首页> 外文期刊>SIAM Journal on Control and Optimization >STOCHASTIC EQUATIONS WITH DELAY: OPTIMAL CONTROL VIA BSDEs AND REGULAR SOLUTIONS OF HAMILTON-JACOBI-BELLMAN EQUATIONS
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STOCHASTIC EQUATIONS WITH DELAY: OPTIMAL CONTROL VIA BSDEs AND REGULAR SOLUTIONS OF HAMILTON-JACOBI-BELLMAN EQUATIONS

机译:带有延迟的随机方程:通过BSDE和Hamilton-Jacobi-Bellman方程的正则解进行最优控制

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摘要

We consider an Ito stochastic differential equation with delay, driven by Brownian motion, whose solution, by an appropriate reformulation, defines a Markov process X with values in a space of continuous functions C, with generator L. We then consider a backward stochastic differential equation depending on X, with unknown processes (Y, Z), and we study properties of the resulting system, in particular we identify the process Z as a deterministic functional of X. We next prove that the forward-backward system provides a suitable solution to a class of parabolic partial differential equations on the space C driven by L, and we apply this result to prove a characterization of the fair price and the hedging strategy for a financial market with memory effects. We also include applications to optimal stochastic control of differential equation with delay: in particular we characterize optimal controls as feedback laws in terms of the process X.
机译:我们考虑一个由布朗运动驱动的具有延迟的Ito随机微分方程,通过适当的公式化,其解通过生成器L定义了一个在连续函数C的空间中具有值的Markov过程X。取决于X,具有未知的过程(Y,Z),并且我们研究所得系统的性质,尤其是将过程Z确定为X的确定性函数。接下来,我们证明前向-后向系统为X提供了合适的解决方案由L驱动的空间C上的一类抛物型偏微分方程,我们应用此结果证明了具有记忆效应的金融市场的公允价格特征和对冲策略。我们还包括具有时滞的微分方程的最优随机控制应用:特别是,我们根据过程X将最优控制表征为反馈定律。

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