dcc.results {ccgarch} | R Documentation |
This function computes the robust standard errors of the estimates of a DCC-GARCH model.
dcc.results(u, garch.para, dcc.para, h, model)
u |
a matrix of the observed residuals (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 volatilities (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 |
A matrix with the estimates in the first row, and the standard errors in the second row.
dcc.results
is called from dcc.estimation
.
When model="diagonal", only the diagonal entries in A and B are used.
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.