You can ignore the warning. You can calculate the values yourself and check that the results are the same:

df = as.data.frame(bi.backtest.nig)

q = quantile(bi.backtest.nig,0.01)
q10 = qdist("nig",0.01,mu=0,sigma=df[10,"Sigma"],skew=df[10,"Skew"],shape=df[10,"Shape"])
as.numeric(q[10])==q10
> TRUE
q5 = qdist("nig",0.01,mu=0,sigma=df[5,"Sigma"],skew=df[5,"Skew"],shape=df[5,"Shape"])
as.numeric(q[5])==q5
> TRUE

The warning will be fixed in the development version (...soon).

Alexios

On 16/08/2015 17:55, Mingersming wrote:
Hi all,

there is one issue I canĀ“t go one myself. I try to fit a nig-distribution in
a rolling window method to a time-series with the fantastic rugarch package.
I use the option 'calculate.VaR' for several other distributions and it
works fine, but if I switch to the nig-distribution, I recieve the following
warning:

In ans[i] = mu[i] + sigma[i] * .qsnigC(p, rho = skew[i],  ... :number of
items to replace is not a multiple of replacement length

I tried to turn off the option and calculate the quantile on my own. I think
there is an misstake with the number of the parameters, but what can I
change to get over?

For code, see below

Best regards

library(quantmod)
library(rugarch)
library(PerformanceAnalytics)

bi <- getSymbols('^GDAXI', from = "2004-01-01", to = "2015-08-01")       
bi <- Ad(get(bi[1]))
bi_tlr <- Return.calculate(bi, method = "log")
bi_tlr <- na.omit(bi_tlr)

ctrl = list(rho = 1, delta = 1e-11, outer.iter = 1000, tol = 1e-12)
cl = makePSOCKcluster(10)

T = nrow(bi_tlr)
t_bt <- nrow(as.xts(bi_tlr)["2006-01-01/2015-08-01"])
t_est <- T - t_bt

spec_nig = ugarchspec(variance.model = list(model = "sGARCH", garchOrder =
c(1,1)),
mean.model = list(armaOrder = c(0,0), include.mean = FALSE),
distribution.model = "nig")

bi.backtest.nig = ugarchroll(spec_nig, data = bi_tlr, n.ahead = 1,
forecast.length = 10, refit.every = 1, refit.window = "moving", solver =
"hybrid", fit.control = list(), solver.control = ctrl, calculate.VaR = TRUE,
VaR.alpha = c(0.01,0.05), cluster = cl,keep.coef = TRUE)





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