dcc.estimation2 {ccgarch}R Documentation

Estimating (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 DCC parameters (2 times 1)
gradient a switch variable whether to use the gradient in the constraint optimisation. passed to sonstrOptim

Value

a list of the estimation results. See the explanations for constrOptim.

Note

"dcc.estimation2" is a wrapper to constrOptim. The restrictions are α + β <=q 1 and α, β >=q 0.

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 Statistics 20, 339-350.

See Also

constrOptim, dcc.estimation1, dcc.estimation


[Package ccgarch version 0.1.1 Index]