In this paper we develop several regression algorithms for solving general stochastic optimal control problems via Monte Carlo. This type of algorithms is particularly useful for problems with a highdimensional state space and complex dependence structure of the underlying Markov process with...

We apply standardized numerical techniques of stochastic optimization (Judd [1998]) to the climate change issue. The model captures the feature that the effects of uncertainty are different with different levels of agent's risk aversion. A major finding is that the effects of stochasticity...

Banks should evaluate whether a borrower is likely to default. The author applies several techniques in the extensive mathematical literature of stochastic optimal control/dynamic programming to derive an optimal debt in an environment where there are risks on both the asset and liabilities...