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Monte Carlo Estimation of Project Volatility for Real Options Analysis

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  • Pedro Godinho

    (GEMF and Faculdade de Economia, Universidade de Coimbra)

Abstract

Volatility is a fundamental parameter for option valuation. In particular, real options models require project volatility, which is very hard to estimate accurately because there is usually no historical data for the underlying asset. Several authors have used a method based on Monte Carlo simulation for estimating project volatility. In this paper we analyse the existing procedures for applying the method, concluding that they will lead to an upward bias in the volatility estimate. We propose different procedures that will provide better results, and we also discuss the business consequences of using upwardly biased volatility estimates in real options analysis.

Suggested Citation

  • Pedro Godinho, 2006. "Monte Carlo Estimation of Project Volatility for Real Options Analysis," GEMF Working Papers 2006-01, GEMF, Faculty of Economics, University of Coimbra.
    • Handle: RePEc:gmf:wpaper:2006-01
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    References listed on IDEAS

    as
    1. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," The Review of Financial Studies, Society for Financial Studies, vol. 14(1), pages 113-147.
    2. Davis, Graham A., 1998. "Estimating Volatility and Dividend Yield When Valuing Real Options to Invest or Abandon," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 2), pages 725-754.
    3. Han T.J. Smit, 1997. "Investment Analysis of Offshore Concessions in the Netherlands," Financial Management, Financial Management Association, vol. 26(2), Summer.
    4. Avinash K. Dixit & Robert S. Pindyck, 1994. "Investment under Uncertainty," Economics Books, Princeton University Press, edition 1, number 5474.
    5. Kelly, Simone, 1998. "A Binomial Lattice Approach for Valuing a Mining Property IPO," The Quarterly Review of Economics and Finance, Elsevier, vol. 38(3, Part 2), pages 693-709.
    6. Longstaff, Francis A & Schwartz, Eduardo S, 2001. "Valuing American Options by Simulation: A Simple Least-Squares Approach," University of California at Los Angeles, Anderson Graduate School of Management qt43n1k4jb, Anderson Graduate School of Management, UCLA.
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    Cited by:

    1. Rosa-Isabel González-Muñoz & Jesús Molina-Muñoz & Andrés Mora-Valencia & Javier Perote, 2024. "Real Options Volatility Surface for Valuing Renewable Energy Projects," Energies, MDPI, vol. 17(5), pages 1-13, March.
    2. Steffen Wehkamp & Lucas Schmeling & Lena Vorspel & Fabian Roelcke & Kai-Lukas Windmeier, 2020. "District Energy Systems: Challenges and New Tools for Planning and Evaluation," Energies, MDPI, vol. 13(11), pages 1-20, June.
    3. Tianyang Wang & James S. Dyer, 2010. "Valuing Multifactor Real Options Using an Implied Binomial Tree," Decision Analysis, INFORMS, vol. 7(2), pages 185-195, June.
    4. Pedro Godinho, 2015. "Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach," GEMF Working Papers 2015-02, GEMF, Faculty of Economics, University of Coimbra.
    5. E. Brandão, Luiz & Dyer, James S. & Hahn, Warren J., 2012. "Volatility estimation for stochastic project value models," European Journal of Operational Research, Elsevier, vol. 220(3), pages 642-648.
    6. Carlos Andrés Zapata Quimbayo, 2020. "OPCIONES REALES Una guía teórico-práctica para la valoración de inversiones bajo incertidumbre mediante modelos en tiempo discreto y simulación de Monte Carlo," Books, Universidad Externado de Colombia, Facultad de Finanzas, Gobierno y Relaciones Internacionales, number 138, April.
    7. Miranda, Oscar & Brandão, Luiz E. & Lazo Lazo, Juan, 2017. "A dynamic model for valuing flexible mining exploration projects under uncertainty," Resources Policy, Elsevier, vol. 52(C), pages 393-404.
    8. Schachter, J.A. & Mancarella, P., 2016. "A critical review of Real Options thinking for valuing investment flexibility in Smart Grids and low carbon energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 261-271.
    9. Pedro Godinho, 2015. "Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach," GEMF Working Papers 2015-02, GEMF, Faculty of Economics, University of Coimbra.
    10. Pareja Vasseur, Julián. DBA & Prada Sánchez, Marcela & Moreno Escobar, Martha, 2019. "Volatilidad en Opciones Reales: Revisión Literaria y un Caso de Aplicación en el Sector Petrolero Colombiano || Real Options Volatility: Literature Review and a Case of Application in the Colombian Oi," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 27(1), pages 136-155, June.
    11. Maria-Teresa Bosch-Badia & Joan Montllor-Serrats & Maria-Antonia Tarrazon-Rodon, 2015. "Corporate Social Responsibility: A Real Options Approach to the Challenge of Financial Sustainability," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-37, May.
    12. Zhang, Mingming & Liu, Liyun & Wang, Qunwei & Zhou, Dequn, 2020. "Valuing investment decisions of renewable energy projects considering changing volatility," Energy Economics, Elsevier, vol. 92(C).

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