```
# NOT RUN {
# A univariate GARCH model is used with rolling out of sample forecasts.
data(dji30ret)
spec = ugarchspec(mean.model = list(armaOrder = c(6,1), include.mean = TRUE),
variance.model = list(model = "gjrGARCH"), distribution.model = "nig")
fit = ugarchfit(spec, data = dji30ret[, 1, drop = FALSE], out.sample = 1000)
pred = ugarchforecast(fit, n.ahead = 1, n.roll = 999)
dmatrix = cbind(as.numeric(fitted(pred)),as.numeric(sigma(pred)),
rep(coef(fit)["skew"],1000), rep(coef(fit)["shape"],1000))
colnames(dmatrix) = c("mu", "sigma", "skew", "shape")
# Get Realized (Oberved) Data
obsx = tail(dji30ret[,1], 1000)
# Transform to Uniform
uvector = apply(cbind(obsx,dmatrix), 1, FUN = function(x) pdist("nig", q = x[1],
mu = x[2], sigma = x[3], skew = x[4], shape = x[5]))
# hist(uvector)
# transform to N(0,1)
nvector = qnorm(uvector)
test1 = BerkowitzTest(data = nvector, lags = 1, significance = 0.05)
test2 = BerkowitzTest(data = nvector, alpha = 0.05, significance = 0.05,
tail.test=TRUE)
test3 = BerkowitzTest(data = nvector, alpha = 0.01, significance = 0.05,
tail.test=TRUE)
# }
```

Run the code above in your browser using DataLab