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Research Article | Open Access

A finite integration method for pricing and hedging path-dependent structured derivatives

Yejin Kim1Wooyeol Jeong2( )Sungchul Lee2
EG Asset Pricing Co., Ltd., Seoul 07241, Korea
Department of Mathematics, Yonsei University, Seoul 03722, Korea
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Abstract

This study introduces the finite integration method (FIM) as a robust numerical approach for pricing equity-linked notes (ELNs). The FIM extends its application beyond vanilla options, effectively addressing the complexities of continuous boundaries and binary payoffs associated with ELNs. We present a comprehensive framework for ELN pricing, including detailed explanations of product structures and a step-by-step description of the FIM methodology. To assess the performance of the FIM, we conduct a comparative analysis against the implicit FDM. Numerical results demonstrate that the FIM outperforms the FDM in terms of reduced pricing errors and more precise hedge parameters (Greeks). We evaluated both one-dimensional barrier options and two-dimensional binary options. Additionally, we proposed an FIM algorithm for pricing a two-dimensional step-down ELN with a knock-in barrier feature. Monte Carlo simulations(MCS) are used as benchmarks to validate the convergence and accuracy of the FIM. The results confirm that the FIM is a robust and practical method for derivative valuation and risk management. Furthermore, the flexibility of the FIM framework allows it to accommodate various complex payoff structures, making it a valuable tool for pricing structured derivatives.

CLC number: 65C20, 91G20

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AIMS Mathematics
Pages 24294-24316

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Cite this article:
Kim Y, Jeong W, Lee S. A finite integration method for pricing and hedging path-dependent structured derivatives. AIMS Mathematics, 2025, 10(10): 24294-24316. https://doi.org/10.3934/math.20251077

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Received: 08 July 2025
Revised: 22 September 2025
Accepted: 16 October 2025
Published: 23 October 2025
©2025 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)