d2lv {ccgarch} | R Documentation |
This function returns the analytical Hessian of the volatility part of the DCC log-likelihood function.
d2lv(u, B, h, model)
u |
a matrix of the observed residuals (T times N) |
B |
the estimated GARCH parameter matrix (N times N) |
h |
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 |
the Hessian of the volatility part of the DCC log-likelihood function (T times N^{2})
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.
Hafner, C.M. and H. Herwartz (2008), “Analytical Quasi Maximum Likelihood Inference in Multivariate Volatility Models” Metrika 67, 219–239.