American Knock‐In Options Pricing of Mean‐Reverting Stock Model With Floating Interest Rate

ABSTRACT Knock‐in options are a kind of exotic options that are path‐dependent. The options will automatically take effect when the price of the underlying assert reaches a specific limit price. This paper studies an American knock‐in options pricing scheme based on a mean‐reverting stock model, considering the floating interest rate under an uncertain market environment. First of all, ‐paths of uncertain differential equations are utilized to derive the pricing formulas for American call and put options. Then, the real data of the financial market are utilized to obtain the corresponding parameters using uncertain maximum likelihood estimation. Subsequently, a hypothesis test is utilized to assess the adequacy of the stock model in fitting the observed data, and several numerical algorithms are developed to validate the efficacy of the stock model.

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Publication Details

Journal
Mathematical Methods in the Applied Sciences
Published
2025-05-30
DOI
https://doi.org/10.1002/mma.11089
Primary Topic
Fuzzy Systems and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

American Knock‐In Options Pricing of Mean‐Reverting Stock Model With Floating Interest Rate

Lifen Jia, Xueyong Liu, Haocheng Wang
Mathematical Methods in the Applied Sciences
Fuzzy Systems and Optimization
article

American Knock‐In Options Pricing of Mean‐Reverting Stock Model With Floating Interest Rate

Lifen Jia, Xueyong Liu, Haocheng Wang
article en

Abstract

ABSTRACT Knock‐in options are a kind of exotic options that are path‐dependent. The options will automatically take effect when the price of the underlying assert reaches a specific limit price. This paper studies an American knock‐in options pricing scheme based on a mean‐reverting stock model, considering the floating interest rate under an uncertain market environment. First of all, ‐paths of uncertain differential equations are utilized to derive the pricing formulas for American call and put options. Then, the real data of the financial market are utilized to obtain the corresponding parameters using uncertain maximum likelihood estimation. Subsequently, a hypothesis test is utilized to assess the adequacy of the stock model in fitting the observed data, and several numerical algorithms are developed to validate the efficacy of the stock model.

Mathematical Methods in the Applied SciencesVol. 48(13)
Capital University of Economics and Business (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 88%
Fuzzy Systems and Optimization
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