The Euler scheme is one of the standard schemes to obtain numerical approximations of stochastic differential equations (SDEs). Its convergence properties are well-known in the case of globally Lipschitz continuous coefficients. However, in many situations, relevant systems do not show a smooth behavior, which results in SDE models with discontinuous drift coefficient. In this work, we will analyze the long time properties of the Euler scheme applied to SDEs with a piecewise constant drift and a constant diffusion coefficient and carry out intensive numerical tests for its convergence properties. We will emphasize on numerical convergence rates and analyze how they depend on properties of the drift coefficient and the initial value. We will...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
The Euler scheme is a well-known method of approximation of solutions of stochastic differential equ...
We are interested in the time discretization of stochastic differential equations with additive d-di...
The Euler scheme is one of the standard schemes to obtain numerical approximations of stochastic dif...
The Euler scheme is one of the standard schemes to obtain numerical approximations of solutions of s...
Abstract: Stochastic differential equations provide a useful means of intro-ducing stochasticity int...
In this paper, we investigate the weak convergence rate of Euler-Maruyama’s approximation for stocha...
AbstractWe prove that, under appropriate conditions, the sequence of approximate solutions construct...
The Euler-Maruyama method is applied to a simple stochastic differential equation (SDE) with discont...
AbstractIn this paper, we are concerned with the numerical approximation of stochastic differential ...
We provide a rate for the strong convergence of Euler approximations for stochastic differential equ...
We consider one-dimensional stochastic differential equations in the particular case of diffusion c...
Beyn W-J, Isaak E, Kruse R. Stochastic C-Stability and B-Consistency of Explicit and Implicit Euler-...
Weak convergence of the Euler scheme for stochastic differential equations is established when coeff...
In the present paper, we first deal with the discretization of stochastic differential equ...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
The Euler scheme is a well-known method of approximation of solutions of stochastic differential equ...
We are interested in the time discretization of stochastic differential equations with additive d-di...
The Euler scheme is one of the standard schemes to obtain numerical approximations of stochastic dif...
The Euler scheme is one of the standard schemes to obtain numerical approximations of solutions of s...
Abstract: Stochastic differential equations provide a useful means of intro-ducing stochasticity int...
In this paper, we investigate the weak convergence rate of Euler-Maruyama’s approximation for stocha...
AbstractWe prove that, under appropriate conditions, the sequence of approximate solutions construct...
The Euler-Maruyama method is applied to a simple stochastic differential equation (SDE) with discont...
AbstractIn this paper, we are concerned with the numerical approximation of stochastic differential ...
We provide a rate for the strong convergence of Euler approximations for stochastic differential equ...
We consider one-dimensional stochastic differential equations in the particular case of diffusion c...
Beyn W-J, Isaak E, Kruse R. Stochastic C-Stability and B-Consistency of Explicit and Implicit Euler-...
Weak convergence of the Euler scheme for stochastic differential equations is established when coeff...
In the present paper, we first deal with the discretization of stochastic differential equ...
Traditional finite-time convergence theory for numerical methods applied to stochastic differential ...
The Euler scheme is a well-known method of approximation of solutions of stochastic differential equ...
We are interested in the time discretization of stochastic differential equations with additive d-di...