Rather than having to re-run your code each time to download the raw price data from Yahoo, to speed up your work,
SRM_mahalanobis= srm.MahalanobisDist(returns)[0]#define Mahalanobis Distance Formula
SRM_correlationsurprise= srm.Correlation_Surprise(returns)#define Correlation Surprise Score
SRM_absorptionratio= srm.Absorption_Ratio(returns)#define Absorption Ratio
write the above into files. so basically in the future you'll just be reading from the files to perform the performance analysis, rather than re-downloading again and again each time from the web.
you can try using pickles, or just use the standard IO methods in python to write to a file.
Hi Daniel,
Rather than having to re-run your code each time to download the raw price data from Yahoo, to speed up your work,
SRM_mahalanobis= srm.MahalanobisDist(returns)[0]#define Mahalanobis Distance Formula SRM_correlationsurprise= srm.Correlation_Surprise(returns)#define Correlation Surprise Score SRM_absorptionratio= srm.Absorption_Ratio(returns)#define Absorption Ratio
write the above into files. so basically in the future you'll just be reading from the files to perform the performance analysis, rather than re-downloading again and again each time from the web.
you can try using pickles, or just use the standard IO methods in python to write to a file.