Systemic Risk-Driven Portfolio Selection

Agostino Capponi () and Alexey Rubtsov ()
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Agostino Capponi: Department of Industrial Engineering and Operations Research, Columbia University, New York, New York 10027
Alexey Rubtsov: Department of Mathematics, Ryerson University, Toronto, Ontario M5B 2K3, Canada; Global Risk Institute in Financial Services, Toronto, Ontario M5J 2H7, Canada

Operations Research, 2022, vol. 70, issue 3, 1598-1612

Abstract: We consider an investor who trades off tail risk and expected growth of the investment. We measure tail risk through the portfolio’s expected losses conditioned on the occurrence of a systemic event: financial market loss being exactly at, or at least at, its value-at-risk (VaR) level and investor’s portfolio losses being above their conditional value-at-risk (CoVaR) level. We decompose the solution to the investment problem in terms of the Markowitz mean-variance portfolio and an adjustment for systemic risk. We show that VaR and CoVaR confidence levels control the relative sensitivity of the investor’s objective function to portfolio-market correlation and portfolio variance, respectively. Our empirical analysis demonstrates that the investor attains higher risk-adjusted returns, compared with well-known benchmark portfolio criteria, during times of market downturn. Portfolios that perform best under adverse market conditions are less diversified and invest on a few stocks that have low correlation with the market.

Keywords: Financial Engineering; systemic risk; portfolio selection; risk management; VaR; CoVaR; risk-adjusted returns (search for similar items in EconPapers)
Date: 2022
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