Solving higher-dimensional continuous time stochastic control problems by value function regression
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- dc.contributor.author Reiter, Michaelca
- dc.contributor.other Universitat Pompeu Fabra. Departament d'Economia i Empresa
- dc.date.accessioned 2018-02-14T15:30:00Z
- dc.date.available 2018-02-14T15:30:00Z
- dc.date.issued 1997-03-01
- dc.date.modified 2017-07-23T02:03:44Z
- dc.description.abstract The paper develops a method to solve higher-dimensional stochastic control problems in continuous time. A finite difference type approximation scheme is used on a coarse grid of low discrepancy points, while the value function at intermediate points is obtained by 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 personal computer.
- dc.format.mimetype application/pdfca
- dc.identifier https://econ-papers.upf.edu/ca/paper.php?id=299
- dc.identifier.citation Journal of Economic Dynamics and Control, 23, (1999), pp. 1329-53
- dc.identifier.uri http://hdl.handle.net/10230/634
- dc.language.iso eng
- dc.relation.ispartofseries Economics and Business Working Papers Series; 299
- dc.rights L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons
- dc.rights.accessRights info:eu-repo/semantics/openAccess
- dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
- dc.subject.keyword dynamic programming
- dc.subject.keyword stochastic control
- dc.subject.keyword approximation
- dc.subject.keyword Microeconomics
- dc.title Solving higher-dimensional continuous time stochastic control problems by value function regressionca
- dc.type info:eu-repo/semantics/workingPaper