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Regime Switching for Dynamic Correlations Author info | Abstract | Publisher info | Download info | Related research | Statistics Denis Pelletier
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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 2004Date of revision:
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Keywords: dynamic correlation ; regime switching ; markov chain ; ARMACH ; Other versions of this item:
Find related papers by JEL classification: C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications G0 - Financial Economics - - General G1 - Financial Economics - - General Financial Markets
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