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Multi-factor Models and Signal Processing Techniques (Hardcover, New)
Loot Price: R4,149
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Multi-factor Models and Signal Processing Techniques (Hardcover, New)
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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. Contents Foreword, Rama Cont. 1. Factor Models and General
Definition. 2. Factor Selection. 3. Least Squares Estimation (LSE)
and Kalman Filtering (KF) for Factor Modeling: A Geometrical
Perspective. 4. A Regularized Kalman Filter (rgKF) for Spiky Data.
Appendix: Some Probability Densities. About the Authors Serge
Darolles is Professor of Finance at Paris-Dauphine University,
Vice-President of QuantValley, co-founder of QAMLab SAS, and member
of the Quantitative Management Initiative (QMI) scientific
committee. His research interests include financial econometrics,
liquidity and hedge fund analysis. He has written numerous
articles, which have been published in academic journals. Patrick
Duvaut is currently the Research Director of Telecom ParisTech,
France. He is co-founder of QAMLab SAS, and member of the
Quantitative Management Initiative (QMI) scientific committee. His
fields of expertise encompass statistical signal processing,
digital communications, embedded systems and QUANT finance.
Emmanuelle Jay is co-founder and President of QAMLab SAS. She has
worked at Aequam Capital as co-head of R&D since April 2011 and
is member of the Quantitative Management Initiative (QMI)
scientific committee. Her research interests include SP for
finance, quantitative and statistical finance, and hedge fund
analysis.
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