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Practical guide to real options in discrete time

Author

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  • Sergey Levendorskiy
  • Svetlana Boyarchenko

Abstract

Continuous time models in the theory of real options give explicit formulas for optimal exercise strategies when options are simple and the price of an underlying asset follows a geometric Brownian motion. This paper suggests a general, computationally simple approach to real options in discrete time. Explicit formulas are derived even for embedded options. Discrete time processes reflect the scarcity of observations in the data, and may account for fat tails and skewness of probability distributions of commodity prices. The method of the paper is based on the use of the expected present value operators.

Suggested Citation

  • Sergey Levendorskiy & Svetlana Boyarchenko, 2004. "Practical guide to real options in discrete time," Computing in Economics and Finance 2004 137, Society for Computational Economics.
    • Handle: RePEc:sce:scecf4:137
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    Citations

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    Cited by:

    1. Boyarchenko, Svetlana & Levendorskii[caron], Sergei, 2007. "Optimal stopping made easy," Journal of Mathematical Economics, Elsevier, vol. 43(2), pages 201-217, February.
    2. Das Gupta, Supratim, 2021. "Using real options to value capacity additions and investment expenditures in renewable energies in India," Energy Policy, Elsevier, vol. 148(PA).
    3. Svetlana Boyarchenko & Sergei Levendorskii, 2004. "Universal bad news principle and pricing of options on dividend-paying assets," Papers cond-mat/0404108, arXiv.org.
    4. Svetlana Boyarchenko & Sergei Levendorskii, 2005. "A theory of endogenous time preference, and discounted utility anomalies," Microeconomics 0506005, University Library of Munich, Germany.
    5. Jukka Lempa, 2008. "On infinite horizon optimal stopping of general random walk," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 67(2), pages 257-268, April.
    6. Luis Alvarez & Teppo Rakkolainen, 2010. "Investment timing in presence of downside risk: a certainty equivalent characterization," Annals of Finance, Springer, vol. 6(3), pages 317-333, July.
    7. Luis Alvarez & Teppo Rakkolainen, 2009. "Optimal payout policy in presence of downside risk," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 69(1), pages 27-58, March.
    8. Svetlana Boyarchenko & Sergei Levendorskii, 2005. "Discount factors ex post and ex ante, and discounted utility anomalies," Microeconomics 0510013, University Library of Munich, Germany, revised 13 Dec 2005.
    9. Svetlana Boyarchenko & Sergei Levendorskii, 2005. "American options: the EPV pricing model," Annals of Finance, Springer, vol. 1(3), pages 267-292, August.
    10. Driouchi, Tarik & So, Raymond H.Y. & Trigeorgis, Lenos, 2020. "Investor ambiguity, systemic banking risk and economic activity: The case of too-big-to-fail," Journal of Corporate Finance, Elsevier, vol. 62(C).
    11. Fernando A. C. C. Fonte & Dalila B. M. M. Fontes, 2007. "Optimal investment timing using Markov jump price processes," FEP Working Papers 245, Universidade do Porto, Faculdade de Economia do Porto.
    12. Boyarchenko, Svetlana & Levendorskii, Sergei, 2008. "Exit problems in regime-switching models," Journal of Mathematical Economics, Elsevier, vol. 44(2), pages 180-206, January.
    13. Boyarchenko, Svetlana & Levendorskii, Sergei, 2010. "Optimal stopping in Levy models, for non-monotone discontinuous payoffs," MPRA Paper 27999, University Library of Munich, Germany.
    14. Das Gupta, Supratim, 2018. "Using real options to study the impact of capacity additions and investment expenditures in renewable energies in India," MPRA Paper 90441, University Library of Munich, Germany.
    15. Detert, Neal & Kotani, Koji, 2013. "Real options approach to renewable energy investments in Mongolia," Energy Policy, Elsevier, vol. 56(C), pages 136-150.

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    More about this item

    Keywords

    Real options; embedded options; expected present value operators;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies

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