Abstract:
This paper utilizes three Multivariate General Autoregressive Conditional
Heteroscedasticity (MGARCH) models to determine variance persistence in the
Greater China region from 2009 to 2014. The first approach applies the Baba,
Engle, Kraft and Kroner (BEKK) model and shows that the Shanghai Stock
Exchange Composite Index (SSEI), Taiwan Capitalization Weighted Stock Index
(TAEIX) and the Hang Seng Stock Index (HSEI) stock returns are all functions
of their lagged covariances and lagged cross-product innovations. The second
MGARCH approach applies two methodologies, namely, dynamic conditional
correlation (DCC), and constant conditional correlation (CCC) estimations. The
DCC model concludes both short- and long-run persistencies between Taiwan’s
TAIEX and Hong Kong’s HSEI. Alternatively, the CCC model confirms the initial
findings of the BEKK model, and adds that the relationships among these three
strong economies are stable in the long-run. The log-likelihood values determine
that the DCC model is better in judging volatility dynamics in the Greater China
region, because of economic clauses brought by the Closer Economic Partnership
Arrangement (CEPA), the Economic Co-operation Framework Agreement
(ECFA) and the Hong Kong - Taiwan Business Cooperation Committee (BCC).
