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Euler-Maruyama approximations in mean-revertingstochastic volatility model under regime-switching

机译:机制转换下均值回复随机波动率模型中的Euler-Maruyama近似

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Stochastic differential equations (SDEs) under regime-switchinghave recently been developed to model various financialquantities. In general, SDEs under regime-switching have noexplicit solutions, so numerical methods for approximations havebecome one of the powerful techniques in the valuation offinancial quantities. In this paper, we will concentrate on theEuler-Maruyama (EM) scheme for the typical hybrid mean-revertingθ-process. To overcome the mathematical difficultiesarising from the regime-switching as well as the non-Lipschitzcoefficients, several new techniques have been developed in thispaper which should prove to be very useful in the numericalanalysis of stochastic systems.
机译:政权转换下的随机微分方程(SDE)最近已经被开发出来,可以对各种金融数量进行建模。通常,制度转换下的SDE没有明确的解决方案,因此近似的数值方法已成为评估财务数量的有力技术之一。在本文中,我们将集中于典型的混合均值回复θ过程的Euler-Maruyama(EM)方案。为了克服由状态切换和非Lipschitz系数引起的数学难题,本文开发了几种新技术,这些新技术在随机系统的数值分析中应被证明非常有用。

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