dcc.results: Computing robust standard errors of the estimates in the (E)DCC-GARCH model
Description
This function computes the robust standard errors of the estimates of a DCC-GARCH model.
Usage
dcc.results(u, garch.para, dcc.para, h, model)
Arguments
u
a matrix of the data used for estimating the (E)DCC-GARCH model $(T \times N)$
garch.para
a vector of the estimates of the volatility parameters
dcc.para
a vector of the estimates of the DCC parameters $(2 \times 1)$
h
a matrix of the estimated conditional variances $(T \times N)$
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
A matrix with the estimates in the first row, and the standard errors in the second row.
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 Statistics20, 339--350.