, or trend-following strategies.
⯁ PIVOT-BASED SWING ANCHORS
Each confirmed pivot is plotted as a label ⬥ directly on the chart:
They also serve as potential manual entry zones, SL/TP anchors, or confirmation points.
⯁ MOMENTUM STATE LABEL
To reinforce the current market mode, a live label is displayed at the most recent candle:
Displays either:
“ Momentum Up ” when price breaks above the upper band.
“ Momentum Down ” when price breaks below the lower band.
“ Range ” when price remains between the bands.
Label color matches the candle color for quick identification.
Automatically updates on each bar close.
This helps discretionary traders filter trades based on market phase.
USAGE
Use the green/red zones to enter with momentum and ride trending moves.
Use the orange zone to stay out or fade ranges.
The step midline can act as a breakout base, pullback anchor, or bias reference.
Combine with other indicators (e.g., order blocks, divergences, or volume) to build high-confluence systems.
CONCLUSION
Step Channel Momentum Trend gives traders a clean, adaptive framework for identifying trend direction, volatility-based breakouts, and ranging environments — all from structural logic and ATR responsiveness. Its stepwise midline provides clarity, while its dynamic color-coded candles make momentum shifts impossible to miss. Whether you’re scalping intraday momentum or managing swing entries, this tool helps you trade with the market’s rhythm — not against it.
Volume Momentum [BackQuant]Volume Momentum
The Volume Momentum indicator is designed to help traders identify shifts in market momentum based on volume data. By analyzing the relative volume momentum, this indicator provides insights into whether the market is gaining strength (uptrend) or losing momentum (downtrend). The strategy uses a combination of percentile-based volume normalization, weighted moving averages (WMA), and exponential moving averages (EMA) to assess volume trends.
The system focuses on the relationship between price and volume, utilizing normalized volume data to highlight key market changes. This approach allows traders to focus on volume-driven price movements, helping them to capture momentum shifts early.
Key Features
1. Volume Normalization and Percentile Calculation:
The signed volume (positive when the close is higher than the open, negative when the close is lower) is normalized against the rolling average volume. This normalized volume is then subjected to a percentile interpolation, allowing for a robust statistical measure of how the current volume compares to historical data. The percentile level is customizable, with 50 representing the median.
2. Weighted and Smoothed Moving Averages for Trend Detection:
The normalized volume is smoothed using weighted moving averages (WMA) and exponential moving averages (EMA). These smoothing techniques help eliminate noise, providing a clearer view of the underlying momentum. The WMA filters out short-term fluctuations, while the EMA ensures that the most recent data points have a higher weight, making the system more responsive to current market conditions.
3. Trend Reversal Detection:
The indicator detects momentum shifts by evaluating whether the volume momentum crosses above or below zero. A positive volume momentum indicates a potential uptrend, while a negative momentum suggests a possible downtrend. These trend reversals are identified through crossover and crossunder conditions, triggering alerts when significant changes occur.
4. Dynamic Trend Background and Bar Coloring:
The script offers customizable background coloring based on the trend direction. When volume momentum is positive, the background is colored green, indicating a bullish trend. When volume momentum is negative, the background is colored red, signaling a bearish trend. Additionally, the bars themselves can be colored based on the trend, further helping traders quickly visualize market momentum.
5. Alerts for Momentum Shifts:
The system provides real-time alerts for traders to monitor when volume momentum crosses a critical threshold (zero), signaling a trend reversal. The alerts notify traders when the market momentum turns bullish or bearish, assisting them in making timely decisions.
6. Customizable Parameters for Flexible Usage:
Users can fine-tune the behavior of the indicator by adjusting various parameters:
Volume Rolling Mean: The period used to calculate the average volume for normalization.
Percentile Interpolation Length: Defines the range over which the percentile is calculated.
Percentile Level: Determines the percentile threshold (e.g., 50 for the median).
WMA and Smoothing Periods: Control the smoothing and response time of the indicator.
7. Trend Background Visualization and Trend-Based Bar Coloring:
The background fill is shaded according to whether the volume momentum is positive or negative, providing a visual cue to indicate market strength. Additionally, bars can be color-coded to highlight the trend, making it easier to see the trend’s direction without needing to analyze numerical data manually.
8. Note on Mean-Reversion Strategy:
If you take the inverse of the signals, this indicator can be adapted for a mean-reversion strategy. Instead of following the trend, the strategy would involve buying assets that are underperforming and selling assets that are overperforming, based on volume momentum. However, it’s important to note that this approach may not work effectively on highly correlated assets, as their price movements may be too similar, reducing the effectiveness of the mean-reversion strategy.
Final Thoughts
The Volume Momentum indicator offers a comprehensive approach to analyzing volume-based momentum shifts in the market. By using volume normalization, percentile interpolation, and smoothed moving averages, this system helps identify the strength and direction of market trends. Whether used for trend-following or adapted for mean-reversion, this tool provides traders with actionable insights into the market’s volume-driven movements, improving decision-making and portfolio management.
PCA Regime-Adjusted MomentumSummary
The PCA Regime-Adjusted Momentum (PCA-RAM) is an advanced market analysis tool designed to provide nuanced insights into market momentum and structural stability. It moves beyond traditional indicators by using Principal Component Analysis (PCA) to deconstruct market data into its most essential patterns.
The indicator provides two key pieces of information:
A smoothed momentum signal based on the market's dominant underlying trend.
A dynamic regime filter that gauges the stability and clarity of the market's structure, advising you when to trust or fade the momentum signals.
This allows traders to not only identify potential shifts in momentum but also to understand the context and confidence behind those signals.
Core Concepts & Methodology
The strength of this indicator lies in its sound, data-driven methodology.
1. Principal Component Analysis (PCA)
At its core, the indicator analyzes a rolling window (default 50 periods) of standardized market data (Open, High, Low, Close, and Volume). PCA is a powerful statistical technique that distills this complex, 5-dimensional data into its fundamental, uncorrelated components of variance. We focus on the First Principal Component (PC1), which represents the single most dominant pattern or "theme" driving the market's behavior in the lookback window.
2. The Momentum Signal
Instead of just looking at price, we project the current market data onto this dominant underlying pattern (PC1). This gives us a raw "projection score" that measures how strongly the current bar aligns with the historically dominant market structure. This raw score is then smoothed using two an exponential moving averages (a fast and a slow line) to create a clear, actionable momentum signal, similar in concept to a MACD.
3. The Dynamic Regime Filter
This is arguably the indicator's most powerful feature. It answers the question: "How clear is the current market picture?"
It calculates the Market Concentration Ratio, which is the percentage of total market variance explained by PC1 alone.
A high ratio indicates that the market is moving in a simple, one-dimensional way (e.g., a clear, strong trend).
A low ratio indicates the market is complex, multi-dimensional, and choppy, with no single dominant theme.
Crucially, this filter is dynamic. It compares the current concentration ratio to its own recent average, allowing it to adapt to any asset or timeframe. It automatically learns what "normal" and "choppy" look like for the specific chart you are viewing.
How to Interpret the Indicator
The indicator is displayed in a separate pane with two key visual elements:
The Momentum Lines (White & Gold)
White Line: The "Fast Line," representing the current momentum.
Gold Line: The "Slow Line," acting as the trend confirmation.
Bullish Signal: A crossover of the White Line above the Gold Line suggests a shift to positive momentum.
Bearish Signal: A crossover of the White Line below the Gold Line suggests a shift to negative momentum.
The Regime Filter (Purple & Dark Red Background)
This is your confidence gauge.
Navy Blue Background (High Concentration): The market structure is stable, simple, and trending. Momentum signals are more reliable and should be given higher priority.
Dark Red Background (Low Concentration): The market structure is complex, choppy, or directionless. Momentum signals are unreliable and prone to failure or "whipsaws." This is a signal to be cautious, tighten stops, or potentially stay out of the market.
Potential Trading Strategies
This tool is versatile and can be used in several ways:
1. Primary Signal Strategy
Condition: Wait for the background to turn Purple, confirming a stable, high-confidence regime.
Entry: Take the next crossover signal from the momentum lines (White over Gold for long, White under Gold for short).
Exit/Filter: Consider exiting positions or ignoring new signals when the background turns Navy.
2. As a Confirmation or Filter for Your Existing Strategy
Do you have a trend-following system? Only enable its long and short signals when the PCA-RAM background is Purple.
Do you have a range-trading or mean-reversion system? It might be most effective when the PCA-RAM background is Navy, indicating a lack of a clear trend.
3. Advanced Divergence Analysis
Look for classic divergences between price and the momentum lines. For example, if the price is making a new high, but the Gold Line is making a lower high, it may indicate underlying weakness in the trend, even on a Purple background. This divergence signal is more powerful because it shows that the new price high is not being confirmed by the market's dominant underlying pattern.
Money Flow Pulse💸 In markets where volatility is cheap and structure is noisy, what matters most isn’t just the move — it’s the effort behind it. Money Flow Pulse (MFP) offers a compact, color-coded readout of real-time conviction by scoring volume-weighted price action on a five-tier scale. It doesn’t try to predict reversals or validate trends. Instead, it reveals the quality of the move in progress: is it fading , driving , exhausting , or hollow ?
🎨 MFP draws from the traditional Money Flow Index (MFI), a volume-enhanced momentum oscillator, but transforms it into a modular “pressure readout” that fits seamlessly into any structural overlay. Rather than oscillating between extremes with little interpretive guidance, MFP discretizes the flow into clean, color-coded regimes ranging from strong inflow (+2) to strong outflow (–2). The result is a responsive diagnostic layer that complements, rather than competes with, tools like ATR and/or On-Balance Volume.
5️⃣ MFP uses a normalized MFI value smoothed over 13 periods and classified into a 5-tier readout of Volume-Driven Conviction :
🍆 Exhaustion Inflow — usually a top or blowoff; not strength, but overdrive (+2)
🥝 Active Inflow — supportive of trend continuation (+1)
🍋 Neutral — chop, coil, or fakeouts (0)
🍑 Selling Intent — weakening structure, possible fade setups (-1)
🍆 Exhaustion Outflow — often signals forced selling or accumulation traps (-2)
🎭 These tiers are not arbitrary. Each one is tuned to reflect real capital behavior across timeframes. For instance, while +1 may support continuation, +2 often precedes exhaustion — especially on the lower timeframes. Similarly, a –1 reading during a pullback suggests sell-side pressure is building, but a shift to –2 may mean capitulation is already underway. The difference between the two can define whether a move is tradable continuation or strategic exhaustion .
🌊 The MFI ROC (Rate of Change) feature can be toggled to become a volatility-aware pulse monitor beneath the derived MFI tier. Instead of scoring direction or structure, ROC reveals how fast conviction is changing — not just where it’s headed, but how hard it's accelerating or decaying. It measures the raw Δ between the current and previous MFI values, exposing bursts of energy, fading pressure, or transitional churn .
🎢 Visually, ROC appears as a low-opacity area fill, anchored to a shared lemon-yellow zero line. When the green swell rises, buying pressure is accelerating; when the red drops, flow is actively deteriorating. A subtle bump may signal early interest — while a steep wave hints at an emotional overreaction. The ROC value itself provides numeric insight alongside the raw MFI score. A reading of +3.50 implies strong upside momentum in the flow — often supporting trend ignition. A score of –6.00 suggests rapid deceleration or full exhaustion — often preceding reversals or failed breakouts.
・ MFI shows you where the flow is
・ ROC tells you how it’s behaving
😎 This blend reveals not just structure or intent — but also urgency . And in flow-based trading, urgency often precedes outcome.
🧩 Divergence isn’t delay — it’s disagreement . One of the most revealing features of MFP is how it exposes momentum dissonance — situations where price and flow part ways. These divergences often front-run pivots , traps , or velocity stalls . Unlike RSI-style divergence, which whispers of exhaustion, MFI divergence signals a breakdown in conviction. The structure may extend — but the effort isn’t there.
・ Price ▲ MFI ▼ → Effortless Markup : Often signals distribution or a grind into liquidity. Without rising MFI, the rally lacks true flow participation — a warning of fragility.
・ Price ▼ MFI ▲ → Absorption or Early Accumulation : Price breaks down, but money keeps flowing in — a hidden bid. Watch for MFI tier shifts or ROC bursts to confirm a reversal.
🏄♂️ These moments don’t require signal overlays or setup hunting. MFP narrates the imbalance. When price breaks structure but flow does not — or vice versa — you’re not seeing trend, you’re seeing disagreement, and that's where edge begins.
💤 MFP is especially effective on intraday charts where volume dislocations matter most. On the 1H or 15m chart, it helps distinguish between breakouts with conviction versus those lacking flow. On higher timeframes, its resolution softens — it becomes more of a drift indicator than a trigger device. That’s by design: MFP prioritizes pulse, not position. It’s not the fire, it’s the heat.
📎 Use MFP in confluence with structural overlays to validate price behavior. A ribbon expansion with rising MFP is real. A compression breakout without +1 flow is "fishy". Watch how MFP behaves near key zones like anchored VWAP, MAs or accumulation pivots. When MFP rises into a +2 and fails to sustain, the reversal isn’t just technical — it’s flow-based.
🪟 MFP doesn’t speak loudly, but it never whispers without reason. It’s the pulse check before action — the breath of the move before the breakout. While it stays visually minimal on the chart, the true power is in the often overlooked Data Window, where traders can read and interpret the score in real time. Once internalized, these values give structure-aware traders a framework for conviction, continuation, or caution.
🛜 MFP doesn’t chase momentum — it confirms conviction. And in markets defined by noise, that signal isn’t just helpful — it’s foundational.
Stochastic Order Flow Momentum [ScorsoneEnterprises]This indicator implements a stochastic model of order flow using the Ornstein-Uhlenbeck (OU) process, combined with a Kalman filter to smooth momentum signals. It is designed to capture the dynamic momentum of volume delta, representing the net buying or selling pressure per bar, and highlight potential shifts in market direction. The volume delta data is sourced from TradingView’s built-in functionality:
www.tradingview.com
For a deeper dive into stochastic processes like the Ornstein-Uhlenbeck model in financial contexts, see these research articles: arxiv.org and arxiv.org
The SOFM tool aims to reveal the momentum and acceleration of order flow, modeled as a mean-reverting stochastic process. In markets, order flow often oscillates around a baseline, with bursts of buying or selling pressure that eventually fade—similar to how physical systems return to equilibrium. The OU process captures this behavior, while the Kalman filter refines the signal by filtering noise. Parameters theta (mean reversion rate), mu (mean level), and sigma (volatility) are estimated by minimizing a squared-error objective function using gradient descent, ensuring adaptability to real-time market conditions.
How It Works
The script combines a stochastic model with signal processing. Here’s a breakdown of the key components, including the OU equation and supporting functions.
// Ornstein-Uhlenbeck model for volume delta
ou_model(params, v_t, lkb) =>
theta = clamp(array.get(params, 0), 0.01, 1.0)
mu = clamp(array.get(params, 1), -100.0, 100.0)
sigma = clamp(array.get(params, 2), 0.01, 100.0)
error = 0.0
v_pred = array.new(lkb, 0.0)
array.set(v_pred, 0, array.get(v_t, 0))
for i = 1 to lkb - 1
v_prev = array.get(v_pred, i - 1)
v_curr = array.get(v_t, i)
// Discretized OU: v_t = v_{t-1} + theta * (mu - v_{t-1}) + sigma * noise
v_next = v_prev + theta * (mu - v_prev)
array.set(v_pred, i, v_next)
v_curr_clean = na(v_curr) ? 0 : v_curr
v_pred_clean = na(v_next) ? 0 : v_next
error := error + math.pow(v_curr_clean - v_pred_clean, 2)
error
The ou_model function implements a discretized Ornstein-Uhlenbeck process:
v_t = v_{t-1} + theta (mu - v_{t-1})
The model predicts volume delta (v_t) based on its previous value, adjusted by the mean-reverting term theta (mu - v_{t-1}), with sigma representing the volatility of random shocks (approximated in the Kalman filter).
Parameters Explained
The parameters theta, mu, and sigma represent distinct aspects of order flow dynamics:
Theta:
Definition: The mean reversion rate, controlling how quickly volume delta returns to its mean (mu). Constrained between 0.01 and 1.0 (e.g., clamp(array.get(params, 0), 0.01, 1.0)).
Interpretation: A higher theta indicates faster reversion (short-lived momentum), while a lower theta suggests persistent trends. Initial value is 0.1 in init_params.
In the Code: In ou_model, theta scales the pull toward \mu, influencing the predicted v_t.
Mu:
Definition: The long-term mean of volume delta, representing the equilibrium level of net buying/selling pressure. Constrained between -100.0 and 100.0 (e.g., clamp(array.get(params, 1), -100.0, 100.0)).
Interpretation: A positive mu suggests a bullish bias, while a negative mu indicates bearish pressure. Initial value is 0.0 in init_params.
In the Code: In ou_model, mu is the target level that v_t reverts to over time.
Sigma:
Definition: The volatility of volume delta, capturing the magnitude of random fluctuations. Constrained between 0.01 and 100.0 (e.g., clamp(array.get(params, 2), 0.01, 100.0)).
Interpretation: A higher sigma reflects choppier, noisier order flow, while a lower sigma indicates smoother behavior. Initial value is 0.1 in init_params.
In the Code: In the Kalman filter, sigma contributes to the error term, adjusting the smoothing process.
Summary:
theta: Speed of mean reversion (how fast momentum fades).
mu: Baseline order flow level (bullish or bearish bias).
sigma: Noise level (variability in order flow).
Other Parts of the Script
Clamp
A utility function to constrain parameters, preventing extreme values that could destabilize the model.
ObjectiveFunc
Defines the objective function (sum of squared errors) to minimize during parameter optimization. It compares the OU model’s predicted volume delta to observed data, returning a float to be minimized.
How It Works: Calls ou_model to generate predictions, computes the squared error for each timestep, and sums it. Used in optimization to assess parameter fit.
FiniteDifferenceGradient
Calculates the gradient of the objective function using finite differences. Think of it as finding the "slope" of the error surface for each parameter. It nudges each parameter (theta, mu, sigma) by a small amount (epsilon) and measures the change in error, returning an array of gradients.
Minimize
Performs gradient descent to optimize parameters. It iteratively adjusts theta, mu, and sigma by stepping down the "hill" of the error surface, using the gradients from FiniteDifferenceGradient. Stops when the gradient norm falls below a tolerance (0.001) or after 20 iterations.
Kalman Filter
Smooths the OU-modeled volume delta to extract momentum. It uses the optimized theta, mu, and sigma to predict the next state, then corrects it with observed data via the Kalman gain. The result is a cleaner momentum signal.
Applied
After initializing parameters (theta = 0.1, mu = 0.0, sigma = 0.1), the script optimizes them using volume delta data over the lookback period. The optimized parameters feed into the Kalman filter, producing a smoothed momentum array. The average momentum and its rate of change (acceleration) are calculated, though only momentum is plotted by default.
A rising momentum suggests increasing buying or selling pressure, while a flattening or reversing momentum indicates fading activity. Acceleration (not plotted here) could highlight rapid shifts.
Tool Examples
The SOFM indicator provides a dynamic view of order flow momentum, useful for spotting directional shifts or consolidation.
Low Time Frame Example: On a 5-minute chart of SEED_ALEXDRAYM_SHORTINTEREST2:NQ , a rising momentum above zero with a lookback of 5 might signal building buying pressure, while a drop below zero suggests selling dominance. Crossings of the zero line can mark transitions, though the focus is on trend strength rather than frequent crossovers.
High Time Frame Example: On a daily chart of NYSE:VST , a sustained positive momentum could confirm a bullish trend, while a sharp decline might warn of exhaustion. The mean-reverting nature of the OU process helps filter out noise on longer scales. It doesn’t make the most sense to use this on a high timeframe with what our data is.
Choppy Markets: When momentum oscillates near zero, it signals indecision or low conviction, helping traders avoid whipsaws. Larger deviations from zero suggest stronger directional moves to act on, this is on $STT.
Inputs
Lookback: Users can set the lookback period (default 5) to adjust the sensitivity of the OU model and Kalman filter. Shorter lookbacks react faster but may be noisier; longer lookbacks smooth more but lag slightly.
The user can also specify the timeframe they want the volume delta from. There is a default way to lower and expand the time frame based on the one we are looking at, but users have the flexibility.
No indicator is 100% accurate, and SOFM is no exception. It’s an estimation tool, blending stochastic modeling with signal processing to provide a leading view of order flow momentum. Use it alongside price action, support/resistance, and your own discretion for best results. I encourage comments and constructive criticism.
JW Momentum IndicatorJW Momentum Indicator
This indicator provides clear and actionable buy/sell signals based on a combination of volume-enhanced momentum, divergence detection, and volatility adjustment. It's designed to identify potential trend reversals and momentum shifts with a focus on high-probability setups.
Key Features:
Volume-Enhanced Momentum: The indicator calculates a custom oscillator that combines momentum with volume, giving more weight to momentum when volume is significant. This helps to identify strong momentum moves.
Divergence Detection: It detects bullish and bearish divergences using pivot highs and lows, highlighting potential trend reversals.
Volatility-Adjusted Signals: The indicator adjusts signal sensitivity based on the Average True Range (ATR), making it more reliable in varying market conditions.
Clear Visuals: Buy and sell signals are clearly indicated with up and down triangles, while divergences are highlighted with distinct labels.
How to Use:
Buy Signals: Look for green up triangles or bullish divergence labels.
Sell Signals: Look for red down triangles or bearish divergence labels.
Oscillator and Thresholds: Use the plotted oscillator and thresholds to confirm signal strength.
Parameters:
Momentum Period: Adjusts the length of the momentum calculation.
Volume Average Period: Adjusts the length of the volume average calculation.
Volatility Period: Adjusts the length of the ATR calculation.
Volatility Multiplier: Adjusts the sensitivity of the volatility-adjusted signals.
Disclaimer:
This indicator is for informational purposes only and should not be considered financial advice. Always conduct 1 thorough research and use appropriate risk management techniques when trading.
TMO (True Momentum Oscillator)TMO ((T)rue (M)omentum (O)scilator)
Created by Mobius V01.05.2018 TOS Convert to TV using Claude 3.7 and ChatGPT 03 Mini :
TMO calculates momentum using the delta of price. Giving a much better picture of trend, tend reversals and divergence than momentum oscillators using price.
True Momentum Oscillator (TMO)
The True Momentum Oscillator (TMO) is a momentum-based technical indicator designed to identify trend direction, trend strength, and potential reversal points in the market. It's particularly useful for spotting overbought and oversold conditions, aiding traders in timing their entries and exits.
How it Works:
The TMO calculates market momentum by analyzing recent price action:
Momentum Calculation:
For a user-defined length (e.g., 14 bars), TMO compares the current closing price to past open prices. It assigns:
+1 if the current close is greater than the open price of the past bar (indicating bullish momentum).
-1 if it's less (indicating bearish momentum).
0 if there's no change.
The sum of these scores gives a raw momentum measure.
EMA Smoothing:
To reduce noise and false signals, this raw momentum is smoothed using Exponential Moving Averages (EMAs):
First, the raw data is smoothed by an EMA over a short calculation period (default: 5).
Then, it undergoes additional smoothing through another EMA (default: 3 bars), creating the primary "Main" line of the indicator.
Lastly, a "Signal" line is derived by applying another EMA (also default: 3 bars) to the main line, adding further refinement.
Trend Identification:
The indicator plots two lines:
Main Line: Indicates current momentum strength and direction.
Signal Line: Acts as a reference line, similar to a moving average crossover system.
When the Main line crosses above the Signal line, it suggests strengthening bullish momentum. Conversely, when the Main line crosses below the Signal line, it indicates increasing bearish momentum.
Overbought/Oversold Levels:
The indicator identifies key levels based on the chosen length parameter:
Overbought zone (positive threshold): Suggests the market might be overheated, and a potential bearish reversal or pullback could occur.
Oversold zone (negative threshold): Suggests the market might be excessively bearish, signaling a potential bullish reversal.
Clouds visually mark these overbought/oversold areas, making it easy to see potential reversal zones.
Trading Applications:
Trend-following: Traders can enter positions based on crossovers of the Main and Signal lines.
Reversals: The overbought and oversold areas highlight high-probability reversal points.
Momentum confirmation: Use TMO to confirm price action or other technical signals, improving trade accuracy and timing.
The True Momentum Oscillator provides clarity in identifying momentum shifts, making it a valuable addition to various trading strategies.
Blockchain Fundamentals: Liquidity Cycle MomentumLiquidity Cycle Momentum Indicator
Overview:
This indicator analyzes global liquidity trends by calculating a unique Liquidity Index and measuring its year-over-year (YoY) percentage change. It then applies a momentum oscillator to the YoY change, providing insights into the cyclical momentum of liquidity. The indicator incorporates a limited historical data workaround to ensure accurate calculations even when the chart’s history is short.
Features Breakdown:
1. Limited Historical Data Workaround
Function: The limit(length) function adjusts the lookback period when there isn’t enough historical data (i.e., near the beginning of the chart), ensuring that calculations do not break due to insufficient data.
2. Global Liquidity Calculation
Data Sources:
TVC:CN10Y (10-year yield from China)
TVC:DXY (US Dollar Index)
ECONOMICS:USCBBS (US Central Bank Balance Sheet)
FRED:JPNASSETS (Japanese assets)
ECONOMICS:CNCBBS (Chinese Central Bank Balance Sheet)
FRED:ECBASSETSW (ECB assets)
Calculation Methodology:
A ratio is computed (cn10y / dxy) to adjust for currency influences.
The Liquidity Index is then derived by multiplying this ratio with the sum of the other liquidity components.
3. Year-over-Year (YoY) Percent Change
Computation:
The indicator determines the number of bars that approximately represent one year.
It then compares the current Liquidity Index to its value one year ago, calculating the YoY percentage change.
4. Momentum Oscillator on YoY Change
Oscillator Components:
1. Calculated using the Chande Momentum Oscillator (CMO) applied to the YoY percent change with a user-defined momentum length.
2. A weighted moving average (WMA) that smooths the momentum signal.
3. Overbought and Oversold zones
Signal Generation:
Buy Signal: Triggered when the momentum crosses upward from an oversold condition, suggesting a potential upward shift in liquidity momentum.
Sell Signal: Triggered when crosses below an overbought condition, indicating potential downward momentum.
State Management:
The indicator maintains a state variable to avoid repeated signals, ensuring that a new buy or sell signal is only generated when there’s a clear change in momentum.
5. Visual Presentation and Alerts
Plots:
The oscillator value and signalline are plotted for visual analysis.
Overbought and oversold levels are marked with dashed horizontal lines.
Signal Markers:
Buy and sell signals are marked with green and maroon circles, respectively.
Background Coloration:
Optionally, the chart’s background bars are colored (yellow for buy signals and fuchsia for sell signals) to enhance visual cues when signals are triggered.
Conclusion
In summary, the Liquidity Cycle Momentum Indicator provides a robust framework to analyze liquidity trends by combining global liquidity data, YoY changes, and momentum oscillation. This makes it an effective tool for traders and analysts looking to identify cyclical shifts in liquidity conditions and potential turning points in the market.
