论文标题
最佳与树木停下来：细节
Optimal Stopping with Trees: The Details
论文作者
论文摘要
本文的目的是首先要回顾S. Becker，P。Cheridito和P. Jentzen引入的最新方法，用于解决使用深层神经网络的高维度最佳停止问题，其次，提出了一种替代算法，通过手机替换神经网络，从而可以对估计的停止规则进行更多的解释。我们特别比较了两种算法相对于Bermudan Max-Call基准测试示例的性能，得出结论，Bermudan Max-call可能不适合作为高维最佳停止问题的基准示例。我们还展示了如何使用算法来绘制停止边界。
The purpose of this paper is two-fold, first, to review a recent method introduced by S. Becker, P. Cheridito, and P. Jentzen, for solving high-dimensional optimal stopping problems using deep Neural Networks, second, to propose an alternative algorithm replacing Neural Networks by CART-trees which allow for more interpretation of the estimated stopping rules. We in particular compare the performance of the two algorithms with respect to the Bermudan max-call benchmark example concluding that the Bermudan max-call may not be suitable to serve as a benchmark example for high-dimensional optimal stopping problems. We also show how our algorithm can be used to plot stopping boundaries.
