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Executive stock option exercise with full and partial information on a drift change point
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Henderson, Vicky, Kladivko, K., Monoyios, M. and Reisinger, C. (2020) Executive stock option exercise with full and partial information on a drift change point. SIAM Journal on Financial Mathematics . (In Press)
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Abstract
We analyse the optimal exercise of an American call executive stock option (ESO) written on a stock whose drift parameter falls to a lower value at a change point, an exponentially distributed random time independent of the Brownian motion driving the stock. Two agents, who do not trade the stock, have differing information on the change point, and seek to optimally exercise the option by maximising its discounted payoff under the physical measure. The first agent has full information, and observes the change point. The second agent has partial information and filters the change point from price observations. This scenario is designed to mimic the positions of two employees of varying seniority, a fully informed executive and a partially informed less senior employee, each of whom receives an ESO. The partial information scenario yields a model under the observation filtration F in which the stock drift becomes a diffusion driven by the innovations process, an F-Brownian motion also driving the stock under F, and the partial information optimal stopping value function has two spatial dimensions. We rigorously characterise the free boundary PDEs for both agents, establish shape and regularity properties of the associated optimal exercise boundaries, and prove the smooth pasting property in both information scenarios, exploiting some stochastic flow ideas to do so in the partial information case. We develop finite difference algorithms to numerically solve both agents’ exercise and valuation problems and illustrate that the additional information of the fully informed agent can result in exercise patterns which exploit the information on the change point, lending credence to empirical studies which suggest that privileged information of bad news is a factor leading to early exercise of ESOs prior to poor stock price performance.
| Item Type: | Journal Article | ||||||
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| Subjects: | H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics |
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| Divisions: | Faculty of Science > Statistics | ||||||
| Library of Congress Subject Headings (LCSH): | Employee stock options, Optimal stopping (Mathematical statistics), Stochastic processes, Change-point problems | ||||||
| Journal or Publication Title: | SIAM Journal on Financial Mathematics | ||||||
| Publisher: | Society for Industrial and Applied Mathematics | ||||||
| ISSN: | 1945-497X | ||||||
| Official Date: | 2020 | ||||||
| Dates: |
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| Date of first compliant deposit: | 1 October 2020 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | In Press | ||||||
| Publisher Statement: | “First Published in SIAM Journal on Financial Mathematics in [volume and number, or year], published by the Society for Industrial and Applied Mathematics (SIAM)” Unauthorized reproduction of this article is prohibited.” | ||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||
| Copyright Holders: | © 2020, Society for Industrial and Applied Mathematics | ||||||
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