Valuing Simple Multiple-Exercise Real Options in Infrastructure Projects
Publication: Journal of Infrastructure Systems
Volume 13, Issue 2
Abstract
The revenue risk is considerable in infrastructure project financing arrangements such as build–operate–transfer (BOT). A potential mitigation strategy for the revenue risk is a governmental revenue guarantee, where the government secures a minimum amount of revenue for a project. Such a guarantee is: (1) only redeemable at distinct points in time; and (2) more economical if the government limits the guarantee’s availability to the early portions of a BOT’s concession period. Hence, a guarantee characterized by this type of structure takes the form of either a Bermudan or a simple multiple-exercise real option, depending upon the number of exercise opportunities afforded. The multi-least-squares Monte Carlo technique is presented and illustrated as a promising approach to determine the fair value of this variety of real option. This method is far more flexible than prevailing approaches, so it represents an important step toward improving risk mitigation and facilitating contractual and financial negotiations in BOT projects.
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Acknowledgments
This work was funded by Grant No. NSFCMS-0408988 from the National Science Foundation, whose support is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the writer and do not necessarily reflect the views of the National Science Foundation.
References
Amram, M., and Kulatilaka, N. (1999). Real options: Managing strategic investment in an uncertain world, Harvard Business School Press, Cambridge, Mass.
Andersen, L. A. (2000). “A simple approach to the pricing of Bermudan swaptions in the multifactor LIBOR market model.” J. Comput. Finance, 3(2), 5–32.
Black, F., and Scholes, M. (1973). “The pricing of options and corporate liabilities.” J. Polit. Econ., 81, 637–659.
Broadie, M., and Glasserman, P. (1997). “Pricing American-style securities using simulation.” J. Econ. Dyn. Control, 21(8), 1323–1352.
Chiara, N. (2006). “Real options methods for improving economic risk management in infrastructure project finance.” Ph.D. dissertation, Columbia Univ., New York.
Clement, D. L. E., and Protter, P. (2002). “An analysis of a least squares regression method for American option pricing.” Finance Stoch., 6(4), 449–471.
Copeland, T. E., and Antikarov, V. (2001). Real options: A practitioner’s guide, Texere, New York.
Dailami, M., Lipkovich, I., and Van Dyck, J. (1999). “INFRISK: A computer simulation approach to risk management in infrastructure project finance transactions.” Paper No. 2083, World Bank, Washington, D.C.
de Neufville, R., Scholtes, S., and Wang, T. (2006). “Real options by spreadsheet: Parking garage case example.” 12(2), 107–111.
Dixit, A. K., and Pindyck, R. S. (1994). Investment under uncertainty, Princeton University Press, Princeton, N.J.
Esty, B. C. (1999). “Improved techniques for valuing large-scale projects.” J. Project Finance, 5(1), 9–25.
Esty, B. C. (2003). Modern project finance: A casebook, Wiley, New York.
Ford, D. N., Lander, D. M., and Voyer, J. J. (2002). “A real options approach to valuing strategic flexibility in uncertain construction projects.” Constr. Manage. Econom., 20(4), 343–351.
Gamba, A. (2003). “Real options: A Monte Carlo approach.” Working papers, Dept. of Economics, Univ. of Verona, Verona, Italy.
Garvin, M. J., and Cheah, Y. J. (2004). “Valuation techniques for infrastructure investment decisions.” Constr. Manage. Econom., 22(5), 373–383.
Haugh, M. B. (2003). “Duality theory and simulation in financial engineering.” Proc., 2003 Winter Simulation Conf., New Orleans.
Ho, S., and Liu, L. Y. (2002). “An option pricing-based model for evaluating the financial viability of privatized infrastructure projects.” Constr. Manage. Econom., 20(2), 143–156.
Irwin, T. (2003). “Public money for private infrastructure.” Paper no. 26601, World Bank, Washington, D.C.
Jaillet, P., Ronn, E. I., and Tompaidis, S. (2004). “Valuation of commodity-based swing options.” Manage. Sci., 50(7), 909–921.
Longstaff, F. A., and Schwartz, E. S. (2001). “Valuing American options by simulation: A simple least-squares approach.” Rev. Financ. Stud., 14(1), 113–147.
Meinshausen, N., and Hambly, B. M. (2004). “Monte Carlo methods for the valuation of multi-exercise options.” Math. Finance, 14(4), 557–583.
Merton, R. C. (1973). “Theory of rational option pricing.” Bell J. Economics and Management, 4, 141–183.
Moreno, M., and Navas, J. F. (2003). “On the robustness of least-squares Monte Carlo (LSM) for pricing American derivatives.” J. Project Finance, 6(2), 107–128.
Myers, S. (1977). “Determinants of corporate borrowing.” J. Financ. Econ., 5(1), 147–175.
Powell, W. B. (2005). Approximate dynamic programming for operations research, http://www.castlelab.princeton.edu (Aug. 29, 2005).
Reinhardt, W. (2004). “State legislative scorecard: Enabling laws for transportation partnerships.” Public Works Financing, 186, 7.
Trigeorgis, L. (1996). Real options: Managerial flexibility and strategy in resource allocation, MIT Press, Cambridge, Mass.
Wang, T., and de Neufvillee, R. (2005). “Real options ‘in’ projects.” http://realoptions.org/papers2005/Tao_Wang_RO_in_projects.pdf (Aug. 8, 2005).
Yescombe, E. R. (2002). Principles of project finance, Academic, San Diego.
Zhao, T., Sundararajan, S. K., and Tseng, C. L. (2004). “Highway development decision-making under uncertainty: A real options approach.” J. Infrastruct. Syst., 10(1), 23–32.
Zhao, T., and Tseng, C. L. (2003). “Valuing flexibility in infrastructure expansion.” J. Infrastruct. Syst., 9(3), 89–97.
Information & Authors
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Published In
Journal of Infrastructure Systems
Volume 13 • Issue 2 • June 2007
Pages: 97 - 104
Copyright
© 2007 ASCE.
History
Received: Nov 4, 2005
Accepted: Jul 24, 2006
Published online: Jun 1, 2007
Published in print: Jun 2007
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