goGARCHspec-class: class: GO-GARCH Specification Class
In rmgarch: Multivariate GARCH Models

Description Objects from the Class Slots Extends Methods Note Author(s) References

Class for the GO-GARCH specification.

The class is returned by calling the function goGARCHspec.

model:: Multivariate model specification.
umodel:: Univariate model specification.

Class "mGARCHspec", directly. Class "GARCHspec", by class "mGARCHspec", distance 2. Class "rGARCH", by class "mGARCHspec", distance 3.

show: signature(object = "goGARCHspec"): Summary method.

The mixing matrix in the GO-GARCH model implemented in the rmgarch package is based on non-parametric independent component analysis (ICA) methodology. The estimation is a 2-stage methodology described in Broda and Paolella (2009) and Zhang and Chan (2009). The extension to the use of the full multivariate affine GH distribution is detailed in Ghalanos et al (2011).

Alexios Galanos

van der Weide, R. 2002, GO-GARCH: a multivariate generalized orthogonal GARCH model, Journal of Applied Econometrics, 549–564.
Zhang, K. and Chan, L. 2009, Efficient factor GARCH models and factor-DCC models, Quantitative Finance, 71–91.
Broda, S.A. and Paolella, M.S. 2009, CHICAGO: A Fast and Accurate Method for Portfolio Risk Calculation, Journal of Financial Econometrics, 412–436.
Ghalanos, A. and Rossi, E. and Urga, G. 2011, Independent Factor Autoregressive Conditional Density Model, Pending–submitted.