Advanced Simulation-Based Methods for Optimal Stopping and Control

With Applications in Finance
2018. Auflage 2018
ISBN: 978-1-137-03350-5
Verlag: Palgrave MacMillan UK

Buch, Englisch, 364 Seiten, Format (B × H): 161 mm x 244 mm, Gewicht: 745 g

Presents the very latest applications of probability modelling to derivatives pricing and risk management

Brings new approaches and applications to the quant’s toolkit - Monte Carlo simulations are the bedrock of much of the quantitative practitioners work and this book presents a core quant topic

Leading researchers Schoenmakers and Belomestny are well regarded for their research in stochastics and probability theory – this book will be well received by the community

Zielgruppe

Research

Autoren/Hrsg.

Belomestny, Denis

Schoenmakers, John

Fachgebiete

• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Finanzsektor & Finanzdienstleistungen: Allgemeines
• Wirtschaftswissenschaften Finanzsektor & Finanzdienstleistungen Anlagen & Wertpapiere
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Mathematik Interdisziplinär Finanz- und Versicherungsmathematik

Inhaltsverzeichnis

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.

Über Autor(innen)

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.