Sharpe Ratio and Information Ratio in R

# MORE INFO: http://www.reakkt.com/2012/07/calculating-sharpe-ratio-and.html

SharpeRatio <- function(x,rf=0.05,fq=1,annualized=FALSE,visualize=FALSE) {
# x  - returns
# rf - risk free or constant benchmark interest rate
# fq - frequency of x per day; 1 - daily
# reference: http://en.wikipedia.org/wiki/Sharpe_ratio

  n <- length(x)

  rft <- (1+rf)^(1/(252*fq))-1

  xrf <- -rft+x # -rep(rft,n)

  xrf.m  <- mean(xrf) # mean
  xrf.sd <- sd(xrf)   # standard deviation

  sharpe.ratio <- xrf.m / xrf.sd

  if (annualized) sharpe.ratio <- sqrt(252*fq)*sharpe.ratio

  if (visualize) {

    matplot(cbind(cumprod(1+x),cumprod(rep(1+rft,n))),type="l",main="Sharpe Ratio",ylab="")
    mtext(paste("value =",format(sharpe.ratio,digits=4),
                ifelse(annualized,"annualized,",""),
                "excess mean =",format(xrf.m,digits=4)),line=0.5)

  }

  return( sharpe.ratio )

}

InformationRatio <- function(x, rb, fq=1, annualized=FALSE, visualize=FALSE) {

  n <- length(x)

  xrb <- x-rb

  xrb.m  <- mean(xrb)
  xrb.sd <- sd(xrb)

  information.ratio <- xrb.m / xrb.sd

  if (annualized) information.ratio <- sqrt(252*fq)*information.ratio

  if (visualize) {

    matplot(cbind(cumprod(1+x),cumprod(1+y)),type="l",main="Information Ratio",ylab="")
    mtext(paste("ratio =",format(information.ratio,digits=4),
                ifelse(annualized,"annualized,",""),
                "excess mean  =",format(xrb.m,digits=4)),line=0.5)

  }

  return( information.ratio )

}

# example:

x <- rnorm(252,mean=0.5,sd=2)/100 # 0.1/100 -> 0.1%
y <- rnorm(252,mean=0.2,sd=1)/100

summary(x)
tail(cumprod(1+x),1)

SharpeRatio(x,rf=0.05,fq=1,annualized=TRUE,visualize=TRUE)
InformationRatio(x,y,fq=1,annualized=FALSE,visualize=TRUE)