Practical Financial Optimization: Decision Making for Financial Engineers - Tapa dura

Acerca del autor

Stavros A. 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).

De la contraportada

This book gives a comprehensive account of financial optimization models used to support decision-making for financial engineers. It starts with the classical static mean-variance analysis and portfolio immunization, moves on to scenario-based models, and builds towards multi-period dynamic portfolio optimization.

As the story unfolds, the relationships between classes of models are revealed. Once the foundations are laid with several building blocks and the broad landscape of financial optimization is charted, the book moves on to analyze several real-world applications. In this way the reader acquires not only solid knowledge of the foundations of financial optimization, but also a taste for the large-scale models that can be grounded on these foundations. The math prerequisite is optimization with matrix algebra.

De la solapa interior

This book gives a comprehensive account of financial optimization models used to support decision-making for financial engineers. It starts with the classical static mean-variance analysis and portfolio immunization, moves on to scenario-based models, and builds towards multi-period dynamic portfolio optimization.

As the story unfolds, the relationships between classes of models are revealed. Once the foundations are laid with several building blocks and the broad landscape of financial optimization is charted, the book moves on to analyze several real-world applications. In this way the reader acquires not only solid knowledge of the fountains of financial optimization, but also a taste for the large-scale models that can be grounded on these foundations. The math prerequisite is optimization with matrix algebra.