import os
import pandas as pd
from sklearn import linear_model
path = rD:\新数据\每日收益率
filenames = os.listdir(path)
for filename in filenames:
print(filename)
for i in filenames:
excel_path = D:\新数据\每日收益率\\ + i
f = open(excel_path, b)
data = pd.read_excel(f) #到此处已是循环读取某文件夹下所有excel文件,下面是在循环中对读进来的文件进行统一的重复的一致的处理
data[ ime] = data.index
data = data.reset_index(drop = True)
data1 = data.iloc[0:110,]#估计窗口的真实收益率
data2 = data.iloc[110:,]#事件窗口的真实收益率
feature = data.columns.tolist()
feature.remove( ime)
feature.remove( 00300)#沪深300指数
dfR = pd.DataFrame(data2[ ime])
dfAR = pd.DataFrame(data2[ ime])
for m in feature:
regr=linear_model.LinearRegression()
regr.fit(data1[ 00300&