英文:
Way of turning Fama-French factors into quarterly in stead of monthly returns
问题
我正在尝试创建季度的Fama French因子。我使用getFamaFrenchFactors包下载了月度因子数据，但我不知道如何将它们转换为季度数据点。
我尝试过使用cumsum对它们进行累加，但在最后创建了非常大的因子。以下是我的代码：
import getFamaFrenchFactors as gffdf_ff3_monthly = gff.famaFrench3Factor(frequency='m')df_ff3_monthly['date_ff_factors'] = pd.to_datetime(df_ff3_monthly['date_ff_factors'])df_ff3_monthly = df_ff3_monthly[df_ff3_monthly['date_ff_factors'] > '2020-12-31']df_ff3_monthly.set_index('date_ff_factors', inplace=True)df_ff3_quarterly = df_ff3_monthly.resample('Q').sum().cumsum()df_ff3_quarterly
英文:
I am trying to create quarterly Fama French factors. I used the getFamaFrenchFactors package to download the factors monthly, but I have no idea how I can turn them into quarterly data points.
I tried to cumsum them, but it created very large factors at the end. This is my code:
import getFamaFrenchFactors as gffdf_ff3_monthly = gff.famaFrench3Factor(frequency='m')df_ff3_monthly['date_ff_factors'] = pd.to_datetime(df_ff3_monthly['date_ff_factors'])df_ff3_monthly = df_ff3_monthly[df_ff3_monthly['date_ff_factors'] > '31-12-2020']df_ff3_monthly.set_index('date_ff_factors', inplace=True)df_ff3_quarterly = df_ff3_monthly.resample('Q').sum().cumsum()df_ff3_quarterly
答案1
得分: 1
你可以计算累积收益率，然后转换为季度数据：
df_quarterly = df_ff3_monthly.add(1).cumprod().resample("Q").last().pct_change()#Out[]:# Mkt-RF SMB HML RF#date_ff_factors#2021-03-31 NaN NaN NaN NaN#2021-06-30 0.081282 -0.018005 -0.022328 0.000000#2021-09-30 -0.003373 -0.037145 0.030646 0.000000#2021-12-31 0.082518 -0.052192 0.022916 0.000100#2022-03-31 -0.056030 -0.053894 0.141307 0.000100#2022-06-30 -0.173744 -0.011717 0.081960 0.001000#2022-09-30 -0.044194 0.033851 -0.037546 0.004607#2022-12-31 0.055603 -0.039705 0.109870 0.008524#2023-03-31 0.065063 0.003491 -0.133761 0.010537#2023-06-30 0.006100 -0.033400 -0.000300 0.003500
英文:
You can calculate the cumulative returns, then back to quarterly:
df_quarterly = df_ff3_monthly.add(1).cumprod().resample("Q").last().pct_change()#Out[]:# Mkt-RF SMB HML RF#date_ff_factors#2021-03-31 NaN NaN NaN NaN#2021-06-30 0.081282 -0.018005 -0.022328 0.000000#2021-09-30 -0.003373 -0.037145 0.030646 0.000000#2021-12-31 0.082518 -0.052192 0.022916 0.000100#2022-03-31 -0.056030 -0.053894 0.141307 0.000100#2022-06-30 -0.173744 -0.011717 0.081960 0.001000#2022-09-30 -0.044194 0.033851 -0.037546 0.004607#2022-12-31 0.055603 -0.039705 0.109870 0.008524#2023-03-31 0.065063 0.003491 -0.133761 0.010537#2023-06-30 0.006100 -0.033400 -0.000300 0.003500
通过集体智慧和协作来改善编程学习和解决问题的方式。致力于成为全球开发者共同参与的知识库，让每个人都能够通过互相帮助和分享经验来进步。
评论