Optimal exercise of executive stock options and implications for firm cost
Jennifer Carpenter (),
Richard Stanton and
Nancy Wallace
Journal of Financial Economics, 2010, vol. 98, issue 2, 315-337
Abstract:
This paper conducts a comprehensive study of the optimal exercise policy for an executive stock option and its implications for option cost, average life, and alternative valuation concepts. The paper is the first to provide analytical results for an executive with general concave utility. Wealthier or less risk-averse executives exercise later and create greater option cost. However, option cost can decline with volatility. We show when there exists a single exercise boundary, yet demonstrate the possibility of a split continuation region. We also show that, for constant relative risk averse utility, the option value does not converge to the Black and Scholes value as the correlation between the stock and the market portfolio converges to one. We compare our model's option cost with the modified Black and Scholes approximation typically used in practice and show that the approximation error can be large or small, positive or negative, depending on firm characteristics.
Keywords: Executive; stock; option; Option; value; Option; life; Exercise; policy; Dynamic; trading (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (31)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304-405X(10)00152-2
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jfinec:v:98:y:2010:i:2:p:315-337
Access Statistics for this article
Journal of Financial Economics is currently edited by G. William Schwert
More articles in Journal of Financial Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().