tvgarchSim: Simulate from a univariate TV-GARCH-X model

Description

Simulate from a univariate multiplicative TV(s)-GARCH(p,q,r)-X model.

Usage

tvgarchSim(n, order.g = 1, order.h = c(1,1,0),
           intercept.g = 1.2, size = 5, speed = 25, location = 0.5, xtv = NULL, 
           intercept.h = 0.2, arch = 0.1, garch = 0.8, asym = NULL, xreg = NULL,
           opt = 0, as.zoo = TRUE, verbose = FALSE, innovations = NULL)

Value

An object of class 'zoo' (if as.zoo = TRUE), otherwise a vector or a matrix (if verbose = TRUE), with the simulated values.

Arguments

n: integer.
order.g: integer vector of length s indicating the number of locations in each transition function of the TV component.
order.h: integer vector of the form c(p,q,r). The first entry controls the GARCH order, the second the ARCH order and the third the asymmetry order of the GARCH-X component.
intercept.g: NULL or numeric with the value of the intercept in the TV component.
size: NULL or numeric vector with the values of the size coefficients.
speed: NULL or numeric vector with the values of the speed coefficients.
location: NULL or numeric vector with the values of the location coefficients.
xtv: NULL or numeric vector, time series or zoo object to include as the transition variable in the TV component. If NULL, calendar time, scaled between 0 and 1, is used as the transition variable.
opt: integer indicating whether the speed parameter in the TV component should be scaled. If 0, no scaling; if 1, speed/sd(xtv); if 2, exp(speed).
intercept.h: numeric with the value of the intercept in the GARCH-X component.
arch: NULL or numeric vector with the values of the ARCH-coefficients.
garch: NULL or numeric vector with the values of the GARCH-coefficients.
asym: NULL or numeric vector with the values of the asymmetry-coefficients.
xreg: NULL or numeric vector with the values of the X-term.
as.zoo: logical. If TRUE, then the returned result is of class zoo.
verbose: logical, if TRUE, the conditional variance and innovations are also returned.
innovations: NULL or numeric vector with the innovations. If NULL, then standard normal innovations are generated with rnorm.

Author

Susana Campos-Martins

Examples

Run this code

set.seed(123)

## Simulate from a TV(1)-GARCH(1,1) model (default):
ySim1 <- tvgarchSim(n = 1500)

## Simulate from a TV(2)-GARCH(1,1) model:
ySim2 <- tvgarchSim(n = 1500, order.g = c(1,2), size = c(0.5,-0.4), 
                    speed = c(1.5,2), location = c(0.2, 0.5,0.8))

## Simulate from a GARCH(1,1) model:
ySim3 <- tvgarchSim(n = 1500, order.g = NULL)

## Simulate from a TV(1)-GARCH(1,1,1)-X model:
ySim4 <- tvgarchSim(n = 1500, order.h = c(1,1,1), asym = 0.025, xreg = ySim3^2)