mGJR.est: Estimate a mGJR(p,q,g) model

In vst/mgarch: Tools for simulating, estimating and diagnosing MGARCH processes

Description

mGJR.est estimates a mGJR(p,q,g) model for two given time series

Usage

mGJR.est(eps1, eps2, order = c(1,1,1), params = NULL, fixed = NULL, method = "BFGS")

Arguments

eps1	first time series
eps2	second time series
order	a three dimensional integer vector giving the orders of the model to be fitted. order[2] refers to the ARCH order and order[1] to the GARCH order and order[3] to the GJR order.
params	initial parameter list for the optimization process
fixed	a two dimensional vector that contains the user specified fixed parameter values.
method	method to be used in the optimization process. See ?optim for available options.

Details

mGJR.est estimates a mGJR(p,q) model, where p stands for the GARCH order, and q stands for the ARCH order

Value

A list of class "mGJR.est" with the following elements:

eps1	first time series
eps2	second time series
length	length of each series
order	order of the mGJR model fitted
estimation.time	time to complete the estimation process
total.time	time to complete the whole routine within the mGJR.est process
estimation	estimation object returned from the optimization process, using optim
aic	the AIC value of the fitted model
est.params	estimated parameter matrices
asy.se.coef	asymptotic theory estimates of standard errors of estimated parameters
cor	estimated conditional correlation series
sd1	first estimated conditional standard deviation series
sd2	second estimated conditional standard deviation series
H.estimated	estimated series of covariance matrices
eigenvalues	estimated eigenvalues for sum of Kronecker products
uncond.cov.matrix	estimated unconditional covariance matrix
resid1	first estimated series of residuals
resid2	second estimated series of residuals

Author(s)

Harald SCHMIDBAUER [e-mail], Vehbi Sinan TUNALIOGLU [e-mail]

References

Bauwens L., S. Laurent, J.V.K. Rombouts: Multivariate GARCH models: A survey, April, 2003

Bollerslev T.: Modelling the coherence in short-run nominal exchange rate: A multivariate generalized ARCH approach, Review of Economics and Statistics, 498–505, 72, 1990

Engle R.F., K.F. Kroner: Multivariate simultaneous generalized ARCH, Econometric Theory, 122-150, 1995

Engle R.F.: Dynamic conditional correlation: A new simple class of multivariate GARCH models, Journal of Business and Economic Statistics, 339–350, 20, 2002

Tse Y.K., A.K.C. Tsui: A multivariate generalized autoregressive conditional heteroscedasticity model with time-varying correlations, Journal of Business and Economic Statistics, 351-362, 20, 2002

Examples

## Not run: 
sim = BEKK.sim(1000)
est = mGJR.est(sim$eps1, sim$eps2)

## End(Not run)

vst/mgarch documentation built on May 3, 2019, 7:09 p.m.