Hello,
I am fairly new to R and trying to calculate value at risk with exponentially
decreasing weights.My function works for a single vector of returns but does
not work with rollapply(), which is what I want to use. The function I am
working on should assig exponentially decreasing weights to the K most recent
returns and then order the returns in an ascending order. Subsequently it
should pick the last return for which the cumulative sum of the weights is
smaller or equal to a significance level. Thus, I am trying to construct a
cumulative distribution function and find a quantile.
This is the function I wrote:
VaRfun <- function(x, lambda = 0.94) {
#create data.frame and order returns such that the lates return is the first
df <- data.frame(weight = c(1:length(x)), return = rev(x)) K <- nrow(df)
constant <- (1-lambda)/(1-lambda^(K))#assign weights to the returns for(i in
1:nrow(df)) { df$weight[i] <- lambda^(i-1) * constant }#order returns in
an ascending order df <- df[order(df$return),]
#add the cumulative sum of the weights df$cum.weight <- cumsum(df$weight)
#calculate value at risk VaR <- -tail((df$return[df$cum.weight <= .05]), 1)
signif(VaR, digits = 3)}
It works for a single vector of returns but if I try to use it with
rollapply(), such as
rollapply(r, width = list(-500, -1), FUN = VaRfun),
it outputs a vector of NAs and I don't know why.
Thank you for your help!
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