Display Abstract

Title Optimal stopping for diffusions via sieve empirical minimization: convergence and complexity

Name Denis Belomestny
Country Germany
Email denis.belomestny@uni-due.de
Co-Author(s)
Submit Time 2014-02-19 15:42:52
Session
Special Session 80: Theory, numerical methods, and applications of stochastic systems and SDEs/SPDEs
Contents
In this talk I present a new approach towards solving optimal stopping problems for multidimensional diffusion with Monte Carlo. The approach is based on the dual representation for the solution of optimal stopping problems and uses martingale sieves to numerically solve the dual optimization problem. I analyze the complexity of the proposed algorithm and prove its convergence.