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Portfolio optimization by minimizing conditional value-at-risk via nondifferentiable optimization

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  • Churlzu Lim
  • Hanif Sherali
  • Stan Uryasev

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  • Churlzu Lim & Hanif Sherali & Stan Uryasev, 2010. "Portfolio optimization by minimizing conditional value-at-risk via nondifferentiable optimization," Computational Optimization and Applications, Springer, vol. 46(3), pages 391-415, July.
    • Handle: RePEc:spr:coopap:v:46:y:2010:i:3:p:391-415
    DOI: 10.1007/s10589-008-9196-3
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    References listed on IDEAS

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    1. Hanif D. Sherali & Churlzu Lim, 2007. "Enhancing Lagrangian Dual Optimization for Linear Programs by Obviating Nondifferentiability," INFORMS Journal on Computing, INFORMS, vol. 19(1), pages 3-13, February.
    2. David F. Shanno, 1978. "Conjugate Gradient Methods with Inexact Searches," Mathematics of Operations Research, INFORMS, vol. 3(3), pages 244-256, August.
    3. Pavlo Krokhmal & Stanislav Uryasev, 2007. "A sample-path approach to optimal position liquidation," Annals of Operations Research, Springer, vol. 152(1), pages 193-225, July.
    4. Churlzu Lim & Hanif Sherali, 2006. "A Trust Region Target Value Method for Optimizing Nondifferentiable Lagrangian Duals of Linear Programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 64(1), pages 33-53, August.
    5. Philippe Artzner & Freddy Delbaen & Jean‐Marc Eber & David Heath, 1999. "Coherent Measures of Risk," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 203-228, July.
    6. Rockafellar, R. Tyrrell & Uryasev, Stanislav, 2002. "Conditional value-at-risk for general loss distributions," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1443-1471, July.
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    Cited by:

    1. Daniel Espinoza & Eduardo Moreno, 2014. "A primal-dual aggregation algorithm for minimizing conditional value-at-risk in linear programs," Computational Optimization and Applications, Springer, vol. 59(3), pages 617-638, December.
    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. Amir Ahmadi-Javid & Malihe Fallah-Tafti, 2017. "Portfolio Optimization with Entropic Value-at-Risk," Papers 1708.05713, arXiv.org.
    4. 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.
    5. Zhang Qingye & Gao Yan, 2017. "An Asset Allocation Model and Its Solving Method," Journal of Systems Science and Information, De Gruyter, vol. 5(2), pages 163-175, April.
    6. Seixas, Mário & Barbosa, António, 2019. "Optimal Value-at-Risk Disclosure," MPRA Paper 97526, University Library of Munich, Germany.
    7. Foad Mahdavi Pajouh & Esmaeel Moradi & Balabhaskar Balasundaram, 2017. "Detecting large risk-averse 2-clubs in graphs with random edge failures," Annals of Operations Research, Springer, vol. 249(1), pages 55-73, February.
    8. Mohammed Bilal Girach & Shashank Oberoi & Siddhartha P. Chakrabarty, 2021. "Is Being “Robust” Beneficial? A Perspective from the Indian Market," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 28(4), pages 469-497, December.
    9. 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.
    10. Vikram Krishnamurthy & Sujay Bhatt, 2015. "Sequential Detection of Market shocks using Risk-averse Agent Based Models," Papers 1511.01965, arXiv.org.
    11. Taras Bodnar & Wolfgang Schmid & Taras Zabolotskyy, 2013. "Asymptotic behavior of the estimated weights and of the estimated performance measures of the minimum VaR and the minimum CVaR optimal portfolios for dependent data," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(8), pages 1105-1134, November.
    12. Maciej Rysz & Alexander Vinel & Pavlo Krokhmal & Eduardo L. Pasiliao, 2015. "A Scenario Decomposition Algorithm for Stochastic Programming Problems with a Class of Downside Risk Measures," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 416-430, May.
    13. 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.
    14. Mohammed Bilal Girach & Shashank Oberoi & Siddhartha P. Chakrabarty, 2019. "Is being `Robust' beneficial?: A perspective from the Indian market," Papers 1908.05002, arXiv.org.
    15. E. G. Birgin & J. M. Martínez, 2016. "On the application of an Augmented Lagrangian algorithm to some portfolio problems," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 4(1), pages 79-92, February.
    16. Mansini, Renata & Ogryczak, Wlodzimierz & Speranza, M. Grazia, 2014. "Twenty years of linear programming based portfolio optimization," European Journal of Operational Research, Elsevier, vol. 234(2), pages 518-535.
    17. Massimiliano Kaucic & Mojtaba Moradi & Mohmmad Mirzazadeh, 2019. "Portfolio optimization by improved NSGA-II and SPEA 2 based on different risk measures," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 5(1), pages 1-28, December.
    18. Bodnar Taras & Schmid Wolfgang & Zabolotskyy Tara, 2012. "Minimum VaR and minimum CVaR optimal portfolios: Estimators, confidence regions, and tests," Statistics & Risk Modeling, De Gruyter, vol. 29(4), pages 281-314, November.

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