Modeling Realized Covariances and Returns
This article proposes new dynamic component models of returns and realized covariance (RCOV) matrices based on time-varying Wishart distributions. Bayesian estimation and model comparison is conducted with a range of multivariate GARCH models and existing RCOV models from the literature. The main method of model comparison consists of a term-structure of density forecasts of returns for multiple forecast horizons. The new joint return-RCOV models provide superior density forecasts for returns from forecast horizons of 1 day to 3 months ahead as well as improved point forecasts for realized covariances. Global minimum variance portfolio selection is improved for forecast horizons up to 3 weeks out. Copyright , Oxford University Press.
Year of publication: |
2013
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Authors: | Jin, Xin ; Maheu, John M. |
Published in: |
Journal of Financial Econometrics. - Society for Financial Econometrics - SoFiE, ISSN 1479-8409. - Vol. 11.2013, 2, p. 335-369
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Publisher: |
Society for Financial Econometrics - SoFiE |
Saved in:
Online Resource
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