A Hybrid Monte Carlo and Finite Difference Method for Option Pricing

Darae Jeong, Minhyun Yoo, Changwoo Yoo, Junseok Kim

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    We propose an accurate, efficient, and robust hybrid finite difference method, with a Monte Carlo boundary condition, for solving the Black–Scholes equations. The proposed method uses a far-field boundary value obtained from a Monte Carlo simulation, and can be applied to problems with non-linear payoffs at the boundary location. Numerical tests on power, powered, and two-asset European call option pricing problems are presented. Through these numerical simulations, we show that the proposed boundary treatment yields better accuracy and robustness than the most commonly used linear boundary condition. Furthermore, the proposed hybrid method is general, which means it can be applied to other types of option pricing problems. In particular, the proposed Monte Carlo boundary condition algorithm can be implemented easily in the code of the existing finite difference method, with a small modification.

    Original languageEnglish
    Pages (from-to)111-124
    Number of pages14
    JournalComputational Economics
    Volume53
    Issue number1
    DOIs
    Publication statusPublished - 2019 Jan 31

    Bibliographical note

    Publisher Copyright:
    © 2017, Springer Science+Business Media, LLC.

    Keywords

    • Black–Scholes equation
    • Boundary condition
    • Finite difference method
    • Monte Carlo simulation
    • Option pricing

    ASJC Scopus subject areas

    • Economics, Econometrics and Finance (miscellaneous)
    • Computer Science Applications

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