问题描述
我在 pandas DataFrame 中有一个时间序列的回报、滚动 beta 和滚动 alpha.如何计算 DataFrame 的 alpha 列的滚动年化 alpha?(我想做相当于=PRODUCT(1+[trailing 12 months])-1 in excel)
I have a time series of returns, rolling beta, and rolling alpha in a pandas DataFrame. How can I calculate a rolling annualized alpha for the alpha column of the DataFrame? (I want to do the equivalent to =PRODUCT(1+[trailing 12 months])-1 in excel)
SPX Index BBOEGEUS Index Beta Alpha
2006-07-31 0.005086 0.001910 1.177977 -0.004081
2006-08-31 0.021274 0.028854 1.167670 0.004012
2006-09-30 0.024566 0.009769 1.101618 -0.017293
2006-10-31 0.031508 0.030692 1.060355 -0.002717
2006-11-30 0.016467 0.031720 1.127585 0.013153
我很惊讶地发现 pandas 中没有为此内置滚动"功能，但我希望有人可以提供一个功能，然后我可以使用 pd.rolling_apply 将其应用于 df['Alpha'] 列.
I was surprised to see that there was no "rolling" function built into pandas for this, but I was hoping somebody could help with a function that I can then apply to the df['Alpha'] column using pd.rolling_apply.
提前感谢您提供的任何帮助.
Thanks in advance for any help you have to offer.
推荐答案
这样可以吗?
import pandas as pd
import numpy as np
# your DataFrame; df = ...
pd.rolling_apply(df, 12, lambda x: np.prod(1 + x) - 1)
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