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 InfoPaper provided by Department of Economics and Business, Universitat Pompeu Fabra in its series Economics Working Papers with number 299.
Date of creation: Mar 1997
Date of revision: Jun 1998
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Web page: http://www.econ.upf.edu/
Dynamic Programming; stochastic control; approximation;
Other versions of this item:
- Reiter, Michael, 1999. "Solving higher-dimensional continuous-time stochastic control problems by value function regression," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1329-1353, September.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
This paper has been announced in the following NEP Reports:
- NEP-ALL-1998-09-14 (All new papers)
- NEP-DGE-1998-09-14 (Dynamic General Equilibrium)
- NEP-ECM-1998-09-14 (Econometrics)
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