From Discrete Intuition to Computational Revolution in the Context of American Chooser Option

Zhixiang Wang; Liwei Su; Shanggeng Zhong; Shaobo Cai

doi:10.54254/2754-1169/2025.GL30023

Advances in Economics, Management and Political SciencesOpen access

From Discrete Intuition to Computational Revolution in the Context of American Chooser Option

Research Article

Open Access

From Discrete Intuition to Computational Revolution in the Context of American Chooser Option

Zhixiang Wang ^1* Liwei Su ², Shanggeng Zhong ³, Shaobo Cai ⁴

¹ Cornell University

² The University of Sheffield

³ Middleton Hall Lane

⁴ The Hong Kong University of Science and Technology

^*Corresponding author: zw658@cornell.edu

Published on 26 November 2025

AEMPS Vol.246

ISSN (Print): 2754-1177

ISSN (Online): 2754-1169

ISBN (Print): 978-1-80590-571-4

ISBN (Online): 978-1-80590-572-1

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Abstract

This paper illustrates the valuation of chooser options within the broader intellectual lineage of modern option pricing theory, providing both a theoretical and methodological framework. Our analysis is anchored in the discrete-time valuation methodology proposed by Cox, Ross, and Rubinstein, commonly known as the CRR model, which remains one of the most influential and practical approaches for demonstrating no-arbitrage pricing. While acknowledging the continuous-time paradigm of the Black–Scholes–Merton (BSM) model as a theoretical benchmark, we leverage the intuitive and adaptable nature of the binomial framework to deconstruct the chooser option’s unique structure. Furthermore, by drawing a conceptual parallel to the work on barrier options by Reiner and Rubinstein, we argue that the analytical treatment of path-dependent but contractually fixed boundaries provides a blueprint for decomposing the chooser’s distinctive payoff mechanism. The core contribution of this work lies in the systematic construction of a binomial pricing model tailored to this instrument. We conclude by outlining pathways for future research, including the extension of this framework to the more complex American-style chooser option—a challenge that requires advanced numerical methods such as the Least-Squares Monte Carlo (LSM) algorithm. Finally, this study proposes a testable hypothesis for future validation: that the structural flexibility embedded in the chooser option may justify a higher premium. Further empirical research is needed to confirm this conjecture and to highlight its potential for both practical implementation and continued academic exploration in complex financial contexts.

Keywords:

Chooser Option, Binomial Pricing Model, Monte Carlo Simulation

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