Forecasting comparison of long term component dynamic models for realized covariance matrices
Luc Bauwens,
Manuela Braione and
Giuseppe Storti
No 2014053, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)
Abstract:
Novel model specifications that include a time-varying long run component in the dynamics of realized covariance matrices are proposed. The adopted modeling framework allows the secular component to enter the model structure either in an additive fashion or as a multiplicative factor, and to be specified parametrically, using a MIDAS filter, or non-parametrically. Estimation is performed by maximizing a Wishart quasi-likelihood function. The one-step ahead forecasting performance of the models is assessed by means of three approaches: the Model Confidence Set, (global) minimum variance portfolios and Value-at-Risk. The results provide evidence in favour of the hypothesis that the proposed models outperform benchmarks incorporating a constant long run component, both in and out-of sample.
Keywords: Realized covariance; component dynamic models; MIDAS; minimum variance portfolio; Model Confidence Set; Value-at-Risk (search for similar items in EconPapers)
JEL-codes: C13 C32 C58 (search for similar items in EconPapers)
Date: 2014-11-30
New Economics Papers: this item is included in nep-ecm, nep-for and nep-ore
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Citations: View citations in EconPapers (14)
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Related works:
Journal Article: Forecasting Comparison of Long Term Component Dynamic Models for Realized Covariance Matrices (2016) 
Working Paper: Forecasting comparison of long term component dynamic models for realized covariance matrices (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:cor:louvco:2014053
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