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Modeling dependence dynamics through copulas with regime switching

  • Silva Filho, Osvaldo Candido da
  • Ziegelmann, Flavio Augusto
  • Dueker, Michael J.

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.

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Article provided by Elsevier in its journal Insurance: Mathematics and Economics.

Volume (Year): 50 (2012)
Issue (Month): 3 ()
Pages: 346-356

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Handle: RePEc:eee:insuma:v:50:y:2012:i:3:p:346-356
Contact details of provider: Web page: http://www.elsevier.com/locate/inca/505554

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  12. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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