Description Usage Arguments Value Note References See Also
This function carries out the second stage (DCC part) estimation of the (E)DCCGARCH model.
1  dcc.estimation2(dvar, para, gradient=0)

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

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 in the
DCC equation.
Engle, R.F. and K. Sheppard (2001), “Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH.” Stern Finance Working Paper Series FIN01027 (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
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