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Pricing American Stock Options by Linear Programming

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  • M. A. H. Dempster
  • J. P. Hutton

Abstract

We investigate numerical solution of finite difference approximations to American option pricing problems, using a new direct numerical method: simplex solution of a linear programming formulation. This approach is based on an extension to the parabolic case of the equivalence between linear order complementarity problems and abstract linear programs known for certain elliptic operators. We test this method empirically, comparing simplex and interior point algorithms with the projected successive overrelaxation (PSOR) algorithm applied to the American vanilla and lookback puts. We conclude that simplex is roughly comparable with projected SOR on average (faster for fine discretizations, slower for coarse), but is more desirable for robustness of solution time under changes in parameters. Furthermore, significant speedups over the results given here have been achieved and will be published elsewhere.

Suggested Citation

  • M. A. H. Dempster & J. P. Hutton, 1999. "Pricing American Stock Options by Linear Programming," Mathematical Finance, Wiley Blackwell, vol. 9(3), pages 229-254, July.
    • Handle: RePEc:bla:mathfi:v:9:y:1999:i:3:p:229-254
    DOI: 10.1111/1467-9965.00069
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    Cited by:

    1. Luca Vincenzo Ballestra, 2018. "Fast and accurate calculation of American option prices," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 41(2), pages 399-426, November.
    2. Zhongkai Liu & Tao Pang, 2016. "An efficient grid lattice algorithm for pricing American-style options," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 5(1), pages 36-55.
    3. Qianru Shang & Brian Byrne, 2021. "American option pricing: Optimal Lattice models and multidimensional efficiency tests," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(4), pages 514-535, April.
    4. S. Dyrting, 2004. "Pricing equity options everywhere," Quantitative Finance, Taylor & Francis Journals, vol. 4(6), pages 663-676.
    5. Louis Bhim & Reiichiro Kawai, 2018. "Smooth Upper Bounds For The Price Function Of American Style Options," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 21(01), pages 1-38, February.
    6. Jérôme Detemple, 2014. "Optimal Exercise for Derivative Securities," Annual Review of Financial Economics, Annual Reviews, vol. 6(1), pages 459-487, December.
    7. Topaloglou, Nikolas & Vladimirou, Hercules & Zenios, Stavros A., 2008. "Pricing options on scenario trees," Journal of Banking & Finance, Elsevier, vol. 32(2), pages 283-298, February.
    8. Hyounggun Song & Sung Kwon Han & Seung Hwan Jeong & Hee Soo Lee & Kyong Joo Oh, 2019. "Using Genetic Algorithms to Develop a Dynamic Guaranteed Option Hedge System," Sustainability, MDPI, vol. 11(15), pages 1-12, July.
    9. Andras Prekopa & Tam�s Sz�ntai, 2010. "On the analytical-numerical valuation of the Bermudan and American options," Quantitative Finance, Taylor & Francis Journals, vol. 10(1), pages 59-74.
    10. Volodymyr Babich, 2006. "Vulnerable options in supply chains: Effects of supplier competition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(7), pages 656-673, October.
    11. Berridge, S.J. & Schumacher, J.M., 2004. "Pricing High-Dimensional American Options Using Local Consistency Conditions," Other publications TiSEM 8c8de631-5039-4eec-a965-3, Tilburg University, School of Economics and Management.
    12. Valeriy Ryabchenko & Sergey Sarykalin & Stan Uryasev, 2004. "Pricing European Options by Numerical Replication: Quadratic Programming with Constraints," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 11(3), pages 301-333, September.
    13. Yoshifumi Muroi & Takashi Yamada, 2006. "Pricing problems of perpetual Bermudan options," Computing in Economics and Finance 2006 345, Society for Computational Economics.
    14. Chockalingam, Arun & Muthuraman, Kumar, 2015. "An approximate moving boundary method for American option pricing," European Journal of Operational Research, Elsevier, vol. 240(2), pages 431-438.
    15. Berridge, S.J. & Schumacher, J.M., 2002. "An Irregular Grid Approach for Pricing High Dimensional American Options," Other publications TiSEM 416a6d43-3466-47e0-b656-d, Tilburg University, School of Economics and Management.
    16. John Board & Charles Sutcliffe & William T. Ziemba, 2003. "Applying Operations Research Techniques to Financial Markets," Interfaces, INFORMS, vol. 33(2), pages 12-24, April.
    17. Nagae, Takeshi & Akamatsu, Takashi, 2008. "A generalized complementarity approach to solving real option problems," Journal of Economic Dynamics and Control, Elsevier, vol. 32(6), pages 1754-1779, June.
    18. Milevsky, Moshe A. & Salisbury, Thomas S., 2006. "Financial valuation of guaranteed minimum withdrawal benefits," Insurance: Mathematics and Economics, Elsevier, vol. 38(1), pages 21-38, February.
    19. Nurşen Aydın & Ş. İlker Birbil & Hüseyin Topaloğlu, 2017. "Delayed Purchase Options in Single-Leg Revenue Management," Transportation Science, INFORMS, vol. 51(4), pages 1031-1045, November.
    20. Yoshifumi Muroi & Takashi Yamada, 2008. "An Explicit Finite Difference Approach to the Pricing Problems of Perpetual Bermudan Options," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 15(3), pages 229-253, December.

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