Multi-factor Models and Signal Processing Techniques: Application to Quantitative Finance [Hardcover]

With recent outbreaks of multiple large-scale financial crises, amplified by interconnected risk sources, a new paradigm of fund management has emerged. This new paradigm leverages embedded quantitative processes and methods to provide more transparent, adaptive, reliable and easily implemented risk assessment-based practices.

This book surveys the most widely used factor models employed within the field of financial asset pricing. Through the concrete application of evaluating risks in the hedge fund industry, the authors demonstrate that signal processing techniques are an interesting alternative to the selection of factors (both fundamentals and statistical factors) and can provide more efficient estimation procedures, based on lq regularized Kalman filtering for instance.

With numerous illustrative examples from stock markets, this book meets the needs of both finance practitioners and graduate students in science, econometrics and finance.

Foreword xi
Rama CONT

Introduction xv

Notations and Acronyms xxi

Chapter 1. Factor Models and General Definition 1

1.1. Introduction 1

1.2. What are factor models? 2

1.3. Why factor models in finance? 7

1.4. How to build factor models? 11

1.5. Historical perspective 14

1.6. Glossary 18

Chapter 2. Factor Selection 23

2.1. Introduction 23

2.2. Qualitative know-how 24

2.3. Quantitative methods based on eigenfactors 31

2.4. Model order choice 36

2.5. Appendix 1: Covariance matrix estimation 38

2.6. Appendix 2: Similarity of the eigenfactor selection with the MUSIC algorithm 46

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