Multi-factor Models and Signal Processing Techniques

, ,

Multi-factor Models and Signal Processing Techniques

, ,

Wysyłka:
Niedostępna
Powiadom o dostępności
Podaj swój e-mail a zostaniesz poinformowany jak tylko pozycja będzie dostępna.
×
Cena 374,85 PLN
Nasza cena 363,23 PLN
Oszczędzasz 3%
Dodaj do Schowka
Zaloguj się
Przypomnij hasło
×
×
Cena 374,85 PLN
Nasza cena 363,23 PLN
Oszczędzasz 3%
Dodaj do Schowka
Zaloguj się
Przypomnij hasło
×
×

Opis: Multi-factor Models and Signal Processing Techniques - Serges Darolles, Patrick Duvaut, Emmanuelle Jay

Multi-factor Models and Signal Processing Techniques surveys the most widely used factor models employed in the realm of the financial asset pricing field. It offers a unique perspective on these models, using the concrete application of evaluating risks in the hedge fund industry to demonstrate that signal processing techniques can be an interesting alternative to the selection of factors, whether they are fundamental or statistical factors. More importantly, the book shows how the signal processing approach can provide more efficient estimation procedures based, for instance, on lq regularized Kalman Filtering.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 2.7. Appendix 3: Large panel data 48 2.8. Chapter 2 highlights 56 Chapter 3. Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective 59 3.1. Introduction 59 3.2. Why LSE and KF in factor modeling? 60 3.3. LSE setup 62 3.4. LSE objective and criterion 63 3.5. How LSE is working (for LSE users and programmers) 64 3.6. Interpretation of the LSE solution . 65 3.7. Derivations of LSE solution 70 3.8. Why KF and which setup? 71 3.9. What are the main properties of the KF model? 74 3.10. What is the objective of KF? 76 3.11. How does the KF work (for users and programmers)? 77 3.12. Interpretation of the KF updates 81 3.13. Practice 86 3.14. Geometrical derivation of KF updating equations 104 3.15. Highlights 112 3.16. Appendix: Matrix inversion lemma 116 Chapter 4. A Regularized Kalman Filter (rgKF) for Spiky Data 117 4.1. Introduction 117 4.2. Preamble: statistical evidence on the KF recursive equations 119 4.3. Robust KF 119 4.4. rgKF: the rgKF(NG,lq ) 121 4.5. Application to detect irregularities in hedge fund returns 128 4.6. Conclusion 130 4.7. Chapter highlights 130 Appendix: Some Probability Densities 133 Conclusion 141 Bibliography 143 Index 153


Szczegóły: Multi-factor Models and Signal Processing Techniques - Serges Darolles, Patrick Duvaut, Emmanuelle Jay

Tytuł: Multi-factor Models and Signal Processing Techniques
Autor: Serges Darolles, Patrick Duvaut, Emmanuelle Jay
Producent: ISTE Publishing Company
ISBN: 9781848214194
Rok produkcji: 2013
Ilość stron: 320
Oprawa: Twarda
Waga: 0.48 kg


Recenzje: Multi-factor Models and Signal Processing Techniques - Serges Darolles, Patrick Duvaut, Emmanuelle Jay

Zaloguj się
Przypomnij hasło
×
×


Klienci, którzy kupili oglądany produkt kupili także: