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Multilevel Monte Carlo for stochastic differential equations with additive fractional noise

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  • Peter Kloeden
  • Andreas Neuenkirch
  • Raffaella Pavani

Abstract

We adopt the multilevel Monte Carlo method introduced by M. Giles (Multilevel Monte Carlo path simulation, Oper. Res. 56(3):607–617, 2008 ) to SDEs with additive fractional noise of Hurst parameter H>1/2. For the approximation of a Lipschitz functional of the terminal state of the SDE we construct a multilevel estimator based on the Euler scheme. This estimator achieves a prescribed root mean square error of order ε with a computational effort of order ε −2 . Copyright Springer Science+Business Media, LLC 2011

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  • Peter Kloeden & Andreas Neuenkirch & Raffaella Pavani, 2011. "Multilevel Monte Carlo for stochastic differential equations with additive fractional noise," Annals of Operations Research, Springer, vol. 189(1), pages 255-276, September.
    • Handle: RePEc:spr:annopr:v:189:y:2011:i:1:p:255-276:10.1007/s10479-009-0663-8
    DOI: 10.1007/s10479-009-0663-8
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    References listed on IDEAS

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    Cited by:

    1. 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).
    2. Jan Matas & Jan Posp'iv{s}il, 2021. "On simulation of rough Volterra stochastic volatility models," Papers 2108.01999, arXiv.org, revised Aug 2022.
    3. 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.
    4. Huang, Chuying & Wang, Xu, 2023. "Strong convergence rate of the Euler scheme for SDEs driven by additive rough fractional noises," Statistics & Probability Letters, Elsevier, vol. 194(C).
    5. Mike Giles & Lukasz Szpruch, 2012. "Multilevel Monte Carlo methods for applications in finance," Papers 1212.1377, arXiv.org.
    6. Richard, Alexandre & Tan, Xiaolu & Yang, Fan, 2021. "Discrete-time simulation of Stochastic Volterra equations," Stochastic Processes and their Applications, Elsevier, vol. 141(C), pages 109-138.
    7. Gurjeet Dhesi & Bilal Shakeel & Marcel Ausloos, 2021. "Modelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approach," Annals of Operations Research, Springer, vol. 299(1), pages 1397-1410, April.
    8. Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.
    9. Sun, Qi & Xu, Weijun & Xiao, Weilin, 2013. "An empirical estimation for mean-reverting coal prices with long memory," Economic Modelling, Elsevier, vol. 33(C), pages 174-181.

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