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Correlation between Time Series Indicators ( Stock Prices )
The Next CEO of Stack Overflow2019 Community Moderator ElectionAirline Fares - What analysis should be used to detect competitive price-setting behavior and price correlations?How to speed up optimization using Differential Evolution?Methods for Determining Possible Causation Between Two Time Serieswhich neural network topology to learn correlations between time series?Calculating correlation between two time variablesFeature selection for time series predictionHow to normalize data of a different nature?Determining the correlations between aggregated data and non aggregated dataHow to find correlation between time-series of different units?Mean Absolute Error increasing with more correlated factors
$begingroup$
I am new to time series analysis and I am currently tackling a stock market prediction problem.
I have a set of market indicators (such as Bollinger Bands, ADX etc) which are derived from the time dependent Open, High, Low and Close prices ( in Dollars ).
I need to find correlations of this indicators with the Open, Low, High and Close prices over time and drop the features which are not correlated enough ( less than 0.70 )
I am working on python. Using Pandas I have tried the pandas.dataframe.corr() method as well, but I want to know if Pearson and Spearman correlation fucntions in pandas serve my purpose ? Is it the right way or is there another way of finding correct correlations ?
Thanks.
machine-learning time-series statistics feature-selection correlation
asked Mar 23 at 9:24
Savinay_Savinay_
774
$endgroup$
add a comment |
$begingroup$
I am new to time series analysis and I am currently tackling a stock market prediction problem.
I have a set of market indicators (such as Bollinger Bands, ADX etc) which are derived from the time dependent Open, High, Low and Close prices ( in Dollars ).
I need to find correlations of this indicators with the Open, Low, High and Close prices over time and drop the features which are not correlated enough ( less than 0.70 )
I am working on python. Using Pandas I have tried the pandas.dataframe.corr() method as well, but I want to know if Pearson and Spearman correlation fucntions in pandas serve my purpose ? Is it the right way or is there another way of finding correct correlations ?
Thanks.
machine-learning time-series statistics feature-selection correlation
asked Mar 23 at 9:24
Savinay_Savinay_
774
$endgroup$
add a comment |
$begingroup$
I am new to time series analysis and I am currently tackling a stock market prediction problem.
I have a set of market indicators (such as Bollinger Bands, ADX etc) which are derived from the time dependent Open, High, Low and Close prices ( in Dollars ).
I need to find correlations of this indicators with the Open, Low, High and Close prices over time and drop the features which are not correlated enough ( less than 0.70 )
I am working on python. Using Pandas I have tried the pandas.dataframe.corr() method as well, but I want to know if Pearson and Spearman correlation fucntions in pandas serve my purpose ? Is it the right way or is there another way of finding correct correlations ?
Thanks.
machine-learning time-series statistics feature-selection correlation
asked Mar 23 at 9:24
Savinay_Savinay_
774
$endgroup$
I am new to time series analysis and I am currently tackling a stock market prediction problem.
I have a set of market indicators (such as Bollinger Bands, ADX etc) which are derived from the time dependent Open, High, Low and Close prices ( in Dollars ).
I need to find correlations of this indicators with the Open, Low, High and Close prices over time and drop the features which are not correlated enough ( less than 0.70 )
I am working on python. Using Pandas I have tried the pandas.dataframe.corr() method as well, but I want to know if Pearson and Spearman correlation fucntions in pandas serve my purpose ? Is it the right way or is there another way of finding correct correlations ?
Thanks.
machine-learning time-series statistics feature-selection correlation
machine-learning time-series statistics feature-selection correlation
asked Mar 23 at 9:24
Savinay_Savinay_
774
asked Mar 23 at 9:24
Savinay_Savinay_
774
asked Mar 23 at 9:24
Savinay_Savinay_
774
asked Mar 23 at 9:24
Savinay_Savinay_
774
asked Mar 23 at 9:24
Savinay_Savinay_
774
774
add a comment |
add a comment |
1 Answer
1
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oldest
votes
$begingroup$
For time series, correlation is a different. A variable might b related past N values of other variables.
This article explains theory behind finding relationships in time series (Skip to section "Stationarity in Time Series") : https://www.quantstart.com/articles/Serial-Correlation-in-Time-Series-Analysis
This is an implementation in Python : https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
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1 Answer
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1 Answer
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active
oldest
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$begingroup$
For time series, correlation is a different. A variable might b related past N values of other variables.
This article explains theory behind finding relationships in time series (Skip to section "Stationarity in Time Series") : https://www.quantstart.com/articles/Serial-Correlation-in-Time-Series-Analysis
This is an implementation in Python : https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
$endgroup$
add a comment |
$begingroup$
For time series, correlation is a different. A variable might b related past N values of other variables.
This article explains theory behind finding relationships in time series (Skip to section "Stationarity in Time Series") : https://www.quantstart.com/articles/Serial-Correlation-in-Time-Series-Analysis
This is an implementation in Python : https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
$endgroup$
add a comment |
$begingroup$
For time series, correlation is a different. A variable might b related past N values of other variables.
This article explains theory behind finding relationships in time series (Skip to section "Stationarity in Time Series") : https://www.quantstart.com/articles/Serial-Correlation-in-Time-Series-Analysis
This is an implementation in Python : https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
$endgroup$
For time series, correlation is a different. A variable might b related past N values of other variables.
This article explains theory behind finding relationships in time series (Skip to section "Stationarity in Time Series") : https://www.quantstart.com/articles/Serial-Correlation-in-Time-Series-Analysis
This is an implementation in Python : https://machinelearningmastery.com/gentle-introduction-autocorrelation-partial-autocorrelation/
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
answered Mar 23 at 13:08
Shamit VermaShamit Verma
1,1191211
1,1191211
add a comment |
add a comment |
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