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.
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Length: 38 pages Date of creation: 07 Jan 2005 Date of revision:
01 Oct 2005 Handle: RePEc:hhs:hastef:0577
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Find related papers by JEL classification: C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
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BAUWENS, Luc & LAURENT, SŽbastien & ROMBOUTS, Jeroen, 2003.
"Multivariate GARCH models: a survey,"
CORE Discussion Papers
2003031, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
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Annastiina Silvennoinen & Timo Teräsvirta, 2008.
"Multivariate GARCH models,"
CREATES Research Papers
2008-06, School of Economics and Management, University of Aarhus.
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