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

Michael Reiter

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)1329-1353
Number of pages25
JournalJournal of Economic Dynamics and Control
Volume23
Issue number9-10
DOIs
StatePublished - Sep 1999

Keywords

  • Approximation
  • Dynamic programming
  • Stochastic control

ASJC Scopus subject areas

  • Economics and Econometrics
  • Control and Optimization
  • Applied Mathematics

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