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Solving higher-dimensional continuous time stochastic control problems by value function regression
Reiter, Michael
Universitat Pompeu Fabra. Departament d'Economia i Empresa
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.
dynamic programming
stochastic control
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