Closed-Form Multi-Factor Copula Models with Observation-Driven Dynamic Factor Loadings

Anne Opschoor, Andre Lucas, Istvan Barra and Dick van Dijk
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Anne Opschoor: Vrije Universiteit Amsterdam
Istvan Barra: Independent Research

No 19-013/IV, Tinbergen Institute Discussion Papers from Tinbergen Institute

Abstract: We develop new multi-factor dynamic copula models with time-varying factor loadings and observation-driven dynamics. The new models are highly flexible, scalable to high dimensions, and ensure positivity of covariance and correlation matrices. A closed-form likelihood expression allows for straightforward parameter estimation and likelihood in- ference. We apply the new model to a large panel of 100 U.S. stocks over the period 2001Ð2014. The proposed multi-factor structure is much better than existing (single- factor) models at describing stock return dependence dynamics in high-dimensions. The new factor models also improve one-step-ahead copula density forecasts and global min- imum variance portfolio performance. Finally, we investigate different mechanisms to allocate firms into groups and find that a simple industry classification outperforms al- ternatives based on observable risk factors, such as size, value or momentum.

Keywords: factor copulas; factor structure; score-driven dynamics; multivariate density forecast (search for similar items in EconPapers)
JEL-codes: C32 C58 G17 (search for similar items in EconPapers)
Date: 2019-02-19, Revised 2019-10-23
New Economics Papers: this item is included in nep-ecm and nep-ets
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Journal Article: Closed-Form Multi-Factor Copula Models With Observation-Driven Dynamic Factor Loadings (2021)
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Persistent link: https://EconPapers.repec.org/RePEc:tin:wpaper:20190013

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