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Weak error analysis for strong approximation schemes of SDEs with super-linear coefficients II: finite moments and higher-order schemes
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This paper is the second in a series of works on weak convergence of one-step schemes for solving stochastic differential equations (SDEs) with one-sided Lipschitz conditions. It is known that the super-linear coefficients may lead to a blowup of moments of solutions and numerical solutions and thus affect the convergence of numerical methods. Wang et al. (2023, IMA J. Numer. Anal.) have analyzed weak convergence of one-step numerical schemes when solutions to SDEs have all finite moments. Therein some modified Euler schemes have been discussed about their weak convergence orders. In this work, we explore the effects of limited orders of moments on the weak convergence of a family of explicit schemes. The schemes are based on approximations/modifications of terms in the Ito-Talyor expansion. We provide a systematic but simple way to establish weak convergence orders for these schemes. We present several numerical examples of these schemes and show their weak convergence orders.
Forward citations
Cited by 2 Pith papers
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Euler-type methods for Levy-driven McKean-Vlasov SDEs with super-linear coefficients: mean-square error analysis
A unified family of Euler-type schemes for Lévy-driven McKean-Vlasov SDEs is shown to converge in mean square with L2 order arbitrarily close to 1/2 under super-linear coefficients.
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On modified Euler methods for McKean-Vlasov stochastic differential equations with super-linear coefficients
A general class of modified Euler methods, including tanh and sin Euler schemes, is shown to converge with strong order 1/2 for McKean-Vlasov SDEs with super-linear coefficients.
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