mtvgarchSim {tvgarch}

Simulate from a multivariate TV-GARCH-X model

Description

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

Usage

mtvgarchSim(n, m = 2, order.g = c(1,1), order.h = c(1,1,0, 1,1,0), 
order.x = NULL, intercept.g = c(1.2,1), size = c(3,5), speed = c(10,25), 
location = c(0.5,0.8), intercept.h = c(0.2,0.3), arch = c(0.10,0.05), 
garch = c(0.80,0.90), asym = NULL, xtv = NULL, xreg = NULL, par.xreg = NULL,  
R = c(1,0.6,0.6,1), dcc = FALSE, par.dcc = NULL, opt = 0, as.zoo = TRUE, 
verbose = FALSE, innovations = NULL)

Arguments

n

integer.

m

integer indicating the dimenson of the multivariate series.

order.g

integer matrix with each row indicating the number of locations in each transition function of the TV components; m rows and max.s columns.

order.h

integer matrix with each row indicating the order.h for each series; the first column controls the GARCH order, the second the ARCH order and the third the asymmetry order of the GARCH-X components.

order.x

NULL or binary matrix indicating which xreg variables should be included as covariates in the GARCH-X components. If provided and xreg is NULL, volatility spillovers for the selected series are included as covariates.

intercept.g

NULL or numeric vector.

size

NULL or numeric matrix containing the size coefficients. Only relevant for TV-GARCH models.

speed

NULL or numeric matrix containing the speed coefficients. Only relevant for TV-GARCH models.

location

NULL or numeric matrix containing the location coefficients; m rows and max.c columns. Only relevant for TV-GARCH models.

intercept.h

numeric matrix.

arch

NULL or numeric matrix containing the ARCH coefficients.

garch

NULL or numeric matrix containing the GARCH-type coefficients.

asym

NULL or numeric matrix containing the asymmetry-type 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. Only relevant for TV-GARCH models.

xreg

numeric vector, matrix, time series or zoo object to include as covariates in the GARCH-X component.

par.xreg

NULL or numeric matrix containing the covariates initial coefficients.

R

matrix of (constant) conditional correlations.

dcc

logical. If TRUE, dynamic conditional correlations are estimated. If FALSE (default), then the conditional correlations are constant.

par.dcc

numeric vector containing the ARCH- and GARCH-type coefficients in the dynamic conditional correlations.

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). Only relevant for TV-GARCH models.

as.zoo

logical. If TRUE, then the returned result is of class zoo.

verbose

logical, if TRUE, the conditional variance and the innovations are also returned.

innovations

NULL or numeric matrix with the innovations. If NULL, then standard normal innovations are generated with rnorm.

Value

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

Author(s)

Susana Campos-Martins

See Also

mtvgarch, tvgarch, garchx, zoo

Examples

set.seed(12345)

## Simulate from a bivariate CCC-TV(1)-GARCH(1,1) model (default):
mySim1 <- mtvgarchSim(n = 1500)

## Simulate from a bivariate CCC-TV(1)-GARCH(1,1)-X model
## (with volatility spillovers)
mySim2 <- mtvgarchSim(n = 1500, order.x = c(0,1,1,0), par.xreg = 
c(0.03,0.04))