Anticipating Linear Stochastic Differential Equations with Adapted Coefficients

H. Kuo, Pujan Shrestha, S. Sinha
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引用次数: 5

Abstract

Stochastic differential equations with adapted integrands and initial conditions are well studied within Itô’s theory. However, such a general theory is not known for corresponding equations with anticipation. We use examples to illustrate essential ideas of the Ayed–Kuo integral and techniques for dealing with anticipating stochastic differential equations. We prove the general form of the solution for a class of linear stochastic differential equations with adapted coefficients and anticipating initial condition, which in this case is an analytic function of a Wiener integral. We show that for such equations, the conditional expectation of the solution is not the same as the solution of the corresponding stochastic differential equation with the initial condition as the expectation of the original initial condition. In particular, we show that there is an extra term in the stochastic differential equation, and give the exact form of this term.
预测具有自适应系数的线性随机微分方程
具有自适应积分和初始条件的随机微分方程在Itô的理论中得到了很好的研究。然而,这样的一般理论并不知道与预期相对应的方程。我们用实例来说明阿依德-郭氏积分的基本思想和处理预测随机微分方程的技术。我们证明了一类具有自适应系数和预期初始条件的线性随机微分方程解的一般形式,在这种情况下,解是Wiener积分的解析函数。我们证明了对于这样的方程,解的条件期望与相应的随机微分方程的解的条件期望不相同,初始条件为原始初始条件的期望。特别地,我们证明了随机微分方程中有一个额外的项,并给出了这个项的确切形式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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