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On the infinite time horizon approximation for L\'evy-driven McKean-Vlasov SDEs with non-globally Lipschitz continuous and super-linearly growth drift and diffusion coefficients
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This paper studies the numerical approximation for McKean-Vlasov stochastic differential equations driven by L\'evy processes. We propose a tamed-adaptive Euler-Maruyama scheme and consider its strong convergence in both finite and infinite time horizons when applying for some classes of L\'evy-driven McKean-Vlasov stochastic differential equations with non-globally Lipschitz continuous and super-linearly growth drift and diffusion coefficients.
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Cited by 1 Pith paper
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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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