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

Multiple version iconThere 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

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

Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

New York University (NYU) - Volatility and Risk Institute ( email )

44 West 4th Street
New York, NY 10012
United States

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
1,428
Abstract Views
6,431
Rank
11,862
PlumX Metrics