Tail Heterogeneity for Dynamic Covariance Matrices: the F-Riesz Distribution

Andre Lucas, Anne Opschoor and Luca Rossini
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Anne Opschoor: Vrije Universiteit Amsterdam
Authors registered in the RePEc Author Service: Francisco A. A. Blasques ()

No 21-010/III, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We introduce a novel model for the dynamics of fat-tailed (realized) covariance-matrix-valued time series using the new F-Riesz distribution. The model allows for different tail behavior across the coordinates of the covariance matrix via two vector-valued degrees of freedom parameters, thus generalizing the familiar Wishart and matrix-F distributions by introducing heterogeneous tail behavior. We show that the filter implied by the new model is invertible and that a two-step targeted maximum likelihood estimator is consistent. Applying the new F-Riesz model to U.S. stocks, both tail-heterogeneity and tail-fatness are empirically relevant and produce large in-sample and out-of-sample likelihood increases and lower ex-post portfolio standard deviations compared to static models or models with homogeneous tail behavior

Keywords: matrix distributions; tail heterogeneity; (inverse) Riesz; fat-tails; realized covariance matrices (search for similar items in EconPapers)
JEL-codes: C32 C58 G17 (search for similar items in EconPapers)
Date: 2021-01-24, Revised 2023-07-11
New Economics Papers: this item is included in nep-ecm and nep-ore
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20210010

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