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Estimating State-Dependent Volatility of Investment Projects: A Simulation Approach

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  • Pedro Godinho

    (Faculty of Economics, University of Coimbra and GEMF, Portugal)

Abstract

Project volatility is an essential parameter for real options analysis, and it may also be useful for risk analysis. Many volatility estimation procedures only consider the volatility in the first year of the project. Others consider that different years may have different values of the project volatility. In this paper I show that volatility may change not only with time but also with the state of the project. I consider two possible definitions for the project volatility, the log-variance and the variance of the project value, and I propose three procedures for estimating state-dependent volatility: two-level simulation, one and a half level simulation and a regression procedure. Computational experiments show that the one and a half level simulation procedure and the regression procedure lead to the most accurate estimations of project volatility.

Suggested Citation

  • 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.
  • Handle: RePEc:gmf:wpaper:2015-02
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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. 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.
    3. 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.
    4. Alexander Triantis, 2005. "Realizing the Potential of Real Options: Does Theory Meet Practice?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 17(2), pages 8-16, March.
    5. Han T.J. Smit, 1997. "Investment Analysis of Offshore Concessions in the Netherlands," Financial Management, Financial Management Association, vol. 26(2), Summer.
    6. Dixit, Avinash & Pindyck, Robert S & Sodal, Sigbjorn, 1999. "A Markup Interpretation of Optimal Investment Rules," Economic Journal, Royal Economic Society, vol. 109(455), pages 179-189, April.
    7. 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.
    8. Costa Lima, Gabriel A. & Suslick, Saul B., 2006. "Estimating the volatility of mining projects considering price and operating cost uncertainties," Resources Policy, Elsevier, vol. 31(2), pages 86-94, June.
    9. Robert McDonald & Daniel Siegel, 1986. "The Value of Waiting to Invest," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 101(4), pages 707-727.
    10. Luiz Brandão & James Dyer, 2005. "Decision Analysis and Real Options: A Discrete Time Approach to Real Option Valuation," Annals of Operations Research, Springer, vol. 135(1), pages 21-39, March.
    11. Alexander, David Richard & Mo, Mengjia & Stent, Alan Fraser, 2012. "Arithmetic Brownian motion and real options," European Journal of Operational Research, Elsevier, vol. 219(1), pages 114-122.
    12. Yunpeng Sun & Daniel W. Apley & Jeremy Staum, 2011. "Efficient Nested Simulation for Estimating the Variance of a Conditional Expectation," Operations Research, INFORMS, vol. 59(4), pages 998-1007, August.
    13. 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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    More about this item

    Keywords

    Finance; Simulation; Project volatility; Real options; Investment analysis.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies

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