# loglik_dcc1: The 1st stage log-likelihood function for the (E)DCC GARCH In ccgarch: Conditional Correlation GARCH models

## Description

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

## Usage

 1  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.

dcc.estimation, dcc.estimation1