okama.Portfolio.skewness_rolling

Portfolio.skewness_rolling(window=60)

Compute rolling skewness of the return time series.

For normally distributed rate of return, the skewness should be about zero. A skewness value greater than zero means that there is more weight in the right tail of the distribution.

Parameters:

windowint, default 60

Size of the moving window in months. The window size should be at least 12 months.

Returns:

Series

Expanding skewness time series

Examples

>>> pf = ok.Portfolio(['BND.US'])
>>> pf.skewness_rolling(window=12*10)
Date
2017-04    0.464916
2017-05    0.446095
2017-06    0.441211
2017-07    0.453947
2017-08    0.464805
...
2021-02    0.007622
2021-03    0.000775
2021-04    0.002308
2021-05    0.022543
2021-06   -0.006534
2021-07   -0.012192
Freq: M, Name: portfolio_8378.PF, dtype: float64

>>> import matplotlib.pyplot as plt
>>> pf.skewness_rolling(window=12*10).plot()
>>> plt.show()