Basic methods for solving optimisation problems in insurance and finance will be described
a short revision of the elements of stochastic analysis as e.g. Ito Integral, Ito's formula and stochastic differential equations; dynamic programming principle, Hamilton-Jacobi-Bellman equation; verification theorems; local time of Brownian motion and singular control theory; examples from actuarial and financial mathematics as e.g. optimal investment problems, minimizing ruin probabilities, etc.; martingal methods in stochastic optimization; introduction into the theory of viscosity solutions
