Optimization Methods in Finance (Mathematics, Finance and Risk)
Cambridge University Press
Edition: 2, 8/9/2018
EAN 9781107056749, ISBN10: 1107056748
Hardcover, 348 pages, 25.4 x 17.8 x 2 cm
Language: English
Originally published in English
Optimization methods play a central role in financial modeling. This textbook is devoted to explaining how state-of-the-art optimization theory, algorithms, and software can be used to efficiently solve problems in computational finance. It discusses some classical mean–variance portfolio optimization models as well as more modern developments such as models for optimal trade execution and dynamic portfolio allocation with transaction costs and taxes. Chapters discussing the theory and efficient solution methods for the main classes of optimization problems alternate with chapters discussing their use in the modeling and solution of central problems in mathematical finance. This book will be interesting and useful for students, academics, and practitioners with a background in mathematics, operations research, or financial engineering. The second edition includes new examples and exercises as well as a more detailed discussion of mean–variance optimization, multi-period models, and additional material to highlight the relevance to finance.
Part I. Introduction
1. Overview of optimization models
2. Linear programming
theory and algorithms
3. Linear programming models
asset-liability management
4. Linear programming models
arbitrage and asset pricing
Part II. Single-Period Models
5. Quadratic programming
theory and algorithms
6. Quadratic programming models
mean-variance optimization
7. Sensitivity of mean-variance models to input estimation
8. Mixed integer programming
theory and algorithms
9. Mixed integer programming models
portfolios with combinatorial constraints
10. Stochastic programming
theory and algorithms
11. Stochastic programming models
risk measures
Part III. Multi-Period Models
12. Multi-period models
simple examples
13. Dynamic programming
theory and algorithms
14. Dynamic programming models
multi-period portfolio optimization
15. Dynamic programming models
the binomial pricing model
16. Multi-stage stochastic programming
17. Stochastic programming models
asset-liability management
Part IV. Other Optimization Techniques
18. Conic programming
theory and algorithms
19. Robust optimization
20. Nonlinear programming
theory and algorithms
Appendix
References
Index.