eccc.estimation: Estimating an (E)CCC-GARCH model

Description

This function estimates an (E)CCC-GARCH(1,1) model and returns estimates, estimated volatility and various diagnostic statistics.

Usage

eccc.estimation(a, A, B, R, dvar, model, method="BFGS")

Arguments

initial values for constants $(N \times 1)$

initial values for an ARCH parameter matrix $(N \times N)$

initial values for a GARCH parameter matrix $(N \times N)$

initial values a constant conditional correlation matrix $(N \times N)$

dvar

a matrix of data used for (E)CCC-GARCH estimation $(T \times N)$

model

a character string describing the model. "diagonal" for the diagonal model and "extended" for the extended (full ARCH and GARCH parameter matrices) model

method

a character string specifying the optimisation method in optim. There are three choices, namely, Nelder-Mead, BFGS (default) and CG.

Value

out: a $(4 \times npar)$ matrix. The estimates are contained in the first row. The remaining rows report standard errors based on three different methods of estimating the asymptotic covariance matrix
h: the estimated conditional variances $(T \times N)$
std.resid: a matrix of the standardised residuals $(T \times N$). See Note.
opt: the detailed results of the optimisation
para.mat: vectorised parameter estimates

References

Bollerslev, T. (1990), “Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model”, Review of Economics and Statistics, 20, 498--505. Nakatani, T. and T. Ter\"asvirta (2009), “Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model”, Econometrics Journal, 12, 147--163.

Nakatani, T. and T. Ter\"asvirta (2008), “Appendix to Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model” Department of Economic Statistics, Stockholm School of Economics, available at http://swopec.hhs.se/hastef/abs/hastef0649.htm.