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Optimal stopping with information constraint

机译:有信息约束的最佳停车

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摘要

We study the optimal stopping problem proposed by Dupuis and Wang (Adv. Appl. Probab. 34:141-157, 2002). In this maximization problem of the expected present value of the exercise payoff, the underlying dynamics follow a linear diffusion. The decision maker is not allowed to stop at any time she chooses but rather on the jump times of an independent Poisson process. Dupuis and Wang (Adv. Appl. Probab. 34:141-157, 2002), solve this problem in the case where the underlying is a geometric Brownian motion and the payoff function is of American call option type. In the current study, we propose a mild set of conditions (covering the setup of Dupuis and Wang in Adv. Appl. Probab. 34:141-157, 2002) on both the underlying and the payoff and build and use a Markovian apparatus based on the Bellman principle of optimality to solve the problem under these conditions. We also discuss the interpretation of this model as optimal timing of an irreversible investment decision under an exogenous information constraint.
机译:我们研究了Dupuis和Wang提出的最佳停车问题(Adv。Appl。Probab。34:141-157,2002)。在运动收益的预期现值的最大化问题中,潜在的动力学遵循线性扩散。决策者不允许在她选择的任何时候停止,而要在独立的Poisson过程的跳跃时间内停止。 Dupuis和Wang(Adv。Appl。Probab。34:141-157,2002)在底层为几何布朗运动且收益函数为美国看涨期权类型的情况下解决了此问题。在当前的研究中,我们提出了基础和收益方面的温和的条件集(包括Adv。Appl。Probab。34:141-157中Dupuis和Wang的设置),并建立并使用了基于基于贝尔曼最优原理来解决这些条件下的问题。我们还将讨论该模型的解释,作为在外源信息约束下不可逆投资决策的最佳时机。

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