dcc.estimation2: Maximising the second stage log-likelihood function of the (E)DCC-GARCH model
Description
This function carries out the second stage (DCC part) estimation of the (E)DCC-GARCH model.
Usage
dcc.estimation2(dvar, para, gradient=0)
Arguments
dvar
a matrix of the standardised residuals $(T \times N)$
para
a vector of the DCC parameters $(2 \times 1)$
gradient
a switch variable whether to use the gradient in the constraint optimisation. passed to
constrOptim
Value
a list of the estimation results. See the explanations for constrOptim.
References
Engle, R.F. and K. Sheppard (2001),
Theoretical and Empirical Properties of Dynamic
Conditional Correlation Multivariate GARCH.Stern Finance Working Paper Series
FIN-01-027 (Revised in Dec. 2001),
New York University Stern School of Business.
Engle, R.F. (2002),
Dynamic Conditional Correlation: A Simple Class of
Multivariate Generalized Autoregressive Conditional
Heteroskedasticity Models.Journal of Business and Economic Statistics20, 339--350.