Portfolio Selection Under Systemic Risk

52 Pages Posted: 1 Apr 2020 Last revised: 16 Mar 2021

See all articles by Weidong Lin

Weidong Lin

Durham University

Jose Olmo

Universidad de Zaragoza; University of Southampton

Abderrahim Taamouti

Durham University Business School

Date Written: March 25, 2020

Abstract

This paper proposes a novel methodology to construct optimal portfolios that explicitly incorporates the occurrence of systemic events. Investors maximize a modified Sharpe ratio that is conditional on a systemic event, with the latter interpreted as a low market return environment. We solve the portfolio allocation problem analytically under the absence of short-selling restrictions and numerically when short-selling restrictions are imposed. This approach for obtaining an optimal portfolio allocation is made operational by embedding it in a multivariate dynamic setting using dynamic conditional correlation and copula models. We evaluate the out-of-sample performance of our portfolio empirically on the US stock market over the period 2007 to 2020 using ex-post wealth paths and systemic risk metrics against mean-variance, equally-weighted, and global minimum variance portfolios. Our portfolio maximizing a modified Sharpe ratio outperforms all competitors under market distress and remains competitive in non-crisis periods.

Keywords: Conditional Volatility Models, Portfolio Allocation, Sharpe Ratio, Systemic Risk, Conditional Tail Risk

JEL Classification: C15, C32, C53, C61, G01, G11

Suggested Citation

Lin, Weidong and Olmo, Jose and Taamouti, Abderrahim, Portfolio Selection Under Systemic Risk (March 25, 2020). Available at SSRN: https://ssrn.com/abstract=3561153 or http://dx.doi.org/10.2139/ssrn.3561153

Weidong Lin (Contact Author)

Durham University ( email )

Old Elvet
Mill Hill Lane
Durham, Durham DH1 3HP
United Kingdom

Jose Olmo

Universidad de Zaragoza ( email )

Gran Via, 2
50005 Zaragoza, Zaragoza 50005
Spain

University of Southampton ( email )

Southampton
United Kingdom

Abderrahim Taamouti

Durham University Business School ( email )

Mill Hill Lane
Durham, DH1 3LB
United Kingdom

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