Oscillator: Which follows Normal Distribution?When doing machine learning using oscillators, it would be better if the oscillators were normally distributed.
So I analyzed the distribution of oscillators.
The value of the oscillator was divided into 50 groups each from 0 to 100.
ex) if rsi value is 45.43 -> group_44, 58.23 -> group_58
Ocscillators : RSI, Stoch, MFI, WT, RVI, etc....
Caution: The normal distribution was verified through an empirical formula.
Oscillaltor
Perfect signal by c00l75 v4-- CONCEPT - HOW IT WORKS ---
This script is based on moving average crossing lines (mirrored) with a signal line.
--- WHAT IS DIFFERENT FROM OTHER MA SCRIPTS ---
It's different in the formula for calculating the moving averages. NOW the length of the moving averages is modifiable to permit the user to tuning system better.
--- WHAT IS IT FOR? ---
It's a trend following script. I needed a script to catch signals for medium term trading (5-20 days) on > H4 TF with smooth lines but pretty quick signal, possibly easy to manage and "plug and play" for Forex market.
--- HOW TO USE IT? ---
Simply you have buy or sell signal looking at crossing lines. Signal line could be used to catch retracements.
--- WHERE SHOULD I USE IT? ---
At the moment I tested it only on Forex market with good results on H1 timeframe. Backtest it by yourself before using it.
Hope I can help someone else to have better trading time. Feel free to comment if you have questions.
NOTE for moderators: It's the update version of a my previous script (Perfect signal by c00l75) to version v4 with added ability to change the periods of the user's choice. To do this I had to republish it because the previous one was an old version of pinescript that is no longer supported.
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
Short Term Bubble RiskThis risk indicator uses the extension of the closing price to the 20W SMA and displays a color-coded risk oscillator. The higher the oscillator is, the greater the short-term risk and vice-versa. This indicator has historically worked well for estimating the short-term risk of Bitcoin and Ethereum on a weekly timeframe.
Expansion IndexWhat is the expansion index?
The expansion index is a concept that charts the relative strength or weakness based on the comparison of recent price changes and overall prices changes for the period.
It can be used as an momentum oscillator and show overbought or oversold price conditions by measuring the relation between the sum of "strong" price changes (which can form trends).
The Expansion Index is most typically used on an 8 day timeframe. It changes on a scale from −100 to +100, with the overbought and oversold levels marked at +60 and −60, respectively.
What about this indicator?
This indicator basically shows the rate of expansion from zero, but also has other uses apart from finding over bought or over sold territory.
Scenarios:
Lets say you are identifying a contraction zone (low volume zone of candles), you can further confirm the contraction if the Index is at or near 0, in this case it might have more strength
and play out more accurately the contraction and expansion.
Once the Expansion begins and price expands from the 0 level you can determine if its overbought which would be around the 1.00 Level or Oversold which would be at around the -1.00 Levels, and a reversal can follow out.
With the rate of change line you can identify trends in market and when reversals will start.
This indicator is best used with contraction, expansion, and trend principles also known as the Forex Master Pattern, as it was for what this specific indicator was designed for.
Thanks to NNAMDERT for writing this indicator and giving full rights. :)
Faytterro Oscillatorwhat is Faytterro oscillator?
An oscillator that perfectly identifies overbought and oversold zones.
what it does?
this places the price between 0 and 100 perfectly but with a little delay. To eliminate this delay, it predicts the price to come, and the indicator becomes clearer as the probability of its prediction increases.
how it does it?
This indicator is obtained with "faytterro bands", another indicator I designed. For more information about faytterro bands:
A kind of stochastic function is applied to the faytterro bands indicator, and then another transformation formula that I have designed and explained in detail in the link above is applied. These formulas are also applied again to calculate the prediction parts.
how to use it?
Use this indicator to see past overbought and oversold zones and to see future ones.
The input named source is used to change the source of the indicator.
The length serves to change the signal frequency of the indicator.
Energy_Arrows[Salty]This script quantifies the energy in a price move by comparing the relationship of 3 configurable exponential moving averages present on a slightly higher timeframe (chosen automatically based on the charts current period). It uses the closing price by default, but this is also configurable using the Source input. There are a few ways to use the information in this indicator. One is to use the values above zero (colored green) to provide a bullish bias for future price, and values below zero (colored red) indicating a bearish bias for future prices. This bias can be shown to be increasing or decreasing base on the upward or downward slope of the indicator. The green and red arrows can be enabled to show if the bias is strengthening or weakening based on the direction they are pointing. Finally, the height changes in the peaks of the indicator can be used to show divergence in the strength of extreme price moves to show when a pull back or reversal may occur.
R Squared - MomentumThis little oscillator just returns the R Squared Value of current price action.
It is designed to show trend direction momentum. Great for confluence!
TMO ScalperTMO - (T)rue (M)omentum (O)scillator) MTF Scalper Version
TMO Scalper is a special custom version of the popular TMO Oscillator. Scalper version was designed specifically for the lower time frames (1-5min intraday scalps). This version prints in the signals directly on top of the oscillator only when the higher aggregations are aligned with the current aggregation (the big wheels must be spinning in order for a small wheel to spin). The scalper consist of three MTF TMO oscillators. First one is the one that plot signals (should be the fastest aggregation), second serves as a short term trend gauge (good rule of thumb is to us 2-5x of the chart time frame or the first aggregation). The third one (optional) is shaded in the background & should only serve as a trend gauge for the day (usually higher time frames 30min+).
Time Frames Preffered by Traders:
1. 1m / 5m / 30m - This one is perfect for catching the fastest moves. However, during choppy days the 1min can produce more false signals..
2. 2m / 10m / 30m - Healthy middle, the 2min aggregation nicely smooths out the 1min mess. Short term gauge is turning slowly (10min for a signal to confirm).
3. 3m / 30m / 60m - This TF is awesome for day traders that prefer to take it slow. Obviously, this combination will produce far less signals during the day.
Hope it helps.
TMO ArrowsTMO - (T)rue (M)omentum (O)scillator) MTF Arrows
Do you want to use TMO but you lack space on the chart? This study is just for you. This is the more user-friendly version of the TMO Oscillator. In terms of the indicator there are no changes except the indicator is converted in to the simple arrows.
There are Four Types of Arrows:
1. TMO Arrow Up - Visualizes the TMO bullish crosses.
2. TMO Arrow Down - Visualizes the TMO bearish crosses.
3. TMO Arrow Up (Oversolds Only) - Visualizes only the bullish crosses that are at or below the oversold zone.
4. TMO Arrow Down (Overboughts Only) - Visualizes only the bearish crosses that are at or above the overbought zone.
In case you only want the arrows for extremes, turn off the Arrow Up / Arrow Down first. Arrows for extremes only are turned off by default.
Hope it helps.
MTF TMOTMO - (T)rue (M)omentum (O)scillator) MTF (Higher Aggregation) Version
TMO calculates momentum using the DELTA of price. Giving a much better picture of the trend, reversals & divergences than most momentum oscillators using price. Aside from the regular TMO, this study combines four different TMO aggregations into one indicator for an even better picture of the trend. Once you look deeper into this study you will realize how complex this tool is. This version also produce much more information like crosses, divergences, overbought / oversold signals, higher aggregation fades etc. It is probably not even possible to explain them all, there could easily be an entire e-book about this study.
I have been using this tool for a couple of years now, and this is what i have learned so far:
Favorite Time Frame Variations:
1. 1m / 5m / 30m - Great for intraday futures or options scalps. 30m TMO serves as the overall trend gauge for the day. 5min dictates the longer term intraday moves as well as direction of the 1min. 1min is for the scalps. When the 5min TMO is sloping higher focus should be on 1min buy signals (red to green cross) and vice versa for the 5min agg. sloping down.
2. 5m / 30m / 60m - Also an interesting variation for day trading the 3-5 min charts. Producing more cleaner & beginner-friendly signals that lasts couple of minutes instead of seconds.
3. 120m / Day / 2 Day - For the 30m to 1H or 2H timeframes. Daily & 2 Day dictates the overall trend. 120 min for the signals. Great for a multi-day swings.
4. Day / 2 Day / Week - Good for the daily charts, swing trading analysis as the weekly dictates the overall trend, daily dictates the signals and the 2 day cleans out the daily signals. If the daily & 2 day are not aligned togather, daily signal means nothing. Weekly dictates 2 day - 2 day dictates daily.
5. Week / Month / 3 Month - Same thing as the previous variation but for the weekly charts.
TMO Length:
The default vanilla settings are 14,5,3. Some traders prefer 21,5,3 as the TMO length is litle higher = TMO will potenially last little longer which could teoretically produce less false signals but slower crosses which means signals will lag more behind price. The lower the length, the faster the oscillator oscillates. It is the noice vs. the lag debate. The Length can be changed, but i would not personally touch the other two. Few points up or down on length will not drastically change much. But changes on Calc Length and Smooth Length can produce totally different signals from the original.
Tips & Tricks:
1. Observe
- This is the best tip & trick I can give you. The #1 best way to learn how any study operates is to just observe how it works in certain situations from the past. MTF TMO is not
an exception.
2. The Power of the Higher Aggregation
- The higher aggregation ALWAYS dictates the lower one. Best way to see this? Just 2x the current timeframe aggregation = so on daily chart, plot the daily & two day TMOs and you will notice how the higher agg. smooths out the current agg. The higher the aggregation is, the smoother (but slower) will the TMO turn. The real power kicks in when the 3 or 4 aggregations are aligned togather in one direction.
3. Position of the Higher Aggregation in Relation to the Extremes
- Overbought / oversold signals might not really work on the current aggregation. But pay attention to the higher aggregations in relation to the extremes. Ex: on the daily chart - daily TMO inside the OB / OS extremes might not mean much. But once the higher aggregations such as 3 day or Weekly TMO enters OB/OS zone togather with the daily, this can be a very powerful signal for a TMO reversion to the zeroline.
4. Crosses
- Yes, crosses do work. Personally, I never really focused on them. The thing about the crosses is that it is crucial to pick the right higher aggregation to the combination of the current one that would be reliable but also print enough signals. The closer the cross is to the OB / OS extremes, the more bigger move can occur. Crosses around the zero line can be considered as less quality crosses.
5. Divergences
- TMO can print awesome divergences. The best divergences are on the current aggregation (TMO agg. same as the chart) since the current agg. oscillates fast, it can usually produce lower lows & higher highs faster then any higher aggregations. Easy setup: wait for the higher aggregation to reach the OB / OS extremes and watch the current (chart) aggregation to print a divergence.
6. Three is Enough
- I personally find more than three aggregations messy and hard to read. But there is always the option to turn on the 4th one. Just switch the TMO 4 Main, TMO 4 Signal and TMO 4 Fill in the style settings.
Hope it helps.
End-pointed SSA of Williams %R [Loxx]End-pointed SSA of Williams %R is an indicator that runes Williams %R SSA calculation through a Singular Spectrum Analysis (SSA) algorithm to derive a smoother final output. The reduction in noise from the traditional Williams %R is significant.
What is Williams %R?
Williams %R , also known as the Williams Percent Range, is a type of momentum indicator that moves between 0 and -100 and measures overbought and oversold levels. The Williams %R may be used to find entry and exit points in the market. The indicator is very similar to the Stochastic oscillator and is used in the same way. It was developed by Larry Williams and it compares a stock’s closing price to the high-low range over a specific period, typically 14 days or periods.
What is Singular Spectrum Analysis ( SSA )?
Singular spectrum analysis ( SSA ) is a technique of time series analysis and forecasting. It combines elements of classical time series analysis, multivariate statistics, multivariate geometry, dynamical systems and signal processing. SSA aims at decomposing the original series into a sum of a small number of interpretable components such as a slowly varying trend, oscillatory components and a ‘structureless’ noise. It is based on the singular value decomposition ( SVD ) of a specific matrix constructed upon the time series. Neither a parametric model nor stationarity-type conditions have to be assumed for the time series. This makes SSA a model-free method and hence enables SSA to have a very wide range of applicability.
For our purposes here, we are only concerned with the "Caterpillar" SSA . This methodology was developed in the former Soviet Union independently (the ‘iron curtain effect’) of the mainstream SSA . The main difference between the main-stream SSA and the "Caterpillar" SSA is not in the algorithmic details but rather in the assumptions and in the emphasis in the study of SSA properties. To apply the mainstream SSA , one often needs to assume some kind of stationarity of the time series and think in terms of the "signal plus noise" model (where the noise is often assumed to be ‘red’). In the "Caterpillar" SSA , the main methodological stress is on separability (of one component of the series from another one) and neither the assumption of stationarity nor the model in the form "signal plus noise" are required.
"Caterpillar" SSA
The basic "Caterpillar" SSA algorithm for analyzing one-dimensional time series consists of:
Transformation of the one-dimensional time series to the trajectory matrix by means of a delay procedure (this gives the name to the whole technique);
Singular Value Decomposition of the trajectory matrix;
Reconstruction of the original time series based on a number of selected eigenvectors.
This decomposition initializes forecasting procedures for both the original time series and its components. The method can be naturally extended to multidimensional time series and to image processing.
The method is a powerful and useful tool of time series analysis in meteorology, hydrology, geophysics, climatology and, according to our experience, in economics, biology, physics, medicine and other sciences; that is, where short and long, one-dimensional and multidimensional, stationary and non-stationary, almost deterministic and noisy time series are to be analyzed.
Included:
Bar coloring
[*Alerts
[*Signals
[*Loxx's Expanded Source Types
Related Williams %R Indicators
Williams %R on Chart w/ Dynamic Zones
Williams %R w/ Bollinger Bands
Intermediate Williams %R w/ Discontinued Signal Lines
Related SSA Indicators
End-pointed SSA of FDASMA
End-pointed SSA of Normalized Price Oscillator
GBTT Magic LineOverview:
This indicator merges concepts from RSI , Stochastic , and Stochastic RSI together and runs at a specific time period to look for potential oversold and overbought scenarios.
Intended use:
To provide educational content about the short term movement of an asset. Can be used on any time frame.
Disclaimer:
NOT intended to be a sole source of Technical Analysis or anything more than an educational tool!
UTG - Gravy TrainThe most complex indicator we've ever developed.
Works on ALL MARKETS!
Gravy Train is a ALL IN ONE - ONE GLANCE indicator.
- It allows you to gauge trend, gives you appropriate LONG & SHORT identifiers
- It identifies when the trades should be over
- Cloud based support & resistance Zones drawn on the chart
- It keeps you OUT of the market in areas of indecision
- It works on ALL timeframes
- Takes the emotion out of trading various markets
- Gravy Train is Unity Trading Groups bread and butter for Scalping, Swing Trading, Position Trading & Day Trading
Unity Trading Group is proud to present Gravy Train!
To gain access to this script, you can find our details in our Signature, use the links below to find out!
Parametric Oscillator (Zeiierman)█ Overview
The Parametric Oscillator (Zeiierman) transforms price movement into a structure-aware momentum field, a flowing wave of oscillator-candles wrapped around a smooth Quick Price Action line. Instead of reading raw closes, it constructs a multi-lane view from open, high, low, and close data to capture how price pressure expands, contracts, and shifts through time. These relationships are then projected into a bounded oscillator domain, creating a dynamic visualization of momentum and market balance.
The oscillator-candles flip green or red to signal shifts in buying or selling strength, while the Quick Line tracks underlying momentum on a 0–100 scale. Together, they reveal where pressure is forming, how quickly it’s changing, and whether that change is sustainable, helping traders spot momentum swings, stretched zones, and directional bias across any timeframe.
⚪ What Makes It Unique
The oscillator’s uniqueness lies in how it constructs and interprets price structure. It builds four independent lanes of open, high, low, and close to measure wave relationships and capture micro-drift, wick aggression, and full price behavior rather than relying solely on closing data.
Beneath the surface, the oscillator runs on a balanced motion function that translates market volatility into a clear rhythm of momentum and structure. Each change in color and gradient reflects the balance between acceleration and stability, revealing the underlying pulse of market behavior.
█ Main features
⚪ Parametric Oscillator
The Parametric Oscillator turns market movement into a visual map of buying and selling pressure. Its oscillator-candles reveal how momentum builds, compresses, and releases, showing the balance between strength and exhaustion in real time. As candles shift color and gradient, traders can instantly read acceleration, fading energy, or volatility spikes, allowing for quick interpretation of trend health and potential reversals.
The display captures both immediate bursts of momentum and the underlying trend’s persistence, giving a continuous view of how pressure evolves across market phases. It can be used to spot areas of buildup before breakouts, early signs of compression before expansion, and the transition points where control shifts from buyers to sellers.
⚪ Quick Price Action
The Quick Price Action line provides a smooth, real-time read of market momentum that often shifts before price itself reacts. Acting as a leading momentum gauge, it highlights subtle changes in strength and direction, helping traders anticipate moves rather than chase them.
When the line begins to turn, it frequently does so well ahead of price, signaling acceleration, exhaustion, or an early phase of reversal. A rise toward higher levels reflects building bullish pressure, while a downturn from elevated zones shows fading strength or emerging sell bias.
It adapts smoothly across symbols and timeframes, the Quick Price Action line gives traders a consistent, early warning system and a clear visual cue of when momentum is starting to shift and where the next meaningful move may form.
█ How to Use
⚪ Trend Following
The Momentum Candle Line helps define the underlying directional bias by measuring the strength and persistence of momentum. When momentum holds above or below the midline (50), it reflects whether buyers or sellers maintain control of the trend. Watching how the candles form relative to that level helps identify continuation or potential shifts in direction.
Maintain a bullish bias when the Momentum Candles stay above 50 and candles form higher lows.
Maintain a bearish bias when they stay below 50 and candles form lower highs.
⚪ Detect Leading Momentum
The Quick Price Line helps identify leading momentum moves that often precede price action. These can signal the start of a new move in that direction or the early stages of a reversal.
When the Quick Line peaks above 80, it indicates strong positive momentum.
When it peaks below 30, it signals strong negative momentum.
By observing how the momentum candles behave around these levels, traders can determine whether the move is likely a continuation or a reversal.
⚪ Fading Price Moves
Momentum drives price to new highs and lows, but when that momentum fades, reversals often follow. The Quick Price Line or the Parametric Oscillator candles can reveal weakening momentum before price reacts, giving traders an early signal. When the Quick Line peaks and then begins to fade, it indicates that momentum is losing strength. This can precede a pause, a range, or a full reversal in price. Likewise, if the Parametric Oscillator starts to fade while price continues to move, it suggests that momentum is weakening and a reversal or pullback may be approaching.
█ How It Works
⚪ Dual-Lane Displacement
Price is decomposed into trend and fast components across the open, high, low, and close. These relationships form four signed streams that describe body drive and wick aggression.
Calculation: Builds relative spreads between the trend and fast components, creating a multi-dimensional price-flow state.
⚪ Parametric Mapping
Each data stream is passed through a parametric transform (defaulting to a momentum-sensitive map) and assembled into synthetic OHLC in oscillator space.
Calculation: Applies a state transform over the data, aggregates into oscillator OHLC, and exponentially smooths for stability.
⚪ Quick Price Action
A companion line extracts recent trend displacement, normalizes it in a rolling window around the local mid, and passes it through a smoothing process controlled by Price Trend (softness). This yields a stable 0–100 scale that reacts quickly yet remains consistent across assets and timeframes.
Calculation: Windowed normalization around a dynamic midpoint with adjustable softness to balance responsiveness and stability.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
