Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)

Anne Péguin-Feissolle () and Bilel Sanhaji
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Anne Péguin-Feissolle: Aix Marseille University (Aix-Marseille School of Economics), CNRS & EHESS, Aix-Marseille, http://www.amse-aixmarseille.fr/en/users/peguin-feissolle#profile-membres

No 1516, AMSE Working Papers from Aix-Marseille School of Economics, France

Abstract: We introduce two multivariate constant conditional correlation tests that require little knowledge of the functional relationship determining the conditional correlations. The first test is based on artificial neural networks and the second one is based on a Taylor expansion of each unknown conditional correlation. These new tests can be seen as general misspecification tests of a large set of multivariate GARCH-type models. We investigate the size and the power of these tests through Monte Carlo experiments. Moreover, we study their robustness to non-normality by simulating some models such as the GARCH?t and Beta?t?EGARCH models. We give some illustrative empirical examples based on financial data.

Keywords: multivariate GARCH; neural network; Taylor expansion (search for similar items in EconPapers)
JEL-codes: C22 C45 C58 (search for similar items in EconPapers)
Pages: 58 pages
Date: 2015-03-10
New Economics Papers: this item is included in nep-cmp, nep-ecm, nep-ets and nep-ore
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Related works:
Working Paper: Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix) (2015)
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Persistent link: https://EconPapers.repec.org/RePEc:aim:wpaimx:1516

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