Portfolio Selection Under Systemic Risk

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.