英文标题：
《Pricing path-dependent Bermudan options using Wiener chaos expansion: an
embarrassingly parallel approach》
---
作者：
J\\\'er\\^ome Lelong (DAO)
---
最新提交年份：
2020
---
英文摘要：
In this work, we propose a new policy iteration algorithm for pricing Bermudan options when the payoff process cannot be written as a function of a lifted Markov process. Our approach is based on a modification of the well-known Longstaff Schwartz algorithm, in which we basically replace the standard least square regression by a Wiener chaos expansion. Not only does it allow us to deal with a non Markovian setting, but it also breaks the bottleneck induced by the least square regression as the coefficients of the chaos expansion are given by scalar products on the L^2 space and can therefore be approximated by independent Monte Carlo computations. This key feature enables us to provide an embarrassingly parallel algorithm.
---
中文摘要：
在这项工作中，我们提出了一种新的策略迭代算法，用于在支付过程不能写成提升马尔可夫过程的函数时对百慕大期权进行定价。我们的方法基于著名的Longstaff-Schwartz算法的改进，在该算法中，我们基本上用维纳混沌展开代替标准最小二乘回归。它不仅允许我们处理非马尔可夫环境，而且还打破了最小二乘回归所造成的瓶颈，因为混沌展开系数是由L^2空间上的标量积给出的，因此可以通过独立的蒙特卡罗计算来近似。这个关键特性使我们能够提供一个令人尴尬的并行算法。
---
分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Computational Finance 计算金融学
分类描述：Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法，包括蒙特卡罗，偏微分方程，格子和其他数值方法，并应用于金融建模
--
一级分类：Mathematics 数学
二级分类：Probability 概率
分类描述：Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用：例如中心极限定理，大偏差，随机微分方程，统计力学模型，排队论
--

---
PDF下载：
-->