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Semitractability of optimal stopping problems via a weighted stochastic mesh algorithm

机译:通过加权随机网格算法最佳停止问题的半衰题

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摘要

In this paper, we propose a Weighted Stochastic Mesh (WSM) algorithm for approximating the value of discrete- and continuous-time optimal stopping problems. In this context, we consider tractability of such problems via a useful notion of semitractability and the introduction of a tractability index for a particular numerical solution algorithm. It is shown that in the discrete-time case the WSM algorithm leads to semitractability of the corresponding optimal stopping problem in the sense that its complexity is bounded in order by epsilon-4logd+2(1/epsilon) with d being the dimension of the underlying Markov chain. Furthermore, we study the WSM approach in the context of continuous-time optimal stopping problems and derive the corresponding complexity bounds. Although we cannot prove semitractability in this case, our bounds turn out to be the tightest ones among the complexity bounds known in the literature. We illustrate our theoretical findings by a numerical example.
机译:在本文中,我们提出了一种加权随机网格(WSM)算法,用于近似离散和连续时间最佳停止问题的值。在这种情况下,我们通过对特定数值解决方案算法的有用概念和引入途径指数的有用概念来考虑这些问题的易释放性。结果表明,在离散时间案例中,WSM算法在其复杂性按顺序界定的意义上导致相应的最佳停止问题的半曲线性,其具有D为D为D的尺寸底层马尔可夫链条。此外,我们在连续时间最佳停止问题的背景下研究WSM方法,并导出相应的复杂性范围。虽然我们在这种情况下不能证明半乳裂性,但我们的界限在文献中已知的复杂性范围内成为最紧密的。我们通过数值例子说明了我们的理论发现。

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