SMI Ergodic Indicator/Oscillator▮ Introduction
The Stochastic Momentum Index Ergodic Indicator (SMII) is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
It provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of "ergodicity", which helps remove market noise.
On ther other hand, the Stochastic Momentum Index Ergodic Oscillator (SMIO) is a histogram that measures the difference between TSI and it's signal line.
By default, in TradingView both SMII and SMIO are provided independently.
Here in this script these two indicators are combined, providing a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
The intrinsic value of this indicator lies in the fact that it allows fine adjustments in both calculation parameters, data source and visualization, features that are not present in the standard indicators or similar.
Also, trend lines breakouts and divergences detector were added.
▮ What to look for
When using the indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI and the price.
If price is rising but the SMI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the "SMII" and the "SMIO", that is, the "Stochastic Momentum Index Ergodic Indicator" together with the "Stochastic Momentum Index Ergodic Oscillator" (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, Stochastic Momentum Index (SMI) Refurbished .
This last one is purely based on the **SMI**, which is implemented using smoothed ratio between the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
SMI
SMI Ergodic Indicator/Oscillator of Money Flow Index▮ Introduction
The Stochastic Momentum Index Ergodic (SMII) indicator is a technical analysis tool designed to predict trend reversals in the price of an asset.
It functions as a momentum oscillator, measuring the ratio of the smoothed price change to the smoothed absolute price change over a given number of previous periods.
The Ergodic SMI is based on the True Strength Index (TSI) and integrates a signal line, which is an exponential moving average (EMA) of the SMI indicator itself.
The Ergodic SMI oscillator provides a clearer picture of market trends than the traditional stochastic oscillator by incorporating the concept of 'ergodicity', which helps remove market noise.
On ther other hand, MFI (Money Flow Index) is a technical analysis indicator used to measure the inflow of money into an asset and thus help identify buying and selling pressure in a given financial instrument.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Motivation: why another indicator?
By combining SMII with MFI, we can gain even more insights into the market.
One way to do this is to use the MFI as an input to the SMII, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Furthermore, there is the possibility of making several fine adjustments to both the calculation and visualization parameters that are not present in other indicators.
▮ What to look for
When using the SMII MFI indicator, there are a few things to look out for.
First, look at the SMII signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMII and the price.
If price is rising but the SMII is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMII is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
Divergences can be considered in both indicator and/or histogram.
Examples:
▮ Notes
The indicator presented here offers both the 'SMII' and the 'SMIO', that is, the 'Stochastic Momentum Index Ergodic Indicator' together with the 'Stochastic Momentum Index Ergodic Oscillator' (histogram), as per the documentation described in reference links.
So it is important to highlight the differences in relation to my other indicator, the 'Stochastic Momentum Index (SMI) of Money Flow Index (MFI)':
This last one is purely based on the SMI , which is implemented using SMA smoothing for the relative range and the high/low range.
Although they may seem the same in some situations, the calculation is actually different. The TSI tends to be more responsive at the expense of being noisier, while the SMI tends to be smoother. Which of these two indicators is best depends on the situation, the context, and the analyst's personal preference.
Please refer to reference links to more info.
▮ References
SMI documentation
SMII documentation
SMIO documentation
MFI documentation
Harmonic Trend Fusion [kikfraben]📈 Harmonic Trend Fusion - Your Personal Trading Assistant
This versatile tool combines multiple indicators to provide a holistic view of market trends and potential signals.
🚀 Key Features:
Multi-Indicator Synergy: Benefit from the combined insights of Aroon, DMI, MACD, Parabolic SAR, RSI, Supertrend, and SMI Ergodic Oscillator, all in one powerful indicator.
Customizable Plot Options: Tailor your chart by choosing which signals to visualize. Whether you're interested in trendlines, histograms, or specific indicators, the choice is yours.
Color-Coded Trends: Quickly identify bullish and bearish trends with the color-coded visualizations. Stay ahead of market movements with clear and intuitive signals.
Table Display: Stay informed at a glance with the interactive table. It dynamically updates to reflect the current market sentiment, providing you with key information and trend direction.
Precision Control: Fine-tune your analysis with precision control over indicator parameters. Adjust lengths, colors, and other settings to align with your unique trading strategy.
🛠️ How to Use:
Customize Your View: Select which indicators to display and adjust plot options to suit your preferences.
Table Insights: Monitor the dynamic table for real-time updates on market sentiment and trend direction.
Indicator Parameters: Experiment with different lengths and settings to find the combination that aligns with your trading style.
Whether you're a seasoned trader or just starting, Harmonic Trend Fusion equips you with the tools you need to navigate the markets confidently. Take control of your trading journey and enhance your decision-making process with this comprehensive trading assistant.
Stochastic Momentum Index (SMI) of Money Flow Index (MFI)"He who does not know how to make predictions and makes light of his opponents, underestimating his ability, will certainly be defeated by them."
(Sun Tzu - The Art of War)
▮ Introduction
The Stochastic Momentum Index (SMI) is a technical analysis indicator that uses the difference between the current closing price and the high or low price over a specific time period to measure price momentum.
On the other hand, the Money Flow Index (MFI) is an indicator that uses volume and price to measure buying and selling pressure.
When these two indicators are combined, they can provide a more comprehensive view of price direction and market strength.
▮ Improvements
By combining SMI with MFI, we can gain even more insights into the market. One way to do this is to use the MFI as an input to the SMI, rather than just using price.
This means we are measuring momentum based on buying and selling pressure rather than just price.
Another way to improve this indicator is to adjust the periods to suit your specific trading needs.
▮ What to look
When using the SMI MFI indicator, there are a few things to look out for.
First, look at the SMI signal line.
When the line crosses above -40, it is considered a buy signal, while the crossing below +40 is considered a sell signal.
Also, pay attention to divergences between the SMI MFI and the price.
If price is rising but the SMI MFI is showing negative divergence, it could indicate that momentum is waning and a reversal could be in the offing.
Likewise, if price is falling but the SMI MFI is showing positive divergence, this could indicate that momentum is building and a reversal could also be in the offing.
In the examples below, I show the use in conjunction with the price SMI, in which the MFI SMI helps to anticipate divergences:
In summary, the SMI MFI is a useful indicator that can provide valuable insights into market direction and price strength.
By adjusting the timeframes and paying attention to divergences and signal line crossovers, traders can use it as part of a broader trading strategy.
However, remember that no indicator is a magic bullet and should always be used in conjunction with other analytics and indicators to make informed trading decisions.
Stochastic Momentum Index (SMI) Refurbished▮Introduction
Stochastic Momentum Index (SMI) Indicator is a technical indicator used in technical analysis of stocks and other financial instruments.
It was developed by William Blau in 1993 and is considered to be a momentum indicator that can help identify trend reversal points.
Basically, it's a combination of the True Strength Index with a signal line to help identify turning points in the market.
SMI uses the stochastic formula to compare the current closing price of an asset with the maximum and minimum price range over a specific period.
He then compares this ratio to a short-term moving average to create an indicator that oscillates between -100 and +100.
When the SMI is above 0, it is considered positive, indicating that the current price is above the short-term moving average.
When it is below 0, it is considered negative, indicating that the current price is below the short-term moving average.
Traders use the SMI to identify potential trend reversal points.
When the indicator reaches an extreme level above +40 or below -40, a trend reversal is possible.
Furthermore, traders also watch for divergences between the SMI and the asset price to identify potential trading opportunities.
It is important to remember that the SMI is a technical indicator and as such should be used in conjunction with other technical analysis tools to get a complete picture of the market situation.
▮ Improvements
The following features were added:
1. 7 color themes, for TSI, Signal and Histogram.
2. Possibility to customize moving average type for TSI/Signal.
3. Dynamic Zones.
4. Crossing Alerts.
5. Alert points on specific ranges.
5. Coloring of bars according to TSI/Signal/Histogram.
▮ Themes
Examples:
▮ About Dynamic Zones
'Most indicators use a fixed zone for buy and sell signals.
Here's a concept based on zones that are responsive to the past levels of the indicator.'
The concept of Dynamic Zones was described by Leo Zamansky ( Ph .D.) and David Stendahl, in the magazine of Stocks & Commodities V15:7 (306-310).
Basically, a statistical calculation is made to define the extreme levels, delimiting a possible overbought/oversold region.
Given user-defined probabilities, the percentile is calculated using the method of Nearest Rank.
It is calculated by taking the difference between the data point and the number of data points below it, then dividing by the total number of data points in the set.
The result is expressed as a percentage.
This provides a measure of how a particular value compares to other values in a data set, identifying outliers or values that are significantly higher or lower than the rest of the data.
▮ What to look for
1. Divergences/weakening of a trend/reversal:
2. Supports, resistances, pullbacks:
3. Overbought/Oversold Points:
▮ Thanks and Credits
- TradingView and PineCoders: for SMI and Moving Averages
- allanster: for Dynamic Zones
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
Multi SMI Ergodic OscillatorThe Multi SMI Ergodic Oscillator (Multi SMIEO) indicator can be used to identify potential buy and sell signals based on the relationship between the TSI and EMA lines.
The script is creating an indicator that plots multiple (3) sets of Time Series Indicator (TSI-Indicator) and Exponential Moving Average (EMA-Signal) lines as a single indicator.
The TSI is a momentum oscillator that helps identify overbought and oversold conditions. It is calculated using the close prices of an asset, a short-term moving average, and a long-term moving average. The script uses three different pairs of input values for the short-term and long-term periods, which can be adjusted by the user.
The EMA is a type of moving average that gives more weight to recent prices. It is calculated by applying a weighting factor to the most recent price, and then adding that weighted value to the previous EMA value. The script uses three different input values for the length of the EMA, which can also be adjusted by the user.
After calculating the TSI and EMA for each set, the script plots them on the same graph, with different colors and widths to differentiate them. The three sets of TSI and EMA lines are plotted to allow the user to compare the results of different periods. The script also plots a horizontal line at zero, which is used as a reference point for the oscillations of the indicator lines.
One way to use this indicator is to look for crossovers between the TSI and the EMA lines. A bullish crossover occurs when the TSI crosses above the EMA. This suggests that the buying pressure is increasing and a potential buy signal is generated. A bearish crossover occurs when the TSI crosses below the EMA. This suggests that the selling pressure is increasing and a potential sell signal is generated.
Some other ways that the indicator can be used include:
1. Identifying trends: The TSI and EMA lines can be used to identify the direction of the trend. An uptrend is present when the TSI and EMA lines are both trending upwards, while a downtrend is present when the TSI and EMA lines are both trending downwards.
2. Overbought and oversold conditions: The TSI can be used to identify overbought and oversold conditions. When the TSI is above the upper limit of the range, the asset is considered overbought and may be due for a price correction. Conversely, when the TSI is below the lower limit of the range, the asset is considered oversold and may be due for a price rebound.
3. Confirming price action: The Multi SMIEO indicator can be used to confirm price action. If a bullish divergence is present, it confirms a potential bullish reversal. If a bearish divergence is present, it confirms a potential bearish reversal.
4. Multiple time frame analysis: By using different periods for the TSI and EMA lines, the indicator can be used to analyze the asset on multiple time frames. It can be useful to compare the results of different periods to get a better understanding of the asset's price movements.
5. Risk management: This indicator can be used as an element of risk management strategy, it can help traders to identify overbought and oversold conditions to set stop loss or take profit levels.
The Multi SMI Ergodic Oscillator (Multi SMIEO) is a versatile indicator that can be used in a number of ways to analyze the price movements of an asset. It can be used to identify potential buy and sell signals, trends, overbought and oversold conditions, and to confirm price action. By using different periods for the TSI and EMA lines, the indicator can also be used to analyze the asset on multiple time frames. However, it is important to remember that indicators are based on historical data, and past performance does not guarantee future results.
It is important to use the indicator as part of a comprehensive trading strategy that includes risk management and other analysis techniques, such as fundamental and technical analysis. It is also important to keep in mind that indicators are not a standalone solution for trading, they should be used in conjunction with other market analysis and research techniques to generate better results.
Lastly, it is important to keep in mind that trading in financial markets comes with a certain level of risk and it is crucial to always have a proper risk management plan in place. Never invest more than you can afford to lose.
DMI Stochastic Momentum IndexConcepts
This is an improved version of the "DMI Stochastic Extreme Refurbished" indicator.
For more information on the main concepts of this indicator, please access this link:
The difference is that here, instead of using the traditional stochastic oscillator, I implemented the use of the Stochastic Momentum Index (SMI).
Stochastic Momentum Index (SMI)
The SMI is considered a refinement of the stochastic oscillator.
It calculates the distance of the current closing price as it relates to the median of the high/low range of price.
William Blau developed the SMI, which attempts to provide a more reliable indicator, less subject to false swings.
The original stochastic is limited to values from 0 to 100, while the SMI varies between the range of -100 to 100.
(Investopedia)
It is worth mentioning that the SMI presented in this script applies to the DMI value, not the screen price.
All TimeFrame OscillatorsI have always fighted to understand the market direction because it looks different on different timeframes.
I wanted an indicator where I can see all the different timeframes at once.
This indicator shows already existing oscillators but not only in the current chart's timeframe, but all the most important higer timeframes at once.
I have started with the stoch, then added as many oscillators as I could.
Experimenting with this I have saw that confluence of 4H 1D and 1W Stoch can be very interesting and can highlight higher timeframe take profit areas and sometimes major tops/bottoms.
Also bounces can be interesting when a lower timeframe stoch is bounced or rejected from a higher one.
Oscillators:
Stoch - Stochastic Oscillator
SMI - Stochastic Momentum Index
Rsi - Relative Strength Index
StochRsi - Stochastic RSI
WaveTrend - Vumanchu alias Market Cypher Wave Trend line
CCI - Commodity Channel Index
CCIStoch - Stochastic CCI
Williams Percent Range - Williams %R
Norm. MACD - Normalized Moving Average Convergence Divergence
Norm. MACD Hist - Normalized MACD Histogramm
PVT - Normalized Price Volume Trend
MFI - Money Flow Index
CMF - Chaikin Money Flow
Chande Momentum - Chande Momentum
Volume - Normalized Volume
CandleValue - Vumanchu alias Market Cypher MoneyFlow
BBWP - Bollinger Band Width Percentile
Line Type
Smooth: lines are smoothed, but the actualy not closed values are not shown
Step: Step lines, the actually open timeframes are calculated as they closed at the current values
Plot Oscillator or it's Slope:
its possible to not plot the oscillator but it's slope
Print dots when:
Cross Up/Down oversold/overbougt level - best for most oscillators. for example when Stoch crosses above 20 or below 80
Cross os/ob and the one higher TF is about to cross - when it's crosses beolw 80 and the higher timeframe oscillator is still above ans sloping down
Cross above/below middle line - for example on RSI being above or below 50 can be interesting
Print triangles when:
All Slope Match - all visible timeframe lines are pointing up or down at the same time
All above/belove middle line - all visible lines are above or belove the middle line
All above/belove middle line and slope match - like the previous one and the slope direction is the same
All above/below oversold/overbougt - all lines are above or below os/ ob. this is the default. it can be a very important confluence
Lower TF in order - 5, 15, 30, 60 minute timeframes are in order.
Higher TF in order - 4H 1D 1W in order (like 4H above 1D abd 1D above 1W). can be interesting at RSI
4H-1D in order - 4H 1D in order .
Print triangles
Print all triangles - print all triangles when the condition is met
Print only first triangles - only show when the condition starts to met
Print only last triangles - small triangles when the condition met first, large when last. tis is the default.
Timeframes to show:
You can turn on/off different timeframs to show or not from the list below:
1m 5m 15m 30m 1H 4H D 5D W M
This is for experimenting/ understanding the market direction on multiple timeframes at once.
Don't take it's signals (and any other indicator's) as exact trade signals. use it as confirmation instead.
Any comments, insights, ideas are welcome.
Combo Backtest 123 Reversal & SMI Ergodic Oscillator This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The SMI Ergodic Indicator is the same as the True Strength Index (TSI) developed by
William Blau, except the SMI includes a signal line. The SMI uses double moving averages
of price minus previous price over 2 time frames. The signal line, which is an EMA of the
SMI, is plotted to help trigger trading signals. Adjustable guides are also given to fine
tune these signals. The user may change the input (close), method (EMA), period lengths
and guide values.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal & Smart Money Index (SMI) This is combo strategies for get a cumulative signal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
WARNING:
- For purpose educate only
- This script to change bars colors.
SMIO strat SMIO strat with longer input which rounds off the trends. The strat is based on when SMIO hits over 0 it sends a buy signal and when it goes under it sends a short signal. The SMIO input was changed from 20, 5, 5 to 35, 15, 15.
Risk Reduction Ultimate TemplateThis is a template not actually meant for trading. I picked two random oscillators. This is a template meant to turn into a live trading strategy, however.
It's literally just a specialized take profit/stop loss system. It is to ensure your bot doesn't make any bad moves that you wouldn't have manually. The code should be pretty well annotated. Putting this into my scripts has made them much better. I will work on a Multiple Trigger template next.
Smart Money Index (SMI)It came to my attention that one very common implementation of SMI was incorrect; rather than subtracting the first hour delta and adding the last hour delta it subtracts the whole day delta and adds the last 30m delta. While this indicator might have had some use, it is not what I understand to be the actual Smart Money Index and so I post this as a correction for use in other scripts.
SMI Stochastic Momentum Index 2x set per Baiynd -Tom1traderStochastic Momemtum Index - a true strength indix tsi with a moving average signal.
This uses the built in with modifications per Anne-Marie Baiynds recommendations - she uses a SIMPLE MOVING AVERAGE
for the signal (signal length at 4x the short length seems to work best to reflect actual price action support or resistance)
Note: Default settings in this code have been updated to her most recent recommendations that I have seen.
video is entitled "The Most Reliable Technical Indicator I Have Ever Used"
Note: I have not discussed this with Ms . Baiynd this is my interpretation of the vids I have seen.
Anne-Marie Baiynd also in talks / videos refers to the use of short / long of 4/20 and 6/40 and have combined both of them here
This overlays both of them with their respective SMAs- a 4/20 lengths and a 6/40 lengths in darker colors and smallest linewidth.
this gives a perspective on slightly higher time frame action.
USAGE: Generally above and below the black dashed zero line is long or short
KEYS: -Plot position relative to zero black, red overbought, green oversold and the gray lines at .25 -.25
Indicator action often more significant out side of the more "neutral" +.25/-.25 area
and near or above/below the red/green dashed lines.
-Steepness of slopes
Slopes of smi plots relate directly to price action where steeper is more momentum.
- -SMI blue relation to its simple moving average orange and the SMI longer dark blue with moving average purple.
MAJOR FEATURE - The average acts as support or resistance to the SMI and the price unless breaking out.
Price is often pausing or reversing iin finding primary/secondary support or resistance as well at those times.
You Can See and anticipate Where Support or Resistance may be Encountered. (much unlike most indicators)
My standard caveat -use at your own risk. Like anyone else I do not know what the next bar/candle is going to do
and I place all of my trades with a management plan in place for the worst case scenario.
That said enjoy your charting and trading.
This was coded starting with the built-in indicator "SMI Ergontic Oscilator / Indicator". You do this by within the Pine Editor select "New" tab and
choose the indicator that you want the code for. This populates the editor with the code for the built in indicator and you can modify it to suit your
purposes and save it / publish it and etc. Thanks for following this and Keep Smiling!
Smart Money Index (50)Added MA50 to help interpret Smart Money Flow Index. Original SMI script by HPotter, idea of MA50 gotten from Troy Bombardia.
Smart Money Index (SMI) Backtest Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
You can change long to short in the Input Settings
WARNING:
- For purpose educate only
- This script to change bars colors.
Smart Money Index (SMI) Strategy Attention:
If you would to use this indicator on the ES, you should have intraday data 60min in your account.
Smart money index (SMI) or smart money flow index is a technical analysis indicator demonstrating investors sentiment.
The index was invented and popularized by money manager Don Hays. The indicator is based on intra-day price patterns.
The main idea is that the majority of traders (emotional, news-driven) overreact at the beginning of the trading day
because of the overnight news and economic data. There is also a lot of buying on market orders and short covering at the opening.
Smart, experienced investors start trading closer to the end of the day having the opportunity to evaluate market performance.
Therefore, the basic strategy is to bet against the morning price trend and bet with the evening price trend. The SMI may be calculated
for many markets and market indices (S&P 500, DJIA, etc.)
The SMI sends no clear signal whether the market is bullish or bearish. There are also no fixed absolute or relative readings signaling
about the trend. Traders need to look at the SMI dynamics relative to that of the market. If, for example, SMI rises sharply when the
market falls, this fact would mean that smart money is buying, and the market is to revert to an uptrend soon. The opposite situation
is also true. A rapidly falling SMI during a bullish market means that smart money is selling and that market is to revert to a downtrend
soon. The SMI is, therefore, a trend-based indicator.
Some analysts use the smart money index to claim that precious metals such as gold will continually maintain value in the future.
WARNING:
- This script to change bars colors.
SMI-VIX-SPY-NDX-Index
This script offers an SMI index of VIX, SPY, and NDX. Rather than overlaying VIX, NDX and SPY on the same chart.
It's much easier to see the correlation between VIX's price and NDX / SPY price in this manner.
Thanks to Buckkets & William Blau for the TSI smoothing method.
Stochastic Momentum IndexStochastic Momentum Index indicator script. This indicator was originally developed by William Blau (Stocks & Commodities V. 11:1 (11-18)).
Inverse Fisher Transform on SMI (Stochastic Momentum Index)Inverse Fisher Transform on SMI (Stochastic Momentum Index)
About John EHLERS:
From California, USA, John is a veteran trader. With 35 years trading experience he has seen it all. John has an engineering background that led to his technical approach to trading ignoring fundamental analysis (with one important exception).
John strongly believes in cycles. He’d rather exit a trade when the cycle ends or a new one starts. He uses the MESA principle to make predictions about cycles in the market and trades one hundred percent automatically.
In the show John reveals:
• What is more appropriate than trading individual stocks
• The one thing he relies upon in his approach to the market
• The detail surrounding his unique trading style
• What important thing underpins the market and gives every trader an edge
About INVERSE FISHER TRANSFORM:
The purpose of technical indicators is to help with your timing decisions to buy or
sell. Hopefully, the signals are clear and unequivocal. However, more often than
not your decision to pull the trigger is accompanied by crossing your fingers.
Even if you have placed only a few trades you know the drill.
In this article I will show you a way to make your oscillator-type indicators make
clear black-or-white indication of the time to buy or sell. I will do this by using the
Inverse Fisher Transform to alter the Probability Distribution Function (PDF) of
your indicators. In the past12 I have noted that the PDF of price and indicators do
not have a Gaussian, or Normal, probability distribution. A Gaussian PDF is the
familiar bell-shaped curve where the long “tails” mean that wide deviations from
the mean occur with relatively low probability. The Fisher Transform can be
applied to almost any normalized data set to make the resulting PDF nearly
Gaussian, with the result that the turning points are sharply peaked and easy to
identify. The Fisher Transform is defined by the equation
1)
Whereas the Fisher Transform is expansive, the Inverse Fisher Transform is
compressive. The Inverse Fisher Transform is found by solving equation 1 for x
in terms of y. The Inverse Fisher Transform is:
2)
The transfer response of the Inverse Fisher Transform is shown in Figure 1. If
the input falls between –0.5 and +0.5, the output is nearly the same as the input.
For larger absolute values (say, larger than 2), the output is compressed to be no
larger than unity. The result of using the Inverse Fisher Transform is that the
output has a very high probability of being either +1 or –1. This bipolar
probability distribution makes the Inverse Fisher Transform ideal for generating
an indicator that provides clear buy and sell signals.
SMI Ergodic Oscillator Backtest ver.2 The SMI Ergodic Indicator is the same as the True Strength Index (TSI) developed by
William Blau, except the SMI includes a signal line. The SMI uses double moving averages
of price minus previous price over 2 time frames. The signal line, which is an EMA of the
SMI, is plotted to help trigger trading signals. Adjustable guides are also given to fine
tune these signals. The user may change the input (close), method (EMA), period lengths
and guide values.
You can use in the xPrice any series: Open, High, Low, Close, HL2, HLC3, OHLC4 and ect...
WARNING:
- For purpose educate only
SMI Ergodic Oscillator Strategy ver.2 The SMI Ergodic Indicator is the same as the True Strength Index (TSI) developed by
William Blau, except the SMI includes a signal line. The SMI uses double moving averages
of price minus previous price over 2 time frames. The signal line, which is an EMA of the
SMI, is plotted to help trigger trading signals. Adjustable guides are also given to fine
tune these signals. The user may change the input (close), method (EMA), period lengths
and guide values.
You can use in the xPrice any series: Open, High, Low, Close, HL2, HLC3, OHLC4 and ect...
WARNING:
- For purpose educate only
