{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

24.index_R

# 24.index_R - University of California Los Angeles...

This preview shows pages 1–2. Sign up to view the full content.

University of California, Los Angeles Department of Statistics Statistics C183/C283 Instructor: Nicolas Christou Constructing the optimal portfolios - Single index model R commands In this example we use data from 5 stocks plus the S & P 500 index. Read the data: data1 <- read.table("http://www.stat.ucla.edu/~nchristo/statistics_c183_c283/ stocks_5_ret.txt", header=TRUE) Read the data in matrix form: b <- as.matrix(data1) Initialize the vectors and matrices: x <- rep(0, 30) xx <- matrix(x, ncol=6, nrow=5) stock <- rep(0,5) alpha <- rep(0,5) beta <- rep(0,5) mse <- rep(0,5) Rbar <- rep(0,5) Ratio <- rep(0,5) col1 <- rep(0,5) col2 <- rep(0,5) col3 <- rep(0,5) col4 <- rep(0,5) col5 <- rep(0,5) Risk free rate: rf <- 0.001 Perform regression of each stock on the index and record α, β, σ 2 i : for(i in 1:5){ alpha[i] <- lm(data=data1,formula=data1[,i] ~ data1[,6])\$coefficients[1] beta[i] <- lm(data=data1,formula=data1[,i] ~ data1[,6])\$coefficients[2] Rbar[i] <- alpha[i]+beta[i]*mean(b[,6]) mse[i] <- sum(lm(data=data1, formula=data1[,i] ~ data1[,6])\$residuals^2)/(nrow(b)-2) Ratio[i] <- (Rbar[i]-rf)/beta[i] stock[i] <- i } So far we have this table: xx <- (cbind(stock,alpha, beta, Rbar, mse, Ratio))

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 2

24.index_R - University of California Los Angeles...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online