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Dear All,   is there a function in R that would help me convert a covariance matrix built based on arithmetic returns to a covariance matrix from log-returns?   As an example of the means and covariance from arithmetic:   mu <-c(0.094,0.006,1.337,1.046,0.263) sigma

...0348),byrow=TRUE,ncol=5) mu <-c(0.094,0.006,1.337,1.046,0.263)   sampling form a lognormal distribution would be reasonable in this case as far as I can tell so with the help of Berend, the cov matrix was converted to log-return from an arithmetic return as follows:   logreturn <- function(am,asigma) {   M <- 1/(1+am)   S <- log( diag(M) %*% asigma %*% diag(M) + 1)   mu <- log(1+am) - diag(S)/2   list(mean=mu, vcov=S) } z <- logreturn(mu, sigma) logmean <-z$mean cov <-z$vcov   following I used : i <-matrix(rlnorm.rplus(5000,logmean,cov),ncol=5),  which will give me result...