American option pricing under stochastic volatility: an empirical evaluation
 Farid AitSahlia,
 Manisha Goswami,
 Suchandan Guha
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Over the past few years, model complexity in quantitative finance has increased substantially in response to earlier approaches that did not capture critical features for risk management. However, given the preponderance of the classical Black–Scholes model, it is still not clear that this increased complexity is matched by additional accuracy in the ultimate result. In particular, the last decade has witnessed a flurry of activity in modeling asset volatility, and studies evaluating different alternatives for option pricing have focused on Europeanstyle exercise. In this paper, we extend these empirical evaluations to American options, as their additional opportunity for early exercise may incorporate stochastic volatility in the pricing differently. Specifically, the present work compares the empirical pricing and hedging performance of the commonly adopted stochastic volatility model of Heston (Rev Financial Stud 6:327–343, 1993) against the traditional constant volatility benchmark of Black and Scholes (J Polit Econ 81:637–659, 1973). Using S&P 100 index options data, our study indicates that this particular stochastic volatility model offers enhancements in line with their Europeanstyle counterparts for inthemoney options. However, the most striking improvements are for outofthemoney options, which because of early exercise are more valuable than their Europeanstyle counterparts, especially when volatility is stochastic.
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 Title
 American option pricing under stochastic volatility: an empirical evaluation
 Journal

Computational Management Science
Volume 7, Issue 2 , pp 189206
 Cover Date
 20100401
 DOI
 10.1007/s1028700800832
 Print ISSN
 1619697X
 Online ISSN
 16196988
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Stochastic volatility
 Indirect inference
 Model calibration
 American option pricing
 S&P 100 index
 Approximate dynamic programming
 Industry Sectors
 Authors

 Farid AitSahlia ^{(1)}
 Manisha Goswami ^{(1)}
 Suchandan Guha ^{(1)}
 Author Affiliations

 1. Department of Industrial and Systems Engineering, Weil Hall 303, University of Florida, Gainesville, FL, 32611, USA