famafrench.FamaFrench.getNumFirms

FamaFrench.getNumFirms(self, factorsBool, dt_start, dt_end, *args)[source]

Construct dataset w/ number of firms in each portfolio at a given frequency and for a given sample period.

Parameters

  • factorsBool (bool) – Flag for choosing whether to construct Fama-French-style factors or not.

  • dt_start (datetime.date) – Starting date for the dataset queried or locally retrieved.

  • dt_end (datetime.date) – Ending date for the dataset queried or locally retrieved.

  • pDim (list, int, [optional]) – Dimensions for sorting on each element in the list self.sortCharacsId.

Returns

portNFirmsTable – Dataset w/ number of firms in each portfolio observed at frequency self.freqType over sample period from dt_start to dt_end for a given portfolio sorting strategy.

Return type

pandas.DataFrame

Note

If factorsBool = True, then the number of firms for the following anomaly/risk-based factors is defined as follows:

  • MKT : total number of firms (each period) in the market portfolio.

  • SMB, HML, RMW, RMWc, CMA, MOM, ST_Rev, LT_Rev : total number of firms (each period) in all portfolios used to construct the factors.

Note

Portfolios require anomaly characteristics from the last fiscal year. To get non-missing observations starting on date dt_start, we construct portfolios using a startdate that is two/three years prior to dt_start. We then slice the resulting pandas.DataFrames starting w/ dt_start.