This book collects some recent developments in stochastic control theory
with applications to financial mathematics. We first address standard
stochastic control problems from the viewpoint of the recently developed
weak dynamic programming principle. A special emphasis is put on the
regularity issues and, in particular, on the behavior of the value
function near the boundary. We then provide a quick review of the main
tools from viscosity solutions which allow to overcome all regularity
problems. We next address the class of stochastic target problems which
extends in a nontrivial way the standard stochastic control problems.
Here the theory of viscosity solutions plays a crucial role in the
derivation of the dynamic programming equation as the infinitesimal
counterpart of the corresponding geometric dynamic programming equation.
The various developments of this theory have been stimulated by
applications in finance and by relevant connections with geometric
flows. Namely, the second order extension was motivated by illiquidity
modeling, and the controlled loss version was introduced following the
problem of quantile hedging. The third part specializes to an overview
of Backward stochastic differential equations, and their extensions to
the quadratic case.