loglik_dcc1: The 1st stage log-likelihood function for the (E)DCC GARCH

In hoanguc3m/ccgarch: Conditional Correlation GARCH models

Description

This function returns a log-likelihood of the (E)DCC-GARCH model in the first stage estimation.

Usage

   loglik.dcc1(param, dvar, model)

Arguments

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

Value

the negative of the first stage log-likelihood

Note

The function is used in optim in dcc.estimation1.

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

dcc.estimation, dcc.estimation1

hoanguc3m/ccgarch documentation built on May 29, 2019, 11:05 p.m.