Dynamic Conditional Beta

Engle, Robert F.

doi:10.2139/ssrn.2404020

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Dynamic Conditional Beta

45 Pages Posted: 4 Mar 2014 Last revised: 12 Aug 2015

See all articles by Robert F. Engle

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

There are 3 versions of this paper

Date Written: June 10, 2015

Abstract

Dynamic Conditional Beta (DCB) is an approach to estimating regressions with time varying parameters. The conditional covariance matrices of the exogenous and dependent variable for each time period are used to formulate the dynamic beta. Joint estimation of the covariance matrices and other regression parameters is developed. Tests of the hypothesis that betas are constant are non-nested tests and several approaches are developed including a novel nested model. The methodology is applied to industry multifactor asset pricing and to global systemic risk estimation with non-synchronous prices.

Keywords: GARCH, DCC, Time Varying Parameters, Multivariate GARCH, Non-Nested Tests, Multi-factor Asset Pricing, Systemic Risk, SRISK

Suggested Citation: Suggested Citation

Engle, Robert F., Dynamic Conditional Beta (June 10, 2015). Available at SSRN: https://ssrn.com/abstract=2404020 or http://dx.doi.org/10.2139/ssrn.2404020