Barycentric rational collocation-based IMEX-BDF2 scheme for option pricing under jump-diffusion models

Wei Zhang , Hu Li

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (10) : 7299 -7329.

PDF (1595KB)
Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (10) :7299 -7329. DOI: 10.3934/era.2026316
Research article
research-article
Barycentric rational collocation-based IMEX-BDF2 scheme for option pricing under jump-diffusion models
Author information +
History +
PDF (1595KB)

Abstract

Jump-diffusion models, such as Merton’s and Kou’s models, are essential in option pricing for capturing the discontinuous jump characteristics of asset prices. However, the nonlocal integral term in the resulting partial integro-differential equation (PIDE) presents substantial numerical challenges. This paper proposes an efficient and high-order numerical framework for pricing European and American options under these models. We employ the barycentric rational interpolation (BRI) collocation method for spatial discretization to achieve high-order accuracy and ensure numerical stability. For temporal discretization, the second-order implicit–explicit backward differentiation formula (IMEX- BDF2) is utilized, and the nonlocal integral term is evaluated via the Gauss–Legendre quadrature. To handle the early exercise constraint of American options, the operator splitting method is integrated into the framework. A rigorous error estimation and convergence analysis are provided to establish the mathematical reliability of the scheme. Numerical experiments demonstrate that the proposed method is highly efficient, providing accurate estimates for option values and stable numerical approximations for their Greeks (delta and gamma), validating its effectiveness for solving PIDEs in financial engineering.

Keywords

jump-diffusion models / barycentric rational interpolation / IMEX-BDF2 scheme / operator splitting method / Gauss–Legendre quadrature / option pricing

Cite this article

Download citation ▾
Wei Zhang, Hu Li. Barycentric rational collocation-based IMEX-BDF2 scheme for option pricing under jump-diffusion models. Electronic Research Archive, 2026, 34 (10) : 7299-7329 DOI:10.3934/era.2026316

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

R. C. Merton, Option pricing when underlying stock returns are discontinuous, J. Financ. Econ., 3 (1976), 125-144. https://doi.org/10.1016/0304-405X(76)90022-2

[2]

S. G. Kou, A jump-diffusion model for option pricing, Manage. Sci., 48 (2002), 1086-1101.

[3]

K. Zhang, S. Wang, Pricing options under jump diffusion processes with fitted finite volume method, Appl. Math. Comput., 201 (2008), 398-413. https://doi.org/10.1016/j.amc.2007.12.043

[4]

W. S. Wang, M. L. Mao, X. Jiang, L. H. Wang, High order semi-imex BDF schemes for nonlinear partial integro-differential equations arising in finance, ESAIM: M2AN, 59 (2025), 643-670. https://doi.org/10.1051/m2an/2025003

[5]

R. Company, V. N. Egorova, L. Jódar, A front-fixing etd numerical method for solving jump-diffusion American option pricing problems, Math. Comput. Simul., 189 (2021), 69-84. https://doi.org/10.1016/j.matcom.2020.07.015

[6]

W. S. Wang, M. Mao, Z. Wang, An efficient variable step-size method for options pricing under jump-diffusion models with nonsmooth payofffunction, ESAIM: M2AN, 55 (2021), 913-938. https://doi.org/10.1051/m2an/2021012

[7]

W. S. Wang, Y. Z. Chen, H. Fang, On the variable two-step IMEX BDF method for parabolic integro-differential equations with nonsmooth initial data arising in finance, SIAM J. Numer. Anal., 57 (2019), 1289-1317. https://doi.org/10.1137/18M1194328

[8]

C. C. Christara, N. C. H. Leung, Option pricing in jump diffusion models with quadratic spline collocation, Appl. Math. Comput., 279 (2016), 28-42. https://doi.org/10.1016/j.amc.2015.12.045

[9]

M. Shirzadi, M. Dehghan, A. F. Bastani, Optimal uniform error estimates for moving least-squares collocation with application to option pricing under jump-diffusion processes, Numer. Methods Partial Differ. Equations, 37 (2021), 98-117. https://doi.org/10.1002/num.22520

[10]

R. Cont, E. Voltchkova, A finite difference scheme for option pricing in jump diffusion and exponential Lévy models, SIAM J. Numer. Anal., 43 (2005), 1596-1626.

[11]

S. Salmia, J. Toivanen, An iterative method for pricing American options under jump-diffusion models, Appl. Numer. Math., 61 (2011), 821-831. https://doi.org/10.1016/j.apnum.2011.02.002

[12]

A. Ebrahimijahan, M. Dehghan, M. Abbaszadeh, A reduced-order model based on integrated radial basis functions with partition of unity method for option pricing under jump-diffusion models, Eng. Anal. Boundary Elem., 155 (2023), 48-61. https://doi.org/10.1016/j.enganabound.2023.05.032

[13]

M. Haghi, R. Mollapourasl, M. Vanmaele, An RBF-FD method for pricing American options under jump-diffusion models, Comput. Math. Appl., 76 (2018), 2434-2459. https://doi.org/10.1016/j.camwa.2018.08.040

[14]

M. K. Kadalbajoo, L. P. Tripathi, A. Kumar, Second order accurate IMEX methods for option pricing under Merton and Kou jump-diffusion models, J. Sci. Comput., 65 (2015), 979-1024. https://doi.org/10.1007/s10915-015-0001-z

[15]

Y. Z. Chen, W. S. Wang, A. G. Xiao, An efficient algorithm for options under Merton’s jump-diffusion model on nonuniform grids, Comput. Econ., 53 (2019), 1565-1591. https://doi.org/10.1007/s10614-018-9823-8

[16]

J. Toivanen, Numerical valuation of European and American options under Kou’s jump-diffusion model, SIAM J. Sci. Comput., 30 (2008), 1949-1970. https://doi.org/10.1137/060674697

[17]

L. Boen, K. J. In’t Hout, Operator splitting schemes for American options under the two-asset Merton jump-diffusion model, Appl. Numer. Math., 153 (2020), 114-131. https://doi.org/10.1016/j.apnum.2020.02.004

[18]

S. Ikonen, J. Toivanen, Operator splitting methods for pricing American put options under stochastic volatility, Numer. Math., 113 (2009), 299-324. https://doi.org/10.1007/s00211-009-0227-5

[19]

V. Maurya, A. Singh, V. S. Yadav, M. K. Rajpoot, Efficient pricing of options in jump-diffusion models: Novel implicit-explicit methods for numerical valuation, Math. Comput. Simul., 217 (2024), 202-225. https://doi.org/10.1016/j.matcom.2023.10.025

[20]

P. A. Forsyth, K. R. Vetzal, Quadratic convergence for valuing American options using a penalty method, SIAM J. Sci. Comput., 23 (2002), 2095-2122. https://doi.org/10.1137/S1064827500382324

[21]

R. Zvan, P. A. Forsyth, K. R. Vetzal, Penalty methods for American options with stochastic volatility, J. Comput. Appl. Math., 91 (1998), 199-218. https://doi.org/10.1016/S0377-0427(98)00037-5

[22]

J. P. Berrut, R. Baltensperger, The linear rational pseudospectral method for boundary value problems, BIT Numer. Math., 41 (2001), 868-879. https://doi.org/10.1023/A:1021916623407

[23]

R. Baltensperger, J. P. Berrut, The linear rational collocation method, J. Comput. Appl. Math., 134 (2001), 243-258. https://doi.org/10.1016/S0377-0427(00)00552-5

[24]

J. Li, J. Z. Qu, Barycentric lagrange interpolation collocation method for solving the Sine-Gordon equation, Wave Motion, 120 (2023), 103159. https://doi.org/10.1016/j.wavemoti.2023.103159

[25]

R. Jiwari, Barycentric rational interpolation and local radial basis functions based numerical algorithms for multidimensional Sine-Gordon equation, Numer. Methods Partial Differ. Equations, 37 (2021), 1965-1992. https://doi.org/10.1002/num.22636

[26]

Y. F. Deng, Z. F. Weng, Barycentric interpolation collocation method based on Crank-Nicolson scheme for the Allen-Cahn equation, AIMS Math., 6 (2021), 3857-3873. https://doi.org/10.3934/math.2021229

[27]

O. Oruç, Two meshless methods based on local radial basis function and barycentric rational interpolation for solving 2D viscoelastic wave equation, Comput. Math. Appl., 79 (2020), 3272-3288. https://doi.org/10.1016/j.camwa.2020.01.025

[28]

T. Liu, H. Y. Liu, Y. Y. Ma, Approximate solution of a kind of time-fractional evolution equations based on fast L1 formula and barycentric Lagrange interpolation, Fractal Fract., 8 (2024), 48. https://doi.org/10.3390/fractalfract8110675

[29]

A. Almendral, C. W. Oosterlee, Numerical valuation of options with jumps in the underlying, Appl. Numer. Math., 53 (2005), 1-18. https://doi.org/10.1016/j.apnum.2004.08.037

[30]

M. S. Floater, K. Hormann, Barycentric rational interpolation with no poles and high rates of approximation, Numer. Math., 107 (2007), 315-331. https://doi.org/10.1007/s00211-007-0093-y

[31]

G. Klein, J. P. Berrut, Linear rational finite differences from derivatives of barycentric rational interpolants, SIAM J. Numer. Anal., 50 (2012), 643-656. https://www.jstor.org/stable/41582753

[32]

J. P. Berrut, M. S. Floater, G. Klein, Convergence rates of derivatives of a family of barycentric rational interpolants, Appl. Numer. Math., 61 (2011), 989-1000. https://doi.org/10.1016/j.apnum.2011.05.001

[33]

M. Costabile, A. Leccadito, I. Massabó, E. Russo, Option pricing under regime-switching jump-diffusion models, J. Comput. Appl. Math., 256 (2014), 152-167. https://doi.org/10.1016/j.cam.2013.07.046

[34]

R. Yadav, D. K. Yadav, A. Kumar, RBF based some implicit-explicit finite difference schemes for pricing option under extended jump-diffusion model, Eng. Anal. Boundary Elem., 156 (2023), 392-406. https://doi.org/10.1016/j.enganabound.2023.08.021

[35]

M. K. Kadalbajoo, A. Kumar, L. P. Tripathi, A radial basis function based implicit-explicit method for option pricing under jump-diffusion models, Appl. Numer. Math., 110 (2016), 159-173. https://doi.org/10.1016/j.apnum.2016.08.006

[36]

J. G. Heywood, R. Rannacher, Finite-element approximation of the nonstationary Navier-Stokes problem part IV: error analysis for second-order time discretization, SIAM J. Numer. Anal., 27 (1990), 353-384.

[37]

J. Shen, On error estimates of the projection methods for the Navier-Stokes equations: second-order schemes, Math. Comput., 65 (1996), 1039-1066.

[38]

C. Canuto, M. Y. Hussaini, A. Quarteroni, T. A. Zang, Spectral Methods: Fundamentals in Single Domains , Berlin, Germany: Springer, 2006. https://doi.org/10.1007/978-3-540-30726-6

[39]

S. Ikonen, J. Toivanen, Operator splitting methods for American option pricing, Appl. Math. Lett., 17 (2004), 809-814. https://doi.org/10.1016/j.aml.2004.06.010

[40]

Y. Kwon, Y. Lee, A second-order finite difference method for option pricing under jump-diffusion models, SIAM J. Numer. Anal., 49 (2011), 2598-2617. https://doi.org/10.1137/090777529

[41]

Y. Kwon, Y. Lee, A second-order tridiagonal method for American options under jump-diffusion models, SIAM J. Sci. Comput., 33 (2011), 1860-1872. https://doi.org/10.1137/100806552

[42]

J. Toivanen, A high-order front-tracking finite difference method for pricing American options under jump-diffusion models, J. Comput. Finance, 13 (2010), 61-79. https://doi.org/10.21314/JCF.2010.222

PDF (1595KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/

〈 〉