Adaptive timestepping for pathwise stability and positivity of strongly discretised nonlinear stochastic differential equations

作者：Kelly Conall^*; Rodkina Alexandra; Rapoo Eeva Maria

来源：Journal of Computational and Applied Mathematics, 2018, 334: 39-57.

DOI：10.1016/j.cam.2017.11.027

• Adaptive timestepping
• Euler-Maruyama method
• Locally Lipschitz coefficients
• A.s. stability and instability
• Positivity

We consider the use of adaptive timestepping to allow a strong explicit Euler-Maruyama discretisation to reproduce dynamical properties of a class of nonlinear stochastic differential equations with a unique equilibrium solution and non-negative, non-globally Lipschitz coefficients. Solutions of such equations may display a tendency towards explosive growth, countered by a sufficiently intense and nonlinear diffusion.
We construct an adaptive timestepping strategy which closely reproduces the almost sure (a.s.) asymptotic stability and instability of the equilibrium, and which can ensure the positivity of solutions with arbitrarily high probability. Our analysis adapts the derivation of a discrete form of the Ito formula from Appleby et al. (2009) in order to deal with the lack of independence of the Wiener increments introduced by the adaptivity of the mesh. We also use results on the convergence of certain martingales and semi-martingales which influence the construction of our adaptive timestepping scheme in a way proposed by Liu & Mao (2017).

• 出版日期2018-5-15