pointers on using VaR.gpd with return series?

I think that there is a problem with the VaR.gpd function, as it works on
USD/EUR and not on EUR/USD values

library(PerformanceAnalytics)
eurusd <- get.hist.quote("EUR/USD", provider="oanda", start = "2006-01-01")
usdeur <- get.hist.quote("USD/EUR", provider="oanda", start = "2006-01-01")

library(VaR)
v1 <- VaR.gpd(as.vector(eurusd))
v2 <- VaR.gpd(as.vector(usdeur))


output:

  

v1 <- VaR.gpd(as.vector(eurusd))
    

Error in optim(init, gpd.liklhd, hessian = TRUE, method = "Nelder-Mead") :
         non-finite finite-difference value [2]
In addition: There were 50 or more warnings (use warnings() to see the 
first 50)

  

Ouch the default parameters there are two possible fixes setting the 
cut-off threshold using p.tr helps.

(a)  doing the following call on your data comes back with some results..

 > v1 <- VaR.gpd(as.vector(eurusd),p.tr=0.95)

(b) The other alternate is to rewrite VaR.gpd and set  hessian=FALSE 
where it makes the call to maximize the log-likelihood.

optim(init, gpd.liklhd, *hessian = TRUE*, method = "Nelder-Mead") :


Neither of these are "the solution"  as this is more an Art than a 
science. Method (a) relates to the question of  how to pick the 
threshold. Very few and
 you have biased fit and too many you are no longer fitting the tail.

In this context I would point you towards the evir library and the 
excellent book by Alex Mcneill on this but doing the following should 
give you some hints..

 >require(evir)
 >shape(danish)

Hope this helps,

Best
Krishna