Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas

57 Pages Posted: 18 Mar 2021

See all articles by Stefano Grassi

Stefano Grassi

University of Rome, Tor Vergata, Faculty of Economics, Department of Economics and Finance

Francesco Violante

affiliation not provided to SSRN

Date Written: March 11, 2021

Abstract

Starting from the Cholesky-GARCH model, recently proposed by Darolles, Francq, and Laurent (2018), the paper introduces the Block-Cholesky GARCH (BC-GARCH). This new model adapts in a natural way to the asset pricing framework. After deriving conditions for stationarity, uniform invertibility and beta tracking, we investigate the finite sample properties of a variety of maximum likelihood estimators suited for the BC-GARCH by means of an extensive Monte Carlo experiment. Finally, we illustrate the usefulness of the BC-GARCH in two empirical applications. The first tests for the presence of beta spillovers in a bivariate system in the context of the Fama and French (1993) three factor framework. The second empirical application consists of a large scale exercise exploring the cross-sectional variation of expected returns for 40 industry portfolios.

Keywords: Cholesky decomposition; Multivariate GARCH, Asset Pricing, Time Varying Beta, Two Pass Regression.

JEL Classification: C12, C22, G12, G13

Suggested Citation

Grassi, Stefano and Violante, Francesco, Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas (March 11, 2021). CEIS Working Paper No. 510, Available at SSRN: https://ssrn.com/abstract=3802874 or http://dx.doi.org/10.2139/ssrn.3802874

Stefano Grassi (Contact Author)

University of Rome, Tor Vergata, Faculty of Economics, Department of Economics and Finance ( email )

Via Columbia, 2
Rome, 00133
Italy

Francesco Violante

affiliation not provided to SSRN

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