Combo Backtest 123 Reversal & Chande Momentum Oscillator This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots Chande Momentum Oscillator. This indicator was
developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what
he calls "pure momentum". For more definitive information on the CMO and
other indicators we recommend the book The New Technical Trader by Tushar
Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder`s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to
clearly see changes in net momentum using the 0 level. The bounded scale
also allows you to conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors
在脚本中搜索"momentum"
Combo Strategy 123 Reversal & Chande Momentum OscillatorThis is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
This indicator plots Chande Momentum Oscillator. This indicator was
developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what
he calls "pure momentum". For more definitive information on the CMO and
other indicators we recommend the book The New Technical Trader by Tushar
Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder`s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to
clearly see changes in net momentum using the 0 level. The bounded scale
also allows you to conveniently compare values across different securities.
WARNING:
- For purpose educate only
- This script to change bars colors.
Rumpy's Dynamic Momentum IndexNote : I haven't been able to determine from the info I've found whether the variable length is used for the average gain/loss part of the calculation and/or for the relative strength portion of the calculation . If anyone knows for certain please let me know.
Type A only uses the variable length for the final relative strength calculation and the fixed RSI length for the average gain/loss.
Type B uses the variable length for both.
I do suspect that Type B is correct though as it is a lot more sensitive to momentum changes while Type A tends to just exaggerate normal RSI
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This indicator, developed by Tushar Chande and Stanley Kroll, is similar to the relative strength index (RSI). The main difference between the two is that the RSI uses a fixed number of time periods (usually 14) in its calculation, while the dynamic momentum index uses different time periods as volatility changes, typically between five and 30.
The dynamic momentum index uses fewer periods in its calculation when volatility is high, and more periods when volatility is low.
The number of time periods used in the dynamic momentum index decreases as volatility in the underlying security increases, making this indicator more responsive to changing prices than the RSI. This is particularly useful when an asset's price moves quickly as it approaches key support or resistance levels. Because the indicator is more sensitive, traders can potentially find earlier entry and exit points than with the RSI.
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If you find it useful please consider a tip/donation :
BTC - 3BMEXEDyWJ58eXUEALYPadbn1wwWKmf6sA
Linear Momentum and Performance IndicatorsThis a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index: The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index: It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index: The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index: The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedbacks are welcome
Hope you enjoy this,
CryptoStatistical
Linear Momentum and Performance Indicators (IFTA Jan 2019)This a porting to Trading View of the 12 new indicators introduced in IFTA Journal (January Edition) by Akram El Sherbini, MFTA, CFTe, CETA.
Indicators are available in "Linear Momentum and Performance Indicators" at page four.
IFTA Journal is available below:
ifta.org
Indicators implemented herein:
Linear Force Index: The linear force index LFI measures the force of buyers and sellers during rallies and declines, respectively. It combines two important pieces of market information—the price acceleration
and volumes.
Pressure Index: The pressure index PRI measures the buying and selling pressure over a certain range within a time interval by moving around its zero line. The index indicates a rise in buying pressure when it crosses above the zero line and a rise in selling pressure
when it crosses below the zero line level. The buying and selling force moves the last price during the session to form a range with low and high boundaries.
Strength Index Index : The strength index SI is a leading indicator to the pressure index. It measures the ability of buyers to resist sellers and vice versa. SI of today is the ratio of the latest pressure index value to the strain of today.
Power Index : It measures the buying and selling power within a time interval by moving around its zero line.
Intensity Index : The intensity index II measures the buying and selling intensity within a time interval by moving around its zero line.
Dynamic Strength Index : The sole purpose of the dynamic strength index DSI and the integral dynamic strength index IDSI is to lead their intensity indicator peers.
Integral Force Index
Integral Pressure Index
Integral Strength Index
Integral Power Index
Integral Intensity Index
Integral Dynamic Strength Index
The following example shows a trade following the signal while several indicators are crossing the zero line:
Integral performance indicators have a fewer number of trades than the performance indicators. This result is normal, as the integral indicators are less sensitive than their peers. Moreover, the power, intensity, and dynamic strength are less sensitive than the force, pressure, and strength indicators. The same applies for their integrals. Therefore, the integrals of power, intensity, and dynamic strength indicators are more inclined to be medium-term indicators.
As the paper is suggesting "the linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Technical indicators are using biased mathematical implementations. For example Momentum Index is in reality a velocity indicator, Force index a Momentum indicator and so on. From a Physical perspective correct momentum, force, velocity etc. needs to be corrected and re-categorized.
The author also gives important insights in how these indicators can be used "simultaneously to identify price turning points and filter irrelevant divergences."
"This paper will attempt to adjust the price momentum and force concepts introduced by Welles Wilder and Alexander Elder, respectively. By introducing the concept of linear momentum, new indicators will emerge to dissect the market performance into six main elements: market’s force, pressure, strength, power, intensity, and dynamic strength. This will lead to a deeper insight about market action. The leading performance indicators can be used simultaneously to identify price turning points and filter irrelevant divergences. The linear momentum and the new performance indicators should make a significant change in categorizing several indicators in technical analysis."
Suggestions and feedback are welcome
Hope you enjoy this,
CryptoStatistical
Newton Force and MomentumThis indicator is meant to show the Force of price, based on Newton's Second Law of Motion; and the momentum of price. Force is the value on the left, and momentum on the right.
Originally this was supposed to only be an indicator looking at Force, but because the already popular indicator called "Momentum" does not calculate the momentum of price, but rather the change of price depending on how far back you want to look; I decided to add the Momentum aspect to the indicator.
*BTW if you find this script useful thank and follow @overttherainbow, because they are the one who gave me the idea for this script.*
Seasonal Momentum Indicator This is basically a 5-period seasonal average with an applied momentum (10 ) applied. This is plotted and compared to the current momentum (10). The current momentum is in red while the seasonal momentum is in blue.
You can see that whenever the seasonal momentum and the current momentum are in the same direction, the probability of the trend continuing is higher. Also whenever there is a divergence in the two; the red line (current momentum) will often catch up to the blue (seasonal momentum).
Another use of this indicator is as a divergence detector. If you turn off the red line, you will have only the blue line plotted on the graph. Take this and apply lines to see if the momentum diverges from the price (see example).
I hope you enjoy this one. It only works for securities which have a five year record. You can use it on different time frames but the annual is probably the best and most useful.
Happy Trading
--SpreadEagle71
CMO & WMA Strategy This indicator plots Chande Momentum Oscillator and its WMA on the
same chart. This indicator plots the absolute value of CMO.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder?s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to clearly
see changes in net momentum using the 0 level. The bounded scale also allows
you to conveniently compare values across different securities.
CMO (Chande Momentum Oscillator) Strategy Backtest This indicator plots Chande Momentum Oscillator. This indicator was
developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what
he calls "pure momentum". For more definitive information on the CMO and
other indicators we recommend the book The New Technical Trader by Tushar
Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder`s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to
clearly see changes in net momentum using the 0 level. The bounded scale
also allows you to conveniently compare values across different securities.
Squeeze Momentum Indicator [LazyBear]
Fixed a typo in the code where BB multiplier was stuck at 1.5. Thanks @ucsgears for bringing it to my notice.
Updated source: pastebin.com
Use the updated source instead of the what TV shows below.
This is a derivative of John Carter's "TTM Squeeze" volatility indicator, as discussed in his book "Mastering the Trade" (chapter 11).
Black crosses on the midline show that the market just entered a squeeze (Bollinger Bands are with in Keltner Channel). This signifies low volatility, market preparing itself for an explosive move (up or down). Gray crosses signify "Squeeze release".
Mr.Carter suggests waiting till the first gray after a black cross, and taking a position in the direction of the momentum (for ex., if momentum value is above zero, go long). Exit the position when the momentum changes (increase or decrease --- signified by a color change). My (limited) experience with this shows, an additional indicator like ADX / WaveTrend, is needed to not miss good entry points. Also, Mr.Carter uses simple momentum indicator, while I have used a different method (linreg based) to plot the histogram.
More info:
- Book: Mastering The Trade by John F Carter
List of all my indicators:
CMO (Chande Momentum Oscillator)Hi
Let me introduce my CMO (Chande Momentum Oscillator) script.
This indicator plots Chandre Momentum Oscillator. This indicator was
developed by Tushar Chande. A scientist, an inventor, and a respected
trading system developer, Mr. Chande developed the CMO to capture what
he calls "pure momentum". For more definitive information on the CMO and
other indicators we recommend the book The New Technical Trader by Tushar
Chande and Stanley Kroll.
The CMO is closely related to, yet unique from, other momentum oriented
indicators such as Relative Strength Index, Stochastic, Rate-of-Change,
etc. It is most closely related to Welles Wilder`s RSI, yet it differs
in several ways:
- It uses data for both up days and down days in the numerator, thereby
directly measuring momentum;
- The calculations are applied on unsmoothed data. Therefore, short-term
extreme movements in price are not hidden. Once calculated, smoothing
can be applied to the CMO, if desired;
- The scale is bounded between +100 and -100, thereby allowing you to
clearly see changes in net momentum using the 0 level. The bounded scale
also allows you to conveniently compare values across different securities.
Crypto Early Momentum — Screener v6 (robust)Screens Crypto Pairs for momentum and assigns a momentum score.
Signal Generator: HTF EMA Momentum + MACDSignal Generator: HTF EMA Momentum + MACD
What this script does
This indicator combines a higher-timeframe EMA trend filter with a MACD crossover on the chart’s timeframe. The goal is to make MACD signals more selective by checking whether they occur in the same direction as the broader trend.
How it works
- On the higher timeframe, two EMAs are calculated (short and long). Their difference is used as a simple momentum measure.
- On the chart timeframe, the MACD is calculated. Crossovers are then filtered with two conditions:
1.They must align with the higher-timeframe EMA trend.
2.They must occur beyond a small “zero band” threshold, with a minimum distance between MACD and signal lines.
- When both conditions are met, the script can plot BUY or SELL labels. ATR is used only to shift labels up or down for visibility.
Visuals and alerts
- Histogram bars show whether higher-timeframe EMA momentum is rising or falling.
- MACD main and signal lines are plotted with optional scaling.
- Dotted lines show the zero band region.
- Optional large BUY/SELL labels appear when conditions are confirmed on the previous bar.
- Alerts can be enabled for these signals; they trigger once per bar close.
Notes and limitations
- Higher-timeframe values are only confirmed once the higher-timeframe candle has closed.
- Scaling factors affect appearance only, not the logic.
- This is an open-source study intended as a learning and charting tool. It does not provide financial advice or guarantee performance.
DNSE VN301!, ADX Momentum StrategyDiscover the tailored Pine Script for trading VN30F1M Futures Contracts intraday.
This strategy applies the Statistical Method (IQR) to break down the components of the ADX, calculating the threshold of "normal" momentum fluctuations in price to identify potential breakouts for entry and exit signals. The script automatically closes all positions by 14:30 to avoid overnight holdings.
www.tradingview.com
Settings & Backtest Results:
- Chart: 30-minute timeframe
- Initial capital: VND 100 million
- Position size: 4 contracts per trade (includes trading fees, excludes tax)
- Backtest period: Sep-2021 to Sep-2025
- Return: over 270% (with 5 ticks slippage)
- Trades executed: 1,000+
- Win rate: ~40%
- Profit factor: 1.2
Default Script Settings:
Calculates the acceleration of changes in the +DI and -DI components of the ADX, using IQR to define "normal" momentum fluctuations (adjustable via Lookback period).
Calculates the difference between each bar’s Open and Close prices, using IQR to define "normal" gaps (adjustable via Lookback period).
Entry & Exit Conditions:
Entry Long: Change in +DI or -DI > Avg IQR Value AND Close Price > Previous Close
Exit Long: (all 4 conditions must be met)
- Change in +DI or -DI > Avg IQR Value
- RSI < Previous RSI
- Close–Open Gap > Avg IQR Gap
- Close Price < Previous Close
Entry Short: Change in +DI or -DI > Avg IQR Value AND Close Price < Previous Close
Exit Short: (all 4 conditions must be met)
- Change in +DI or -DI > Avg IQR Value
- RSI > Previous RSI
- Close–Open Gap > Avg IQR Gap
- Close Price > Previous Close
Disclaimers:
Trading futures contracts carries a high degree of risk, and price movements can be highly volatile. This script is intended as a reference tool only. It should be used by individuals who fully understand futures trading, have assessed their own risk tolerance, and are knowledgeable about the strategy’s logic.
All investment decisions are the sole responsibility of the user. DNSE bears no liability for any potential losses incurred from applying this strategy in real trading. Past performance does not guarantee future results. Please contact us directly if you have specific questions about this script.
POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV)
Version: PineScript™v6
📌Description
The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss.
POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously.
The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities.
🚀Points of Innovation
Micro-POC calculation using advanced OHLC-based volume distribution estimation
Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency
Persistence scoring system that quantifies directional consistency over multiple periods
Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts
Dynamic color-coded visualization system with intensity-based feedback
Comprehensive customization options for resolution, periods, and thresholds
🔧Core Components
POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms
Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization
Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration
Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting
Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation
Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships
🔥Key Features
Real-time POC calculation with 10-100 configurable price bands for optimal precision
Velocity tracking with customizable lookback periods from 5 to 50 bars
Acceleration measurement for detecting momentum changes in POC movement
Persistence scoring to validate signal strength and filter false signals
Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions
Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps
Adjustable information table displaying real-time metrics and current signals
Heat ribbon visualization showing price-POC relationship intensity
Multiple threshold settings for customizing signal sensitivity
Export capability for use with separate panel indicators
🎨Visualization
POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude
Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity
Signal Markers: Clear exhaustion top/bottom signals with labeled shapes
Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status
Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions
📖Usage Guidelines
POC Calculation Settings
POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar
Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation
POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise
Velocity Settings
Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity
Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration
Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals
Persistence Settings
Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation
Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals
Visual Settings
Show POC Connecting Lines: Toggle display of colored lines connecting POC levels
Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship
Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon
Alert Settings
Enable Continuation Alerts: Toggle alerts for continuation pattern detection
Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection
Enable POC Gap Alerts: Toggle alerts for significant POC gaps
Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts
✅Best Use Cases
Identifying trend continuation opportunities when POC velocity aligns with price direction
Spotting potential reversal points through exhaustion pattern detection
Confirming breakout validity by monitoring POC gap behavior
Adding volume-based context to traditional technical analysis
Managing position sizing based on POC-price basis strength
⚠️Limitations
POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution
Effectiveness may vary in low-volume or highly volatile market conditions
Requires complementary analysis tools for complete trading decisions
Signal frequency may be lower in ranging markets compared to trending conditions
Performance optimization needed for very short timeframes below 1-minute
💡What Makes This Unique
Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data
Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels
Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator
Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions
Persistence Validation: Unique scoring system to filter signals based on directional consistency
🔬How It Works
Volume Distribution Estimation:
Divides each bar into configurable price bands for volume analysis
Applies sophisticated weighting based on OHLC relationships and proximity to close
Identifies the price level with maximum estimated volume as the POC
Velocity and Acceleration Calculation:
Measures POC rate of change over specified lookback periods
Normalizes values using ATR for consistent cross-market performance
Calculates acceleration as the rate of change of velocity
Signal Generation Process:
Combines trend direction analysis using EMA crossovers
Applies velocity and persistence thresholds to filter signals
Generates continuation, exhaustion, and gap alerts based on specific criteria
💡Note:
This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.
3 SMA + RSI + MACD + MTF Ultimate Dashboard🎯 Overview:
High-precision trading indicator combining trend, momentum, and multi-timeframe confirmation for reliable buy/sell signals in Forex, Crypto, and other markets.
🔹 Core Features:
📈 3 SMAs (7/25/99) – Short, Medium & Long-term trend detection
⚡ RSI Filter – Avoid weak signals (Buy >55 / Sell <45)
💎 MACD with Threshold – Reduce false crossovers
⏱️ Multi-Timeframe Trend (H4) – Confirm overall market direction
✅ Dashboard & Signals:
🟢 Clear Buy & Sell arrows on chart
📊 Live dashboard showing filter status & total signals
🔔 Audio & Push Alerts – Mobile/Desktop/Webhook
💎 Benefits:
⚡ Minimizes false signals
📈 Works on M15, H1, H4, Daily
🎯 Combines trend, momentum, and confirmation filters in one dashboard
⚠️ Note: Signals are generated only after candle close for maximum reliability.
Optimized Trend-Momentum SignalsThis indicator combines trend, momentum, and volume-strength factors into a single buy/sell signal system. It integrates:
SMA 200 → Identifies the long-term trend (price above = bullish bias, below = bearish bias).
MACD (12,26,9) → Confirms momentum direction with line crossovers.
RSI (7) → Filters strength (above 50 = bullish, below 50 = bearish).
ROC (45) → Validates positive or negative rate of change.
Signal Logic:
Buy Signal → Price above SMA 200, MACD bullish, RSI > 50, and ROC > 0.
Sell Signal → Price below SMA 200, MACD bearish, RSI < 50, and ROC < 0.
Features:
Clear arrows for BUY and SELL signals.
Long-term SMA plotted for trend visualization.
Alerts built-in for real-time notifications.
This tool helps traders filter out noise and act only when all major confirmation factors align, reducing false signals and improving decision-making.
Breakout Volume Momentum [5m]Breakout Volume Momentum Indicator (Pine Script v5)
This TradingView Pine Script v5 indicator plots a green dot below a 5-minute price bar whenever all the breakout and volume conditions are met. It is optimized for live intraday trading (not backtesting) and includes customizable inputs for thresholds and trading session times. Key features and conditions of this indicator:
Gap Up Threshold: Current price is up at least X% (default 20%) from the previous day’s close (uses higher-timeframe daily data) before any signal can trigger.
Relative Volume (RVOL): Current bar’s volume is at least Y× (default 2×) the average volume of the last 20 bars. This ensures unusually high volume is present, indicating strong interest.
Trend Alignment: Price is trading above the VWAP (Volume-Weighted Average Price) and above a fast EMA. In addition, the fast EMA (default 9) is above the slower EMA (default 20) to confirm bullish momentum
tradingview.com
tradingview.com
. These filters ensure the stock is in an intraday uptrend (above the average price and rising EMAs).
Intraday Breakout (optional): Optionally require the price to break above the recent intraday high (default last 30 bars). If enabled, a signal only occurs when the stock exceeds its prior range high, confirming a breakout. This can be toggled on/off in the settings.
Avoid Parabolic Spikes: The script skips any bar with an excessively large range (default >12% from low to high), to avoid triggering on spiky or unsustainable parabolic candles.
Time Window Filter: Signals are restricted to a specific session window (by default 09:30 – 11:00 exchange time, typically the morning session) and will not trigger outside these hours. The session window is adjustable via inputs
stackoverflow.com
.
Alerts: An alert condition is provided so you can set a Trading View alert to send a push notification when a green dot signal fires. The alert message includes the ticker and price at the time of signal.
Multi-Timeframe RSI Momentum StrategyMulti-Timeframe RSI Momentum Strategy
To display two different timeframes of the Relative Strength Index (RSI) on TradingView, you can utilize the "Multi-Timeframe RSI" indicator or a similar custom script. This allows you to visualize the RSI for both your current chart's timeframe and a higher (or lower) timeframe, providing a more comprehensive view of momentum
Bullish Divergence SMI Base & Trigger with ATR FilterDescription:
A bullish divergence indicator combining the Stochastic Momentum Index (SMI) and Average True Range (ATR) to pinpoint high-probability entries:
1. Base Arrow (Orange ▲):
• Marks every SMI %K / %D bullish crossover where %K < –70 (deep oversold)—the first half of the divergence setup.
• Each new qualifying crossover replaces the previous base, continuously “arming” the divergence signal.
• Configurable SMI lookbacks, oversold threshold, and a base timeout (default 100 days) to clear stale bases.
2. Trigger Arrow (Green ▲):
• Completes the bullish divergence: fires on the next SMI bullish crossover where %K > –60 and price has dropped below the base arrow’s close by at least N × ATR (default 1 × 14-day ATR).
• A dashed green line links the base and trigger to visually confirm the divergence.
• Resets after triggering, ready for a new divergence cycle.
Inputs:
• SMI %K Length, EMA Smoothing, %D Length
• Oversold Base Level (–70), Trigger Level (–60)
• ATR Length (14), ATR Multiplier (1.0)
• Base Timeout (100 days)
Ideal for any market, this study highlights genuine bullish divergences—oversold momentum crossovers that coincide with significant price reactions—before entering long trades.
Squeeze Momentum Regression Clouds [SciQua]╭──────────────────────────────────────────────╮
☁️ Squeeze Momentum Regression Clouds
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🔍 Overview
The Squeeze Momentum Regression Clouds (SMRC) indicator is a powerful visual tool for identifying price compression , trend strength , and slope momentum using multiple layers of linear regression Clouds. Designed to extend the classic squeeze framework, this indicator captures the behavior of price through dynamic slope detection, percentile-based spread analytics, and an optional UI for trend inspection — across up to four customizable regression Clouds .
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⚙️ Core Features
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Up to 4 Regression Clouds – Each Cloud is created from a top and bottom linear regression line over a configurable lookback window.
Slope Detection Engine – Identifies whether each band is rising, falling, or flat based on slope-to-ATR thresholds.
Spread Compression Heatmap – Highlights compressed zones using yellow intensity, derived from historical spread analysis.
Composite Trend Scoring – Aggregates directional signals from each Cloud using your chosen weighting model.
Color-Coded Candles – Optional candle coloring reflects the real-time composite score.
UI Table – A toggleable info table shows slopes, compression levels, percentile ranks, and direction scores for each Cloud.
Gradient Cloud Styling – Apply gradient coloring from Cloud 1 to Cloud 4 for visual slope intensity.
Weight Aggregation Options – Use equal weighting, inverse-length weighting, or max pooling across Clouds to determine composite trend strength.
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🧪 How to Use the Indicator
1. Understand Trend Bias with Cloud Colors
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Each Cloud changes color based on its current slope:
Green indicates a rising trend.
Red indicates a falling trend.
Gray indicates a flat slope — often seen during chop or transitions.
Cloud 1 typically reflects short-term structure, while Cloud 4 represents long-term directional bias. Watch for multi-Cloud alignment — when all Clouds are green or red, the trend is strong. Divergence among Clouds often signals a potential shift.
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2. Use Compression Heat to Anticipate Breakouts
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The space between each Cloud’s top and bottom regression lines is measured, normalized, and analyzed over time. When this spread tightens relative to its history, the script highlights the band with a yellow compression glow .
This visual cue helps identify squeeze zones before volatility expands. If you see compression paired with a changing slope color (e.g., gray to green), this may indicate an impending breakout.
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3. Leverage the Optional Table UI
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The indicator includes a dynamic, floating table that displays real-time metrics per Cloud. These include:
Slope direction and value , with historical Min/Max reference.
Top and Bottom percentile ranks , showing how price sits within the Cloud range.
Current spread width , compared to its historical norms.
Composite score , which blends trend, slope, and compression for that Cloud.
You can customize the table’s position, theme, transparency, and whether to show a combined summary score in the header.
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4. Analyze Candle Color for Composite Signals
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When enabled, the indicator colors candles based on a weighted composite score. This score factors in:
The signed slope of each Cloud (up, down, or flat)
The percentile pressure from the top and bottom bands
The degree of spread compression
Expect green candles in bullish trend phases, red candles during bearish regimes, and gray candles in mixed or low-conviction zones.
Candle coloring provides a visual shorthand for market conditions , useful for intraday scanning or historical backtesting.
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🧰 Configuration Guidance
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To tailor the indicator to your strategy:
Use Cloud lengths like 21, 34, 55, and 89 for a balanced multi-timeframe view.
Adjust the slope threshold (default 0.05) to control how sensitive the trend coloring is.
Set the spread floor (e.g., 0.15) to tune when compression is detected and visualized.
Choose your weighting style : Inverse Length (favor faster bands), Equal, or Max Pooling (most aggressive).
Set composite weights to emphasize trend slope, percentile bias, or compression—depending on your market edge.
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✅ Best Practices
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Use aligned Cloud colors across all bands to confirm trend conviction.
Combine slope direction with compression glow for early breakout entry setups.
In choppy markets, watch for Clouds 1 and 2 turning flat while Clouds 3 and 4 remain directional — a sign of potential trend exhaustion or consolidation.
Keep the table enabled during backtesting to manually evaluate how each Cloud behaved during price turns and consolidations.
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📌 License & Usage Terms
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This script is provided under the Creative Commons Attribution-NonCommercial 4.0 International License .
✅ You are allowed to:
Use this script for personal or educational purposes
Study, learn, and adapt it for your own non-commercial strategies
❌ You are not allowed to:
Resell or redistribute the script without permission
Use it inside any paid product or service
Republish without giving clear attribution to the original author
For commercial licensing , private customization, or collaborations, please contact Joshua Danford directly.
FFT Signal AnalyzerFFT Signal Analyzer
The FFT Signal Analyzer uses a simplified Fast Fourier Transform (FFT) approach to extract dominant cyclical components from price data. By detrending and applying adaptive smoothing, the indicator highlights frequency-driven signals that traditional indicators often miss.
This tool is ideal for traders who want to visualize cyclical market behavior, identify turning points, and confirm entries/exits with frequency-based momentum signals.
How it works:
Removes price trend via detrending (moving average subtraction)
Applies a bandpass filter (EMA) to isolate dominant frequency components
Normalizes the signal using a z-score for consistent visibility
Amplifies the signal for easy interpretation
Highlights slope changes with background coloring (green = rising, red = falling)
Use Cases:
Use zero-line crosses to detect cycle shifts or momentum pivots
Combine with trend filters (e.g., GRJMOM) for high-probability setups
Ideal for detecting underlying rhythm in sideways or oscillating markets
Best for:
Swing traders, scalpers, and cycle analysts looking for frequency-aware confirmation signals
Works on all timeframes and asset classes
TDPO-RSI (Time-Decaying Percentile RSI)TDPO-RSI (Time-Decaying Percentile RSI)
TDPO-RSI is a modern, statistically-enhanced momentum indicator that improves on traditional RSI by using percentile-based analysis with exponential time decay. Instead of averaging gains and losses equally, this indicator ranks them by size and weights recent data more heavily—resulting in a more responsive and noise-resistant signal.
How it works:
Calculates percentile rank of gains and losses over a lookback window
Applies a decay factor (lambda) to give more weight to recent price action
Outputs a percentile-based RSI value between 0 and 100
Optional smoothing via EMA for clearer crossover signals
Key Uses:
Identify overbought/oversold zones (default: 70/30)
Use raw vs. smoothed RSI crossovers for entries
Detect momentum shifts earlier than traditional RSI
Suitable for scalping, trend continuation, and reversal setups
Inputs:
Lookback Length: Number of bars used for percentile calculation
Decay Factor (lambda): How quickly older data fades in influence (0.80–0.99)
Smoothing EMA: Smooths the final output to reduce noise
Tip: Combine with price structure and volume for best results. Higher timeframes can be used for trend context, while lower timeframes help with precise entries.
This tool is ideal for traders who want adaptive momentum analysis rooted in statistical behavior.
