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

Stefano Grassi () and Francesco Violante ()
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Stefano Grassi: University of Rome Tor Vergata and CREATES - Aarhus University

No 2021-05, Working Papers from Center for Research in Economics and Statistics

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. 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. (search for similar items in EconPapers)
JEL-codes: C12 C22 C58 G12 G13 (search for similar items in EconPapers)
Pages: 50 pages
Date: 2021-03-03
New Economics Papers: this item is included in nep-ets and nep-ore
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http://crest.science/RePEc/wpstorage/2021-05.pdf CREST working paper version (application/pdf)

Related works:
Working Paper: Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas (2021)
Working Paper: Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas (2021)
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