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arXiv 0901.3082math.PR
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Levy驱动的随机微分方程的模拟与逼近

Simulation and approximation of Levy-driven stochastic differential equations

Nicolas Fournier

摘要:

考虑Levy驱动的随机微分方程的模拟问题。通常不可能模拟列维过程的增量。因此,除了欧拉格式之外,我们还必须近似地模拟这些增量。我们使用的方法,其中大的跳跃是准确模拟,而小的跳跃近似高斯变量。利用Rio关于中心极限定理的一些最新结果,本着Komlos-Major-Tsunady著名论文的精神,我们得到了这个数值格式的强误差估计.当Levy测度在0附近非常奇异时,这种误差仍然是合理的,而忽略小跳跃时情况并非如此。在同样的精神,我们研究的问题的近似Levy驱动的S.D.E.被一个布朗的S.D.E.当Levy过程没有大的跳跃时。

英文摘要:

We consider the problem of the simulation of Levy-driven stochastic differential equations. It is generally impossible to simulate the increments of a Levy-process. Thus in addition to an Euler scheme, we have to simulate approximately these increments. We use a method in which the large jumps are simulated exactly, while the small jumps are approximated by Gaussian variables. Using some recent results of Rio about the central limit theorem, in the spirit of the famous paper by Komlos-Major-Tsunady, we derive an estimate for the strong error of this numerical scheme. This error remains reasonnable when the Levy measure is very singular near 0, which is not the case when neglecting the small jumps. In the same spirit, we study the problem of the approximation of a Levy-driven S.D.E. by a Brownian S.D.E. when the Levy process has no large jumps.

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