Advanced simulation-based methods for optimal stopping and control : with applications in finance
Author(s)
Bibliographic Information
Advanced simulation-based methods for optimal stopping and control : with applications in finance
Palgrave Macmillan, c2018
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references (p. 355-361) and index
Description and Table of Contents
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.
Table of Contents
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.
by "Nielsen BookData"