@Article{NMTMA-3-1,
author = {},
title = {The State Equations Methods for Stochastic Control Problems},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2010},
volume = {3},
number = {1},
pages = {79--96},
abstract = {<p style="text-align: justify;">The state equations of stochastic control problems, which are
controlled stochastic differential equations, are proposed to be
discretized by the weak midpoint rule and predictor-corrector
methods for the Markov chain approximation approach. Local
consistency of the methods are proved. Numerical tests on a
simplified Merton&#39;s portfolio model show better simulation to
feedback control rules by these two methods, as compared with the
weak Euler-Maruyama discretisation used by Krawczyk. This suggests a
new approach of improving accuracy of approximating Markov chains
for stochastic control problems.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2009.m99006},
url = {https://global-sci.com/article/90718/the-state-equations-methods-for-stochastic-control-problems}
}