We provide a comparative analysis of qualitative features of different numerical methods for the inhomogeneous geometric Brownian motion (IGBM). The conditional and asymptotic mean and variance of the IGBM are known and the process can be characterised according to Feller's boundary classification. We compare the frequently used Euler-Maruyama and Milstein methods, two Lie-Trotter and two Strang splitting schemes and two methods based on the ordinary differential equation (ODE) approach, namely the classical Wong-Zakai approximation and the recently proposed log-ODE scheme. First, we prove that, in contrast to the Euler-Maruyama and Milstein schemes, the splitting and ODE schemes preserve the boundary properties of the process, independently of the choice of the time discretisation step. Second, we derive closed-form expressions for the conditional and asymptotic means and variances of all considered schemes and analyse the resulting biases. While the Euler-Maruyama and Milstein schemes are the only methods which may have an asymptotically unbiased mean, the splitting and ODE schemes perform better in terms of variance preservation. The Strang schemes outperform the Lie-Trotter splittings, and the log-ODE scheme the classical ODE method. The mean and variance biases of the log-ODE scheme are very small for many relevant parameter settings. However, in some situations the two derived Strang splittings may be a better alternative, one of them requiring considerably less computational effort than the log-ODE method. The proposed analysis may be carried out in a similar fashion on other numerical methods and stochastic differential equations with comparable features.
翻译:我们比较了不同数字方法的定性特征,这些不同数字方法对于不均匀的布朗运动(IGBM)具有不同的质量特征。已知IGBM的有条件和无损平均值和差异,这一过程可以按照Feller的边界分类来定性。我们比较了常用的Euler-Maruyama和Milstein方法、两个Lie-Trotter和两个Strang分拆办法以及基于普通差异方程(ODE)方法的两种方法,即古典黄崎和最近提议的对数-ODE办法。首先,我们证明,与Euler-Maruyama和Milstein办法不同的是,分裂和对流程的偏差平均值和差异值方案相比,分裂和对流程的边界特性进行了区分。我们比较了经常使用的Euler-Marumayma和Milstein两种方法以及基于普通差异方程(ODE)的办法。虽然EU-Marum和Milstein计划是唯一可能具有不偏向性方法的方法,但在一种不偏向的对数值和正变数方法中,但是,有些对数值的对数值的对数值的对等和正态办法的分析方法进行更好的对等式办法可能比。