Momentum adjusted Moving Average by DGTA brand new Moving Average , calculated using Momentum, Acceleration and Probability (Psychological Effect).
Momentum adjusted Moving Average(MaMA) is an indicator that measures Price Action by taking into consideration not only Price movements but also its Momentum, Acceleration and Probability. MaMA, provides faster responses comparing to the regular Moving Average
Here is the math of the MaMA idea
Momentum measures change in price over a specified time period
momentum = source – source(length)
where,
source, indicates current bar’s price value
source(length), indicates historical price value of length bars earlier
Lets play with this formula and rewrite it by moving source(length) to other side of the equation
source = source(length) + momentum
to avoid confusion let’s call the source that we aim to predict as adjustedSource
adjustedSource = source(length) + momentum
looks nice the next value of source simply can be calculated by summing of historical value of the source value and value of the momentum. I wish it was so easy, the formula holds true only when the momentum is conserved/constant/steady but momentum move up or down with the price fluctuations (accelerating or decelerating)
Let’s add acceleration effects on our formula, where acceleration is change in momentum for a given length. Then the formula will become as (skipped proof part of acceleration effects, you may google for further details)
adjustedSource = source(length) + momentum + 1/2 * acceleration
here again the formula holds true when the acceleration is constant and once again it is not the case for trading, acceleration also changes with the price fluctuations
Then, how we can benefit from all of this, it has value yet requires additional approaches for better outcome
Let’s simulate behaviour with some predictive approach such as using probability (also known as psychological effect ), where probability is a measure for calculating the chances or the possibilities of the occurrence of a random event. As stated earlier above momentum and acceleration are changing with the price fluctuations, by using the probability approach we can add a predictive skill to determine the likelihood of momentum and acceleration changes (remember it is a predictive approach). With this approach, our equations can be expresses as follows
adjustedSource = source(length) + momentum * probability
adjustedSource = source(length) + ( momentum + 1/2 * acceleration ) * probability , with acceleration effect
Finally, we plot MaMA with the new predicted source adjustedSource, applying acceleration effect is made settable by the used from the dialog box, default value is true.
What to look for:
• Trend Identification
• Support and Resistance
• Price Crossovers
Recommended settings are applied as default settings, if you wish to change the length of the MaMA then you should also adjust length of Momentum (and/or Probability). For example for faster moving average such as 21 period it would be suggested to set momentum length to 13
Alternative usage , set moving average length to 1 and keep rest lengths with default values, it will produce a predictive price line based on momentum and probability. Experience acceleration factor by enabling and disabling it
Conclusion
MaMA provide an added level of confidence to a trading strategy and yet it is important to always be aware that it implements a predictive approach in a chaotic market use with caution just like with any indicator
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer : The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Cerca negli script per "momentum"
Momentum 4 Ways Smoothed [Salty]This is an enhance version of Momentum 4 Ways that shows 4 ways to calculate momentum and display each one along with their combined average value.
This study was created to compare 4 different momentum values against their combined average using different display styles to allow the user to experiment with different views of momentum.
- Added the ability to smooth the Average Momentum value. Default Smoothing value is 5.
- Added the ability to use different average calculations. Default is WMA.
- Added the ability to select the number of momentum values to average (1-4). Default is 4.
- Added the ability to use VWAP instead of price as the input.
The Smoothed Average Momentum line is color coded so that it is green when it is moving in the bullish direction and red when it is moving in the bearish direction.
Momentum RibbonThe Momentum Ribbon is a collection of Moving Averages which indicate the severity of pull-backs in a given market.
As the ribbon spreads apart, it indicates more and more significant support/resistance for a trending market. As it is compressed back together, it displays a blue colour to indicate a "cooling" of trend momentum.
Adjustable Moving Average periods and types! You can customize the parameters of your ribbon to your heart's content!
Momentum Table - Felipe📊 Momentum Table – By Felipe
This multi-timeframe momentum dashboard displays a clean and color-coded overview of key trend and momentum indicators across 6 major timeframes (5m to 1W), directly on your chart. It’s ideal for quickly identifying market strength, trend alignment, and potential reversals at a glance.
🔍 Features:
EMA Trend Check (EMA 9, 20, 100, 200):
Compares the current close against each EMA.
✅ Green check = price is above the EMA (bullish bias).
🔻 Red arrow = price is below the EMA (bearish bias).
Visual trend alignment helps you spot strong directional setups.
RSI (Relative Strength Index):
Displays current RSI (14) value per timeframe.
Background color highlights momentum conditions:
🔴 Red = Overbought (>70)
🟢 Green = Oversold (<30)
⚪ Gray = Neutral
Stochastic RSI:
Uses Stoch RSI applied to RSI (14) for sensitivity.
Background color follows the same logic as RSI for quick visual cues.
Compact Visual Table:
Located in the bottom-right corner.
Clean design with headers and rows labeled by timeframe.
Helps traders monitor trend and momentum confluence across multiple timeframes in real time.
This tool supports momentum-based strategies, EMA stacking confirmation, and multi-timeframe alignment, making it ideal for scalpers, swing traders, and trend followers alike.
Momentum Zones [TradersPro]OVERVIEW
The Momentum Zones indicator is designed for momentum stock traders to provide a visible trend structure with actionable price levels. The indicator has been designed for high-growth, bullish stocks on a daily time frame but can be used on any chart and timeframe.
Momentum zones help traders focus on the momentum structure of price, enabling disciplined trading plans with specific entry, exit, and risk management levels.
It is built using CCI values, allowing for fixed trend range calculations. It is most effective when applied to screens of stocks with high RSI, year-to-date (YTD) price gains of 25% or higher, as well as stocks showing growth in both sales and earnings quarter-over-quarter and year-over-year.
CONCEPTS
The indicator defines and colors uptrends (green), downtrends (red), and trends in transition or pausing (yellow).
The indicator can be used for new trend entry or trend continuation entry. New trend entry can be done on the first green bar after a red bar. Trend continuation entries can be done with the first green bar after a yellow bar. The yellow transition zones can be used as price buffers for stop-loss management on new entries.
To see the color changes, users need to be sure to uncheck the candlestick color settings. This can be done by right-clicking the chart, going to Symbols, and unchecking the candle color body, border, and wick boxes.
Remember to check them if the indicator is turned off, or the candles will be blank with no color.
The settings also correspond to the screening function to get a list of stocks entering various momentum zones so you can have a prime list of the stocks meeting any other fundamental criteria you may desire. Traders can then use the indicator for the entry and risk structure of the trading plan.
Momentum Performance This Indicator displays the momentum (performance) of the symbol in percent.
You can compare the performance with other symbols.
The default benchmarks are the S&P 500, the MSCI World and the FTSE All World EX US.
The default length corresponds to one year in the timeframes monthly, weekly and daily.
In intraday the default length is 200, but you can also set your own setting.
You have also the opportunity to display a average momentum performance of the main symbol.
Momentum Indicator avg short return minus avg long returnAverage daily return over the period 2-12 months ago minus the average daily return over the period 1-5 years ago
=> a higher return 2-12 months ago indicates a higher return in coming months according to research, because of the momentum risk factor premium
=> a higher return 1-5 years ago indicates a lower return in coming months according to research, because of the momentum risk factor premium
Momentum Acceleration by DGTItalian physicist Galileo Galilei is usually credited with being the first to measure speed by considering the distance covered and the time it takes. Galileo defined speed as the distance covered during a period of time. In equation form, that is v = Δd / Δt where v is speed, Δd is change in distance, and Δt is change in time. The Greek symbol for delta, a triangle (Δ), means change.
Is the speed getting faster or slower?
Acceleration will be the answer, acceleration is defined as the rate of change of speed over a set period of time, meaning something is getting faster or slower. Mathematically expressed, acceleration denoted as a is a = Δv / Δt , where Δv is the change in speed and Δt is the change in time.
How to apply in trading
Lets think about Momentum, Rate of Return, Rate of Change all are calculated in almost same approach with Speed
Momentum measures change in price over a specified time period,
Rate of Change measures percent change in price over a specified time period,
Rate of Return measures the net gain or loss over a specified time period,
And Speed measures change in distance over a specified time period
So we may state that measuring the change in distance is also measuring the change in price over a specified time period which is length, hence
speed can be calculated as (source – source )/length and acceleration becomes (speed – speed )/length
In this study acceleration is used as signal line and result plotted as arrows demonstrating bull or bear direction where direction changes can be considered as trading setups
Just a little fun, since we deal with speed the short name of the study is named after famous cartoon character Speedy Gonzales
Trading success is all about following your trading strategy and the indicators should fit within your trading strategy, and not to be traded upon solely
Disclaimer: The script is for informational and educational purposes only. Use of the script does not constitutes professional and/or financial advice. You alone the sole responsibility of evaluating the script output and risks associated with the use of the script. In exchange for using the script, you agree not to hold dgtrd TradingView user liable for any possible claim for damages arising from any decision you make based on use of the script
Momentum Linear RegressionThe original script was posted on ProRealCode by user Nicolas.
This is an indicator made of the linear regression applied to the rate of change of price (or momentum). I made a simple signal line just by duplicating the first one within a period decay in the past, to make those 2 lines cross. You can add more periods decay to made signal smoother with less false entry.
Median Momentum with Buy/Sell Signals and Bar ColorMomentum Calculation:
Momentum is calculated as the difference between the current close price and the close price momentum_length periods ago: momentum = close - close .
Highest and Lowest Momentum:
The highest and lowest momentum values over the specified length are calculated.
Median Momentum:
The median momentum is calculated as the average of the highest and lowest momentum values.
Color Setting:
medianColor is set based on whether the momentum is above, below, or equal to the median momentum.
barColor is set similarly for bar coloring.
Plotting:
The script plots the median momentum and the actual momentum values.
Buy and sell signals are generated when momentum crosses over or under the median momentum.
The script also plots the buy and sell signals with arrows on the chart.
MomentumIndicatorsLibrary "MomentumIndicators"
This is a library of 'Momentum Indicators', also denominated as oscillators.
The purpose of this library is to organize momentum indicators in just one place, making it easy to access.
In addition, it aims to allow customized versions, not being restricted to just the price value.
An example of this use case is the popular Stochastic RSI.
# Indicators:
1. Relative Strength Index (RSI):
Measures the relative strength of recent price gains to recent price losses of an asset.
2. Rate of Change (ROC):
Measures the percentage change in price of an asset over a specified time period.
3. Stochastic Oscillator (Stoch):
Compares the current price of an asset to its price range over a specified time period.
4. True Strength Index (TSI):
Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the
absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized
in a range between 100 and -100.
5. Stochastic Momentum Index (SMI):
Combination of the True Strength Index with a signal line to help identify turning points in the market.
6. Williams Percent Range (Williams %R):
Compares the current price of an asset to its highest high and lowest low over a specified time period.
7. Commodity Channel Index (CCI):
Measures the relationship between an asset's current price and its moving average.
8. Ultimate Oscillator (UO):
Combines three different time periods to help identify possible reversal points.
9. Moving Average Convergence/Divergence (MACD):
Shows the difference between short-term and long-term exponential moving averages.
10. Fisher Transform (FT):
Normalize prices into a Gaussian normal distribution.
11. Inverse Fisher Transform (IFT):
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is through the
application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity, to a scale limited
between -1 and +1, allowing them to be more easily visualized and compared.
12. Premier Stochastic Oscillator (PSO):
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing average of
the %K value, resulting in a symmetric scale of 1 to -1
# Indicators of indicators:
## Stochastic:
1. Stochastic of RSI (Relative Strengh Index)
2. Stochastic of ROC (Rate of Change)
3. Stochastic of UO (Ultimate Oscillator)
4. Stochastic of TSI (True Strengh Index)
5. Stochastic of Williams R%
6. Stochastic of CCI (Commodity Channel Index).
7. Stochastic of MACD (Moving Average Convergence/Divergence)
8. Stochastic of FT (Fisher Transform)
9. Stochastic of Volume
10. Stochastic of MFI (Money Flow Index)
11. Stochastic of On OBV (Balance Volume)
12. Stochastic of PVI (Positive Volume Index)
13. Stochastic of NVI (Negative Volume Index)
14. Stochastic of PVT (Price-Volume Trend)
15. Stochastic of VO (Volume Oscillator)
16. Stochastic of VROC (Volume Rate of Change)
## Inverse Fisher Transform:
1.Inverse Fisher Transform on RSI (Relative Strengh Index)
2.Inverse Fisher Transform on ROC (Rate of Change)
3.Inverse Fisher Transform on UO (Ultimate Oscillator)
4.Inverse Fisher Transform on Stochastic
5.Inverse Fisher Transform on TSI (True Strength Index)
6.Inverse Fisher Transform on CCI (Commodity Channel Index)
7.Inverse Fisher Transform on Fisher Transform (FT)
8.Inverse Fisher Transform on MACD (Moving Average Convergence/Divergence)
9.Inverse Fisher Transfor on Williams R% (Williams Percent Range)
10.Inverse Fisher Transfor on CMF (Chaikin Money Flow)
11.Inverse Fisher Transform on VO (Volume Oscillator)
12.Inverse Fisher Transform on VROC (Volume Rate of Change)
## Stochastic Momentum Index:
1.Stochastic Momentum Index of RSI (Relative Strength Index)
2.Stochastic Momentum Index of ROC (Rate of Change)
3.Stochastic Momentum Index of VROC (Volume Rate of Change)
4.Stochastic Momentum Index of Williams R% (Williams Percent Range)
5.Stochastic Momentum Index of FT (Fisher Transform)
6.Stochastic Momentum Index of CCI (Commodity Channel Index)
7.Stochastic Momentum Index of UO (Ultimate Oscillator)
8.Stochastic Momentum Index of MACD (Moving Average Convergence/Divergence)
9.Stochastic Momentum Index of Volume
10.Stochastic Momentum Index of MFI (Money Flow Index)
11.Stochastic Momentum Index of CMF (Chaikin Money Flow)
12.Stochastic Momentum Index of On Balance Volume (OBV)
13.Stochastic Momentum Index of Price-Volume Trend (PVT)
14.Stochastic Momentum Index of Volume Oscillator (VO)
15.Stochastic Momentum Index of Positive Volume Index (PVI)
16.Stochastic Momentum Index of Negative Volume Index (NVI)
## Relative Strength Index:
1. RSI for Volume
2. RSI for Moving Average
rsi(source, length)
RSI (Relative Strengh Index). Measures the relative strength of recent price gains to recent price losses of an asset.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of RSI
roc(source, length)
ROC (Rate of Change). Measures the percentage change in price of an asset over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of ROC
stoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Compares the current price of an asset to its price range over a specified time period.
Parameters:
kLength
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Oscillator and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Oscillator and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Oscillator and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
stoch(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Stochastic Oscillator. Customized source. Compares the current price of an asset to its price range over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
kLength : (int) Period of loopback to calculate the stochastic
kSmoothing : (int) Period for smoothig stochastic
dSmoothing : (int) Period for signal (moving average of stochastic)
maTypeK : (int) Type of Moving Average for Stochastic Oscillator
maTypeD : (int) Type of Moving Average for Stochastic Oscillator Signal
almaOffsetKD : (float) Offset for Arnaud Legoux Moving Average for Stoch and Signal
almaSigmaKD : (float) Sigma for Arnaud Legoux Moving Average for Stoch and Signal
lsmaOffSetKD : (int) Offset for Least Squares Moving Average for Stoch and Signal
Returns: A tuple of Stochastic Oscillator and Moving Average of Stochastic Oscillator
tsi(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet)
TSI (True Strengh Index). Measures the price change, calculating the ratio of the price change (positive or negative) in relation to the absolute price change.
The values of both are smoothed twice to reduce noise, and the final result is normalized in a range between 100 and -100.
Parameters:
source : (float) Source of series (close, high, low, etc.)
shortLength : (int) Short length
longLength : (int) Long length
maType : (int) Type of Moving Average for TSI
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) TSI
smi(sourceTSI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
SMI (Stochastic Momentum Index). A TSI (True Strengh Index) plus a signal line.
Parameters:
sourceTSI : (float) Source of series for TSI (close, high, low, etc.)
shortLengthTSI : (int) Short length for TSI
longLengthTSI : (int) Long length for TSI
maTypeTSI : (int) Type of Moving Average for Signal of TSI
almaOffsetTSI : (float) Offset for Arnaud Legoux Moving Average
almaSigmaTSI : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSetTSI : (int) Offset for Least Squares Moving Average
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
Returns: A tuple with TSI, signal of TSI and histogram of difference
wpr(source, length)
Williams R% (Williams Percent Range). Compares the current price of an asset to its highest high and lowest low over a specified time period.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
Returns: (float) Series of Williams R%
cci(source, length, maType, almaOffset, almaSigma, lsmaOffSet)
CCI (Commodity Channel Index). Measures the relationship between an asset's current price and its moving average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period of loopback
maType : (int) Type of Moving Average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: (float) Series of CCI
ultimateOscillator(fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Combines three different time periods to help identify possible reversal points.
Parameters:
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
ultimateOscillator(source, fastLength, middleLength, slowLength)
UO (Ultimate Oscilator). Customized source. Combines three different time periods to help identify possible reversal points.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Fast period of loopback
middleLength : (int) Middle period of loopback
slowLength : (int) Slow period of loopback
Returns: (float) Series of Ultimate Oscilator
macd(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet)
MACD (Moving Average Convergence/Divergence). Shows the difference between short-term and long-term exponential moving averages.
Parameters:
source : (float) Source of series (close, high, low, etc.)
fastLength : (int) Period for fast moving average
slowLength : (int) Period for slow moving average
signalLength : (int) Signal length
maTypeFast : (int) Type of fast moving average
maTypeSlow : (int) Type of slow moving average
maTypeMACD : (int) Type of MACD moving average
almaOffset : (float) Offset for Arnaud Legoux Moving Average
almaSigma : (float) Sigma for Arnaud Legoux Moving Average
lsmaOffSet : (int) Offset for Least Squares Moving Average
Returns: A tuple with MACD, Signal, and Histgram
fisher(length)
Fisher Transform. Normalize prices into a Gaussian normal distribution.
Parameters:
length
Returns: A tuple with Fisher Transform and signal
fisher(source, length)
Fisher Transform. Customized source. Normalize prices into a Gaussian normal distribution.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length
Returns: A tuple with Fisher Transform and signal
inverseFisher(source, length, subtrahend, denominator)
Inverse Fisher Transform.
Transform the values of the Fisher Transform into a smaller and more easily interpretable scale is
through the application of an inverse transformation to the hyperbolic tangent function.
This transformation takes the values of the FT, which range from -infinity to +infinity,
to a scale limited between -1 and +1, allowing them to be more easily visualized and compared.
Parameters:
source : (float) Source of series (close, high, low, etc.)
length : (int) Period for loopback
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of Inverse Fisher Transform
premierStoch(length, smoothlen)
Premier Stochastic Oscillator (PSO).
Normalizes the standard stochastic oscillator by applying a five-period double exponential smoothing
average of the %K value, resulting in a symmetric scale of 1 to -1.
Parameters:
length : (int) Period for loopback
smoothlen : (int) Period for smoothing
Returns: (float) Series of PSO
premierStoch(source, smoothlen, subtrahend, denominator)
Premier Stochastic Oscillator (PSO) of custom source.
Normalizes the source by applying a five-period double exponential smoothing average.
Parameters:
source : (float) Source of series (close, high, low, etc.)
smoothlen : (int) Period for smoothing
subtrahend : (int) Denominator. Useful in unbounded indicators. For example, in CCI.
denominator
Returns: (float) Series of PSO
stochRsi(sourceRSI, lengthRSI, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceRSI
lengthRSI
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochRoc(sourceROC, lengthROC, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
sourceROC
lengthROC
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochUO(fastLength, middleLength, slowLength, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
fastLength
middleLength
slowLength
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochWPR(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochFT(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVolume(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochMFI(source, length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochOBV(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochNVI(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochPVT(source, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
source
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
stochVROC(length, kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD)
Parameters:
length
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
iftRSI(sourceRSI, lengthRSI, lengthIFT)
Parameters:
sourceRSI
lengthRSI
lengthIFT
iftROC(sourceROC, lengthROC, lengthIFT)
Parameters:
sourceROC
lengthROC
lengthIFT
iftUO(fastLength, middleLength, slowLength, lengthIFT)
Parameters:
fastLength
middleLength
slowLength
lengthIFT
iftStoch(kLength, kSmoothing, dSmoothing, maTypeK, maTypeD, almaOffsetKD, almaSigmaKD, lsmaOffSetKD, lengthIFT)
Parameters:
kLength
kSmoothing
dSmoothing
maTypeK
maTypeD
almaOffsetKD
almaSigmaKD
lsmaOffSetKD
lengthIFT
iftTSI(source, shortLength, longLength, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
shortLength
longLength
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftCCI(source, length, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
length
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftFisher(length, lengthIFT)
Parameters:
length
lengthIFT
iftMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftWPR(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftMFI(source, length, lengthIFT)
Parameters:
source
length
lengthIFT
iftCMF(length, lengthIFT)
Parameters:
length
lengthIFT
iftVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, lengthIFT)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
lengthIFT
iftVROC(length, lengthIFT)
Parameters:
length
lengthIFT
smiRSI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiROC(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVROC(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiWPR(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiFT(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCCI(source, length, maTypeCCI, almaOffsetCCI, almaSigmaCCI, lsmaOffSetCCI, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
maTypeCCI
almaOffsetCCI
almaSigmaCCI
lsmaOffSetCCI
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiUO(fastLength, middleLength, slowLength, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
fastLength
middleLength
slowLength
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMACD(source, fastLength, slowLength, signalLength, maTypeFast, maTypeSlow, maTypeMACD, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
fastLength
slowLength
signalLength
maTypeFast
maTypeSlow
maTypeMACD
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVol(shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiMFI(source, length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiCMF(length, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
length
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiOBV(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVT(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiVO(shortLen, longLen, maType, almaOffset, almaSigma, lsmaOffSet, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
shortLen
longLen
maType
almaOffset
almaSigma
lsmaOffSet
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiPVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
smiNVI(source, shortLengthTSI, longLengthTSI, maTypeTSI, almaOffsetTSI, almaSigmaTSI, lsmaOffSetTSI, maTypeSignal, smoothingLengthSignal, almaOffsetSignal, almaSigmaSignal, lsmaOffSetSignal)
Parameters:
source
shortLengthTSI
longLengthTSI
maTypeTSI
almaOffsetTSI
almaSigmaTSI
lsmaOffSetTSI
maTypeSignal
smoothingLengthSignal
almaOffsetSignal
almaSigmaSignal
lsmaOffSetSignal
rsiVolume(length)
Parameters:
length
rsiMA(sourceMA, lengthMA, maType, almaOffset, almaSigma, lsmaOffSet, lengthRSI)
Parameters:
sourceMA
lengthMA
maType
almaOffset
almaSigma
lsmaOffSet
lengthRSI
MomentumLibrary "Momentum"
Contains utilities varying algorithms for measuring momentum.
simple(fast, slow, src, fastType, slowType) Derives momentum from two moving averages of different lengths.
Parameters:
fast : The length of the fast moving average.
slow : The length of the slow moving average.
src : The series to measure from. Default is 'close'.
fastType : The type of moving average the fast should use. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
slowType : The type of moving average the slow should use. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
stochRSI(fast, fast, rsiLen, stochLen, src, kmode) Returns the K and D values of a Stochastic RSI. Allows for different moving averages to produce the K value.
Parameters:
fast : The length to average the stochastic.
fast : The length to smooth out K and produce D.
rsiLen : The length of the RSI.
stochLen : The length of stochastic.
src : The series to measure from. Default is 'close'.
kmode : The type of moving average to generate. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
Returns:
macd(fast, slow, signal, src, fastType, slowType, slowType) Same as well-known MACD formula but allows for different moving averages types to be used.
Parameters:
fast : The length of the fast moving average.
slow : The length of the slow moving average.
signal : The length of average to applied to smooth out the signal.
src : The series to measure from. Default is 'close'.
fastType : The type of moving average the fast should use. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
slowType : The type of moving average the slow should use. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
slowType : The type of moving average the signal should use. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
Returns:
Clenow MomentumClenow Momentum Method
The Clenow Momentum Method, developed by Andreas Clenow, is a systematic, quantitative trading strategy focused on capturing medium- to long-term price trends in financial markets. Popularized through Clenow’s book, Stocks on the Move: Beating the Market with Hedge Fund Momentum Strategies, the method leverages momentum—an empirically observed phenomenon where assets that have performed well in the recent past tend to continue performing well in the near future.
Theoretical Foundation
Momentum investing is grounded in behavioral finance and market inefficiencies. Investors often exhibit herding behavior, underreact to new information, or chase trends, causing prices to trend beyond fundamental values. Clenow’s method builds on academic research, such as Jegadeesh and Titman (1993), which demonstrated that stocks with high returns over 3–12 months outperform those with low returns over similar periods.
Clenow’s approach specifically uses **annualized momentum**, calculated as the rate of return over a lookback period (typically 90 days), annualized to reflect a yearly percentage. The formula is:
Momentum=(((Close N periods agoCurrent Close)^N252)−1)×100
- Current Close: The most recent closing price.
- Close N periods ago: The closing price N periods back (e.g., 90 days).
- N: Lookback period (commonly 90 days).
- 252: Approximate trading days in a year for annualization.
This metric ranks stocks by their momentum, prioritizing those with the strongest upward trends. Clenow’s method also incorporates risk management, diversification, and volatility adjustments to enhance robustness.
Methodology
The Clenow Momentum Method involves the following steps:
1. Universe Selection:
- A broad universe of liquid stocks is chosen, often from major indices (e.g., S&P 500, Nasdaq 100) or global exchanges.
- Filters should exclude illiquid stocks (e.g., low average daily volume) or those with extreme volatility.
2. Momentum Calculation:
- Stocks are ranked based on their annualized momentum over a lookback period (typically 90 days, though 60–120 days can be common tests).
- The top-ranked stocks (e.g., top 10–20%) are selected for the portfolio.
3. Volatility Adjustment (Optional):
- Clenow sometimes adjusts momentum scores by volatility (e.g., dividing by the standard deviation of returns) to favor stocks with smoother trends.
- This reduces exposure to erratic price movements.
4. Portfolio Construction:
- A diversified portfolio of 10–25 stocks is constructed, with equal or volatility-weighted allocations.
- Position sizes are often adjusted based on risk (e.g., 1% of capital per position).
5. Rebalancing:
- The portfolio is rebalanced periodically (e.g., weekly or monthly) to maintain exposure to high-momentum stocks.
- Stocks falling below a momentum threshold are replaced with higher-ranked candidates.
6. Risk Management:
- Stop-losses or trailing stops may be applied to limit downside risk.
- Diversification across sectors reduces concentration risk.
Implementation in TradingView
Key features include:
- Customizable Lookback: Users can adjust the lookback period in pinescript (e.g., 90 days) to align with Clenow’s methodology.
- Visual Cues: Background colors (green for positive, red for negative momentum) and a zero line help identify trend strength.
- Integration with Screeners: TradingView’s stock screener can filter high-momentum stocks, which can then be analyzed with the custom indicator.
Strengths
1. Simplicity: The method is straightforward, relying on a single metric (momentum) that’s easy to calculate and interpret.
2. Empirical Support: Backed by decades of academic research and real-world hedge fund performance.
3. Adaptability: Applicable to stocks, ETFs, or other asset classes, with flexible lookback periods.
4. Risk Management: Diversification and periodic rebalancing reduce idiosyncratic risk.
5. TradingView Integration: Pine Script implementation enables real-time visualization, enhancing decision-making for stocks like NVDA or SPY.
Limitations
1. Mean Reversion Risk: Momentum can reverse sharply in bear markets or during sector rotations, leading to drawdowns.
2. Transaction Costs: Frequent rebalancing increases trading costs, especially for retail traders with high commissions. This is not as prevalent with commission free trading becoming more available.
3. Overfitting Risk: Over-optimizing lookback periods or filters can reduce out-of-sample performance.
4. Market Conditions: Underperforms in low-momentum or highly volatile markets.
Practical Applications
The Clenow Momentum Method is ideal for:
Retail Traders: Use TradingView’s screener to identify high-momentum stocks, then apply the Pine Script indicator to confirm trends.
Portfolio Managers: Build diversified momentum portfolios, rebalancing monthly to capture trends.
Swing Traders: Combine with volume filters to target short-term breakouts in high-momentum stocks.
Cross-Platform Workflow: Integrate with Python scanners to rank stocks, then visualize on TradingView for trade execution.
Comparison to Other Strategies
Vs. Minervini’s VCP: Clenow’s method is purely quantitative, while Minervini’s Volatility Contraction Pattern (your April 11, 2025 query) combines momentum with chart patterns. Clenow is more systematic but less discretionary.
Vs. Mean Reversion: Momentum bets on trend continuation, unlike mean reversion strategies that target oversold conditions.
Vs. Value Investing: Momentum outperforms in bull markets but may lag value strategies in recovery phases.
Conclusion
The Clenow Momentum Method is a robust, evidence-based strategy that capitalizes on price trends while managing risk through diversification and rebalancing. Its simplicity and adaptability make it accessible to retail traders, especially when implemented on platforms like TradingView with custom Pine Script indicators. Traders must be mindful of transaction costs, mean reversion risks, and market conditions. By combining Clenow’s momentum with volume filters and alerts, you can optimize its application for swing or position trading.
Long Short MomentumThis indicator is designed to visualize short-term and long-term momentum trends.The indicator calculates two momentum lines based on customizable lengths: a short momentum (Short Momentum) over a smaller period and a long momentum (Long Momentum) over a longer period. These lines are plotted relative to the chosen price source, typically the closing price.
The histogram, colored dynamically based on momentum direction, gives visual cues:
Green: Both short and long momentum are positive, indicating an upward trend.
Red: Both are negative, indicating a downward trend.
Gray: Mixed momentum, suggesting potential trend indecision.
Polychromatic Momentum IndicatorPolychromatic Momentum is a generalized Momentum study considering a number of Momentum values controlled by the length input. The greatest weight is given to the most recent Momentum value, while the precedent values are given lesser weight. Each Momentum value is assigned weight equal to inverse square root of Momentum distance (number of bars prior to the current bar). Then the sum of the weighted Momentum values is divided by the sum of the square roots.
Multiple Standard MomentumMultiple Standard Momentum
The momentum indicator is a technical indicator that measures the speed and strength of the price movement of a financial asset. This indicator is used to identify the underlying strength of a trend and predict potential changes in price direction.
The calculation of the momentum indicator is based on the difference between the current price and the price of a previous period. The result is displayed on a chart, which can be positive or negative, depending on whether the current price is higher or lower than the price of the previous period. The indicator can be used on any time frame, but is generally used on short-term charts.
To use the momentum indicator , you look for two types of signals:
🔹 Crossover Signal – When the indicator crosses the zero line, it can signal a change of direction in the price trend.
🔹 Divergence – When the asset price moves in one direction and the indicator moves in the opposite direction, a divergence can be identified. This divergence may indicate a possible trend reversal.
COMPOSITION AND MODE OF USE OF THE INDICATOR
🔹 This indicator displays multiple Momentum levels on a single chart, allowing you to view multiple Momentum lines. Each level is represented on the chart where it can be hidden or shown as desired for better market analysis.
🔹 In addition, a zero trend line (also known as a horizontal trend line) has been added. The zero trend line is a horizontal line that indicates the point at which the current price equals the opening price, which allows users to draw a custom zero trend line on the chart using different colors and time periods of calculation.
* Highest performing custom setup for the Zero Trend Line. For Operations of:
- One Minute: Trend Line Time Frame = Five Minutes.
- Three Minutes: Trend Line Time Frame = Fifteen Minutes.
- Five Minutes: Trend Line Time Frame = Thirty Minutes.
- Fifteen Minutes: Trend Line Time Frame = Sixty Minutes.
Rules For Trading
🔹 Bullish:
* The Zero Trend Line must be in Green Color.
* When the Momentum Line Crosses the Zero Line from Bottom to Top.
🔹 Bearish:
* The Zero Trend Line must be in Red Color.
* When the Momentum Line Crosses the Zero Line from Top to Bottom.
In addition, parameters were defined to activate or deactivate the graphic signal taking into account the previous requirement (Bullish and Bearish):
🔹 Long or Buy = ▲
🔹 Short or Sell = ▼
This script can be used in different markets such as forex, indices, and cryptocurrencies for analysis and trading. However, it is important to note that no trading strategy is guaranteed to be profitable, and traders should always conduct their own research and risk management.
Basic Polychromatic Momentum IndicatorBasic Polychromatic Momentum Indicator with alerts
PMI involves taking the difference between the current price and the price n periods ago, and then subtracting from it the difference between the current price and the price n periods ago, divided by n. This gives a smoothed version of the momentum indicator.
The user can also specify a smoothing factor using the "smoothing" input, which applies a simple moving average to the PMI. The resulting smoothed PMI is plotted on the chart in blue, with a dotted gray line at the zero level.
EMA Ribbon + ADX MomentumHere's a description for your TradingView indicator publication:
The EMA Ribbon + ADX Momentum indicator combines exponential moving averages (EMA) with the Average Directional Index (ADX) to identify strong trends and potential trading opportunities. This powerful tool offers:
🎯 Key Features:
EMA Ribbon (10, 21, 34, 55) for trend direction
ADX integration for trend strength confirmation
Clear visual signals with color-coded backgrounds
Real-time trend status display
Strength metrics with exact percentage values
📊 How It Works:
EMA Ribbon: Four EMAs form a ribbon pattern that shows trend direction through their stacking order
ADX Integration: Confirms trend strength when above the threshold (default 25)
Visual Signals:
Green background: Strong bullish trend
Red background: Strong bearish trend
Gray background: Neutral or weak trend
📈 Trading Signals:
STRONG BULL: EMAs properly stacked bullish + high ADX + DI+ > DI-
STRONG BEAR: EMAs properly stacked bearish + high ADX + DI- > DI+
BULL/BEAR TREND: Shows regular trend conditions without strength confirmation
NEUTRAL: No clear trend structure
🔧 Customizable Parameters:
ADX Length: Adjust trend calculation period
ADX Threshold: Modify strength confirmation level
ADX Panel Toggle: Show/hide the ADX indicator panel
💡 Best Uses:
Trend following strategies
Entry/exit timing
Trade confirmation
Market structure analysis
Risk management tool
This indicator helps traders identify not just trend direction, but also trend strength, making it particularly useful for both position entry timing and risk management. The clear visual signals and real-time metrics make it suitable for traders of all experience levels.
Note: As with all technical indicators, best results are achieved when used in conjunction with other forms of analysis and proper risk management.
Momentum Memory Indicator
The Momentum Memory Indicator (MMI) is a custom tool designed to predict future price movements based on the historical momentum of an asset. By calculating the Rate of Change (ROC) and then averaging it over a specified "memory" period, the MMI provides a prediction that reflects both recent and slightly older momentum data. The prediction is visualized as a histogram, with colors indicating the direction of the momentum.
**Parameters:**
1. **Rate of Change Period (ROC Period):** This parameter sets the period for the Rate of Change calculation, which measures the momentum of the asset. The default value is 14.
2. **Memory Period:** This parameter determines the period over which the average momentum is calculated. By considering momentum over this "memory" period, the indicator aims to provide a more stable and reliable prediction. The default value is 5.
**Logic:**
1. **Rate of Change (Momentum):** The ROC is calculated based on the asset's closing prices over the specified ROC period. It provides a measure of how much the price has changed over that period, indicating momentum.
2. **Average Momentum:** The average momentum is calculated by taking a simple moving average (SMA) of the ROC values over the memory period. This smoothens out the momentum data and provides a more stable value for prediction.
3. **Prediction:** The prediction is calculated by adjusting the current closing price based on the average momentum. This gives an estimate of where the price might be in the next period, assuming the momentum continues.
4. **Prediction Color:** The color of the prediction histogram is determined by the direction of the average momentum. A positive momentum results in a green histogram, while a negative momentum results in a red histogram.
**Plots:**
1. **Prediction (Histogram):** Represents the predicted price movement based on the average momentum. The direction and magnitude of the histogram bars provide insights into the expected price change. The color of the bars (green or red) indicates the direction of the momentum.
Relative Strength and MomentumRelative Strength and Momentum Indicator
Unlock deeper market insights with the Relative Strength and Momentum Indicator—a powerful tool designed to help traders and investors identify the strongest stocks and sectors based on relative performance. This custom indicator displays essential information on relative strength and momentum for up to 15 different symbols, compared against a benchmark index, all within a clear and organized table format.
Key Features:
1. Customizable Inputs: Choose up to 15 symbols to compare, along with a benchmark index, allowing you to tailor the indicator to your trading strategy. The 'Lookback Period' input defines how many weeks of data are analyzed for relative strength and momentum.
2. Relative Strength Calculation: For each selected symbol, the indicator calculates the Relative Strength (RS) against the chosen benchmark. This RS is further refined using an exponential moving average (EMA) to smooth the results, providing a more stable trend overview.
3. Momentum Analysis: Momentum is determined by analyzing the rate of change in relative strength. The indicator calculates a momentum rank for each symbol, based on its relative strength’s improvement or deterioration.
4. Percentile Ranking System: Each symbol is assigned a percentile rank (from 1 to 100) based on its relative strength compared to the others. Similarly, momentum rankings are also assigned from 1 to 100, offering a clear understanding of which assets are outperforming or underperforming.
5. Visual Indicators:
a. Green: Signals improving or stable relative strength and momentum.
b. Red: Indicates declining relative strength or momentum.
c. Aqua: Highlights symbols performing well on both relative strength and momentum—ideal candidates for further analysis.
6. Two Clear Tables:
a. Relative Strength Rank Table: Displays weekly rankings of relative strength for each symbol.
b. Momentum Table: Shows momentum trends, helping you identify which symbols are gaining or losing strength.
7. Color-Coded for Easy Analysis: The tables are color-coded to make analysis quick and straightforward. A green color means the symbol is performing well in terms of relative strength or momentum, while red indicates weaker performance. Aqua marks symbols that are excelling in both areas.
Use Case:
a. Sector Comparison: Identify which sectors or indexes are showing both relative strength and momentum to pick high-potential stocks. This allows you to align with broader market trends for improved trade entries.
b. Stock Selection: Quickly compare symbols within the same sector to find the stronger performers.
