This function carries out the second stage (DCC part) estimation of the (E)DCC-GARCH model.
dcc.estimation2(dvar, para, gradient=0)
a matrix of the standardised residuals (T \times N)
a vector of the DCC parameters (2 \times 1)
a switch variable whether to use the gradient in the constraint optimisation. passed to
a list of the estimation results. See the explanations for
dcc.estimation2 is a wrapper to
constrOptim. The restrictions are
α + β ≤q 1 and α, β ≥q 0 in the
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.
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