Multi-factor models and signal processing techniques: application to quantitative finance

Abstract : 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.
Type de document :
Ouvrage (y compris édition critique et traduction)
ISTE ; J. Wiley, pp.184, 2013
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Contributeur : Christine Okret-Manville <>
Soumis le : vendredi 10 novembre 2017 - 16:58:06
Dernière modification le : jeudi 11 janvier 2018 - 06:17:41


  • HAL Id : hal-01632892, version 1



Serge Darolles, Patrick Duvaut, Emmanuelle Jay. Multi-factor models and signal processing techniques: application to quantitative finance. ISTE ; J. Wiley, pp.184, 2013. 〈hal-01632892〉



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