Dynamic programming and its application in economics and finance

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Abstract/Contents

Abstract
Multistage decision problems are numerically challenging. Typically the work to solve such problems is an exponential function with respect to both the number of stages and the number of decision parameters. The problems have been researched extensively and a wide variety of methods to solve them have been proposed. Inevitably all methods are limited in the size of problem they can solve. The purpose of our work is to develop a new more efficient algorithm and one that can run on parallel architectures, thereby extending significantly the size of problems that are tractable. We present a numerical dynamic programming algorithm that has three components: optimization, approximation, and integration. A key feature of the approximation methods we use is to preserve mathematical features such as convexity and differentiability, which enables us to use powerful optimization methods. To illustrate the efficiency of the new method we present extensive results on optimal growth models and dynamic portfolio problems, using our implementation of the algorithm on the Condor Master-Worker system.

Description

Type of resource text
Form electronic; electronic resource; remote
Extent 1 online resource.
Copyright date 2010
Publication date 2009, c2010; 2009
Issuance monographic
Language English

Creators/Contributors

Associated with Cai Yongyang
Associated with Stanford University, Institute for Computational and Mathematical Engineering.
Primary advisor Judd, Kenneth L
Primary advisor Murray, Walter
Thesis advisor Judd, Kenneth L
Thesis advisor Murray, Walter
Thesis advisor Saunders, Michael A
Advisor Saunders, Michael A

Subjects

Genre Theses

Bibliographic information

Statement of responsibility Cai Yongyang.
Note Submitted to the Institute for Computational and Mathematical Engineering.
Thesis Thesis (Ph.D.)--Stanford University, 2010.
Location electronic resource

Access conditions

Copyright
© 2010 by Cai Yongyang

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