RSI with HMA & Momentum ZonesRSI with HMA & Momentum Zones — Indicator Description
This indicator combines Relative Strength Index (RSI) analysis with Hull Moving Averages (HMA) and Momentum Zone detection to provide a multi-layered view of market strength, trend shifts, and divergence signals.
It includes:
Main Features:
RSI Core:
Standard RSI calculated from a customizable source (close, open, etc.) with adjustable length.
A dynamic RSI Signal Line is plotted with selectable smoothing types (SMA, EMA, SMMA, WMA, VWMA) to enhance trend-following signals.
RSI crossovers of its signal line change color (green for bullish crossovers, red for bearish crossunders).
Hull Moving Averages (HMA):
Two HMA lines are plotted based on the RSI:
Short HMA (fast) and Long HMA (slow).
Color shifts indicate crossovers between RSI and Short HMA (short-term trend change) and Short HMA vs Long HMA (longer-term trend shifts).
Momentum Zones:
When the gap between the RSI and the Long HMA exceeds a user-defined threshold:
A green background highlights strong bullish momentum.
A red background highlights strong bearish momentum.
Helps visualize when momentum becomes extended.
Divergence Detection (Optional):
Regular and hidden bullish and bearish divergences are automatically detected between price and RSI.
Divergences are plotted on the RSI pane with labels ("Bull", "H Bull", "Bear", "H Bear").
Adjustable lookback settings for fine-tuning sensitivity.
Alerts are available for all divergence events.
Visual Enhancements:
A shaded cloud fills between RSI and its signal line, green for bullish bias and red for bearish bias.
Horizontal bands at 70, 50, and 30 levels to mark traditional RSI zones (overbought, neutral, oversold).
Customization Options:
All major components — RSI settings, Signal Line type, HMA lengths, Momentum Zone threshold, and Divergence controls — are fully adjustable.
Cari dalam skrip untuk "momentum"
RSI-Volume Momentum Signal ScoreRSI-Volume Momentum Signal Score
Description
The RSI-Volume Momentum Signal Score is a predictive technical indicator designed to identify bullish and bearish momentum shifts by combining volume-based momentum with the Relative Strength Index (RSI). It generates a Signal Score derived from:
• The divergence between short-term and long-term volume (Volume Oscillator), and
• RSI positioning relative to a user-defined threshold.
This hybrid approach helps traders detect early signs of price movement based on volume surges and overbought/oversold conditions.
The Signal Score is computed as follows:
Signal Score = Volume Momentum x RSI Divergence Factor
Volume Momentum = tanh ((Volume Oscillator value (vo) – Volume Threshold)/Scaling Factor)
RSI Divergence Factor = ((RSI Threshold – RSI Period)/Scaling Factor)
Or,
Signal Score = tanh((vo - voThreshold) / scalingFactor) * ((rsiThreshold - rsi) / scalingFactor)
The logic of this formula are as follows:
• If Volume Oscillator >= Volume Threshold and RSI <= RSI Threshold: Bullish Signal (+1 x Scaling Factor)
• If Volume Oscillator >= Volume Threshold and RSI >= (100 – RSI Threshold): Bearish Signal (-1 x Scaling Factor)
• Otherwise: Neutral (0)
The tanh function provides the normalization process. It ensures that the final signal score is bounded between -1 and 1, increases sensitivity to early changes in volume patterns based on RSI conditions, and prevent sudden jumps in signals ensuring smooth and continuous signal line.
Input Fields
The input fields allow users to customize the behavior of the indicator based on their trading strategy:
Short-Term Volume MA
- Default: `2`
- Description: The period for the short-term moving average of volume.
- Purpose: Captures short-term volume trends.
Long-Term Volume MA)
- Default: `10`
- Description: The period for the long-term moving average of volume.
- Purpose: Captures long-term volume trends for comparison with the short-term trend.
RSI Period)
- Default: `3`
- Description: The period for calculating the RSI.
- Purpose: Measures the relative strength of price movements over the specified period.
Volume Oscillator Threshold
- Default: `70`
- Description: The threshold for the Volume Oscillator to determine significant volume momentum.
- Purpose: Filters out weak volume signals.
RSI Threshold
- Default: `25`
- Description: The RSI level used to identify overbought or oversold conditions.
- Purpose: Helps detect potential reversals in price momentum.
Signal Scaling Factor
- Default: `10`
- Description: A multiplier for the signal score.
- Purpose: Adjusts the magnitude of the signal score for better visualization.
How To Use It for Trading:
Upcoming Bullish Signal: Signal line turns from Gray to Green or from Green to Gray
Upcoming Bearish Signal: Signal line turns from Gray to Red or from Red to Gray
Note: The price that corresponds to the transition of Signal line from Gray to Green or Red and vise versa is the signal price for upcoming bullish or bearish signal.
The signal score dynamically adjusts based on volume and RSI thresholds, making it adaptable to various market conditions, and this is what makes the indicator unique from other traditional indicators.
Unique Features
Unlike traditional indicators, this indicator combines two different dimensions—volume trends and RSI divergence—for more comprehensive signal generation. The use of tanh() to scale and smooth the signal is a mathematically elegant way to manage signal noise and highlight genuine trends. Traders can tune the scaling factor and thresholds to adapt the indicator for scalping, swing trading, or longer-term investing.
MACD Volume Strategy (BBO + MACD State, Reversal Type)Overview
MACD Volume Strategy (BBO + MACD State, Reversal Type) is a momentum-based reversal system that combines MACD crossover logic with volume filtering to enhance signal accuracy and minimize noise. It aims to identify structural trend shifts and manage risk using predefined parameters.
※This strategy is for educational and research purposes only. All results are based on historical simulations and do not guarantee future performance.
Strategy Objectives
Identify early trend transitions with high probability
Filter entries using volume dynamics to validate momentum
Maintain continuous exposure using a reversal-style model
Apply a consistent 1:1.5 risk-to-reward ratio per trade
Key Features
Integrated MACD and volume oscillator filtering
Zero repainting (all signals confirmed on closed candles)
Automatic position flipping for seamless direction shifts
Stop-loss and take-profit based on recent structural highs/lows
Trading Rules
Long Entry Conditions
MACD crosses above the zero line (BBO Buy arrow)
Volume oscillator is positive (short EMA > long EMA)
MACD is above the signal line
Close any existing short and enter a new long
Short Entry Conditions
MACD crosses below the zero line (BBO Sell arrow)
Volume oscillator is positive
MACD is below the signal line
Close any existing long and enter a new short
Exit Rules
Take Profit (TP) = Entry ± (risk distance × 1.5)
Stop Loss (SL) = Recent swing low (for long) or high (for short)
Early Exit = Triggered when a reversal signal appears (flip logic)
Risk Management Parameters
Pair: ETH/USD
Timeframe: 10-minute
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted for sustainable practice)
Total Trades: 312 (backtest on selected dataset)
※Risk parameters are fully configurable and should be adjusted to suit each trader's personal setup and broker conditions.
Parameters & Configurations
Volume Short Length: 6
Volume Long Length: 12
MACD Fast Length: 11
MACD Slow Length: 21
Signal Smoothing: 10
Oscillator MA Type: SMA
Signal Line MA Type: SMA
Visual Support
Green arrow = Long entry
Red arrow = Short entry
MACD lines, signal line, and histogram
SL/TP markers plotted directly on the chart
Strategic Advantages & Uniqueness
Volume filtering eliminates low-participation, weak signals
Structurally aligned SL/TP based on recent market pivots
No repainting — decisions are made only on closed candles
Always in the market due to the reversal-style framework
Inspirations & Attribution
This strategy is inspired by the excellent work of:
Bitcoinblockchainonline – “BBO_Roxana_Signals MACD + vol”
Leveraging MACD zero-line cross and volume oscillator for intuitive signal generation.
HasanRifat – “MACD Fake Filter ”
Introduced a signal filter using MACD wave height averaging to reduce false positives.
This strategy builds upon those ideas to create a more automated, risk-aware, and technically adaptive system.
Summary
MACD Volume Strategy is a clean, logic-first automated trading system built for precision-seeking traders. It avoids discretionary bias and provides consistent signal logic under backtested historical conditions.
100% mechanical — no discretionary input required
Designed for high-confidence entries
Can be extended with filters, alerts, or trailing stops
※Strategy performance depends on market context. Past performance is not indicative of future results. Use with proper risk management and careful configuration.
Range Tightening Indicator (RTI)The Range Tightening Indicator (RTI) quantifies price volatility relative to recent price action, helping traders identify low-volatility consolidations that often precede breakouts.
Range Tightening is calculated by measuring the range between each bar’s high and low prices over a chosen lookback period.
A 5-bar period is recommended for shorter-term momentum setups and a 15-bar period is recommended for swing trading. An option for a custom period is available to suit specific strategies. The default look back for custom is 50, ideal for longer term traders.
Other Key Features:
Dynamic Color Coding: The RTI line turns green when volatility doubles after a drop to or below 20, flagging significant volatility shifts commonly seen before breakouts.
Low-Volatility Dots: Orange dots appear on the RTI line when two or more consecutive bars show RTI values below 20, visually marking extended low-volatility periods.
Volatility Zones: Shaded zones provide quick context:
Zone 1 (0-5): Extremely tight volatility, shown in red.
Zone 2 (5-10): Low volatility, shown in light green.
Zone 3 (10-15): Moderate low volatility, shown in green.
The RTI indicator is ideal for traders looking to anticipate breakout conditions, with features that highlight consolidation phases, support momentum strategies, and help improve entry timing by focusing on shifts in volatility.
This indicator was inspired after Deepvue's RMV Indicator, but uses a different calculation. Results may vary.
Aggressor Volume ImbalanceAggressor volume imbalance represents the ratio between market aggressor buy volume (market buy orders) and market aggressor sell volume (market sell orders). This ratio enables traders to evaluate the interest of market aggressors and whether aggressive market activity favours the price's direction.
Analysing aggressor volume is critical in understanding market sentiment and aids in identifying shifts in momentum and potential exhaustion points in the market. When the aggressor buy volume significantly exceeds the sell volume, it typically indicates strong buying interest, driving prices higher if the offer-side liquidity cannot contain it, and vice versa.
How it Works
The imbalance ratio is calculated as follows, according to the selected session timeframe (see settings):
imbalance := ((buyVolumeAccumulator - sellVolumeAccumulator)
/ (buyVolumeAccumulator + sellVolumeAccumulator)) * 100
Aggressive Volume Imbalance uses lower timeframe historical data to calculate Historical Aggressor Volume Imbalances, while live data is used for live aggressor volume imbalances.
How to Use It
You can set the indicator to use any historical data timeframe you prefer. However, it is highly recommended to use lower timeframes (e.g., 1 second), as the lower the timeframe, the more granular the data.
The indicator resets to 0% whenever a new session timeframe begins (e.g., a new day) and calculates new values for the rest of the session. This can be configured in the settings.
Shadow Range IndexShadow Range Index (SRI) introduces a new concept to calculate momentum, shadow range.
What is range?
Traditionally, True Range (TR) is the current high minus the current low of each bar in the timeframe. This is often used successfully on its own in indicators, or as a moving average in ATR (Average True Range).
To calculate range, SRI uses an innovative calculation of current bar range that also considers the previous bar. It calculates the difference between its maximum upward and maximum downward values over the number of bars the user chooses (by adjusting ‘Range lookback’).
What is shadow range?
True Range (TR) uses elements in its calculation (the highs and lows of the bar) that are also visible on the chart bars. Shadow range does not, though.
SRI calculates shadow range in a similar formula to range, except that this time it works out the difference between the minimum upward and minimum downward movement. This movement is by its nature less than the maximums, hence a shadow of it. Although more subtle, shadow range is significant, because it is quantifiable, and goes in one direction or another.
Finally, SRI smoothes shadow range and plots it as a histogram, and also smoothes and plots range as a signal line. Useful up and down triangles show trend changes, which optionally colour the chart bars.
Here’s an example of a long trade setup:
In summary, Shadow Range Index identifies and traces maximum and minimum bar range movement both up and down, and plots them as centred oscillators. The dynamics between the two can provide insights into the chart's performance and future direction.
Credit to these authors, whose MA or filters form part of this script:
@balipour - Super Smoother MA
@cheatcountry - Hann window smoothing
@AlgoAlpha - Gaussian filter
FX DispersionThis script calculates the dispersion of a basket of 5 FX pairs and then calculates the z-score the z-score is then made into a composite using the 30 and 60 ema of the z-score to smooth any noise. It must be used on one of the FX pairs in the basket and on the 1-minute timeframe as it has been hardcoded for 1 min use below.
Interpretation - Dispersion is a component of volatility - the dispersion of the underlying basket increases above 0.5 and decreases below 0.5.
Although increased dispersion is beneficial to momentum and trend-following strategies on the monthly and weekly timeframes. Observe this on the 1-minute timeframe and how dispersion crossing above/ below 0.5 it can signal reversion or momentum for the next period.
TASC 2023.12 Growth and Value Switching System█ OVERVIEW
This script implements a rotation system for trading value and growth ETFs, as developed by Markos Katsanos and detailed in the article titled 'Growth Or Value?' in TASC's December 2023 edition of Traders' Tips . The purpose of this script is to demonstrate how short-term momentum can be employed to track market trends and provide clarity on when to switch between value and growth.
█ CONCEPTS
The central concept of the presented rotation strategy is based on the observation that the stock market undergoes cycles favoring either growth or value stocks. Consequently, the script introduces a momentum trading system that is designed to switch between value and growth equities based on prevailing market conditions. Specifically tailored for long-term index investors, the system focuses on trading Vanguard's value and growth ETFs ( VTV and VUG ) on a weekly timeframe.
To identify the ETF likely to outperform, the script uses a custom relative strength indicator applied to both VTV and VUG in comparison with an index ( SPY ). To minimize risk and drawdowns during bear markets, when both value and growth experience downtrends, the script employs the author's custom volume flow indicator (VFI) and blocks trades when its reading indicates money outflow . Positions are closed if the relative strength of the current open trade ETF falls below that of the other ETF for two consecutive weeks and is also below its moving average. Additionally, the script implements a stop-loss when the ETF is trading below its 40-week moving average, but only during bear markets.
The script plots the relative strengths of the value and growth equities along with the signals triggered by the aforementioned rules. Information about the current readings of the relative strength and volume flow indicators, along with the current open position, is displayed in a table.
█ CALCULATIONS
The script uses the request.security() function to gather price data for both equities and the reference index. Custom relative strength and volume flow indicators are calculated based on the formulas presented in the original article. By default, the script employs the same parameters for these indicators as proposed in the original article for VTV and VUG on a weekly timeframe.
Machine Learning Momentum Oscillator [ChartPrime]The Machine Learning Momentum Oscillator brings together the K-Nearest Neighbors (KNN) algorithm and the predictive strength of the Tactical Sector Indicator (TSI) Momentum. This unique oscillator not only uses the insights from TSI Momentum but also taps into the power of machine learning therefore being designed to give traders a more comprehensive view of market momentum.
At its core, the Machine Learning Momentum Oscillator blends TSI Momentum with the capabilities of the KNN algorithm. Introducing KNN logic allows for better handling of noise in the data set. The TSI Momentum is known for understanding how strong trends are and which direction they're headed, and now, with the added layer of machine learning, we're able to offer a deeper perspective on market trends. This is a fairly classical when it comes to visuals and trading.
Green bars show the trader when the asset is in an uptrend. On the flip side, red bars mean things are heading down, signaling a bearish movement driven by selling pressure. These color cues make it easier to catch the sentiment and direction of the market in a glance.
Yellow boxes are also displayed by the oscillator. These boxes highlight potential turning points or peaks. When the market comes close to these points, they can provide a heads-up about the possibility of changes in momentum or even a trend reversal, helping a trader make informed choices quickly. These can be looked at as possible reversal areas simply put.
Settings:
Users can adjust the number of neighbours in the KNN algorithm and choose the periods they prefer for analysis. This way, the tool becomes a part of a trader's strategy, adapting to different market conditions as they see fit. Users can also adjust the smoothing used by the oscillator via the smoothing input.
Support and Resistance Oscillator [CC]The Support and Resistance Oscillator is an experimental script I created to identify when the current price breaks a support or resistance line and reflect this value in an oscillator formula. This indicator uses a threshold to decide the dividing line between buying and selling points. Feel free to change the threshold or smoothing settings to see if you find anything better since this is so experimental. I'm double smoothing the difference between the indicator and its signal line to attempt to capture a combo of the price momentum combined with the general support and resistance levels. I have used dark colors for strong signals and lighter colors for normal signals and make sure to buy when the line turns green and sell when it turns red.
Let me know if there are any other scripts or indicators you would like to see me publish!
WillyCycle Oscillator&DoubleMa/ErkOzi/version 2This oscillator can be customized by adjusting the length of the Willy period, the length of Willy's EMA, and the upper and lower bands. The upper and lower bands help traders identify overbought and oversold conditions.
The WillyCycle Oscillator is a technical analysis tool used to measure the momentum of an asset and identify overbought and oversold conditions based on the price range of a specific period and calculating the percentage of the closing price in that range. The WillyCycle Oscillator consists of two main components: Willy and Willy's EMA. The Willy component is the percentage calculation of the asset's price range, and Willy's EMA is the exponential moving average of the Willy component. Willy's EMA is used to smooth out the Willy component and make it easier to identify trends.
*** When the oscillator is above the 80 level, it indicates that the asset is overbought, and when it is below the 20 level, it indicates that the asset is oversold. Traders can use these levels as a guide for buying and selling signals.
***Traders can also use the WillyCycle Oscillator to identify trend reversals. When the oscillator rises above the 50 level, it signals a potential uptrend, and when it falls below the 50 level, it signals a potential downtrend.
***I have added a smoothed line option to the WillyCycle Oscillator, which allows traders to see a more smoothed version of the oscillator. This option can be enabled by setting the 'smoothed' input to true. The default value for the smoothed line is 15.
***We have also changed the value range of the WillyCycle Oscillator from -100 to 100 to 0 to 100. This change was made to make the oscillator more user-friendly and easier to read.
In conclusion, the WillyCycle Oscillator is a versatile tool that can help traders identify potential trading opportunities and trend reversals. Traders can customize the oscillator to fit their trading style and preferences. Adding a smoothed line and changing the value range can enhance the user experience and make the oscillator easier to use.
Adaptive Fisherized ROCIntroduction
Hello community, here I applied the Inverse Fisher Transform, Ehlers dominant cycle determination and smoothing methods on a simple Rate of Change (ROC) indicator
You have a lot of options to adjust the indicator.
Usage
The rate of change is most often used to measure the change in a security's price over time.
That's why it is a momentum indicator.
When it is positive, prices are accelerating upward; when negative, downward.
It is useable on every timeframe and could be a potential filter for you your trading system.
IMO it could help you to confirm entries or find exits (e.g. you have a long open, roc goes negative, you exit).
If you use a trend-following strategy, you could maybe look out for red zones in an in uptrend or green zones in a downtrend to confirm your entry on a pullback.
Signals
ROC above 0 => confirms bullish trend
ROC below 0 => confirms bearish trend
ROC hovers near 0 => price is consolidating
Enjoy! 🚀
Delta-RSI Strategy (with filters)Delta-RSI Strategy (with filters):
This is a version of the Delta-RSI Oscillator strategy with several criteria available to filter entry and exit signals. This script is also suitable for backtesting over a user-defined period and offers several risk management options (take profit and stop loss).
Since the publication of the Delta-RSI Oscillator script, I have been asked many times to make it compatible with the Strategy Tester and add filtering criteria to minimize "false" signals. This version covers many of these requests. Feel free to insert your favorite D-RSI parameters and play around!
ABOUT DELTA-RSI
Delta-RSI represents a smoothed time derivative of the RSI designed as a momentum indicator (see links below):
INPUT DESCTIPTION
MODEL PARAMETERS
Polynomial Order : The order of local polynomial used to interpolate the relative strength index (RSI).
Length : The length of the lookback frame where local regression is applied.
RSI Length : The timeframe of RSI used as input.
Signal Length : The signal line is a EMA of the D-RSI time series. This input parameter defines the EMA length.
ALLOWED ENTRIES
The strategy can include long entries, short entries or both.
ENTRY AND EXIT CONDITIONS
Zero-crossing : bullish trade signal triggered when D-RSI crosses zero from negative to positive values (bearish otherwise)
Signal Line Crossing : bullish trade signal triggered when D-RSI crosses from below to above the signal line (bearish otherwise)
Direction Change : bullish trade signal triggered when D-RSI was negative and starts ascending (bearish otherwise)
APPLY FILTERS TO
The filters (described below) can be applied to long entry, short entry and exit signals.
RELATIVE VOLUME FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the current volume is greater than N times the average over the last M bars.
VOLATILITY FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the N-period average true range, ATR, is greater than the M-period ATR. If N < M, this condition implies increasing volatility.
OVERBOUGHT/OVERSOLD FILTER
When activated, the D-RSI-driven entries and exits will be triggered only if the value of 14-period RSI is in the range between N and M.
STOP LOSS/TAKE PROFIT
Fixed and trailing stop loss as well as take profit options are available.
FIXED BACKTESTING START/END DATES
If the checkboxes are not checked, the strategy will backtest all available price bars.
+ BB %B: MA selection, bar coloring, multi-timeframe, and alerts+ %B is, at its simplest, the classic Bollinger Bands %B indicator with a few added bells and whistles.
However, the right combination of bells and whistles will often improve and make a more adaptable indicator.
Classically, Bollinger Bands %B is an indicator that measures volatility, and the momentum and strength of a trend, and/or price movements.
It shows "overbought" and "oversold" spots on a chart, and is also useful for identifying divergences between price and trend (similar to RSI).
With + %B I've added the options to select one or two moving averages, candle coloring, and a host of others.
Let's start with the moving averages:
There are options for two: one faster and one slower. Or combine them how you will, or omit one or both of them entirely.
Here you will find options for SMA, EMA (as well as double and triple), Hull MA, Jurik MA, Least Squares MA, Triangular MA, Volatility Adjusted MA, and Weighted MA.
A moving average essentially helps to define trend by smoothing the noise of movements of the underlying asset, or, in this case, the output of the indicator.
All of these MAs available track this in a different way, and it's up to the trader to figure out which makes most sense to him/her.
MA's, in my opinion, improve the basic %B by providing a clearer picture of what the indicator is actually "seeing", and may be useful for providing entries and exits.
Next up is candle coloring:
I've added the option for this indicator to color candles on the chart based on where the %B is in relation to its upper and lower bounds, and median line.
If the %B is above the median but below the upper bound, candles will be green (showing bullish market structure). If %B is below the median but above the lower bound, candles will be red (denoting bearish market structure).
Overbought and oversold candles will also be colored on the chart, so that a quick glance will tell you whether price action is bullish/bearish or "oversold"/"overbought".
I've also added functionality that enables candles to be colored based on if the %B has crossed up or crossed down the primary moving average.
One example as a way to potentially use these features is if the candles are showing oversold coloration followed by the %B crossing up your moving average coloration. You might consider a long there (or exit a short position if you are short).
And the last couple of tweaks:
You may set the timeframe to whatever you wish, so maybe you're trading on the hourly, but you want to know where the %B is on the 4h chart. You can do that.
The background fill for the indicator is split into bullish and bearish halves. Obviously you may turn the background off, or make it all one color as well.
I've also added alerts, so you may set alerts for "overbought" and "oversold" conditions.
You may also set alerts for %B crossing over or under the primary moving average, or for crossing the median line.
All of these things may be turned on and off. You can pretty much customize this to your heart's delight. I see no reason why anyone would use the standard %B after playing with this.
I am no coder. I had this idea in my head, though, and I made it happen through referencing another indicator I was familiar with, and watching tutorials on YouTube.
Credits:
Firstly, thanks to www.tradingview.com for his brilliant, free tutorials on YouTube.
Secondly, thanks to www.tradingview.com for his beautiful SSL Hybrid indicator (and his clean code) from which I obtained the MAs.
Please enjoy this indicator, and I hope that it serves you well. :)
Customizable Percentage Price Oscillator (PPO)The PPO is basically the MACD but in percentage terms. This is better for comparing momentum across different securities.
This script is a standard PPO but with many options for customization. You can set the moving average type of the signal and the oscillator lines separately. You can also weight any moving average of the PPO by volume.
Supported Types of MA:
SMA
EMA
ALMA
HMA
WMA
Personally, I believe weighting by volume is helpful across markets but especially helpful for equities. I like to use 3,10,16 settings similar to Linda Raschke but with EMA instead of SMA. This indicator is especially useful for signaling trend continuation and generating exit signals. For entries, I believe this indicator should not be blindly followed and works better when combined with a trend or price action signal.
If there are requests for more types of moving average to be used with the PPO, I would be down to implement them, but I believe most moving averages are pretty similar.
Smooth First Derivative IndicatorIntroducing the Smooth First Derivative indicator. For each time step, the script numerically differentiates the price data using prior datapoints from the look-back window. The resulting time derivative (the rate of price change over time) is presented as a centered oscillator.
A first derivative is a versatile tool used in functional data analysis. When applied to price data, it can be applied to analyze momentum, confirm trend direction, and identify pivot points.
Model Description:
The model assumes that, within the look-back window, price data can be well approximated by a smooth differentiable function. The first derivative can then be computed numerically using a noise-robust one-sided differentiator. The current version of the script employs smooth differentiators developed by P. Holoborodko (www.holoborodko.com). Note that the Indicator should not be confused with Constance Brown's Derivative Oscillator.
Input parameter:
The Bandwidth parameter sets the number of points in the moving look-back window and thus determines the smoothness of the first derivative curve. Note that a smoother Indicator shows a greater lag.
Interpretation:
When using this Indicator, one should recall that the first derivative can simply be interpreted as the slope of the curve:
- The maximum (minimum) in the Indicator corresponds to the point at which the market experiences the maximum upward (downward) slope, i.e., the inflection point. The steeper the slope, the greater the Indicator value.
- The positive-to-negative zero-crossing in the Indicator suggests that the market has formed a local maximum (potential start of a downtrend or a period of consolidation). Likewise, a zero-crossing from negative to positive is a potential bullish signal.
MA MTF Momentum HistogramMy own interpretation indicator which i call multi time frame moving averages momentum with NO LAG EMA support (Optional).
The indicator is calculated by subtracting the long-term EMA from the short-term EMA .
This pretty much resembles the MACD moving averages calculation but without the smoothing of the histogram.
Can also be used to find divergences.
The background shows the main trend with higher time frame which can be set in the settings.
Aimed to use with Higher time frame (Double or more) but can also work with lower time frame.
How to use the indicator?
==Histogram==
Green: Momentum of asset is positive and increasing.
Lighter Green: Momentum of asset is still positive but decreasing and can revert to negative momentum.
Red: Momentum of asset is negative and increasing.
Lighter Red: Momentum of asset is still negative but increasing and revert to positive momentum.
==Background Color - Main Trend==
Green: HTF (Higher time frame) momentum is positive.
RED: HTF momentum is negative.
Feel free to comment and Follow to stay updated with upcoming scripts: www.tradingview.com
NOTE: BARS ARE COLORED BY DEFAULT WITH HISTOGRAM COLORS! (Can be changed in settings)
Stochastic Heat MapA series of 28 stochastic oscillators plotted horizontally and stacked vertically from bottom to top as the oscillator background.
Each oscillator has been interpreted and the value has been used to colour the lines in.
Lower lines are shorter term stochastics and higher lines are longer term stochastics.
The average of the 28 stochastics has been taken and then used to plot the fast oscillator line, which also has a slow oscillator line to follow.
The oscillator line can be used to colour in the candles.
Inputs:
MA: multiple smoothing methods
Theme: multiple colours
Increment: stochastic length start and increments
Smooth Fast: smooth fast length
Smooth Slow: smooth slow length
Paint Bars: colour candles
Waves: toggle method to weight/increment stochastics
Heat map shows momentum extremes:
Trend Lines for RSI, CCI, Momentum, OBVHello Traders!
After publishing Trend Lines for RSI yesterday, I realized that Trend Lines for more indicators needed by the traders. so I decided to make it for four different indicators: RSI, CCI, OBV, Momentum
In the indicator options you can choose the indicator from pull-down menu.
How it works?
- On each bar it finds last 10 higher and lower Pivot Points (PP) for the indicator.
- from first bar to 10. Pivot Point it searchs if a trend line is possible
- for each PP it starts searching from the last PP .
- it checks if drawing a trend line possible or not and also it's broken or not
- if it's broken then optionally it shows broken trend lines as dotted (or you can option not to see broken lines)
- if it finds a continues trend line then it stops searhing more and draw trend line, this is done by checking angles (I did this to make the script faster, otherwise you may get error because of it needs time more than .2sec)
- the script makes this process for each PP
- then shows the trend lines
P.S. it may need 3-10 seconds when you added the script to the chart at first (because of calculations)
Trend lines for CCI:
Trend Lines for OBV
Trend Lines for Momentum:
You may want to watch how Trend Lines script works (that was made for RSI)
s3.tradingview.com
If you still didn't see Trend Lines v2 then visit:
All Comments are welcome..
Enjoy!
[BTX] TRIX + MA combined indicator (open version)This indicator combines TRIX and MA of TRIX in one. You can choose which type of moving average line to be used (EMA or SMA).
Default values are 12 periods for TRIX and 10 periods for MA/TRIX, which helps better response to price movement.
This indicator can use in all markets, all timeframes. This is an update to my indicator, which is a protected script. You can find it at the link: .
What is the TRIX (Triple Exponential Average) indicator?
TRIX is a momentum oscillator that displays the percent rate of change of a triple exponentially smoothed moving average. It was developed in the early 1980s by Jack Hutson, an editor for 'Technical Analysis of Stocks and Commodities' magazine. With its triple smoothing, TRIX is designed to filter out insignificant price movements. Chartists can use TRIX to generate signals similar to MACD. A signal line can be applied to look for signal line crossovers. A directional bias can be determined with the absolute level. Bullish and bearish divergences can be used to anticipate reversals.
McClellan Oscillator [LazyBear]Developed by Sherman and Marian McClellan, the McClellan Oscillator is a breadth indicator derived from Net Advances, the number of advancing issues less the number of declining issues. Subtracting the 39-day exponential moving average of Net Advances from the 19-day exponential moving average of Net Advances forms the oscillator.
As the formula reveals, the McClellan Oscillator is a momentum indicator that works similar to MACD.
McClellan Oscillator signals can be generated with breadth thrusts, centerline crossovers, overall levels and divergences.
I have added the following options:
- Can choose Advancing/Declining issues of any market. Default is NYSE.
- Can show the EMAs and/or oscillator.
- Ratio Adjusted Calculation mode (as explained in the stockcharts link below) or default mode.
- Can use custom timeframe. Default is chart timeframe.
More info:
stockcharts.com
Complete list of my indicators:
docs.google.com
Thanks @mpinky for pointing out the StockCharts version of this oscillator.
Squeeze Pro Momentum BAR color - KLTDescription:
The Squeeze Pro Momentum indicator is a powerful tool designed to detect volatility compression ("squeeze" zones) and visualize momentum shifts using a refined color-based system. This script blends the well-known concepts of Bollinger Bands and Keltner Channels with an optimized momentum engine that uses dynamic color gradients to reflect trend strength, direction, and volatility.
It’s built for traders who want early warning of potential breakouts and clearer insight into underlying market momentum.
🔍 How It Works:
📉 Squeeze Detection:
This indicator identifies "squeeze" conditions by comparing Bollinger Bands and Keltner Channels:
When Bollinger Bands are inside Keltner Channels → Squeeze is ON
When Bollinger Bands expand outside Keltner Channels → Squeeze is OFF
You’ll see squeeze zones classified as:
Wide
Normal
Narrow
Each represents varying levels of compression and breakout potential.
⚡ Momentum Engine:
Momentum is calculated using linear regression of the price's deviation from a dynamic average of highs, lows, and closes. This gives a more accurate representation of directional pressure in the market.
🧠 Smart Candle Coloring (Optimized):
The momentum color logic is inspired by machine learning principles (no hardcoded thresholds):
EMA smoothing and rate of change (ROC) are used to detect momentum acceleration.
ATR-based filters help remove noise and false signals.
Colors are dynamically assigned based on both direction and trend strength.
🧪 How to Use It:
Look for Squeeze Conditions — especially narrow squeezes, which tend to precede high-momentum breakouts.
Confirm with Momentum Color — strong colors often indicate trend continuation; fading colors may signal exhaustion.
Combine with Price Action — use this tool with support/resistance or patterns for higher probability setups.
Recommended For:
Trend Traders
Breakout Traders
Volatility Strategy Users
Anyone who wants visual clarity on trend strength
📌 Tip: This indicator works great when layered with volume and price action patterns. It is fully non-repainting and supports overlay on price charts.
Magnificent 7 OscillatorThe Magnificent 7 Oscillator is a sophisticated momentum-based technical indicator designed to analyze the collective performance of the seven largest technology companies in the U.S. stock market (Apple, Microsoft, Alphabet, Amazon, NVIDIA, Tesla, and Meta). This indicator incorporates established momentum factor research and provides three distinct analytical modes: absolute momentum tracking, equal-weighted market comparison, and relative performance analysis. The tool integrates five different oscillator methodologies and includes advanced breadth analysis capabilities.
Theoretical Foundation
Momentum Factor Research
The indicator's foundation rests on seminal momentum research in financial markets. Jegadeesh and Titman (1993) demonstrated that stocks with strong price performance over 3-12 month periods tend to continue outperforming in subsequent periods¹. This momentum effect was later incorporated into formal factor models by Carhart (1997), who extended the Fama-French three-factor model to include a momentum factor (UMD - Up Minus Down)².
The momentum calculation methodology follows the academic standard:
Momentum(t) = / P(t-n) × 100
Where P(t) is the current price and n is the lookback period.
The focus on the "Magnificent 7" stocks reflects the increasing market concentration observed in recent years. Fama and French (2015) noted that a small number of large-cap stocks can drive significant market movements due to their substantial index weights³. The combined market capitalization of these seven companies often exceeds 25% of the total S&P 500, making their collective momentum a critical market indicator.
Indicator Architecture
Core Components
1. Data Collection and Processing
The indicator employs robust data collection with error handling for missing or invalid security data. Each stock's momentum is calculated independently using the specified lookback period (default: 14 periods).
2. Composite Oscillator Calculation
Following Fama-French factor construction methodology, the indicator offers two weighting schemes:
- Equal Weight: Each active stock receives identical weighting (1/n)
- Market Cap Weight: Reserved for future enhancement
3. Oscillator Transformation Functions
The indicator provides five distinct oscillator types, each with established technical analysis foundations:
a) Momentum Oscillator (Default)
- Pure rate-of-change calculation
- Centered around zero
- Direct implementation of Jegadeesh & Titman methodology
b) RSI (Relative Strength Index)
- Wilder's (1978) relative strength methodology
- Transformed to center around zero for consistency
- Scale: -50 to +50
c) Stochastic Oscillator
- George Lane's %K methodology
- Measures current position within recent range
- Transformed to center around zero
d) Williams %R
- Larry Williams' range-based oscillator
- Inverse stochastic calculation
- Adjusted for zero-centered display
e) CCI (Commodity Channel Index)
- Donald Lambert's mean reversion indicator
- Measures deviation from moving average
- Scaled for optimal visualization
Operational Modes
Mode 1: Magnificent 7 Analysis
Tracks the collective momentum of the seven constituent stocks. This mode is optimal for:
- Technology sector analysis
- Growth stock momentum assessment
- Large-cap performance tracking
Mode 2: S&P 500 Equal Weight Comparison
Analyzes momentum using an equal-weighted S&P 500 reference (typically RSP ETF). This mode provides:
- Broader market momentum context
- Size-neutral market analysis
- Comparison baseline for relative performance
Mode 3: Relative Performance Analysis
Calculates the momentum differential between Magnificent 7 and S&P 500 Equal Weight. This mode enables:
- Sector rotation analysis
- Style factor assessment (Growth vs. Value)
- Relative strength identification
Formula: Relative Performance = MAG7_Momentum - SP500EW_Momentum
Signal Generation and Thresholds
Signal Classification
The indicator generates three signal states:
- Bullish: Oscillator > Upper Threshold (default: +2.0%)
- Bearish: Oscillator < Lower Threshold (default: -2.0%)
- Neutral: Oscillator between thresholds
Relative Performance Signals
In relative performance mode, specialized thresholds apply:
- Outperformance: Relative momentum > +1.0%
- Underperformance: Relative momentum < -1.0%
Alert System
Comprehensive alert conditions include:
- Threshold crossovers (bullish/bearish signals)
- Zero-line crosses (momentum direction changes)
- Relative performance shifts
- Breadth Analysis Component
The indicator incorporates market breadth analysis, calculating the percentage of constituent stocks with positive momentum. This feature provides insights into:
- Strong Breadth (>60%): Broad-based momentum
- Weak Breadth (<40%): Narrow momentum leadership
- Mixed Breadth (40-60%): Neutral momentum distribution
Visual Design and User Interface
Theme-Adaptive Display
The indicator automatically adjusts color schemes for dark and light chart themes, ensuring optimal visibility across different user preferences.
Professional Data Table
A comprehensive data table displays:
- Current oscillator value and percentage
- Active mode and oscillator type
- Signal status and strength
- Component breakdowns (in relative performance mode)
- Breadth percentage
- Active threshold levels
Custom Color Options
Users can override default colors with custom selections for:
- Neutral conditions (default: Material Blue)
- Bullish signals (default: Material Green)
- Bearish signals (default: Material Red)
Practical Applications
Portfolio Management
- Sector Allocation: Use relative performance mode to time technology sector exposure
- Risk Management: Monitor breadth deterioration as early warning signal
- Entry/Exit Timing: Utilize threshold crossovers for position sizing decisions
Market Analysis
- Trend Identification: Zero-line crosses indicate momentum regime changes
- Divergence Analysis: Compare MAG7 performance against broader market
- Volatility Assessment: Oscillator range and frequency provide volatility insights
Strategy Development
- Factor Timing: Implement growth factor timing strategies
- Momentum Strategies: Develop systematic momentum-based approaches
- Risk Parity: Use breadth metrics for risk-adjusted portfolio construction
Configuration Guidelines
Parameter Selection
- Momentum Period (5-100): Shorter periods (5-20) for tactical analysis, longer periods (50-100) for strategic assessment
- Smoothing Period (1-50): Higher values reduce noise but increase lag
- Thresholds: Adjust based on historical volatility and strategy requirements
Timeframe Considerations
- Daily Charts: Optimal for swing trading and medium-term analysis
- Weekly Charts: Suitable for long-term trend analysis
- Intraday Charts: Useful for short-term tactical decisions
Limitations and Considerations
Market Concentration Risk
The indicator's focus on seven stocks creates concentration risk. During periods of significant rotation away from large-cap technology stocks, the indicator may not represent broader market conditions.
Momentum Persistence
While momentum effects are well-documented, they are not permanent. Jegadeesh and Titman (1993) noted momentum reversal effects over longer time horizons (2-5 years).
Correlation Dynamics
During market stress, correlations among the constituent stocks may increase, reducing the diversification benefits and potentially amplifying signal intensity.
Performance Metrics and Backtesting
The indicator includes hidden plots for comprehensive backtesting:
- Individual stock momentum values
- Composite breadth percentage
- S&P 500 Equal Weight momentum
- Relative performance calculations
These metrics enable quantitative strategy development and historical performance analysis.
References
¹Jegadeesh, N., & Titman, S. (1993). Returns to buying winners and selling losers: Implications for stock market efficiency. Journal of Finance, 48(1), 65-91.
Carhart, M. M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.
Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
Wilder, J. W. (1978). New concepts in technical trading systems. Trend Research.
