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.
Using the Kelly Criterion for Investing.- Designing Minimum Guaranteed Return Funds.- Performance Enhancements for Defined Benefit Pension Plans.- Hedging Market and Credit Risk in Corporate Bond...
: Optimal Models for Economics and Finance.- Mathematics of Optimal Control.- Computing Optimal Control : The SCOM package.- Computing Optimal Growth and Development Models.- Modelling Financial...
This book is about optimization techniques and is subdivided into two parts. In the first part a wide overview on optimization theory is presented. Optimization is presented as being composed of five...
The book offers an interdisciplinary perspective on finance, with a special focus on stock markets. It presents new methodologies for analyzing stock markets' behavior and discusses theories and...