Bayesian Hierarchical Copula Models with a Dirichlet–Laplace Prior

Paolo Onorati and Brunero Liseo ()
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Paolo Onorati: The Department MEMOTEF, Sapienza University of Rome, 00161 Roma, Italy
Brunero Liseo: The Department MEMOTEF, Sapienza University of Rome, 00161 Roma, Italy

Stats, 2022, vol. 5, issue 4, 1-17

Abstract: We discuss a Bayesian hierarchical copula model for clusters of financial time series. A similar approach has been developed in recent paper. However, the prior distributions proposed there do not always provide a proper posterior. In order to circumvent the problem, we adopt a proper global–local shrinkage prior, which is also able to account for potential dependence structures among different clusters. The performance of the proposed model is presented via simulations and a real data analysis.

Keywords: global–local shrinkage prior; MCMC; model-based clustering; GARCH (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2022
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