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Regime switching for dynamic correlations

  • Pelletier, Denis

We propose a new model for the variance between multiple time series, the Regime Switching Dynamic Correlation. We decompose the covariances into correlations and standard deviations and the correlation matrix follow a regime switching model; it is constant within a regime but different across regimes. The transitions between the regimes are governed by a Markov chain. This model does not suffer from a curse of dimensionality and it allows analytic computation of multi-step ahead conditional expectations of the variance matrix. We also present an empirical application which illustrates that our model can have a better in-sample fit of the data than the Dynamic Conditional Correlation model proposed by Engle(JBES, 2002)

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 131 (2006)
Issue (Month): 1-2 ()
Pages: 445-473

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Handle: RePEc:eee:econom:v:131:y:2006:i:1-2:p:445-473
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