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Realized Beta GARCH: A Multivariate GARCH Model with Realized Measures of Volatility and CoVolatility

  • Peter R. Hansen


    (Stanford University, Department of Economics and CREATES)

  • Asger Lunde


    (Aarhus University, School of Economics and Management and CREATES)

  • Valeri Voev


    (Aarhus University, School of Economics and Management and CREATES)

We introduce a multivariate GARCH model that utilizes and models realized measures of volatility and covolatility. The realized measures extract information contained in high-frequency data that is particularly beneficial during periods with variation in volatility and covolatility. Applying the model to market returns in conjunction with an individual asset yields a model for the conditional regression coefficient, known as the beta. We apply the model to a set of highly liquid stocks and find that conditional betas are much more variable than usually observed with rolling-window OLS regressions with dailty data. In the empirical part of the paper we examine the cross-sectional as well as the time variation of the conditional beta series. The model links the conditional and realized second moment measures in a self-contained system of equations, making it amenable to extensions and easy to estimate. A multi-factor extension of the model is briefly discussed.

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Paper provided by School of Economics and Management, University of Aarhus in its series CREATES Research Papers with number 2010-74.

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Length: 19
Date of creation: 29 Nov 2010
Date of revision:
Handle: RePEc:aah:create:2010-74
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