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Factor-Targeted Asset Allocation: A Reverse Optimization Approach

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  • Jacky S. H. Lee
  • Marco Salerno

Abstract

We demonstrate that using a mean-variance portfolio to obtain implied factor risk premia can result in stable weights for a factor portfolio when assets’ expected returns follow a factor structure that is subject to pricing errors. We propose a methodology to construct asset portfolios based on these factor portfolio weights, taking into account the possibility of pricing errors. Our simulation shows that these “factor-targeted” portfolios have higher and more stable Sharpe ratios than traditional allocation methodologies in various scenarios involving expected return assumptions. Furthermore, while our factor-targeted portfolios exhibit similar Sharpe ratios to the mean-variance portfolio built using factors for high levels of pricing errors, the factor-targeted portfolios have more stable portfolio weights, which makes them more appealing in practice.

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  • Jacky S. H. Lee & Marco Salerno, 2023. "Factor-Targeted Asset Allocation: A Reverse Optimization Approach," Financial Analysts Journal, Taylor & Francis Journals, vol. 79(3), pages 75-94, July.
    • Handle: RePEc:taf:ufajxx:v:79:y:2023:i:3:p:75-94
    DOI: 10.1080/0015198X.2023.2214074
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