Valuing Multifactor Real Options Using an Implied Binomial Tree

Authors:
Tianyang Wang;James S. Dyer
Affiliations:
McCombs School of Business, The University of Texas at Austin, Austin, Texas 78712;McCombs School of Business, The University of Texas at Austin, Austin, Texas 78712
Venue:
Decision Analysis
Year:
2010

Citing 5
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Abstract

This paper proposes an approach for solving a multifactor real options problem by approximating the underlying stochastic process with an implied binomial tree. The implied binomial tree is constructed to be consistent with simulated market information. By simulating European option prices as artificial market information, we apply the implied binomial tree method for real options valuation when the options are contingent on the value of market uncertainties that are not traded assets. Compared to the discrete approximations suggested in the current literature, this method offers a more flexible distribution assumption for project values and therefore provides an alternative approach to estimating the value of high-dimensional real options. For risk managers, it serves as a capital budgeting method for projects with managerial flexibility.