ESO Valuation with Job Termination Risk and Jumps in Stock Price

SIAM Journal on Financial Mathematics, vol. 6, no. 1, pp. 487-516, 2015

28 Pages Posted: 3 Mar 2013 Last revised: 26 Oct 2015

See all articles by Tim Leung

Tim Leung

University of Washington - Department of Applied Math

Haohua Wan

Columbia University - Department of Industrial Engineering and Operations Research (IEOR)

Date Written: April 29, 2014

Abstract

Employee stock options (ESOs) are American-style call options that can be terminated early due to employment shock. This paper studies an ESO valuation framework that accounts for job termination risk and jumps in the company stock price. Under general Levy stock price dynamics, we show that a higher job termination risk induces the ESO holder to voluntarily accelerate exercise, which in turn reduces the cost to the company. The holder's optimal exercise boundary and ESO cost are determined by solving an inhomogeneous partial integro-differential variational inequality (PIDVI). We apply Fourier transform to simplify the variational inequality and develop accurate numerical methods. Furthermore, when the stock price follows a geometric Brownian motion, we provide closed-form formulas for both the vested and unvested perpetual ESOs. Our model is also applied to evaluate the probabilities of ESO cost exceedance and contract termination.

Keywords: employee stock option, American option, job termination, Levy processes, Fourier transform

JEL Classification: C41, G13, J33

Suggested Citation

Leung, Tim and Wan, Haohua, ESO Valuation with Job Termination Risk and Jumps in Stock Price (April 29, 2014). SIAM Journal on Financial Mathematics, vol. 6, no. 1, pp. 487-516, 2015, Available at SSRN: https://ssrn.com/abstract=2227170 or http://dx.doi.org/10.2139/ssrn.2227170

Tim Leung (Contact Author)

University of Washington - Department of Applied Math ( email )

Lewis Hall 217
Department of Applied Math
Seattle, WA 98195
United States

HOME PAGE: http://faculty.washington.edu/timleung/

Haohua Wan

Columbia University - Department of Industrial Engineering and Operations Research (IEOR) ( email )

331 S.W. Mudd Building
500 West 120th Street
New York, NY 10027
United States

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