dcc_loglik {dccmidas}R Documentation

cDCC log-likelihood (second step)

Description

Obtains the log-likelihood of the cDCC model in the second step. For details, see Aielli (2013) and Engle (2002).

Usage

dcc_loglik(param, res, K_c = NULL)

Arguments

param

Vector of starting values.

res

Array of standardized daily returns, coming from the first step estimation.

K_c

optional Number of initial observations to exclude from the estimation

Value

The resulting vector is the log-likelihood value for each t.

References

Aielli GP (2013). “Dynamic conditional correlation: on properties and estimation.” Journal of Business & Economic Statistics, 31(3), 282–299. doi:10.1080/07350015.2013.771027.

Engle R (2002). “Dynamic conditional correlation: A simple class of multivariate generalized autoregressive conditional heteroskedasticity models.” Journal of Business & Economic Statistics, 20(3), 339–350. doi:10.1198/073500102288618487.


[Package dccmidas version 0.1.2 Index]