| loglik.dcc1 {ccgarch} | R Documentation |
This function returns a log-likelihood of the (E)DCC-GARCH model in the first stage estimation.
loglik.dcc1(param, dvar, model)
param |
initial values for a vector of the parameters (npar times 1) |
dvar |
a matrix of the data (T 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 |
the negative of the first stage log-likelihood
The function is used in optim in dcc.estimation1.
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.
dcc.estimation,
dcc.estimation1