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Valuation by Simulation of Contingent Claims with Multiple Early Exercise Opportunities

Author

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  • Alfredo Ibáñez

Abstract

This paper introduces the application of Monte Carlo simulation technology to the valuation of securities that contain many (buying or selling) rights, but for which a limited number can be exercised per period, and penalties if a minimum quantity is not exercised before maturity. These securities combine the characteristics of American options, with the additional constraint that only a few rights can be exercised per period and therefore their price depends also on the number of living rights (i.e., American‐Asian‐style payoffs), and forward securities. These securities give flexibility‐of‐delivery options and are common in energy markets (e.g., take‐or‐pay or swing options) and as real options (e.g., the development of a mine). First, we derive a series of properties for the price and the optimal exercise frontier of these securities. Second, we price them by simulation, extending the Ibáñez and Zapatero (2004) method to this problem.
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Suggested Citation

  • Alfredo Ibáñez, 2002. "Valuation by Simulation of Contingent Claims with Multiple Early Exercise Opportunities," Computing in Economics and Finance 2002 114, Society for Computational Economics.
    • Handle: RePEc:sce:scecf2:114
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    Cited by:

    1. Dong, Wenfeng & Kang, Boda, 2019. "Analysis of a multiple year gas sales agreement with make-up, carry-forward and indexation," Energy Economics, Elsevier, vol. 79(C), pages 76-96.
    2. Cartea, Álvaro & Williams, Thomas, 2008. "UK gas markets: The market price of risk and applications to multiple interruptible supply contracts," Energy Economics, Elsevier, vol. 30(3), pages 829-846, May.
    3. Marcelo G. Figueroa, 2006. "Pricing Multiple Interruptible-Swing Contracts," Birkbeck Working Papers in Economics and Finance 0606, Birkbeck, Department of Economics, Mathematics & Statistics.
    4. Kovacevic, Raimund M. & Pflug, Georg Ch., 2014. "Electricity swing option pricing by stochastic bilevel optimization: A survey and new approaches," European Journal of Operational Research, Elsevier, vol. 237(2), pages 389-403.
    5. Alesii, Giuseppe, 2005. "VaR in real options analysis," Review of Financial Economics, Elsevier, vol. 14(3-4), pages 189-208.
    6. Thomas Deschatre & Joseph Mikael, 2020. "Deep combinatorial optimisation for optimal stopping time problems : application to swing options pricing," Papers 2001.11247, arXiv.org, revised Jan 2021.
    7. Dai, Min & Kwok, Yue Kuen, 2008. "Optimal multiple stopping models of reload options and shout options," Journal of Economic Dynamics and Control, Elsevier, vol. 32(7), pages 2269-2290, July.
    8. Wang, Chuan-Ju & Kao, Ming-Yang, 2016. "Optimal search for parameters in Monte Carlo simulation for derivative pricing," European Journal of Operational Research, Elsevier, vol. 249(2), pages 683-690.

    More about this item

    Keywords

    American; Real and Swing Options; Simulation; Dynamic Programming;
    All these keywords.

    JEL classification:

    • G0 - Financial Economics - - General

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