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

Paolella, Marc S; Polak, Paweł; Walker, Patrick S (2019). Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns. Journal of Econometrics, 213(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.

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scopus Subject Areas:Social Sciences & Humanities > Economics and Econometrics
Scope:Discipline-based scholarship (basic research)
Language:English
Date:1 December 2019
Deposited On:16 Jan 2020 08:12
Last Modified:22 Oct 2024 01:39
Publisher:Elsevier
ISSN:0304-4076
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.jeconom.2019.07.002
Official URL:https://www.sciencedirect.com/science/article/pii/S0304407619301563
Other Identification Number:merlin-id:18056
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