Hi, it would be nice if the VaR package could get expanded to work with more models. I wrote a function which calculates the VaR for a Garch(1,1) AR(2) model. Since I am fairly new to R I am sure it can be written much neater. If someone feels like having a go, here is what I have written library(fSeries) library(tseries) VaR.Garch <- function(data,stockId=1,p=0.01,dt=1) { r <- diff(log(data)) #fit Garch(1,1), Ar(2) modell fit = garchFit(~arma(2,0), ~garch(1,1), series = r) #init vars rhat[1:3] <- 0 a[1:3] <- 0 sigma[1:3] <- 0 VaR[1:3] <- 0 for (t in 3:length(r)) { #Calculate r suggested by AR rhat[t] <- fit at fit$matcoef[1,1] + fit at fit$matcoef[2,1] * r[t-1] + fit at fit$matcoef[3,1]* r[t-2] #calculate error from fitted AR a[t] <- r[t] - rhat[t] #estimate sigma sigma[t] <- sqrt(fit at fit$matcoef[4,1] + fit at fit$matcoef[5,1] * sigma[t-1]^2 + fit at fit$matcoef[6,1] * a[t - 1]^2) # calculate the value at risk VaR[t] <- (1 - exp(rhat[t] * dt + sqrt(dt) * qnorm(p) * sigma[t])) * data[t] } list(VaR=VaR,r=rhat,std=sigma) } Sorry if this isn't the right place to post this. Benjamin