Advanced Simulation-Based Methods for Optimal Stopping and Control

This is an advanced guide to optimal stopping and control, focusing on advanced Monte Carlo simulation and its application to finance. Written for quantitative finance practitioners and researchers in academia, the book looks at the classical simulation based algorithms before introducing some of the new, cutting edge approaches under development.

Dr. John Schoenmakers (Berlin, Germany) is Deputy head of the Stochastic Algorithms and Nonparametric statistics research group at the Weierstrass Institute for Applied Analysis and Stochastics. His fields of interest include advanced modeling of equity and interest rate term structures, pricing and structuring of high dimensional callable derivatives, and general risk measures, stochastic modeling, Monte Carlo methods and many more. He has held the position of Visiting Professor at HU Berlin, and is on the editorial board of the Journal of Computational Finance, Monte Carlo Methods and its Applications, and International Journal of Portfolio Analysis and Management.
Dr. Denis Belomestny (Duisburg, Germany) is Senior Researcher at Weierstrass Institute for Applied Analysis and Stochastics, where he works on the Statistical Data Analysis and Applied Mathematical Finance project. Previously, he was a researcher at the Institute for Applied Mathematics at Bonn University. His research interests include nonparametric statistics, stochastic processes and financial mathematics, and his research is published in a number of peer reviewed publications.