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Robust portfolio optimization: a categorized bibliographic review

Author

Listed:
  • Panos Xidonas

    (ESSCA Business School)

  • Ralph Steuer

    (University of Georgia)

  • Christis Hassapis

    (University of Cyprus)

Abstract

Robust portfolio optimization refers to finding an asset allocation strategy whose behavior under the worst possible realizations of the uncertain inputs, e.g., returns and covariances, is optimized. The robust approach is in contrast to the classical approach, where one estimates the inputs to a portfolio allocation problem and then treats them as certain and accurate. In this paper we provide a categorized bibliography on the application of robust mathematical programming to the portfolio selection problem. With no similar surveys available, one of the aims of this review is to provide quick access for those interested, but maybe not yet in the area, so they know what the area is about, what has been accomplished and where everything can be found. Toward this end, a total of 148 references have been compiled and classified in various ways. Additionally, the number of Scopus© citations by contribution and journal is recorded. Finally, a brief discussion of the review’s major findings is provided and some solid leads on future directions are given.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:annopr:v:292:y:2020:i:1:d:10.1007_s10479-020-03630-8
    DOI: 10.1007/s10479-020-03630-8
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    References listed on IDEAS

    as
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    Cited by:

    1. Tuoyuan Cheng & Kan Chen, 2023. "A General Framework for Portfolio Construction Based on Generative Models of Asset Returns," Papers 2312.03294, arXiv.org.
    2. Marah-Lisanne Thormann & Phan Tu Vuong & Alain B. Zemkoho, 2024. "The Boosted Difference of Convex Functions Algorithm for Value-at-Risk Constrained Portfolio Optimization," Papers 2402.09194, arXiv.org.
    3. Bernardo K. Pagnoncelli & Domingo Ramírez & Hamed Rahimian & Arturo Cifuentes, 2023. "A Synthetic Data-Plus-Features Driven Approach for Portfolio Optimization," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 187-204, June.
    4. Yuyun Hidayat & Titi Purwandari & Sukono & Igif Gimin Prihanto & Rizki Apriva Hidayana & Riza Andrian Ibrahim, 2023. "Mean-Value-at-Risk Portfolio Optimization Based on Risk Tolerance Preferences and Asymmetric Volatility," Mathematics, MDPI, vol. 11(23), pages 1-26, November.
    5. Tom'as de la Rosa, 2023. "Planning for the Efficient Updating of Mutual Fund Portfolios," Papers 2311.16204, arXiv.org.
    6. Petukhina, Alla & Klochkov, Yegor & Härdle, Wolfgang Karl & Zhivotovskiy, Nikita, 2024. "Robustifying Markowitz," Journal of Econometrics, Elsevier, vol. 239(2).
    7. Qi, Yue & Liao, Kezhi & Liu, Tongyang & Zhang, Yu, 2022. "Originating multiple-objective portfolio selection by counter-COVID measures and analytically instigating robust optimization by mean-parameterized nondominated paths," Operations Research Perspectives, Elsevier, vol. 9(C).
    8. Pejman Peykani & Mojtaba Nouri & Mir Saman Pishvaee & Camelia Oprean-Stan & Emran Mohammadi, 2023. "Credibilistic Multi-Period Mean-Entropy Rolling Portfolio Optimization Problem Based on Multi-Stage Scenario Tree," Mathematics, MDPI, vol. 11(18), pages 1-23, September.
    9. Masashi Ieda, 2021. "Continuous-time Portfolio Optimization for Absolute Return Funds," Papers 2108.09985, arXiv.org, revised Mar 2022.
    10. Abbas Khademi & Ahmadreza Marandi & Majid Soleimani-damaneh, 2024. "A new dual-based cutting plane algorithm for nonlinear adjustable robust optimization," Journal of Global Optimization, Springer, vol. 89(3), pages 559-595, July.
    11. Mynbayeva, Elmira & Lamb, John D. & Zhao, Yuan, 2022. "Why estimation alone causes Markowitz portfolio selection to fail and what we might do about it," European Journal of Operational Research, Elsevier, vol. 301(2), pages 694-707.
    12. Härdle, Wolfgang & Klochkov, Yegor & Petukhina, Alla & Zhivotovskiy, Nikita, 2021. "Robustifying Markowitz," IRTG 1792 Discussion Papers 2021-018, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Chakrabarti, Deepayan, 2021. "Parameter-free robust optimization for the maximum-Sharpe portfolio problem," European Journal of Operational Research, Elsevier, vol. 293(1), pages 388-399.
    14. Alireza Ghahtarani & Ahmed Saif & Alireza Ghasemi, 2021. "Robust Portfolio Selection Problems: A Comprehensive Review," Papers 2103.13806, arXiv.org, revised Jan 2022.
    15. Masashi Ieda, 2022. "Continuous-Time Portfolio Optimization for Absolute Return Funds," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 29(4), pages 675-696, December.
    16. Wolfgang Karl Hardle & Yegor Klochkov & Alla Petukhina & Nikita Zhivotovskiy, 2022. "Robustifying Markowitz," Papers 2212.13996, arXiv.org.

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    15. Ashrafi, Hedieh & Thiele, Aurélie C., 2021. "A study of robust portfolio optimization with European options using polyhedral uncertainty sets," Operations Research Perspectives, Elsevier, vol. 8(C).
    16. Kolm, Petter N. & Tütüncü, Reha & Fabozzi, Frank J., 2014. "60 Years of portfolio optimization: Practical challenges and current trends," European Journal of Operational Research, Elsevier, vol. 234(2), pages 356-371.
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