d2lv: Hessian of the DCC log-likelihood function

In ccgarch: Conditional Correlation GARCH models

Description

This function returns the analytical Hessian of the volatility part of the DCC log-likelihood function.

Usage

    d2lv(u, B, h, model)

Arguments

u	a matrix of the data data used for estimating the (E)DCC-GARCH(1,1) model (T \times N)
B	a GARCH parameter matrix (N \times N)
h	a matrix of the 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

the Hessian of the volatility part of the DCC log-likelihood function (T \times N^{2})

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 Statistics 20, 339–350.

Hafner, C.M. and H. Herwartz (2008), “Analytical Quasi Maximum Likelihood Inference in Multivariate Volatility Models.” Metrika 67, 219–239.

ccgarch documentation built on May 29, 2017, 12:58 p.m.