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Multi-Factor Models and Signal Processing Techniques: Application to Quantitative Finance

1, 2013

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Improving portfolios global performance using a cleaned and robust covariance matrix estimate

Soft computing (Berlin, Germany), 2020-06, Vol.24 (12), p.8643-8654

2020

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Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading

IEEE journal of selected topics in signal processing, 2016-09, Vol.10 (6), p.979-981

2016

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BORD: bayesian optimum radar detector

Signal processing, 2003-06, Vol.83 (6), p.1151-1162

2003

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Improving Portfolios Global Performance with Robust Covariance Matrix Estimation: Application to the Maximum Variety Portfolio

2018 26th European Signal Processing Conference (EUSIPCO), 2018, p.1107-1111

2018

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Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems

Documents de travail du Centre d'Économie de la Sorbonne, 2021

2021

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Bayesian Optimum Radar Detector in non-Gaussian noise

2002 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2002, Vol.2, p.II-1289-II-1292

2002

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New methods of radar performances analysis

Signal processing, 2000-12, Vol.80 (12), p.2527-2540

2000

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5 - Robust Portfolio Allocation with Systematic Risk Contribution Restrictions

Risk-Based and Factor Investing, 2016, p.123-146

2016

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Factor Models and General Definition

Multi-Factor Models and Signal Processing Techniques, 2013, p.1-21

2013

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Some Probability Densities

Multi‐Factor Models and Signal Processing Techniques, 2013, p.133-139

2013

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A Regularized Kalman Filter (rgKF) for Spiky Data

Multi-Factor Models and Signal Processing Techniques, 2013, p.117-132

2013

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Factor Selection

Multi-Factor Models and Signal Processing Techniques, 2013, p.23-58

2013

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Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective

Multi-Factor Models and Signal Processing Techniques, 2013, p.59-116

2013

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Introduction

Multi-Factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Foreward

Multi-factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Color Plate

Multi-factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Conclusion

Multi-Factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Intro

Multi-factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Foreword

Multi-Factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Notations and Acronyms

Multi-Factor Models and Signal Processing Techniques, 2013

2013

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Conclusion

Multi-factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Introduction

Multi-factor Models and Signal Processing Techniques, 2013

2013

Volltextzugriff (PDF)

Appendix: Some Probability Densities

Multi-Factor Models and Signal Processing Techniques, 2013

2013

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Conclusion

Multi‐Factor Models and Signal Processing Techniques, 2013, p.141-142

2013

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Multi-Factor Models and Signal Processing Techniques: Application to Quantitative Finance

Improving portfolios global performance using a cleaned and robust covariance matrix estimate

Introduction to the Issue on Financial Signal Processing and Machine Learning for Electronic Trading

BORD: bayesian optimum radar detector

Improving Portfolios Global Performance with Robust Covariance Matrix Estimation: Application to the Maximum Variety Portfolio

Frequency causality measures and Vector AutoRegressive (VAR) models: An improved subset selection method suited to parsimonious systems

Bayesian Optimum Radar Detector in non-Gaussian noise

New methods of radar performances analysis

5 - Robust Portfolio Allocation with Systematic Risk Contribution Restrictions

Factor Models and General Definition

Some Probability Densities

A Regularized Kalman Filter (rgKF) for Spiky Data

Factor Selection

Least Squares Estimation (LSE) and Kalman Filtering (KF) for Factor Modeling: A Geometrical Perspective

Introduction

Foreward

Color Plate

Conclusion

Intro

Foreword

Notations and Acronyms

Conclusion

Introduction

Appendix: Some Probability Densities

Conclusion

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