gsSim: Simulation of ARMA-GARCH/APARCH process

In GEVStableGarch: ARMA-GARCH/APARCH Models with GEV and Stable Distributions

Description

This functions simulates time series following ARMA-GARCH/APARCH models with GEV and stable distributions. This function was developed through the available code from fGarch package available at CRAN.

Usage

gsSim(spec = gsSpec(), n = 100, n.start = 100)

Arguments

spec	A model specified with function gsSpec.
n	The size of simulated time series.
n.start	Length of the "burn-in" period of the simulated time series.

Details

The initial values of the time series are fixed and the recursion formulas of the model are used to simulate the dynamics of the process. We do not verify the stationarity conditions of the model because the simulation of non-stationary process could also be of interest by the researcher.

Value

The function returns an object containing the following items:

model	A string describing the estimated model.
cond.dist	The conditional distribution used to fit the model.
series	An array with three columns, where the first column contains the simulated ARMA-GARCH/APARCH process (garch), the second column the conditional standard deviations ("sigma"), and the last column the innovations ("eps").

Author(s)

Thiago do Rego Sousa for the latest modifications
Diethelm Wuertz for the original implementation of the garchSpec function from package fGarch

References

Brockwell, P.J., Davis, R.A. (1996). Introduction to Time Series and Forecasting. Springer, New York.

Wuertz, D., Chalabi, Y., with contribution from Miklovic, M., Boudt, C., Chausse, P., and others (2013). fGarch: Rmetrics - Autoregressive Conditional Heteroskedastic Modelling, R package version 3010.82, http://CRAN.R-project.org/package=fGarch.

Wuertz, D., Chalabi, Y., Luksan, L. (2009). Parameter Estimation of ARMA Models with GARCH/ APARCH Errors: An R and SPlus SoftwareImplementation. Journal of Statistical Software, forthcoming, http://www-stat.wharton.upenn.edu/~steele/...WurtzEtAlGarch.pdf.

Examples

# Simulation of a ARMA-APARCH process with stable conditional distribution
#x <- GSgarch.Sim(N = 2500, mu = 0.1,a = c(0.2,0.3),b = c(0.2,0.5),
#omega = 0.1, alpha = c(0.1,0.2),beta = c(0.1,0.1),gm=c(0.3,-0.3),
#delta = 1,skew = 0.3,shape = 1.9, cond.dis = "stable")

Example output

Loading required package: Rsolnp
Loading required package: skewt

GEVStableGarch documentation built on May 2, 2019, 5:53 a.m.