Solving higher-dimensional continuous-time stochastic control problems by value function regression
AbstractThe 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.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Economic Dynamics and Control.
Volume (Year): 23 (1999)
Issue (Month): 9-10 (September)
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Web page: http://www.elsevier.com/locate/jedc
Other versions of this item:
- Michael Reiter, 1997. "Solving higher-dimensional continuous time stochastic control problems by value function regression," Economics Working Papers 299, Department of Economics and Business, Universitat Pompeu Fabra, revised Jun 1998.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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