famafrench.FamaFrench.getFamaFrenchStats

FamaFrench.getFamaFrenchStats(self, dataType, dataFreq, dt_start, dt_end, *args)[source]

Detailed summary statistics tables of portfolio returns (which may include factor returns), number of firms in each portfolio, or average anomaly portfolio characteristics at a given frequency and for a given sample period.

Parameters

  • dataType (str) –

    Dataset type to construct. Possible choices are:

    • Returns

    • Factors

    • NumFirms

    • Characs

  • dataFreq (str) –

    Observation frequency of the portfolios. Possible choices are:

    • D : daily

    • W : weekly

    • M : monthly

    • Q : quarterly (3-months)

    • A : annual

  • 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 idList. For example, if idList = ['ME', 'BM'] and dim = [5, 5], then the portfolio sorting strategy is characterized by a bivariate quintile sort on both size and book-to-market.

  • pRetType (str, [optional]) –

    Weighting-scheme for portfolios. Possible choices are:

    • vw : value-weights

    • ew : equal-weights

Returns

Return type

None

Note

Currently, this method only prints out a table w/ detailed summary statistics. Future versions of the package will provide more in-depth statistical analysis and their outputs.

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.