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Robust parametric tests of constant conditional correlation in a MGARCH model

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  • Wasel Shadat
  • Chris Orme

Abstract

This article provides a rigorous asymptotic treatment of new and existing asymptotically valid conditional moment (CM) testing procedures of the constant conditional correlation (CCC) assumption in a multivariate GARCH model. Full and partial quasi maximum likelihood estimation (QMLE) frameworks are considered, as is the robustness of these tests to non-normality. In particular, the asymptotic validity of the LM procedure proposed by Tse (2000) is analyzed, and new asymptotically robust versions of this test are proposed for both estimation frameworks. A Monte Carlo study suggests that a robust Tse test procedure exhibits good size and power properties, unlike the original variant which exhibits size distortion under non-normality.

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  • Wasel Shadat & Chris Orme, 2018. "Robust parametric tests of constant conditional correlation in a MGARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 37(6), pages 551-576, July.
    • Handle: RePEc:taf:emetrv:v:37:y:2018:i:6:p:551-576
    DOI: 10.1080/07474938.2015.1122120
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