anchor.diff:  print(results.summary())
   
   
  +-------------------
   
   
   
   
   
  -
  -
  
positive.code: 
  ( Ri - Rf ) = alpha + beta * ( Rm - Rf ).
  
  Gene Fama and Ken French argued convincingly that there are additional risk factors that can better describe the expected excess return, namely a size premium (SMB) and a value premium (HML). Recent research has shown that the expected return can further be improved with additional factors. Cliff Asness eloquently  https://www.aqr.com/cliffs-perspective/our-model-goes-to-six-and-saves-value-from-redundancy-along-the-way[describes them] as follows:
  
  . Premium Factors
  * RM-RF - The return spread between the capitalization weighted stock market and cash.
  
negative.code: from urllib import urlopen
  import pandas.io.data as web
  import statsmodels.api as sm
  url = urlopen("http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/F-F_Research_Data_5_Factors_2x3_CSV.zip")
  zipfile = ZipFile(StringIO(url.read()))
  FFdata = pd.read_csv(zipfile.open('F-F_Research_Data_5_Factors_2x3.CSV'), 
  