Title: A multi-factor realized GARCH with an application to the Fama-French model
Authors: Ilya Archakov - University of Vienna (Austria) [presenting]
Asger Lunde - Aarhus University and CREATES (Denmark)
Peter Hansen - University of North Carolina (United States)
Abstract: A novel approach is proposed to model and measure systematic risk in equity markets. Asset returns are modeled in a multiple regression framework with GARCH-type dynamics for conditional variances and correlations, which imply temporal variation of the regression coefficients, that are commonly referred to as betas. The model incorporates information from high-frequency based realized measures. These help to identify the latent covariance process and enable the model to promptly adapt to changes. Our framework is consistent with the broad class of linear factor models in the asset pricing literature, and we apply our framework to the famous three-factor Fama-French model in an empirical analysis with more than 800 individual assets. We document an appreciable cross-sectional and temporal variation of the model-implied risk loadings with the especially strong (though short-lived) distortion around the Financial Crisis episode. In addition, we find a significant heterogeneity in a relative explanatory power of the Fama-French factors across the different sectors of economy and detect a fluctuation of the risk premia estimates over time. The empirical evidence emphasizes the importance of taking into account dynamic aspects of the underlying covariance structure in asset pricing models.