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

Stefano Grassi () and Francesco Violante ()
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Stefano Grassi: DEF Università di Roma "Tor Vergata", http://www.ceistorvergata.it

No 510, CEIS Research Paper from Tor Vergata University, CEIS

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. (search for similar items in EconPapers)
JEL-codes: C12 C22 G12 G13 (search for similar items in EconPapers)
Pages: 57 pages
Date: 2021-03-11, Revised 2021-03-11
New Economics Papers: this item is included in nep-cwa and nep-ore
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Working Paper: Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas (2021) Downloads
Working Paper: Asset Pricing Using Block-Cholesky GARCH and Time-Varying Betas (2021) Downloads
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