Modeling and forecasting realized covariance matrices with accounting for leverage

The existing dynamic models for realized covariance matrices do not account for an asymmetry with respect to price directions. We modify the recently proposed conditional autoregressive Wishart (CAW) model to allow for the leverage effect. In the conditional threshold autoregressive Wishart (CTAW) m...

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Bibliographic Details
Published inEconometric reviews Vol. 37; no. 2; pp. 114 - 139
Main Authors Anatolyev, Stanislav, Kobotaev, Nikita
Format Journal Article
LanguageEnglish
Published New York Taylor & Francis 07.02.2018
Taylor & Francis Ltd
Subjects
Assets
Autoregressive models
CAW
Covariance matrix
Dynamic models
Econometrics
Economic models
Forecasting
Leverage
Matrices
MIDAS
Predictions
realized volatility
rolatility forecasting
Specifications
Switches
Volatility
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Summary:The existing dynamic models for realized covariance matrices do not account for an asymmetry with respect to price directions. We modify the recently proposed conditional autoregressive Wishart (CAW) model to allow for the leverage effect. In the conditional threshold autoregressive Wishart (CTAW) model and its variations the parameters governing each asset's volatility and covolatility dynamics are subject to switches that depend on signs of previous asset returns or previous market returns. We evaluate the predictive ability of the CTAW model and its restricted and extended specifications from both statistical and economic points of view. We find strong evidence that many CTAW specifications have a better in-sample fit and tend to have a better out-of-sample predictive ability than the original CAW model and its modifications.
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ISSN:0747-4938
1532-4168
DOI:10.1080/07474938.2015.1035165