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Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns

Marc S. Paolella, Paweł Polak and Patrick S. Walker

Journal of Econometrics, 2019, vol. 213, issue 2, 493-515

Abstract: A non-Gaussian multivariate regime switching dynamic correlation model for financial asset returns is proposed. It incorporates the multivariate generalized hyperbolic law for the conditional distribution of returns. All model parameters are estimated consistently using a new two-stage expectation–maximization algorithm that also allows for incorporation of shrinkage estimation via quasi-Bayesian priors. It is shown that use of Markov switching correlation dynamics not only leads to highly accurate risk forecasts, but also potentially reduces the regulatory capital requirements during periods of distress. In terms of portfolio performance, the new regime switching model delivers consistently higher Sharpe ratios and smaller losses than the equally weighted portfolio and all competing models. Finally, the regime forecasts are employed in a new dynamic risk control strategy that avoids most losses during the financial crisis and vastly improves risk-adjusted returns.

Keywords: GARCH; Markov switching; Multivariate generalized hyperbolic distribution; Portfolio optimization; Value-at-risk (search for similar items in EconPapers)
JEL-codes: C01 C32 C51 C53 C58 G11 G17 (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1016/j.jeconom.2019.07.002

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Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

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