Advanced Simulation-Based Methods for Optimal Stopping and Control With Applications in Finance

Advanced Simulation-Based Methods for Optimal Stopping and Control With Applications in Finance / by Denis Belomestny, John Schoenmakers.

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 th...

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Bibliographic Details
Main Authors: Belomestny, Denis (Author), Schoenmakers, John (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: London : Palgrave Macmillan UK : Imprint: Palgrave Macmillan, 2018.
Edition:1st ed. 2018.
Series:Springer eBook Collection.
Subjects:
Corporations—Finance.
Applied mathematics.
Engineering mathematics.
Business enterprises—Finance.
Mathematical models.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
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.

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