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Pricing American Options Based on the Binomial Tree Model

In: Management Information Systems in a Digitalized AI World

Author

Listed:
  • Zhuohao Cao

    (Central University of Finance and Economics)

  • Xiaohui Huang

    (University of Birmingham Joint Institute, Jinan University)

  • Wentao Xiao

    (Lancaster University)

  • Qiqian Zeng

    (University of Birmingham Joint Institute, Jinan University)

Abstract

Due to their inherent flexibility to be exercised at any time before expiration, American options present a valuation challenge that is more complex and costly compared to European options, which can only be exercised at expiration. This paper seeks to elucidate the premium of American options through a 2-period binomial tree model under the assumption that the product of downside and upside probabilities equals one. This work explores the price differential between American and European options across a spectrum of interest rates r and strike prices K. Furthermore, this work investigates the implications of dividends on American call option premiums by employing a 1-period binomial tree model. The inclusion of dividends adds a layer of complexity to the valuation process, necessitating the derivation of risk-neutral probabilities that account for dividends while maintaining no-arbitrage conditions. Our analysis reveals how variations in interest rates, strike prices, and the presence of dividends significantly influence American option premiums. By providing a detailed framework, our findings contribute to a deeper understanding of the pricing dynamics of American options, enabling better strategic decision-making for investors and financial practitioners alike. This comprehensive approach sheds light on the intricate relationships that govern option valuation in diverse market conditions.

Suggested Citation

  • Zhuohao Cao & Xiaohui Huang & Wentao Xiao & Qiqian Zeng, 2025. "Pricing American Options Based on the Binomial Tree Model," Springer Proceedings in Business and Economics, in: Eric Tsui & Montathar Faraon & Kari Rönkkö (ed.), Management Information Systems in a Digitalized AI World, pages 223-232, Springer.
  • Handle: RePEc:spr:prbchp:978-981-96-6526-6_15
    DOI: 10.1007/978-981-96-6526-6_15
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