mGJR: Bivariate GJR Estimation

In mgarchBEKK: Simulating, Estimating and Diagnosing MGARCH (BEKK and mGJR) Processes

Bivariate GJR Estimation

Description

Provides bivariate GJR (mGJR(p,q,g)) estimation procedure.

Usage

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

Arguments

eps1	First time series.
eps2	Second time series.
order	mGJR(p, q, g) order a three element integer vector giving the order 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 parameters for the optim function.
fixed	A two dimensional vector that contains the user specified fixed parameter values.
method	The method that will be used by the optim function. See ?optim for available options.

Value

Estimation results packaged as mGJR class instance. The values are defined as:

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

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(sim$eps1, sim$eps2)

## End(Not run)

mgarchBEKK documentation built on Dec. 6, 2022, 9:10 a.m.