Solving higher-dimensional continuous time stochastic control problems by value function regression


Autoria(s): Reiter, Michael
Contribuinte(s)

Universitat Pompeu Fabra. Departament d'Economia i Empresa

Data(s)

15/09/2005

Resumo

The paper develops a method to solve higher-dimensional stochasticcontrol problems in continuous time. A finite difference typeapproximation scheme is used on a coarse grid of low discrepancypoints, while the value function at intermediate points is obtainedby regression. The stability properties of the method are discussed,and applications are given to test problems of up to 10 dimensions.Accurate solutions to these problems can be obtained on a personalcomputer.

Identificador

http://hdl.handle.net/10230/634

Idioma(s)

eng

Direitos

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info:eu-repo/semantics/openAccess

<a href="http://creativecommons.org/licenses/by-nc-nd/3.0/es/">http://creativecommons.org/licenses/by-nc-nd/3.0/es/</a>

Palavras-Chave #Microeconomics #dynamic programming #stochastic control #approximation
Tipo

info:eu-repo/semantics/workingPaper