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A Highly Accurate Finite Element Method to Price Discrete Double Barrier Options

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  • A. Golbabai
  • L. Ballestra
  • D. Ahmadian

Abstract

We develop a highly accurate numerical method for pricing discrete double barrier options under the Black–Scholes (BS) model. To this aim, the BS partial differential equation is discretized in space by the parabolic finite element method, which is based on a variational formulation and thus is well-suited for dealing with the non-smoothness of the discrete barrier option solutions. In addition, the approximation in time is performed using the implicit Euler scheme, which allows us to remove spurious oscillations that may occur at each monitoring date, and whose convergence rate is enhanced by means of a repeated Richardson extrapolation procedure. Numerical experiments are carried out which reveal that the method proposed achieves fourth-order accuracy in both space and time (even if the solutions being approximated are non-smooth), and performs hundredths of times better than a finite difference scheme in Wade et al. (J Comput Appl Math 204:144–158, 2007 ). To the best of our knowledge, the one developed in the present paper is the first lattice-based approach for discrete barrier options which is empirically shown to be fourth-order accurate in both space and time. Copyright Springer Science+Business Media New York 2014

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  • A. Golbabai & L. Ballestra & D. Ahmadian, 2014. "A Highly Accurate Finite Element Method to Price Discrete Double Barrier Options," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 153-173, August.
    • Handle: RePEc:kap:compec:v:44:y:2014:i:2:p:153-173
    DOI: 10.1007/s10614-013-9388-5
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    Cited by:

    1. Amirhossein Sobhani & Mariyan Milev, 2017. "A Numerical Method for Pricing Discrete Double Barrier Option by Legendre Multiwavelet," Papers 1703.09129, arXiv.org, revised Mar 2017.
    2. Xie, Fei & He, Zhijian & Wang, Xiaoqun, 2019. "An importance sampling-based smoothing approach for quasi-Monte Carlo simulation of discrete barrier options," European Journal of Operational Research, Elsevier, vol. 274(2), pages 759-772.
    3. Ahmad Golbabai & Omid Nikan, 2020. "A Computational Method Based on the Moving Least-Squares Approach for Pricing Double Barrier Options in a Time-Fractional Black–Scholes Model," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 119-141, January.
    4. Keegan Mendonca & Vasileios E. Kontosakos & Athanasios A. Pantelous & Konstantin M. Zuev, 2018. "Efficient Pricing of Barrier Options on High Volatility Assets using Subset Simulation," Papers 1803.03364, arXiv.org, revised Mar 2018.
    5. Detemple, Jérôme & Laminou Abdou, Souleymane & Moraux, Franck, 2020. "American step options," European Journal of Operational Research, Elsevier, vol. 282(1), pages 363-385.
    6. Huang, Min & Luo, Guo, 2022. "A simple and efficient numerical method for pricing discretely monitored early-exercise options," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    7. Sheng-Feng Luo & Hsin-Chieh Wong, 2023. "Continuity correction: on the pricing of discrete double barrier options," Review of Derivatives Research, Springer, vol. 26(1), pages 51-90, April.
    8. Xiao, Shuang & Ma, Shihua, 2016. "Pricing discrete double barrier options under Lévy processes: An extension of the method by Milev and Tagliani," Finance Research Letters, Elsevier, vol. 19(C), pages 67-74.
    9. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach to compute the first-passage probability density function in a time-changed Brownian model: Applications in finance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 330-344.
    10. Darae Jeong & Minhyun Yoo & Junseok Kim, 2016. "Accurate and Efficient Computations of the Greeks for Options Near Expiry Using the Black-Scholes Equations," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-12, April.
    11. A. Aimi & C. Guardasoni & L. Ortiz-Gracia & S. Sanfelici, 2023. "Fast Barrier Option Pricing by the COS BEM Method in Heston Model," Papers 2301.00648, arXiv.org, revised Jan 2023.
    12. Amirhossein Sobhani & Mariyan Milev, 2017. "A Numerical Method for Pricing Discrete Double Barrier Option by Lagrange Interpolation on Jacobi Node," Papers 1712.01060, arXiv.org, revised Feb 2018.
    13. Kontosakos, Vasileios E. & Mendonca, Keegan & Pantelous, Athanasios A. & Zuev, Konstantin M., 2021. "Pricing discretely-monitored double barrier options with small probabilities of execution," European Journal of Operational Research, Elsevier, vol. 290(1), pages 313-330.
    14. Min Huang & Guo Luo, 2019. "A simple and efficient numerical method for pricing discretely monitored early-exercise options," Papers 1905.13407, arXiv.org, revised Jun 2019.
    15. Ballestra, Luca Vincenzo & Pacelli, Graziella & Radi, Davide, 2016. "A very efficient approach for pricing barrier options on an underlying described by the mixed fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 240-248.
    16. Ballestra, Luca Vincenzo & Cecere, Liliana, 2016. "A numerical method to estimate the parameters of the CEV model implied by American option prices: Evidence from NYSE," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 100-106.

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