fGarch (version 4033.92)

VaR: Compute Value-at-Risk (VaR) and expected shortfall (ES)

Description

Compute Value-at-Risk (VaR) and Expected Shortfall (ES) for a fitted GARCH-APARCH model.

Usage

# S3 method for fGARCH
VaR(dist, p_loss = 0.05, ..., tol)
# S3 method for fGARCH
ES(dist, p_loss = 0.05, ...)

Arguments

dist

an object from class "fGARCH", obtained from garchFit().

p_loss

level, default is 0.05.

...

not used.

tol

tollerance

Details

We provide methods for the generic functions cvar::VaR and cvar::ES.

See Also

VaR and ES in package cvar

Examples

## simulate a time series of returns
x <- garchSim( garchSpec(), n = 500)
class(x)
## fit a GARCH model
fit <- garchFit(~ garch(1, 1), data = x, trace = FALSE)

head(VaR(fit))
head(ES(fit))

## use plot method for fitted GARCH models
plot(fit, which = 14) # VaR
plot(fit, which = 15) # ES
plot(fit, which = 16) # VaR & ES
## plot(fit) # choose the plot interactively

## diy plots

## overlay VaR and ES over returns
## here x is from class 'timeSeries', so we convert VaR/ES to timeSeries
## don't forget to negate the result of VaR()/ES(),
plot(x)
lines(timeSeries(-VaR(fit)), col = "red")
lines(timeSeries(-ES(fit)), col = "blue")

## alternatively, plot losses (rather than returns) and don't negate VaR()/ES()
plot(-x)
lines(timeSeries(VaR(fit)), col = "red")
lines(timeSeries(ES(fit)), col = "blue")