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Strong order one convergence of a drift implicit Euler scheme: Application to the CIR process

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  • Alfonsi, Aurélien

Abstract

We study the convergence of a drift implicit scheme for one-dimensional SDEs that was considered by Alfonsi (2005) for the Cox–Ingersoll–Ross (CIR) process. Under general conditions, we obtain a strong convergence of order 1. In the CIR case, Dereich et al. (2012) have shown recently a strong convergence of order 1/2 for this scheme. Here, we obtain a strong convergence of order 1 under more restrictive assumptions on the CIR parameters.

Suggested Citation

  • Alfonsi, Aurélien, 2013. "Strong order one convergence of a drift implicit Euler scheme: Application to the CIR process," Statistics & Probability Letters, Elsevier, vol. 83(2), pages 602-607.
  • Handle: RePEc:eee:stapro:v:83:y:2013:i:2:p:602-607
    DOI: 10.1016/j.spl.2012.10.034
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    References listed on IDEAS

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    1. Detemple, Jerome & Garcia, Rene & Rindisbacher, Marcel, 2006. "Asymptotic properties of Monte Carlo estimators of diffusion processes," Journal of Econometrics, Elsevier, vol. 134(1), pages 1-68, September.
    2. Alfonsi Aurélien, 2005. "On the discretization schemes for the CIR (and Bessel squared) processes," Monte Carlo Methods and Applications, De Gruyter, vol. 11(4), pages 355-384, December.
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    Citations

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    Cited by:

    1. Mario Hefter & Arnulf Jentzen, 2019. "On arbitrarily slow convergence rates for strong numerical approximations of Cox–Ingersoll–Ross processes and squared Bessel processes," Finance and Stochastics, Springer, vol. 23(1), pages 139-172, January.
    2. Antoine Jacquier & Emma R. Malone & Mugad Oumgari, 2019. "Stacked Monte Carlo for option pricing," Papers 1903.10795, arXiv.org.
    3. Andrei Cozma & Christoph Reisinger, 2017. "Strong convergence rates for Euler approximations to a class of stochastic path-dependent volatility models," Papers 1706.07375, arXiv.org, revised Oct 2018.
    4. Hong, Jialin & Huang, Chuying & Kamrani, Minoo & Wang, Xu, 2020. "Optimal strong convergence rate of a backward Euler type scheme for the Cox–Ingersoll–Ross model driven by fractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 130(5), pages 2675-2692.
    5. C'onall Kelly & Gabriel J. Lord, 2021. "An adaptive splitting method for the Cox-Ingersoll-Ross process," Papers 2112.09465, arXiv.org, revised Feb 2023.
    6. Halidias Nikolaos, 2015. "Constructing positivity preserving numerical schemes for the two-factor CIR model," Monte Carlo Methods and Applications, De Gruyter, vol. 21(4), pages 313-323, December.
    7. Umut Çetin & Julien Hok, 2024. "Speeding up the Euler scheme for killed diffusions," Finance and Stochastics, Springer, vol. 28(3), pages 663-707, July.
    8. Ngo, Hoang Long & Luong, Duc Trong, 2019. "Tamed Euler–Maruyama approximation for stochastic differential equations with locally Hölder continuous diffusion coefficients," Statistics & Probability Letters, Elsevier, vol. 145(C), pages 133-140.
    9. Kęstutis Kubilius & Aidas Medžiūnas, 2022. "Pathwise Convergent Approximation for the Fractional SDEs," Mathematics, MDPI, vol. 10(4), pages 1-16, February.
    10. Kęstutis Kubilius & Aidas Medžiūnas, 2020. "Positive Solutions of the Fractional SDEs with Non-Lipschitz Diffusion Coefficient," Mathematics, MDPI, vol. 9(1), pages 1-14, December.
    11. Andrei Cozma & Christoph Reisinger, 2015. "Exponential integrability properties of Euler discretization schemes for the Cox-Ingersoll-Ross process," Papers 1601.00919, arXiv.org.
    12. Andrei Cozma & Christoph Reisinger, 2017. "Strong order 1/2 convergence of full truncation Euler approximations to the Cox-Ingersoll-Ross process," Papers 1704.07321, arXiv.org, revised Oct 2018.
    13. Jean-Francois Chassagneux & Antoine Jacquier & Ivo Mihaylov, 2014. "An explicit Euler scheme with strong rate of convergence for financial SDEs with non-Lipschitz coefficients," Papers 1405.3561, arXiv.org, revised Apr 2016.
    14. Gadat, Sébastien & Costa, Manon & Huang, Lorick, 2022. "CV@R penalized portfolio optimization with biased stochastic mirror descent," TSE Working Papers 22-1342, Toulouse School of Economics (TSE), revised Nov 2023.
    15. Halidias Nikolaos, 2015. "A new numerical scheme for the CIR process," Monte Carlo Methods and Applications, De Gruyter, vol. 21(3), pages 245-253, September.
    16. Mouna Ben Derouich & Ahmed Kebaier, 2022. "Interpolated Drift Implicit Euler MLMC Method for Barrier Option Pricing and application to CIR and CEV Models," Papers 2210.00779, arXiv.org, revised Sep 2024.
    17. Cetin, Umut & Hok, Julien, 2024. "Speeding up the Euler scheme for killed diffusions," LSE Research Online Documents on Economics 120789, London School of Economics and Political Science, LSE Library.
    18. Nikolaos Halidias & Ioannis Stamatiou, 2015. "Approximating explicitly the mean reverting CEV process," Papers 1502.03018, arXiv.org, revised May 2015.
    19. Gao, Xiangyu & Wang, Jianqiao & Wang, Yanxia & Yang, Hongfu, 2022. "The truncated Euler–Maruyama method for CIR model driven by fractional Brownian motion," Statistics & Probability Letters, Elsevier, vol. 189(C).

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