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R：如何一次为多个返回数据滚动回归？在一个数据框中使用因变量而在另一个数据框中使用回归量？

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大家好我想问一下，有没有办法一次性多次返回滚动窗口回归，一个数据框中的因变量和另一个数据框中的回归量？我试图结合rollapply和sapply功能来做到这一点 . 到目前为止，我似乎无法使其工作 .

对于金融背景：我想要做的是计算Fama-Macbeth回归的回归量 . 使用滚动窗口向前滚动1个月以更新回归量 . 与最初的1973年Fama-macbeth不同，估计期延长了4年 .

我附上了下面的示例脚本所需的.csv文件的链接，它包含来自雅虎财经的每日价格数据，以便你们可以更好地了解我想要做的事情 .

here are some csv files for the script，只需将其放入R工作目录并运行此脚本即可 .

library(xts)
library(quantmod)
library(lmtest)
library(sandwich)
library(MASS)
library(tseries)


data.AMZN<-read.csv("AMZN.csv",header=TRUE)
date<-as.Date(data.AMZN$Date,format="%Y-%m-%d")
data.AMZN<-cbind(date, data.AMZN[,-1])
data.AMZN<-data.AMZN[order(data.AMZN$date),]
data.AMZN<-xts(data.AMZN[,2:7],order.by=data.AMZN[,1])
names(data.AMZN)<-
  paste(c("AMZN.Open","AMZN.High","AMZN.Low",
          "AMZN.Close","AMZN.Volume","AMZN.Adjusted"))
data.AMZN[c(1:3,nrow(data.AMZN)),]

data.YHOO<-read.csv("YHOO.csv",header=TRUE)
date<-as.Date(data.YHOO$Date,format="%Y-%m-%d")
data.YHOO<-cbind(date, data.YHOO[,-1])
data.YHOO<-data.YHOO[order(data.YHOO$date),]
data.YHOO<-xts(data.YHOO[,2:7],order.by=data.YHOO[,1])
names(data.YHOO)<-
  paste(c("YHOO.Open","YHOO.High","YHOO.Low",
          "YHOO.Close","YHOO.Volume","YHOO.Adjusted"))
data.YHOO[c(1:3,nrow(data.YHOO)),]

data.mkt<-read.csv("GSPC.csv",header=TRUE)
date<-as.Date(data.mkt$Date,format="%Y-%m-%d")
data.mkt<-cbind(date, data.mkt[,-1])
data.mkt<-data.mkt[order(data.mkt$date),]
data.mkt<-xts(data.mkt[,2:7],order.by=data.mkt[,1])
names(data.mkt)[1:6]<-
  paste(c("GSPC.Open","GSPC.High","GSPC.Low",
          "GSPC.Close","GSPC.Volume","GSPC.Adjusted"))
data.mkt[c(1:3,nrow(data.mkt))]

rets<-diff(log(data.AMZN$AMZN.Adjusted))
rets$YHOO<-diff(log(data.YHOO$YHOO.Adjusted))
names(rets)[1]<-"AMZN"

mktrets<-diff(log(data.mkt$GSPC.Adjusted))
names(mktrets)[1]<- "GSPC"


rets<-rets[-1,]
rets.df = as.data.frame(rets)

mktrets<-mktrets[-1,]
mktrets.df = as.data.frame(mktrets)

# combining this funtion : do 252 days rolling window linear regression, 
#for a single asset as dependent variable and the other as regressor, in the same data frame
coeffs<-rollapply(rets,
                  width=252,
                  FUN=function(X)
                  {
                    roll.reg=lm(AMZN~YHOO,#YHOO is supposed to be GSPC, just an illustration.
                                data=as.data.frame(X))
                    return(summary(roll.reg)$coef)
                  },
                  by.column=FALSE)

#With this funtion : it does linear regressions for multiple assets in a different data frame at once
#and put it in a matrix.

Coefficients = sapply(1:ncol(rets),function(x) {
  summary(lm(rets[,x]~mktrets[,1]))$coefficients
}
)

#I need to the rolling regressions with different data frames because 
#in the real application,i need to assign a unique and specific regressor to 
#each dependent variable

也许问题太多了，但我真的需要这样做 . 任何关于如何做到这一点或任何其他方式的建议将非常感激 .

多谢你们 .

r linear-regression finance

1 回答

  • 0

    如果你需要所有系数，你可以修改 rollapply 中的函数（编辑：结果需要是一个向量）：

    coeffs<-rollapply(1:nrow(rets),
              width=252,
              FUN=function(i) #i=1:252
              {
                yrets=rets.df[i,]
                xmktrets=mktrets.df[i,]
                Coefficients =do.call("cbind",lapply(1:ncol(yrets),function(y) { #y=2
                  t(summary(lm(yrets[,y]~xmktrets))$coefficients)
                } ))
                rs=c()
                for(j in 1:4)rs<-c(rs,Coefficients[j,])
                c(rs,Data=as.Date(index(rets)[max(i)],"%y-%m-%d"))
              },
              by.column=FALSE)

    然后你可以从coeffs中提取信息：

    #the betas
colnames(rets)
plot.zoo(coeffs[,c(1,2)],col=2:3,main=colnames(rets)[1]) #"AMZN"

    enter image description here

    plot.zoo(coeffs[,c(3,4)],col=3:4,main=colnames(rets)[2]) #"YHOO"

    enter image description here

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