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How to write regression loop over moving window and store data?


How do I download a file over HTTP using Python?How do I loop through or enumerate a JavaScript object?How do I break out of nested loops in Java?How do I iterate over a JSON structure?How to break out of jQuery each LoopIterating over dictionaries using 'for' loopsHow do I install pip on Windows?How to move a file in PythonHow do I write JSON data to a file?How to iterate over rows in a DataFrame in Pandas?






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0















Trying to write a loop to run a regression on multiple portfolios. It's over a 3 year moving window (so 1990-1993, 1991-1994, 1992-1995,...) and I would like to store the data in another dataframe and be able to access a particular portfolio and year. How can I get the data only from the 3 year window? This is the start I have, any tips? (I am a beginner programmer, thanks for any help!)



for i in range (4):
reg = smf.ols('LS_ret'+str(i)+'~ExMkt+HML+SMB', data=portfolioLS).fit()
reg.summary()
year = 1990
outcome = pd.DataFrame()
outcome = reg['LS_ret'+str(i)+year]
while year in range (1990,2017):
year = year + 1









share|improve this question






















  • Each time the for loop runs, year is reset to 1990.

    – James Phillips
    Mar 25 at 13:18

















0















Trying to write a loop to run a regression on multiple portfolios. It's over a 3 year moving window (so 1990-1993, 1991-1994, 1992-1995,...) and I would like to store the data in another dataframe and be able to access a particular portfolio and year. How can I get the data only from the 3 year window? This is the start I have, any tips? (I am a beginner programmer, thanks for any help!)



for i in range (4):
reg = smf.ols('LS_ret'+str(i)+'~ExMkt+HML+SMB', data=portfolioLS).fit()
reg.summary()
year = 1990
outcome = pd.DataFrame()
outcome = reg['LS_ret'+str(i)+year]
while year in range (1990,2017):
year = year + 1









share|improve this question






















  • Each time the for loop runs, year is reset to 1990.

    – James Phillips
    Mar 25 at 13:18













0












0








0








Trying to write a loop to run a regression on multiple portfolios. It's over a 3 year moving window (so 1990-1993, 1991-1994, 1992-1995,...) and I would like to store the data in another dataframe and be able to access a particular portfolio and year. How can I get the data only from the 3 year window? This is the start I have, any tips? (I am a beginner programmer, thanks for any help!)



for i in range (4):
reg = smf.ols('LS_ret'+str(i)+'~ExMkt+HML+SMB', data=portfolioLS).fit()
reg.summary()
year = 1990
outcome = pd.DataFrame()
outcome = reg['LS_ret'+str(i)+year]
while year in range (1990,2017):
year = year + 1









share|improve this question














Trying to write a loop to run a regression on multiple portfolios. It's over a 3 year moving window (so 1990-1993, 1991-1994, 1992-1995,...) and I would like to store the data in another dataframe and be able to access a particular portfolio and year. How can I get the data only from the 3 year window? This is the start I have, any tips? (I am a beginner programmer, thanks for any help!)



for i in range (4):
reg = smf.ols('LS_ret'+str(i)+'~ExMkt+HML+SMB', data=portfolioLS).fit()
reg.summary()
year = 1990
outcome = pd.DataFrame()
outcome = reg['LS_ret'+str(i)+year]
while year in range (1990,2017):
year = year + 1






python loops while-loop regression






share|improve this question













share|improve this question











share|improve this question




share|improve this question










asked Mar 25 at 1:29









aceace

11




11












  • Each time the for loop runs, year is reset to 1990.

    – James Phillips
    Mar 25 at 13:18

















  • Each time the for loop runs, year is reset to 1990.

    – James Phillips
    Mar 25 at 13:18
















Each time the for loop runs, year is reset to 1990.

– James Phillips
Mar 25 at 13:18





Each time the for loop runs, year is reset to 1990.

– James Phillips
Mar 25 at 13:18












0






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