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Dynamic Conditional Beta

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  • Robert F. Engle

Abstract

Dynamic conditional beta 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.

Suggested Citation

  • Robert F. Engle, 2016. "Dynamic Conditional Beta," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 643-667.
    • Handle: RePEc:oup:jfinec:v:14:y:2016:i:4:p:643-667.
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbw006
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    References listed on IDEAS

    as
    1. Viral V. Acharya & Lasse H. Pedersen & Thomas Philippon & Matthew Richardson, 2017. "Measuring Systemic Risk," The Review of Financial Studies, Society for Financial Studies, vol. 30(1), pages 2-47.
    2. repec:fip:fedhpr:y:2010:i:may:p:65-71 is not listed on IDEAS
    3. Anil K. Bera & Philip Garcia & Jae-Sun Roh, 1997. "Estimation of Time-Varying Hedge Ratios for Corn and Soybeans: BGARCH and Random Coefficient Approaches," Finance 9712007, University Library of Munich, Germany.
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