Systematic and multifactor risk models revisited

Michel Fliess () and Cédric Join ()
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Michel Fliess: LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau] - X - École polytechnique - IP Paris - Institut Polytechnique de Paris - CNRS - Centre National de la Recherche Scientifique, AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques
Cédric Join: NON-A - Non-Asymptotic estimation for online systems - Centre Inria de l'Université de Lille - Inria - Institut National de Recherche en Informatique et en Automatique - CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 - Centrale Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique, AL.I.E.N. - ALgèbre pour Identification & Estimation Numériques, CRAN - Centre de Recherche en Automatique de Nancy - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique

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Abstract: Systematic and multifactor risk models are revisited via methods which were already successfully developed in signal processing and in automatic control. The results, which bypass the usual criticisms on those risk modeling, are illustrated by several successful computer experiments.

Keywords: Systematic risk; market risk; multifactor risk; beta; alpha; trend; volatility; nonstandard analysis (search for similar items in EconPapers)
Date: 2013-12-16
Note: View the original document on HAL open archive server: https://polytechnique.hal.science/hal-00920175v1
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Published in First Paris Financial Management Conference, Dec 2013, Paris, France. http://khuongnguyen.free.fr/PFMC-2013/Program_Papers.pdf

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00920175

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