by
Frank J. Fabozzi, CFA
Yale University and Journal of Portfolio Management

Sergio M. Focardi
The Intertek Group

Petter N. Kolm
Yale University

Contents
Foreword . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Chapter 1. Forecasting Financial Markets. . . . . . . . . . . . . . . . . . 1
Chapter 2. General Equilibrium Theories: Concepts and
Applicability. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
Chapter 3. Extended Framework for Applying Modern
Portfolio Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Chapter 4. New Territory: Modeling for Portfolio and
Tactical Asset Management. . . . . . . . . . . . . . . . . . . . 35
Chapter 5. New Territory: Forecastability and the Long-Term
Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
Chapter 6. Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
Chapter 7. Model Selection, Data Snooping, Overfitting, and
Model Risk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
Chapter 8. Predictive Models of Return . . . . . . . . . . . . . . . . . . . 76
Chapter 9. Model Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
Chapter 10. Practical Considerations When Using
Optimization Software. . . . . . . . . . . . . . . . . . . . . . . . 104
Chapter 11. Models in Practice: Industry Survey Results . . . . . . . 112
Chapter 12. Quantitative Modeling Today and Tomorrow . . . . . 119
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124