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Regime Switching for Dynamic Correlations

  • Denis Pelletier

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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Paper provided by Econometric Society in its series Econometric Society 2004 North American Summer Meetings with number 230.

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Date of creation: 11 Aug 2004
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Handle: RePEc:ecm:nasm04:230
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