英文标题：
《Parallel American Monte Carlo》
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作者：
Calypso Herrera and Louis Paulot
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最新提交年份：
2014
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英文摘要：
In this paper we introduce a new algorithm for American Monte Carlo that can be used either for American-style options, callable structured products or for computing counterparty credit risk (e.g. CVA or PFE computation). Leveraging least squares regressions, the main novel feature of our algorithm is that it can be fully parallelized. Moreover, there is no need to store the paths and the payoff computation can be done forwards: this allows to price structured products with complex path and exercise dependencies. The key idea of our algorithm is to split the set of paths in several subsets which are used iteratively. We give the convergence rate of the algorithm. We illustrate our method on an American put option and compare the results with the Longstaff-Schwartz algorithm.
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中文摘要：
本文介绍了一种新的美式蒙特卡罗算法，该算法既可用于美式期权、可赎回结构性产品，也可用于计算交易对手信用风险（如CVA或PFE计算）。利用最小二乘回归，我们算法的主要新特点是可以完全并行化。此外，不需要存储路径，支付计算可以向前进行：这允许对具有复杂路径的结构化产品进行定价，并执行依赖关系。我们算法的关键思想是将路径集拆分为若干子集，这些子集被迭代使用。我们给出了算法的收敛速度。我们在美式看跌期权上演示了我们的方法，并将结果与Longstaff-Schwartz算法进行了比较。
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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
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一级分类：Quantitative Finance 数量金融学
二级分类：Pricing of Securities 证券定价
分类描述：Valuation and hedging of financial securities, their derivatives, and structured products
金融证券及其衍生产品和结构化产品的估值和套期保值
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