Active Premium

perfana.core.returns.active_premium(ra, rb, freq=None, geometric=True, prefixes=('PRT', 'BMK'))[source]

The return on an investment’s annualized return minus the benchmark’s annualized return.

Parameters

  • ra (Union[DataFrame, Iterable[Union[int, float]], ndarray, Series]) – The assets returns vector or matrix

  • rb (Union[DataFrame, Iterable[Union[int, float]], ndarray, Series]) – The benchmark returns

  • freq (Optional[str]) – Frequency of the data. Use one of monthly, quarterly, semi-annually, yearly

  • geometric – If True, calculates the geometric returns. Otherwise, calculates the arithmetic returns

  • prefixes – Prefix to apply to overlapping column names in the left and right side, respectively. This is also applied when the column name is an integer (i.e. 0 -> PRT_0). It is the default name of the Series data if there are no name to the Series

Returns

Active premium of each strategy against benchmark

Return type

TimeSeriesData

Examples

>>> from perfana.datasets import load_etf
>>> from perfana.core import active_premium
# Get returns starting from the date where all etf has data
>>> etf = load_etf().dropna().pa.to_returns().dropna()
>>> active_premium(etf, etf)
          VBK       BND       VTI       VWO
VBK  0.000000 -0.055385 -0.010407 -0.063939
BND  0.055385  0.000000  0.044979 -0.008554
VTI  0.010407 -0.044979  0.000000 -0.053532
VWO  0.063939  0.008554  0.053532  0.000000
>>> active_premium(etf.VBK, etf.BND)
          VBK
BND  0.055385