The constant conditional correlation general autoregressive
conditional heteroskedasticity (GARCH) model is among the most commonly
applied multivariate GARCH models and serves as a benchmark against
which other models can be compared. In this paper we consider an
extension to this model and examine its fourth-moment structure. The
extension, first defined by Jeantheau (1998,
Econometric Theory 14, 70–86), is motivated by the
result found and discussed in this paper that the squared observations
from the extended model have a rich autocorrelation structure. This
means that already the first-order model is capable of reproducing a
whole variety of autocorrelation structures observed in financial
return series. These autocorrelations are derived for the first- and
the second-order constant conditional correlation GARCH model. The
usefulness of the theoretical results of the paper is demonstrated by
reconsidering an empirical example that appeared in the original paper
on the constant conditional correlation GARCH model.This research has been supported by the Swedish Research
Council of Humanities and Social Sciences and the Tore Browaldh's
Foundation. A part of this work was carried out while the second author
was visiting the School of Finance and Economics, University of Technology,
Sydney, whose kind hospitality is gratefully acknowledged. The paper has
been presented at the Econometric Society European Meeting, Venice, August
2002. We thank participants for comments and two anonymous referees for
their remarks. Any errors and shortcomings in the paper remain our own
responsibility.