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Modeling dependence dynamics through copulas with regime switching

Osvaldo Candido (), Flavio Augusto Ziegelmann and Michael Dueker

Insurance: Mathematics and Economics, 2012, vol. 50, issue 3, 346-356

Abstract: Measuring dynamic dependence between international financial markets has recently attracted great interest in financial econometrics because the observed correlations rose dramatically during the 2008–09 global financial crisis. Here, we propose a novel approach for measuring dependence dynamics. We include a hidden Markov chain (MC) in the equation describing dependence dynamics, allowing the unobserved time-varying dependence parameter to vary according to both a restricted ARMA process and an unobserved two-state MC. Estimation is carried out via the inference for the margins in conjunction with filtering/smoothing algorithms. We use block bootstrapping to estimate the covariance matrix of our estimators. Monte Carlo simulations compare the performance of regime switching and no switching models, supporting the regime-switching specification. Finally the proposed approach is applied to empirical data, through the study of the S&P500 (USA), FTSE100 (UK) and BOVESPA (Brazil) stock market indexes.

Keywords: Asymmetric dependence; Copulas; Markov switching; Bootstrap test (search for similar items in EconPapers)
JEL-codes: C15 C46 G15 (search for similar items in EconPapers)
Date: 2012
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DOI: 10.1016/j.insmatheco.2012.01.001

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