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Factor-based higher-order moment portfolio optimization

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  • Wang, Peiwen
  • Huang, Guanglin
  • Lu, Wanbo

Abstract

In general, higher-order moment portfolio is an NP-hard non-convex polynomial optimization problem. In this article, we study the properties of higher-order moment portfolio optimization with the factor models. We prove that under mild conditions, the higher-order moment portfolio optimization formulated via the expected utility function is a convex optimization problem, allowing gradient descent algorithms to efficiently converge to the global optimal solution. Moreover, the computational complexity of the factor-based higher-order moment portfolio optimization grows linearly with the number of assets N, which ensures its applicability in high-dimensional scenarios. Our simulation studies and empirical analysis confirm these findings. These conclusions contribute to a better understanding of the advantages of structured modeling in higher-order moment portfolio optimization, thereby integrating model estimation and optimization for portfolio selection.

Suggested Citation

  • Wang, Peiwen & Huang, Guanglin & Lu, Wanbo, 2025. "Factor-based higher-order moment portfolio optimization," Finance Research Letters, Elsevier, vol. 85(PC).
    • Handle: RePEc:eee:finlet:v:85:y:2025:i:pc:s1544612325012796
    DOI: 10.1016/j.frl.2025.108021
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    Keywords

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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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