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Early Exercise Decision in American Options with Dividends, Stochastic Volatility, and Jumps

Published online by Cambridge University Press:  08 October 2018

Antonio Cosma Open the ORCID record for Antonio Cosma [Opens in a new window] ,
Stefano Galluccio ,
Paola Pederzoli  and
Olivier Scaillet Open the ORCID record for Olivier Scaillet [Opens in a new window]
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Abstract

Using a fast numerical technique, we investigate a large database of investors’ suboptimal nonexercise of short-maturity American call options on dividend-paying stocks listed on the Dow Jones. The correct modeling of the discrete dividend is essential for a correct calculation of the early exercise boundary, as confirmed by theoretical insights. Pricing with stochastic volatility and jumps instead of the Black–Scholes–Merton benchmark cuts the amount lost by investors through suboptimal exercise by one-quarter. The remaining three-quarters are largely unexplained by transaction fees and may be interpreted as an opportunity cost for the investors to monitor optimal exercise.

Type
Research Article
Information
Journal of Financial and Quantitative Analysis , Volume 55 , Issue 1 , February 2020 , pp. 331 - 356
Copyright
Copyright © Michael G. Foster School of Business, University of Washington 2018 

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Footnotes

1

We thank Jarrad Harford (the editor) and Gurdip Bakshi (the referee) for constructive criticism and numerous suggestions, which led to substantial improvements over the previous version. We also thank Jérôme Detemple, Darrell Duffie, Emmanuel Gobet, Jens Jackwerth, Franck Moraux, David Newton, Adrien Treccani, and Alfonso Valdesogo for valuable insight and help in addition to the participants at the 2010 and the 2016 World Congress of the Bachelier Finance Society, the 2011 European Econometric Society, the 2013 Mathematical Finance Day, the 2014 Conference on Mathematical and Statistical Methods for Actuarial Sciences and Finance, the 2014 International Symposium on Differential Equations and Stochastic Analysis in Mathematical Finance, the 2015 General Advanced Mathematical Methods in Finance and Swissquote Conference, the 2015 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, the 2015 International Conference on Computational and Financial Econometrics, the 2015 International Conference on Computational Finance, the 2016 SGF Conference, the 2016 Financial Engineering and Risk Management Symposium, the 2016 French Finance Association (AFFI) conference, the 2016 Stochmod16 conference, the 2016 European Finance Association meeting, and seminars at the University of Geneva and the University of Orléans. Scaillet received support from the Swiss National Science Foundation through the National Centres of Competence in Research (NCCR) Finrisk. Pederzoli acknowledges the financial support of the Swiss NSF (grant 100018-149307). Part of the research was conducted when Pederzoli was visiting London School of Economics. A previous version of this paper circulated under the title “Valuing American Options Using Fast Recursive Projections.”

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