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Xiaojie Wang - One of the best experts on this subject based on the ideXlab platform.

  • On the backward Euler Method for a generalized Ait-Sahalia-type rate model with Poisson jumps
    Numerical Algorithms, 2020
    Co-Authors: Yuying Zhao, Xiaojie Wang, Mengchao Wang
    Abstract:

    This article aims to reveal the mean-square convergence rate of the backward Euler Method (BEM) for a generalized Ait-Sahalia interest rate model with Poisson jumps. The main difficulty in the analysis is caused by the non-globally Lipschitz drift and diffusion coefficients of the model. We show that the BEM preserves the positivity of the original problem. Furthermore, we successfully recover the mean-square convergence rate of order one-half for the BEM. The theoretical findings are accompanied by several numerical examples.

  • On the backward Euler Method for a generalized Ait-Sahalia-type rate model with Poisson jumps.
    arXiv: Numerical Analysis, 2020
    Co-Authors: Yuying Zhao, Xiaojie Wang, Mengchao Wang
    Abstract:

    This article aims to reveal the mean-square convergence rate of the backward Euler Method (BEM) for a generalized Ait-Sahaliz interest rate model with Poisson jumps. The main difficulty in the analysis is caused by the non-globally Lipschitz drift and diffusion coefficients of the model. We show that the BEM preserves positivity of the original problem. Furthermore, we successfully recover the mean-square convergence rate of order one-half for the BEM. The theoretical findings are accompanied by several numerical examples.

  • A transformed jump-adapted backward Euler Method for jump-extended CIR and CEV models
    Numerical Algorithms, 2016
    Co-Authors: Xu Yang, Xiaojie Wang
    Abstract:

    A novel time-stepping scheme, called transformed jump-adapted backward Euler Method, is developed in this paper to simulate a class of jump-extended CIR and CEV models. The proposed scheme is able to preserve the positivity of the underlying problems. Furthermore, its strong convergence rate of order one is recovered for the considered models with non-Lipschitz diffusion coefficients. Numerical examples are finally reported to confirm our theoretical findings.

  • a note on an accelerated exponential Euler Method for parabolic spdes with additive noise
    Applied Mathematics Letters, 2015
    Co-Authors: Xiaojie Wang, Ruisheng Qi
    Abstract:

    Abstract This note aims to present further results on the accelerated exponential Euler Method proposed in Jentzen & Kloeden (2009). In contrast to very restrictive assumptions made there, we reformulate appropriate conditions on the drift coefficient of SPDEs to include a large class of nonlinear Nemytskii operators. In our setting, the Method achieves the convergence order in time of 1 2 − ϵ for arbitrarily small ϵ > 0 in the case of space–time white noise. For the trace-class noise case, multiple spatial dimensions are allowed and an optimal convergence rate is attained based on optimal regularity results of the mild solution, which improves the corresponding convergence results in Jentzen et al. (2011).

  • a note on an accelerated exponential Euler Method for parabolic spdes with additive noise
    Applied Mathematics Letters, 2015
    Co-Authors: Xiaojie Wang
    Abstract:

    Abstract This note aims to present further results on the accelerated exponential Euler Method proposed in Jentzen & Kloeden (2009). In contrast to very restrictive assumptions made there, we reformulate appropriate conditions on the drift coefficient of SPDEs to include a large class of nonlinear Nemytskii operators. In our setting, the Method achieves the convergence order in time of 1 2 − ϵ for arbitrarily small ϵ > 0 in the case of space–time white noise. For the trace-class noise case, multiple spatial dimensions are allowed and an optimal convergence rate is attained based on optimal regularity results of the mild solution, which improves the corresponding convergence results in Jentzen et al. (2011).

Alexander Aleksandrov - One of the best experts on this subject based on the ideXlab platform.

Chiping Zhang - One of the best experts on this subject based on the ideXlab platform.

Mengchao Wang - One of the best experts on this subject based on the ideXlab platform.

Denis Efimov - One of the best experts on this subject based on the ideXlab platform.