[R] Expanding VaR package

[Benjamin Dickgiesser]

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