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Recent advancements in robust optimization for investment management

Author

Listed:
  • Jang Ho Kim

    (Kyung Hee University)

  • Woo Chang Kim

    (Korea Advanced Institute of Science and Technology (KAIST))

  • Frank J. Fabozzi

    (EDHEC Business School)

Abstract

Robust optimization has become a widely implemented approach in investment management for incorporating uncertainty into financial models. The first applications were to asset allocation and equity portfolio construction. Significant advancements in robust portfolio optimization took place since it gained popularity almost two decades ago for improving classical models on portfolio optimization. Recently, studies applying the worst-case framework to bond portfolio construction, currency hedging, and option pricing have appeared in the practitioner-oriented literature. Our focus in this paper is on recent advancements to categorize robust optimization models into asset allocation at the asset class level and portfolio selection at the individual asset level, and we further separate robust portfolio selection approaches specific to each asset class. This organization provides a clear overview on how robust optimization is extensively implemented in investment management.

Suggested Citation

  • Jang Ho Kim & Woo Chang Kim & Frank J. Fabozzi, 2018. "Recent advancements in robust optimization for investment management," Annals of Operations Research, Springer, vol. 266(1), pages 183-198, July.
    • Handle: RePEc:spr:annopr:v:266:y:2018:i:1:d:10.1007_s10479-017-2573-5
    DOI: 10.1007/s10479-017-2573-5
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    References listed on IDEAS

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    2. Panos Xidonas & Ralph Steuer & Christis Hassapis, 2020. "Robust portfolio optimization: a categorized bibliographic review," Annals of Operations Research, Springer, vol. 292(1), pages 533-552, September.
    3. Jang Ho Kim & Yongjae Lee & Woo Chang Kim & Frank J. Fabozzi, 2022. "Goal-based investing based on multi-stage robust portfolio optimization," Annals of Operations Research, Springer, vol. 313(2), pages 1141-1158, June.
    4. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2022. "Robust portfolio selection problems: a comprehensive review," Operational Research, Springer, vol. 22(4), pages 3203-3264, September.
    5. Rubesam, Alexandre, 2022. "Machine learning portfolios with equal risk contributions: Evidence from the Brazilian market," Emerging Markets Review, Elsevier, vol. 51(PB).
    6. Kouaissah, Noureddine, 2023. "Robust reward-risk performance measures with weakly second-order stochastic dominance constraints," The Quarterly Review of Economics and Finance, Elsevier, vol. 88(C), pages 53-62.
    7. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.

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