dcc.estimation2 {ccgarch} | R Documentation |
This function carries out the second stage (DCC part) estimation of the (E)DCC-GARCH model.
dcc.estimation2(dvar, para, gradient=0)
dvar |
a matrix of the standardised residuals (T times N) |
para |
a vector of DCC parameters (2 times 1) |
gradient |
a switch variable whether to use the gradient in the constraint optimisation. passed to
sonstrOptim |
a list of the estimation results. See the explanations for constrOptim
.
"dcc.estimation2" is a wrapper to constrOptim
. The restrictions are
α + β <=q 1 and α, β >=q 0.
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 Statistics 20, 339-350.
constrOptim
,
dcc.estimation1
,
dcc.estimation