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‘Safe Assets’ during COVID-19: A Portfolio Management Perspective

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  • Julien Chevallier

    (IPAG Lab, IPAG Business School, 184 Boulevard Saint-Germain, 75006 Paris, France
    Economics Department, Université Paris 8 (LED), 2 Rue de la Liberté, 93526 Saint-Denis, France)

Abstract

The pandemic crisis of COVID-19 hit the financial markets like a shockwave on 16 March 2020. This paper attempts to capture which ‘safe assets’ asset managers could have fled during the first wave of the pandemic. From an investment manager’s perspective, candidate assets are stocks, bonds, exchange rates, commodities, gold, and (gold-backed) cryptocurrencies. Empirical tests of the ‘Safe-Haven’ hypothesis are conducted, upon which the selection of assets is performed. The methodological framework hinges on the Global Minimum Variance Portfolio with Monte Carlo simulations, and the routine is performed under Python. Other optimization techniques, such as risk parity and equal weighting, are added for robustness checks. The benchmark portfolio hits a yearly profitability of 7.2% during such a stressful event (with 3.6% downside risk). The profitability can be enhanced to 8.4% (even 14.4% during sub-periods) with a careful selection of ‘Safe assets’. Besides short- to long-term U.S. bonds, we document that investors’ exposure to Chinese, Argentinian, and Mexican stocks during COVID-19 could have been complemented with Swiss and Japanese currencies, grains, physical gold mine ETFs, or gold-backed tokens for defensive purposes.

Suggested Citation

  • Julien Chevallier, 2023. "‘Safe Assets’ during COVID-19: A Portfolio Management Perspective," Commodities, MDPI, vol. 2(1), pages 1-39, January.
    • Handle: RePEc:gam:jcommo:v:2:y:2023:i:1:p:2-51:d:1052000
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    References listed on IDEAS

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    Cited by:

    1. Wael Dammak & Halilibrahim Gökgöz & Ahmed Jeribi, 2025. "Analysis of Gold, Bitcoin, and Gold-Backed Cryptocurrencies as Safe Havens during Global Crises: A Focus on Artificial Intelligence Companies," Computational Economics, Springer;Society for Computational Economics, vol. 66(4), pages 2843-2872, October.
    2. Diseko, Nomathemba Veronica & Bonga-Bonga, Lumengo & Manguzvane, Mathias Mandla, 2015. "Dynamic portfolio rebalancing with safe-haven assets," MPRA Paper 123408, University Library of Munich, Germany.

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