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)


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
Issue number1
Publication statusPublished - 2019 Jan 31

Bibliographical note

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


  • 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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