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Regime Switching for Dynamic Correlations

Author

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  • Denis Pelletier
Abstract
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)

Suggested Citation

  • Denis Pelletier, 2004. "Regime Switching for Dynamic Correlations," Econometric Society 2004 North American Summer Meetings 230, Econometric Society.
    • Handle: RePEc:ecm:nasm04:230
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    More about this item

    Keywords

    dynamic correlation; regime switching; markov chain; ARMACH;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • G0 - Financial Economics - - General
    • G1 - Financial Economics - - General Financial Markets

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