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

Author

Listed:
  • Antonio Cosma

    (Université du Luxembourg)

  • Stefano Galluccio

    (BNP Paribas Fixed Income)

  • Paola Pederzoli

    (University of Geneva and Swiss Finance Institute)

  • O. Scaillet

    (University of Geneva and Swiss Finance Institute)

Abstract

Using a fast numerical technique, we investigate a large database of investor suboptimal nonexercise of short maturity American call options on dividend-paying stocks listed on the Dow Jones. The correct modelling 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 by a quarter the amount lost by investors through suboptimal exercise. 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.

Suggested Citation

  • Antonio Cosma & Stefano Galluccio & Paola Pederzoli & O. Scaillet, 2016. "Early Exercise Decision in American Options with Dividends, Stochastic Volatility and Jumps," Swiss Finance Institute Research Paper Series 16-73, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1673
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    2. Weihan Li & Jin E. Zhang & Xinfeng Ruan & Pakorn Aschakulporn, 2024. "An empirical study on the early exercise premium of American options: Evidence from OEX and XEO options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(7), pages 1117-1153, July.
    3. Boswijk, H. Peter & Laeven, Roger J.A. & Vladimirov, Evgenii, 2024. "Estimating option pricing models using a characteristic function-based linear state space representation," Journal of Econometrics, Elsevier, vol. 244(1).
    4. Ha, Mijin & Park, Sangmin & Yoon, Ji-Hun & Kim, Donghyun, 2025. "Pricing of American timer options," The North American Journal of Economics and Finance, Elsevier, vol. 78(C).
    5. Bryzgalova, Svetlana & Pavlova, Anna & Sikorskaya, Taisiya, 2025. "Strategic arbitrage in segmented markets," Journal of Financial Economics, Elsevier, vol. 166(C).
    6. Cho, Junhyun & Kim, Yejin & Lee, Sungchul, 2022. "An accurate and stable numerical method for option hedge parameters," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    7. Haozhe Su & M. V. Tretyakov & David P. Newton, 2021. "Deep learning of transition probability densities for stochastic asset models with applications in option pricing," Papers 2105.10467, arXiv.org, revised Jul 2023.

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