garch.sim: Simulate a GARCH process

In TSA: Time Series Analysis

Simulate a GARCH process

Description

Simulate a GARCH process.

Usage

garch.sim(alpha, beta, n = 100, rnd = rnorm, ntrans = 100,...)

Arguments

alpha	The vector of ARCH coefficients including the intercept term as the first element
beta	The vector of GARCH coefficients
n	sample size
rnd	random number generator for the noise; default is normal
ntrans	burn-in size, i.e. number of initial simulated data to be discarded
...	parameters to be passed to the random number generator

Details

Simulate data from the GARCH(p,q) model: x_t=σ_{t|t-1} e_t where \{e_t\} is iid, e_t independent of past x_{t-s}, s=1,2,…, and

σ_{t|t-1}=∑_{j=1}^p β_j σ_{t-j|t-j-1}+ α_0+∑_{j=1}^q α_j x_{t-i}^2

Value

simulated GARCH time series of size n.

Author(s)

Kung-Sik Chan

Examples

set.seed(1235678)
garch01.sim=garch.sim(alpha=c(.01,.9),n=500)
plot(garch01.sim,type='l', main='',ylab=expression(r[t]),xlab='t')

TSA documentation built on July 5, 2022, 5:05 p.m.