Practical Financial Optimization

Stavros Zenios is Professor of Business and Public Administration at the University of Cyprus, Director of the HERMES European Center of Excellence on Computational Finance and Economics, and Senior Fellow at the Wharton Financial Institutions Center of the University of Pennsylvania. His previous books include Financial Optimization (1996); Parellel Optimization: Theory Algorithms, and Applications (1997); and Performance of Financial Institutions: Efficiency, Innovation, Regulation (2000).

• Foreword. Preface.Acknowledgements.List of Models.Notation.I. Introduction.1. An Optimization View of Financial Engineering.2. Basics of Risk Management.II. Portfolio Optimization Models.3. Mean-Variance Analysis.4. Portfolio Models for Fixed Income.5. Scenario Optimization.6. Dynamic Portfolio Optimization with Stochastic Programming.7. Index Funds.8. Designing Financial Products.9. Scenario Generation.III. Applications.10. Application I: International Asset Allocation.11. Application II: Corporate Bond Portfolios.12. Application III: Insurance Policies with Guarantees.13. Application IV: Personal Financial Planning.IV. Library of Financial Optimization Models.14. FINLIB: A Library of Financial Optimization ModelsA. Basics of Optimization.B. Basics of Probability Theory.C. Stochastic Processes.Bibliography.Index.

"This volume is both a comprehensive guide to optimization techniques useful in financial decision making and a well-illustrated essay on the relationship between theory and practice. While the real problem may always be more complex than any model of it we build, that does not necessarily imply that the largest, most complex model will serve us best. Zenios supplies the reader with a spectrum of optimization models, from simple to complex, and sage advice on how to use them."From the Foreword by Harry M. Markowitz, Nobel Laureate in Economics "Most books on portfolio optimization focus on continuous time stochastic control models. By contrast, Zenios's decision to focus on mathematical programming models in financial engineering is an auspicious one. The book is well organized and clearly written, and uses a minimum of technical prerequisites (both mathematical and financial). It should therefore be accessible and of interest to a broad audience: industry practitioners interested in the potential application of optimization to the problems they face, students curious about how optimization is applied in finance, and professional researchers who would like a comprehensive overview of the uses of mathematical programming in financial engineering."David Saunders, University of Waterloo