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Econometrics 2016, 4(4), 43; doi:10.3390/econometrics4040043

Pair-Copula Constructions for Financial Applications: A Review

Department of Statistical Analysis, Image Analysis and Machine Learning, Norwegian Computing Center, N-0314 Oslo, Norway
Academic Editor: Jean-David Fermanian
Received: 1 September 2016 / Revised: 4 October 2016 / Accepted: 18 October 2016 / Published: 29 October 2016
(This article belongs to the Special Issue Recent Developments in Copula Models)
View Full-Text   |   Download PDF [361 KB, uploaded 29 October 2016]   |  

Abstract

This survey reviews the large and growing literature on the use of pair-copula constructions (PCCs) in financial applications. Using a PCC, multivariate data that exhibit complex patterns of dependence can be modeled using bivariate copulae as simple building blocks. Hence, this model represents a very flexible way of constructing higher-dimensional copulae. In this paper, we survey inference methods and goodness-of-fit tests for such models, as well as empirical applications of the PCCs in finance and economics. View Full-Text
Keywords: pair-copula constructions; vines; dependence; conditional distribution; flexibility pair-copula constructions; vines; dependence; conditional distribution; flexibility
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Aas, K. Pair-Copula Constructions for Financial Applications: A Review. Econometrics 2016, 4, 43.

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