Robust equity portfolio management + website : formulations, implementations, and properties using MATLAB

✍ Scribed by Fabozzi, Frank J.; Kim, Jang-Ho; Kim, Woo Chang

• Publisher: Wiley
• Year: 2015
• Tongue: English
• Leaves: 259
• Series: Frank J. Fabozzi series
• Category: Library

✦ Synopsis

"This is a comprehensive book on robust portfolio optimization, which includes up-to-date developments and will interest readers looking for advanced material on portfolio optimization. The book will also attract introductory-level readers because it begins by reviewing the foundations of portfolio optimization. The material in this book emphasizes applications in equity portfolio management and includes MATLAB codes that can assist readers of all levels in implementing robust models. The book aims to help the reader fully understand formulations, performances, and properties of robust portfolios. Application in the equity market is described throughout the book and the implementation of robust models is explained in detail with example code"--

"The book will be most helpful for readers who are interested in learning about the quantitative side of equity portfolio management, mainly portfolio optimization and risk analysis. Mean-variance portfolio optimization is covered in detail, leading to an extensive discussion on robust portfolio optimization. Nonetheless, readers without prior knowledge of portfolio management or mathematical modeling should be able to follow the presentation since basic concepts are covered in each chapter. Furthermore, the main quantitative approaches are presented with MATLAB examples, allowing readers to easily implement portfolio problems in MATLAB or similar modeling software. There is an online appendix that provides the MATLAB codes presented in the chapter boxes (www.wiley.com/go/robustequitypm)"-- Read more...

Abstract:

A comprehensive portfolio optimization guide, with provided MATLAB code Robust Equity Portfolio Management + Website offers the most comprehensive coverage available in this burgeoning field. Read more...

✦ Table of Contents

Content: The Frank J. Fabozzi Series
Title Page
Copyright
Table of Contents
Dedication
Preface
Chapter 1: Introduction
1.1 Overview of the Chapters
1.2 Use of MATLAB
Notes
Chapter 2: Mean-Variance Portfolio Selection
2.1 Return of Portfolios
2.2 Risk of Portfolios
2.3 Diversification
2.4 Mean-Variance Analysis
2.5 Factor Models
2.6 Example
Key Points
Notes
Chapter 3: Shortcomings of Mean-Variance Analysis
3.1 Limitations on the Use of Variance
3.2 Difficulty in Estimating the Inputs
3.3 Sensitivity of Mean-Variance Portfolios
3.4 Improvements on Mean-Variance Analysis Key PointsNotes
Chapter 4: Robust Approaches for Portfolio Selection
4.1 Robustness
4.2 Robust statistics
4.3 Shrinkage Estimation
4.4 Monte Carlo Simulation
4.5 Constraining Portfolio Weights
4.6 Bayesian Approach
4.7 Stochastic Programming
4.8 Additional Approaches
Key Points
Notes
Chapter 5: Robust Optimization
5.1 Worst-Case Decision Making
5.2 Convex Optimization
5.3 Robust Counterparts
5.4 Interior Point Methods
Key Points
Notes
Chapter 6: Robust Portfolio Construction
6.1 Some Preliminaries
6.2 Mean-Variance Portfolios
6.3 Constructing Robust Portfolios 6.4 Robust Portfolios with Box Uncertainty6.5 Robust Portfolios with Ellipsoidal Uncertainty
6.6 Closing Remarks
Key Points
Notes
Chapter 7: Controlling Third and Fourth Moments of Portfolio Returns via Robust Mean-Variance Approach
7.1 Controlling Higher Moments of Portfolio Return
7.2 Why Robust Formulation Controls Higher Moments
7.3 Empirical Tests
Key Points
Notes
Chapter 8: Higher Factor Exposures of Robust Equity Portfolios
8.1 Importance of Portfolio Factor Exposure
8.2 Fundamental Factor Models in the Equity Market 8.3 Factor Dependency of Robust Portfolios: Theoretical Arguments8.4 Factor Dependency of Robust Portfolios: Empirical Findings
8.5 Factor Movements and Robust Portfolios
8.6 Robust Formulations That Control Factor Exposure
Key Points
Notes
Chapter 9: Composition of Robust Portfolios
9.1 Overview of Analyses
9.2 Composition Based on Investment Styles
9.3 Composition Based on Additional Factors
9.4 Composition Based on Stock Betas
9.5 Robust Portfolio Construction Based on Stock Beta Attributes
Key Points
Notes
Chapter 10: Robust Portfolio Performance 10.1 Portfolio Performance Measures10.2 Historical Performance of Robust Portfolios
10.3 Measuring Robustness
Key Points
Notes
Chapter 11: Robust Optimization Software
11.1 YALMIP
11.2 ROME (Robust Optimization Made Easy)
11.3 AIMMS
Key Points
Notes
About the Authors
About the Companion Website
Index
End User License Agreement

✦ Subjects

Portfolio management;Investments;Mathematical models;Investment analysis;Mathematical models;BUSINESS & ECONOMICS;Investments & Securities