随机控制问题的对偶算法:在不确定波动模型和CVA中的应用

ERN: Other Econometric Modeling: Derivatives (Topic) Pub Date : 2015-04-23 DOI:10.2139/ssrn.2598529

P. Henry-Labordère, C. Litterer, Zhenjie Ren

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引用次数: 5

摘要

我们在Rogers [SIAM J. Control Optim]的精神下推导了一个算法。， 46(2007)，第1116—1132页)和Davis和Burstein[《随机统计学》，第40(1992)，第203—256页]，这导致了随机控制问题的上界。我们的边界补充了Guyon和Henry-Labordere最近得到的低偏估计[J]。第一版。金融，14 (2011)，pp. 37—71。我们在数学金融的激励下用数值例子来评估我们的估计。

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A Dual Algorithm for Stochastic Control Problems: Applications to Uncertain Volatility Models and CVA

We derive an algorithm in the spirit of Rogers [SIAM J. Control Optim., 46 (2007), pp. 1116--1132] and Davis and Burstein [Stochastics Stochastics Rep., 40 (1992), pp. 203--256] that leads to upper bounds for stochastic control problems. Our bounds complement lower biased estimates recently obtained in Guyon and Henry-Labordere [J. Comput. Finance, 14 (2011), pp. 37--71]. We evaluate our estimates in numerical examples motivated by mathematical finance.

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ERN: Other Econometric Modeling: Derivatives (Topic)

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