dcc_mat_est {dccmidas}R Documentation

Obtains the matrix H_t and R_t, under the cDCC model

Description

Obtains the matrix H_t and R_t, under the cDCC model For details, see Aielli (2013) and Engle (2002).

Usage

dcc_mat_est(est_param, res, Dt, K_c)

Arguments

est_param

Vector of estimated values

res

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

Dt

Diagonal matrix of standard deviations

K_c

optional Number of initial observations to exclude from the H_t and R_t calculation

Value

A list with the H_t and R_t matrices, 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]