SSE/EFI Working Paper Series in Economics and Finance
No 577:
Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations
Annastiina Silvennoinen ()
and Timo Teräsvirta ()
Abstract: In this paper we propose a new multivariate GARCH model
with time-varying conditional correlation structure. The approach adopted
here is based on the decomposition of the covariances into correlations and
standard deviations. The time-varying conditional correlations change
smoothly between two extreme states of constant correlations according to
an endogenous or exogenous transition variable. An LM test is derived to
test the constancy of correlations and LM and Wald tests to test the
hypothesis of partially constant correlations. Analytical expressions for
the test statistics and the required derivatives are provided to make
computations feasible. An empirical example based on daily return series of
five frequently traded stocks in the Standard & Poor 500 stock index
completes the paper. The model is estimated for the full five-dimensional
system as well as several subsystems and the results discussed in
detail.
Keywords: Multivariate GARCH; Constant conditional correlation; Dynamic conditional correlation; Return comovement; Volatility model evaluation; (follow links to similar papers)
JEL-Codes: C12; C32; C51; C52; G10; (follow links to similar papers)
38 pages, January 7, 2005, Revised October 1, 2005
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