Advanced Simulation-Based Methods for Optimal Stopping and Control
With Applications in Finance
1st Edition
Published on 31. January 2018
XVI, 364 pages
978-1-137-03351-2 (ISBN)
Description
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.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Palgrave Macmillan UK
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XVI, 364 p. 14 illus.
File size
5,40 MB
ISBN-13
978-1-137-03351-2 (9781137033512)
DOI
10.1057/978-1-137-03351-2
Schweitzer Classification
Other editions
Additional editions
Denis Belomestny | John Schoenmakers
Advanced Simulation-Based Methods for Optimal Stopping and Control
With Applications in Finance
Book
02/2018
Palgrave Macmillan
€117.69
Shipment within 10-20 days
Persons
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.
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.
Content
1. Introduction 2.- Basics of Monte Carlo methods 3.- Basics of standard optimal stopping, multiple stopping, and optimal control problem 4.- Dual representations for standard optimal stopping, multiple stopping, and optimal control problems. 5.- Primal algorithms for optimal stopping problems: regression algorithms, optimization algorithms, policy iteration. Extensions to multiple stopping, examples. 6.- Multilevel primal algorithms. 7.- Multilevel dual algorithms 8.- Convergence analysis of primal algorithms. 9.- Convergence analysis of dual algorithms. 10.- Consumption based approaches. 11.- Dimension reduction for primal algorithms. 12.- Variance reduction for dual algorithms. 13.- Conclusion.
