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Systemic Risk-Driven Portfolio Selection

Author

Listed:
  • 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)

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.

Suggested Citation

  • Agostino Capponi & Alexey Rubtsov, 2022. "Systemic Risk-Driven Portfolio Selection," Operations Research, INFORMS, vol. 70(3), pages 1598-1612, May.
    • Handle: RePEc:inm:oropre:v:70:y:2022:i:3:p:1598-1612
    DOI: 10.1287/opre.2021.2234
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