def ta_ewma_covariance(df: Typing.PatchedPandas,
convert_to='returns',
alpha=0.97):
data = df.copy()
if convert_to == 'returns':
data = df.pct_change()
if convert_to == 'log-returns':
data = _np.log(df) - _np.log(df.shift(1))
data.columns = data.columns.to_list()
return data.ewm(com=alpha).cov()
def ta_log_returns(df: Typing.PatchedPandas, period=1):
current = df
lagged = df.shift(period)
return _wcs("log_return", np.log(current) - np.log(lagged))
