Solving Free-boundary Problems with Applications in Finance

K. Muthuraman, Sunil Kumar
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引用次数: 11

Abstract

Stochastic control problems in which there are no bounds on the rate of control reduce to so-called free-boundary problems in partial differential equations (PDEs). In a free-boundary problem the solution of the PDE and the domain over which the PDE must be solved need to be determined simultaneously. Examples of such stochastic control problems are singular control, optimal stopping, and impulse control problems. Application areas of these problems are diverse and include finance, economics, queuing, healthcare, and public policy. In most cases, the free-boundary problem needs to be solved numerically. In this survey, we present a recent computational method that solves these free-boundary problems. The method finds the free-boundary by solving a sequence of fixed-boundary problems. These fixed-boundary problems are relatively easy to solve numerically. We summarize and unify recent results on this moving boundary method, illustrating its application on a set of classical problems, of increasing difficulty, in finance. This survey is intended for those are primarily interested in computing numerical solutions to these problems. To this end, we include actual Matlab code for one of the problems studied, namely, American option pricing.
解决自由边界问题及其在金融中的应用
对控制速率没有限制的随机控制问题可归结为偏微分方程中的自由边界问题。在自由边界问题中,需要同时确定偏微分方程的解和偏微分方程必须求解的区域。这类随机控制问题的例子有奇异控制、最优停止和脉冲控制问题。这些问题的应用领域多种多样,包括金融、经济、排队、医疗保健和公共政策。在大多数情况下,自由边界问题需要用数值方法求解。在这项调查中,我们提出了一种新的计算方法来解决这些自由边界问题。该方法通过求解一系列固定边界问题来寻找自由边界。这些固定边界问题比较容易用数值方法求解。我们总结并统一了这一移动边界方法的最新成果,并举例说明了它在金融领域一系列难度越来越大的经典问题上的应用。这个调查是为那些主要感兴趣的计算数值解决这些问题。为此,我们包含了所研究问题之一的实际Matlab代码,即美式期权定价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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