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rperformanceanalyticsrollapplycomputational-finance

Estimation of rolling Value at Risk (VaR) using R

I need to perform rolling VaR estimation of daily stock returns. At first I did the following:

library(PerformanceAnalytics)
data(edhec)
sample<-edhec[,1:5]
var605<-rollapply(as.zoo(sample),width=60,FUN=function(x) VaR(R=x,p=.95,method="modified",invert=T),by.column=TRUE,fill=NA)

It performs the computation and returns a zoo object but gives a series of warnings as follows:

VaR calculation produces unreliable result (inverse risk) for column: 1 : -0.00030977098532231

Then, I tried the same with sample of my data as follows:

library(foreign)
sample2 <- read.dta("sample2.dta")
sample2.xts <- xts(sample2[,-1],order.by=as.Date(sample2$datadate,format= "%Y-%m-%d"))
any(is.na(sample2.xts))
var605<-rollapply(as.zoo(sample2.xts),width=60,FUN=function(x) VaR(R=x,p=.95,method="modified",invert=T),by.column=TRUE,fill=NA)

But is does not return any zoo object and gives the following warnings and error:

VaR calculation produces unreliable result (inverse risk) for column: 1 : -0.0077322590200255
Error in if (eval(tmp < 0)) { : missing value where TRUE/FALSE needed
Called from: top level

From an earlier post (Using rollapply function for VaR calculation using R) I understand that rolling estimation cannot be performed if complete rolling window is missing, but in my data (sample2.dta) there are no missing values.

sample2.dta can be downloaded from https://drive.google.com/file/d/0B8usDJAPeV85WDdDQTFEbGQwaUU/edit?usp=sharing

Can anyone please help me to resolve and understand this issue?

Solution

  • 1) We can reproduce the warning using only VaR as follows:

    > VaR(R = edhec[seq(25, length=60), 5], p = .95, method = "modified", invert = TRUE)
VaR calculation produces unreliable result (inverse risk) for column: 1 : -0.000203691774704274
    Equity Market Neutral
VaR                    NA

    Try using a different method=.

    > VaR(R = edhec[seq(25, length=60), 5], p = .95, method = "gaussian", invert = TRUE)
    Equity Market Neutral
VaR          -0.001499347

    2) With "gaussian" I still got warnings on the real data set but no errors. Try experimenting with the other "method" argument values that are available as well. See ?VaR .

    3) Note that by.column = TRUE can be omitted as it is the default.