Séminaires de recherche

An Information-Theoretic Asset Pricing Model

Finance

Intervenant : Christian Julliard
LSE - The London School of Economics

9 mars 2017 - T015 - De 14h00 à 15h15


We show that a non-parametric estimate of the pricing kernel, extracted using an information-theoretic approach, delivers out-of-sample smaller pricing errors and better cross-sectional fit than leading factor models, and identifies the maximum Sharpe ratio portfolio. This information SDF identifies a novel source of risk not captured by Fama-French and momentum factors, revealing an ‘information anomaly’ that generates annualized alphas of about 9%–24%. A tradable information portfolio that mimics this kernel has high out-of-sample Sharpe ratio (about 1 or more), outperforming both the 1/N benchmark and Value and Momentum strategies combined. These results hold for wide cross-sections of test portfolios.

Finance

Intervenant : Xavier Gabaix

13 juin 2019 - T104 - De 14h00 à 15h15


Finance

Intervenant : Adriano Rampini

23 mai 2019 - T105 - De 14h00 à 15h15


Finance

Intervenant : Luke Taylor

16 mai 2019 - T105 - De 14h00 à 15h15


Finance

Intervenant : Jessica Jeffers

18 avril 2019 - T104 - De 14h00 à 15h15


Finance

Intervenant : Emil Verner

4 avril 2019 - T104 - De 14h00 à 15h15


Contacts  

Département Finance 

Campus HEC Paris
1, rue de la Libération
78351 Jouy-en-Josas cedex
France

Faculté  

Daniel SCHMIDT

Finance

Voir le CV

4th Annual HEC Paris Workshop Preliminary Program “Banking, Finance, Macroeconomics and the Real Economy”  


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