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Advanced Simulation-Based Methods for Optimal Stopping and Control With Applications in Finance
Author
Title
Advanced Simulation-Based Methods for Optimal Stopping and Control [electronic resource] : With Applications in Finance / by Denis Belomestny, John Schoenmakers.
ISBN
9781137033512
Publication
London : Palgrave Macmillan UK : Imprint: Palgrave Macmillan, 2018.
Physical Description
1 online resource (XVI, 364 p.) 14 illus.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
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.
Variant and related titles
Springer ebooks.
Other formats
Printed edition:
Format
Books / Online
Language
English
Added to Catalog
May 07, 2018
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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