dcc.estimation1 {ccgarch}R Documentation

Estimating the first stage (E)DCC-GARCH

Description

This function carries out the first stage (volatility part) estimation of the (E)DCC-GARCH model.

Usage

    dcc.estimation1(dvar, a, A, B, model)

Arguments

dvar a matrix of the observed residuals (T times N)
a a vector of constants (N times 1)
A an ARCH parameter matrix (N times N)
B a GARCH parameter matrix (N times N)
model a character string describing the model. "diagonal" for the diagonal model and "extended" for the extended (full ARCH and GARCH parameter matrices) model

Value

a list of the estimation results. See the explanations in optim.

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

optim, dcc.estimation2, dcc.estimation


[Package ccgarch version 0.1.1 Index]