Copulas and time series with long-ranged dependencies

Rémy Chicheportiche () and Anirban Chakraborti ()
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Rémy Chicheportiche: MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris, FiQuant - Chaire de finance quantitative - MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec
Anirban Chakraborti: FiQuant - Chaire de finance quantitative - MICS - Mathématiques et Informatique pour la Complexité et les Systèmes - CentraleSupélec, MAS - Mathématiques Appliquées aux Systèmes - EA 4037 - Ecole Centrale Paris

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Abstract: We review ideas on temporal dependencies and recurrences in discrete time series from several areas of natural and social sciences. We revisit existing studies and redefine the relevant observables in the language of copulas (joint laws of the ranks). We propose that copulas provide an appropriate mathematical framework to study nonlinear time dependencies and related concepts--like aftershocks, Omori law, recurrences, and waiting times. We also critically argue, using this global approach, that previous phenomenological attempts involving only a long-ranged autocorrelation function lacked complexity in that they were essentially monoscale.

Keywords: recurrence intervals; copulas; long-ranged correlations; time series (search for similar items in EconPapers)
Date: 2014-04-08
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Citations: View citations in EconPapers (7)

Published in Physical Review E : Statistical, Nonlinear, and Soft Matter Physics, 2014, 89, pp.042117. ⟨10.1103/PhysRevE.89.042117⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-00977135

DOI: 10.1103/PhysRevE.89.042117

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