【发布时间】:2017-05-23 04:38:12
【问题描述】:
在金融的背景下,假设有一个资产权重数据框和一个每日协方差矩阵面板:
w = pd.DataFrame({'Date':pd.to_datetime(['2016-01-01','2016-01-02','2016-01-03']),'A1':[0.3,0.1,0.1],'A2':[0.4,0.4,0.4]}).set_index(['Date'])
covar = [[[0.000087,0.000017],[0.000087,0.000017],[0.000087,0.000017]],[[0.000017,0.00019],[0.000017,0.00019],[0.000017,0.00019]]]
covPanel = pd.Panel(covar, items=['A1', 'A2'], major_axis=pd.to_datetime(['2016-01-01','2016-01-02','2016-01-03']), minor_axis=['A1', 'A2'])
要计算1天的投资组合方差,可以使用以下函数:
def portVar(w,sigma):
return w.dot(sigma.dot(w))
我可以每天将最后一行权重应用于协方差矩阵以获得每日方差:
out = covPanel.apply(lambda cov1: portVar(w.iloc[-1,:],cov1),axis = [2,0])
但是我如何将上述函数成对地应用于数据框和协方差矩阵,每天(无循环)?
换句话说,类似于:
pd.ApplyPairwise(portVar,w,covPanel)
并像上面的“out”一样返回每日方差?
【问题讨论】:
标签: pandas covariance finance portfolio