Advanced Simulation-Based Methods for Optimal Stopping and Control [electronic resource] : With Applications in Finance /
Belomestny, Denis.author.
Schoenmakers, John.author.
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.
Includes bibliographical references and index.
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.
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.
Corporations-Finance.
Mathematics.
Business enterprises-Finance.
Corporate Finance.
Applications of Mathematics.
Business Finance.
Mathematical Modeling and Industrial Mathematics.