def rolling_corr(x, y, **kwargs):
""" Rolling correlation between columns from x and y. """
def rolling(dataframe, *args, **kwargs):
ret = dataframe.copy()
for col in ret:
ret[col] = rolling_m(ret[col], *args, **kwargs)
return ret
n, k = x.shape
EX = rolling(x, **kwargs)
EY = rolling(y, **kwargs)
EX2 = rolling(x ** 2, **kwargs)
EY2 = rolling(y ** 2, **kwargs)
RXY = np.zeros((n, k, k))
for i, col_x in enumerate(x):
for j, col_y in enumerate(y):
DX = EX2[col_x] - EX[col_x] ** 2
DY = EY2[col_y] - EY[col_y] ** 2
RXY[:, i, j] = rolling_m(x[col_x] * y[col_y], **kwargs) - EX[col_x] * EY[col_y]
RXY[:, i, j] = RXY[:, i, j] / np.sqrt(DX * DY)
return RXY, EX.values
def rolling(dataframe, *args, **kwargs):
ret = dataframe.copy()
for col in ret:
ret[col] = rolling_m(ret[col], *args, **kwargs)
return ret
def rolling(dataframe, *args, **kwargs):
ret = dataframe.copy()
for col in ret:
ret[col] = rolling_m(ret[col], *args, **kwargs)
return ret