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Dynamic Copulas and Long Range Dependence

23 Pages Posted: 29 Feb 2012  

Beatriz V.M. Mendes

Instituto Nacional de Matemática Pura e Aplicada (IMPA)

Silvia Regina Costa Lopes

University of Sao Paulo (USP) - Institute of Mathematics and Statistics (IME)

Date Written: October 1, 2011

Abstract

This paper extends the evolution equation of Patton (2006) for the time variation of the copula parameters by specifying an autoregressive fractionally integrated term. For any copula parameter there is a suitable one-to-one transformation so that the maximum likelihood estimation method may be employed. It is suggested an exploratory tool based on the copula data cross products for detecting the presence of long range dependence on the copula level of real data. We simulate from copula models possessing long range dependence and work out two examples using real data. Modeling long range dependence on the level of dynamic copulas has the potential for providing improved forecasts and are useful for financial and economic applications.

Keywords: Long Memory, Conditional Copulas, Time Series, Financial

JEL Classification: C22, C51, G10

Suggested Citation

Mendes, Beatriz V.M. and Costa Lopes, Silvia Regina, Dynamic Copulas and Long Range Dependence (October 1, 2011). Frontiers in Finance and Economics, Vol. 8, No. 2, pp. 89-111, 2011. Available at SSRN: https://ssrn.com/abstract=2012497

Beatriz V.M. Mendes (Contact Author)

Instituto Nacional de Matemática Pura e Aplicada (IMPA) ( email )

Estrada Dona Castorina 110
Rio de Janeiro, 22460
Brazil

Silvia Regina Costa Lopes

University of Sao Paulo (USP) - Institute of Mathematics and Statistics (IME)

Sao Paulo
Brazil

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