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Factor-based portfolio optimization

Author

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  • Auh, Jun Kyung
  • Cho, Wonho

Abstract

A parsimonious factor model mitigates idiosyncratic noise in historical data for portfolio optimization. We use market predictors and machine learning to incorporate forward-looking information into expected returns. The combination of the factor model and forward-looking returns improves out-of-sample performance, conforming to the theoretical assumption that the mean and variance correspond to future returns.

Suggested Citation

  • Auh, Jun Kyung & Cho, Wonho, 2023. "Factor-based portfolio optimization," Economics Letters, Elsevier, vol. 228(C).
    • Handle: RePEc:eee:ecolet:v:228:y:2023:i:c:s0165176523001623
    DOI: 10.1016/j.econlet.2023.111137
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    References listed on IDEAS

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    More about this item

    Keywords

    Portfolio optimization; Factor model; Algorithmic trading; Machine learning;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G24 - Financial Economics - - Financial Institutions and Services - - - Investment Banking; Venture Capital; Brokerage

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