A Flexible Regime Switching Model for Asset Returns

52 Pages Posted: 16 May 2019 Last revised: 25 May 2019

See all articles by Marc S. Paolella

Marc S. Paolella

University of Zurich - Department of Banking and Finance; Swiss Finance Institute

Pawel Polak

Stony Brook University-Department of Applied Mathematics and Statistics; Institute for Advanced Computational Science

Patrick S. Walker

University of Zurich, Department of Banking and Finance; OLZ AG

Date Written: May 16, 2019

Abstract

A non-Gaussian multivariate regime switching dynamic correlation model for fi nancial 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 dynamic risk control strategy that avoids most losses during the fi nancial crisis and vastly improves risk-adjusted returns.

Keywords: GARCH; Markov Switching; Multivariate Generalized Hyperbolic Distribution; Portfolio Optimization; Value-at-Risk

JEL Classification: C32, C51, C53, G11, G17, G32

Suggested Citation

Paolella, Marc S. and Polak, Pawel and Walker, Patrick S., A Flexible Regime Switching Model for Asset Returns (May 16, 2019). Swiss Finance Institute Research Paper No. 19-27, Available at SSRN: https://ssrn.com/abstract=3389305 or http://dx.doi.org/10.2139/ssrn.3389305

Marc S. Paolella

University of Zurich - Department of Banking and Finance

Plattenstr. 14
Zürich, 8032
Switzerland

Swiss Finance Institute

c/o University of Geneva
40, Bd du Pont-d'Arve
CH-1211 Geneva 4
Switzerland

Pawel Polak

Stony Brook University-Department of Applied Mathematics and Statistics ( email )

Stony Brook University
Stony Brook, NY 11794
United States

Institute for Advanced Computational Science ( email )

100 Nicolls Rd
Mailstop 5250
Stony Brook, NY 11794
United States

HOME PAGE: http://https://sites.google.com/view/pawelpolak/

Patrick S. Walker (Contact Author)

University of Zurich, Department of Banking and Finance ( email )

Plattenstrasse 14
Zürich, CH-8032
Switzerland

HOME PAGE: http://www.bf.uzh.ch/

OLZ AG ( email )

Gessnerallee 38
Zurich, Zurich 8001
Switzerland

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
268
Abstract Views
1,257
Rank
172,785
PlumX Metrics