Double-implicit and split two-step Milstein schemes for stochastic differential equations
DOI10.1080/00207160.2015.1081182zbMath1355.65013OpenAlexW2314728264MaRDI QIDQ2958270
Fengze Jiang, Xiaofeng Zong, Chao Yue, Cheng-Ming Huang
Publication date: 1 February 2017
Published in: International Journal of Computer Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207160.2015.1081182
strong convergenceexponential mean square stabilitydouble-implicit Milstein methodsplit two-step Milstein method
Stability and convergence of numerical methods for ordinary differential equations (65L20) Computational methods for stochastic equations (aspects of stochastic analysis) (60H35) Numerical solutions to stochastic differential and integral equations (65C30)
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Cites Work
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- Convergence, nonnegativity and stability of a new Milstein scheme with applications to finance
- Exponential mean square stability of numerical methods for systems of stochastic differential equations
- Theta schemes for SDDEs with non-globally Lipschitz continuous coefficients
- Split-step Milstein methods for multi-channel stiff stochastic differential systems
- Numerical solution of stochastic differential equations with jumps in finance
- A review on stochastic differential equations for applications in hydrology
- A family of fully implicit Milstein methods for stiff stochastic differential equations with multiplicative noise
- Discrete-time approximations of stochastic delay equations: the Milstein scheme.
- Bifurcation theory of functional differential equations
- Mean square stability and dissipativity of two classes of theta methods for systems of stochastic delay differential equations
- Mean-square convergence of stochastic multi-step methods with variable step-size
- Asymptotic mean-square stability of two-step methods for stochastic ordinary differential equations
- Continuous Markov processes and stochastic equations
- An Algorithmic Introduction to Numerical Simulation of Stochastic Differential Equations
- Strong convergence of split-step theta methods for non-autonomous stochastic differential equations
- On Two-step Schemes for SDEs with Small Noise
- Approximate Integration of Stochastic Differential Equations
- Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
- The tamed Milstein method for commutative stochastic differential equations with non-globally Lipschitz continuous coefficients
- Preserving exponential mean square stability and decay rates in two classes of theta approximations of stochastic differential equations
- Multi-Step Maruyama Methods for Stochastic Delay Differential Equations
- Multistep methods for SDEs and their application to problems with small noise
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