Hi Rafael,

VaRloss and VaRTest take the realized and conditional quantiles, whilst

the ESTest takes the realized, conditional expected shortfall and

conditional quantiles (as the help file example shows).

Here is a short script showing how VaRloss can be used:

################################################################

# ideally you want to test many models with different distributions

# for this example

library(xts)

library(rugarch)

data("sp500ret")

R = xts(as.numeric(sp500ret[,1]), as.Date(rownames(sp500ret)))

spec<-vector(mode="list", length=2)

spec[[1]]<-ugarchspec(mean.model = list(armaOrder=c(2,1)),

variance.model=list(model="sGARCH"))

spec[[2]]<-ugarchspec(mean.model = list(armaOrder=c(2,1)),

variance.model=list(model="gjrGARCH"))

fitlist = vector(mode="list", length = 2)

for(i in 1:2){

tmp = ugarchroll(spec[[i]], R, n.ahead = 1, forecast.length = 1500,

refit.every = 50,refit.window = "moving", windows.size = 1500, solver =

"hybrid",calculate.VaR = FALSE, keep.coef = FALSE)

if(!is.null(tmp@model$noncidx)){

tmp = resume(tmp, solver = "solnp", fit.control = list(scale=1),

solver.control = list(tol=1e-7, delta=1e-6), cluster = cluster)

if(!is.null(tmp@model$noncidx)) fitlist[[i]] = NA

} else{

fitlist[[i]] = as.data.frame(tmp, which = "density")

}

}

## The cost of misspecification using VaR

qx1 = qx5 = matrix(NA, ncol = 2, nrow = 1500)

for(i in 1:2){

qx5[,i] = as.numeric(apply(fitlist[[i]], 1, function(x) qdist("norm",

0.05, mu = x["Mu"],sigma = x["Sigma"], skew = x["Skew"], shape =

x["Shape"])))

qx1[,i] = as.numeric(apply(fitlist[[i]], 1, function(x) qdist("norm",

0.01, mu = x["Mu"],sigma = x["Sigma"], skew = x["Skew"], shape =

x["Shape"])))

}

VL5 = apply(qx5, 2, function(x) VaRloss(0.05, fitlist[[1]][,"Realized"], x))

test <- mcsTest(VL5, 0.05, 5000, 1, "stationary")

################################################################

Regards,

Alexios

On 12/15/2017 4:09 AM, Rafael Bressan wrote:

> Hello,

>

> someone, maybe Alexios even, could confirm what are the arguments to these

> functions?

>

> I suspect that VaRloss and VaRTest the inputs are the actual realized

> RETURNS and corresponding lower quantiles for VaR,

>

> while to ESTest it seems to be the opposite, the actual LOSSES and

> corresponding higher quantiles.

>

> I checked the source code but still in doubt.

>

> Thanks,

> Rafael

>

> [[alternative HTML version deleted]]

>

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