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Fast gradient descent method for Mean-CVaR optimization

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  • Garud Iyengar
  • Alfred Ma

Abstract

We propose an iterative gradient descent algorithm for solving scenario-based Mean-CVaR portfolio selection problem. The algorithm is fast and does not require any LP solver. It also has efficiency advantage over the LP approach for large scenario size. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Garud Iyengar & Alfred Ma, 2013. "Fast gradient descent method for Mean-CVaR optimization," Annals of Operations Research, Springer, vol. 205(1), pages 203-212, May.
    • Handle: RePEc:spr:annopr:v:205:y:2013:i:1:p:203-212:10.1007/s10479-012-1245-8
    DOI: 10.1007/s10479-012-1245-8
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    References listed on IDEAS

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    Cited by:

    1. Chang, Kuo-Hao & Cuckler, Robert & Lee, Song-Lin & Lee, Loo Hay, 2022. "Discrete conditional-expectation-based simulation optimization: Methodology and applications," European Journal of Operational Research, Elsevier, vol. 298(1), pages 213-228.
    2. L. Jeff Hong & Zhaolin Hu & Liwei Zhang, 2014. "Conditional Value-at-Risk Approximation to Value-at-Risk Constrained Programs: A Remedy via Monte Carlo," INFORMS Journal on Computing, INFORMS, vol. 26(2), pages 385-400, May.
    3. Yuichi Takano & Keisuke Nanjo & Noriyoshi Sukegawa & Shinji Mizuno, 2015. "Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs," Computational Management Science, Springer, vol. 12(2), pages 319-340, April.
    4. Leurent, Martin & Da Costa, Pascal & Jasserand, Frédéric & Rämä, Miika & Persson, Urban, 2018. "Cost and climate savings through nuclear district heating in a French urban area," Energy Policy, Elsevier, vol. 115(C), pages 616-630.
    5. Amir Ahmadi-Javid & Malihe Fallah-Tafti, 2017. "Portfolio Optimization with Entropic Value-at-Risk," Papers 1708.05713, arXiv.org.
    6. Ken Kobayashi & Yuichi Takano & Kazuhide Nakata, 2021. "Bilevel cutting-plane algorithm for cardinality-constrained mean-CVaR portfolio optimization," Journal of Global Optimization, Springer, vol. 81(2), pages 493-528, October.
    7. Ahmadi-Javid, Amir & Fallah-Tafti, Malihe, 2019. "Portfolio optimization with entropic value-at-risk," European Journal of Operational Research, Elsevier, vol. 279(1), pages 225-241.
    8. Zhao, Lima & Huchzermeier, Arnd, 2017. "Integrated operational and financial hedging with capacity reshoring," European Journal of Operational Research, Elsevier, vol. 260(2), pages 557-570.
    9. Pengyu Qian & Zizhuo Wang & Zaiwen Wen, 2015. "A Composite Risk Measure Framework for Decision Making under Uncertainty," Papers 1501.01126, arXiv.org.
    10. Virginie Gabrel & Cécile Murat & Aurélie Thiele, 2018. "Portfolio optimization with pw-robustness," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 267-290, September.
    11. Jiarui Chu & Ludovic Tangpi, 2021. "Non-asymptotic estimation of risk measures using stochastic gradient Langevin dynamics," Papers 2111.12248, arXiv.org, revised Feb 2023.

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