In this paper we develop several regression algorithms for solving general stochastic optimal control problems via … dependence structure of the underlying Markov process with respect to some control. The main idea of the algorithms is to …

We present the regression-based Monte Carlo simulation algorithms for solving the stochastic control models associated … remaining account value will be paid to the beneficiary as a death benefit. The bang-bang control strategy analyzed under the …

-dimensional stochastic control problems without restrictions on the state dynamics, including problems with state variables affected by … control. However, when applied to stochastic control problems in the multiperiod expected utility models, the regression t … transform the value function of stochastic control problems to improve the regression t, and then using either the 'Smearing …

In this paper we develop several regression algorithms for solving general stochastic optimal control problems via … dependence structure of the underlying Markov process with respect to some control. The main idea behind the algorithms is to … investor. -- Optimal stochastic control ; Regression methods ; Convergence analysis. …

-dimensional stochastic control problems, including problems with state variables affected by control. However, when applied to the stochastic … control problems in the multi-period expected utility models, the regression fit tends to contain errors which accumulate over …. We also present and utilise recent improvements in the LSMC algorithms such as control randomisation with policy …