Robust Portfolio Optimization and Management

Book Preface

This book can be used in teaching courses in advanced econometrics, financial engineering, quantitative investments and portfolio managefprefment, as the main course book, as supplemental reading on advanced topics, and/or for student projects. The material in Chapters 2 through 11 of the book is appropriate for undergraduate advanced electives on investment management, and all topics in the book are accessible to graduate students in finance, economics or in the mathematical and physical sciences.

The material is also appropriate for use in advanced graduate electives in the decision sciences and operations research that focus on applications of quantitative techniques in finance.

For a typical course, it is natural to start with Chapters 2, 5, and 6 where modern portfolio and asset pricing theory and standard estimation techniques are covered. Basic practical considerations are presented in Chapters 4 and 11. Chapters 3, 7, 8, 10, 12, and 13 are more advanced and do not have to be covered in full. A possibility is to focus on the most common techniques used in portfolio management today, such as Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) (in Chapter 3), shrinkage estimators and the Black-Litterman model (in Chapter 8), robust optimization (in Chapters 10 and 12), and transaction costs and portfolio rebalancing (in Chapter 13). Student projects can be based on specialized topics such as multiaccount optimization (in Chapter 4), numerical optimization techniques (in Chapter 9), modern trading strategies, optimal execution, and algorithmic trading (in Chapter 14)