Modelling Realized Covariances and Returns

Xin Jin () and John Maheu

Working Papers from University of Toronto, Department of Economics

Abstract: This paper proposes new dynamic component models of realized covariance (RCOV) matrices based on recent work in time-varying Wishart distributions. The specifications are linked to returns for a joint multivariate model of returns and covariance dynamics that is both easy to estimate and forecast. Realized covariance matrices are constructed for 5 stocks using high-frequency intraday prices based on positive semi-definite realized kernel estimates. The models are compared based on a term-structure of density forecasts of returns for multiple forecast horizons. Relative to multivariate GARCH models that use only daily returns, the joint RCOV and return models provide significant improvements in density forecasts from forecast horizons of 1 day to 3 months ahead. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out.

Keywords: eigenvalues; dynamic conditional correlation; predictive likelihoods; MCMC (search for similar items in EconPapers)
JEL-codes: C11 C32 C53 G17 (search for similar items in EconPapers)
Pages: 33 pages
Date: 2010-07-16
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Citations: View citations in EconPapers (14)

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Related works:
Journal Article: Modeling Realized Covariances and Returns (2013)
Working Paper: Modelling Realized Covariances and Returns (2012)
Working Paper: Modelling Realized Covariances and Returns (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:tor:tecipa:tecipa-408

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