mGJR: 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"
)

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

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.

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

Run this code

if (FALSE) {
  sim = BEKK.sim(1000)
  est = mGJR(sim$eps1, sim$eps2)
}