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Developing a multi-period robust optimization model considering American style options

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  • Saeed Marzban
  • Masoud Mahootchi
  • Alireza Arshadi Khamseh

Abstract

The main goal in this study is to introduce a new linear model for multi-period portfolio optimization. The proposed optimization model can take both stocks and their respective American style options into consideration. Moreover, to hedge the resulting portfolio, the robust counterpart of this model is developed in which the level of robustness can be determined using the length and the type of the uncertainty set. The experiments results which are obtained based on the data of Dow Jones stock market verify the performance of the proposed models compared to what has been achieved using Bertsimas et al.’s optimization model. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Saeed Marzban & Masoud Mahootchi & Alireza Arshadi Khamseh, 2015. "Developing a multi-period robust optimization model considering American style options," Annals of Operations Research, Springer, vol. 233(1), pages 305-320, October.
  • Handle: RePEc:spr:annopr:v:233:y:2015:i:1:p:305-320:10.1007/s10479-013-1461-x
    DOI: 10.1007/s10479-013-1461-x
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    References listed on IDEAS

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    1. Maria Scutellà & Raffaella Recchia, 2013. "Robust portfolio asset allocation and risk measures," Annals of Operations Research, Springer, vol. 204(1), pages 145-169, April.
    2. Frank Lutgens & Jos Sturm & Antoon Kolen, 2006. "Robust One-Period Option Hedging," Operations Research, INFORMS, vol. 54(6), pages 1051-1062, December.
    3. A. L. Soyster, 1973. "Technical Note—Convex Programming with Set-Inclusive Constraints and Applications to Inexact Linear Programming," Operations Research, INFORMS, vol. 21(5), pages 1154-1157, October.
    4. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    5. D. Goldfarb & G. Iyengar, 2003. "Robust Portfolio Selection Problems," Mathematics of Operations Research, INFORMS, vol. 28(1), pages 1-38, February.
    6. Zymler, Steve & Rustem, Berç & Kuhn, Daniel, 2011. "Robust portfolio optimization with derivative insurance guarantees," European Journal of Operational Research, Elsevier, vol. 210(2), pages 410-424, April.
    7. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
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    Cited by:

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    4. 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).

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