Assessing tail risk for nonlinear dependence of MSCI sector indices: A copula three-stage approach

Giovanni de Luca (), Dominique Guegan () and Giorgia Rivieccio ()
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Giovanni de Luca: Parthenope University - PARTHENOPE - Università degli Studi di Napoli “Parthenope” = University of Naples
Dominique Guegan: UP1 - Université Paris 1 Panthéon-Sorbonne, CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, Labex ReFi - UP1 - Université Paris 1 Panthéon-Sorbonne, University of Ca’ Foscari [Venice, Italy]
Giorgia Rivieccio: Parthenope University - PARTHENOPE - Università degli Studi di Napoli “Parthenope” = University of Naples

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: The author propose a copula-based three-stage estimation technique in order to describe the serial and cross-sectional nonlinear dependence among financial multiple time series, exploring the existence of tail risk. We find out on MSCI World Sector Indices the higher performance of the approach against the classical Vector AutoRegressive models, giving the implications of misspecified assumptions for margins and/or joint distribution and providing tail dependence measures of financial variables involved in the analysis.

Keywords: Tail dependence; Multiple time series; Copula function; Three stage estimator (search for similar items in EconPapers)
Date: 2018-10
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Published in Finance Research Letters, 2018, ⟨10.1016/j.frl.2018.10.018⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:cesptp:halshs-01917629

DOI: 10.1016/j.frl.2018.10.018

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