Using the Binomial Model for the Valuation of Real Options in Computing Optimal Subsidies for Chinese Renewable Energy Investments

22 Pages Posted: 8 Jun 2018

See all articles by Xiaoran Liu

Xiaoran Liu

University of Texas at Austin

Ehud I. Ronn

University of Texas at Austin - Department of Finance

Date Written: May 28, 2018

Abstract

For the valuation and implementation of renewable energy investments, the issue of providing private investors with a financial incentive to accelerate their investment is frequently a critical component. We apply this principle to the Chinese context. This paper focuses on using the binomial model to compute the required subsidy that would incentivize investors to optimal immediate exercise of the American-style option embedded at the launching phase of the projects for Chinese renewable energy investments. In addition, this paper also aims at contrasting the binomial model with the more-laborious Monte-Carlo simulation previously used to evaluate the proper subsidy. By using the same data but a different method, and reducing the number of uncertain factors to one, it is suggested these two methods have similar outcomes but the binomial method requires substantially less computation and is more self-explanatory. This paper thus provides government with an easy-to-implement alternative way to compute the required subsidy.

Keywords: Real options in energy markets, using the binomial model to value American-style options

JEL Classification: G12, G13

Suggested Citation

Liu, Xiaoran and Ronn, Ehud I., Using the Binomial Model for the Valuation of Real Options in Computing Optimal Subsidies for Chinese Renewable Energy Investments (May 28, 2018). Available at SSRN: https://ssrn.com/abstract=3186274 or http://dx.doi.org/10.2139/ssrn.3186274

Xiaoran Liu

University of Texas at Austin ( email )

2317 Speedway
Austin, TX 78712
United States

Ehud I. Ronn (Contact Author)

University of Texas at Austin - Department of Finance ( email )

Graduate School of Business
Austin, TX 78712
United States
512-471-5853 (Phone)
512-471-5073 (Fax)

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