Lin Deng, Michael Stanley Smith, Worapree Maneesoonthorn
arXiv 16 May 2025 · Statistics — Methodology
arXiv:2505.10849 · PDF · DOI · OpenAlex · Extracted main text
Multivariate distributions that allow for asymmetry and heavy tails are important building blocks in many econometric and statistical models. The Unified Skew-t (UST) is a promising choice because it is both scalable and allows for a high level of flexibility in the asymmetry in the distribution. However, it suffers from parameter identification and computational hurdles that have to date inhibited its use for modeling data. In this paper we propose a new tractable variant of the unified skew-t (TrUST) distribution that addresses both challenges. Moreover, the copula of this distribution is shown to also be tractable, while allowing for greater heterogeneity in asymmetric dependence over variable pairs than the popular skew-t copula. We show how Bayesian posterior inference for both the distribution and its copula can be computed using an extended likelihood derived from a generative representation of the distribution. The efficacy of this Bayesian method, and the enhanced flexibility of both the TrUST distribution and its implicit copula, is first demonstrated using simulated data. Applications of the TrUST distribution to highly skewed regional Australian electricity prices, and the TrUST copula to intraday U.S. equity returns, demonstrate how our proposed distribution and its copula can provide substantial increases in accuracy over the popular skew-t and its copula in practice.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Deng, L., Smith, M. S., and Maneesoonthorn, W (2025) Large skew-t copula models and asymmetric dependence in intraday equity returns self | 1.000 | 8 | 4 | 100% |
| 2 | Azzalini, A. and Capitanio, A (2003) Distributions generated by perturbation of symmetry with emphasis on a multivariate skew t -distribution | 0.928 | 4 | 4 | 100% |
| 3 | Yoshiba, T (2018) Maximum likelihood estimation of skew-t copulas with its applications to stock returns | 0.928 | 4 | 3 | 100% |
| 4 | Arellano-Valle, R. B. and Azzalini, A (2006) On the unification of families of skew-normal distributions | 0.928 | 4 | 3 | 100% |
| 5 | Wang, K., Karling, M. J., Arellano-Valle, R. B., and Genton, M. G (2024) Multivariate unified skew-t distributions and their properties | 0.928 | 4 | 3 | 100% |
| 6 | Oh, D. H. and Patton, A. J (2023) Dynamic factor copula models with estimated cluster assignments | 0.737 | 3 | 2 | 100% |
| 7 | Wang, K., Arellano-Valle, R. B., Azzalini, A., and Genton, M. G (2023) On the non-identifiability of unified skew-normal distributions | 0.737 | 3 | 2 | 100% |
| 8 | Smith, M. S. and Maneesoonthorn, W (2018) Inversion copulas from nonlinear state space models with an application to inflation forecasting self | 0.644 | 2 | 2 | 100% |
| 9 | Ando, T., Greenwood-Nimmo, M., and Shin, Y (2022) Quantile connectedness: modeling tail behavior in the topology of financial networks | 0.644 | 2 | 2 | 100% |
| 10 | Branco, M. D. and Dey, D. K (2001) A general class of multivariate skew-elliptical distributions | 0.644 | 2 | 2 | 100% |
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