Valuing Multifactor Real Options Using an Implied Binomial Tree

Wang, T., & Dyer, J. S. (2010). Valuing multifactor real options using an implied binomial tree. Decision Analysis, 7(2), 185-195.

Posted: 20 Apr 2015

See all articles by Tianyang Wang

Tianyang Wang

Colorado State University - Department of Finance & Real Estate

James Dyer

University of Texas at Austin

Date Written: July 18, 2010

Abstract

This paper proposes an approach for solving a multi-factor 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.

Keywords: real options; implied binomial tree; multifactor; simulation

JEL Classification: G13

Suggested Citation

Wang, Tianyang and Dyer, James, Valuing Multifactor Real Options Using an Implied Binomial Tree (July 18, 2010). Wang, T., & Dyer, J. S. (2010). Valuing multifactor real options using an implied binomial tree. Decision Analysis, 7(2), 185-195., Available at SSRN: https://ssrn.com/abstract=2596098

Tianyang Wang (Contact Author)

Colorado State University - Department of Finance & Real Estate ( email )

Finance and Real Estate Department
1272 Campus Delivery
Fort Collins, CO 80523
United States

James Dyer

University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 78712
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Abstract Views
590
PlumX Metrics