dcc.estimation1 {ccgarch} | R Documentation |
This function carries out the first stage (volatility part) estimation of the (E)DCC-GARCH model.
dcc.estimation1(dvar, a, A, B, model)
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 |
a list of the estimation results. See the explanations in optim
.
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.
optim
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dcc.estimation2
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dcc.estimation