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Volatility comovement: a multifrequency approach

  • Calvet, Laurent E.
  • Fisher, Adlai J.
  • Thompson, Samuel B.

We implement a multifrequency volatility decomposition of three exchange rates and show that components with similar durations are strongly correlated across series. This motivates a bivariate extension of the Markov-Switching Multifractal (MSM) introduced in Calvet and Fisher (2001, 2004). Bivariate MSM is a stochastic volatility model with a closed-form likelihood. Estimation can proceed by ML for state spaces of moderate size, and by simulated likelihood via a particle filter in high-dimensional cases. We estimate the model and confirm its main assumptions in likelihood ratio tests. Bivariate MSM compares favorably to a standard multivariate GARCH both in- and out-of-sample. We extend the model to multivariate settings with a potentially large number of assets by proposing a parsimonious multifrequency factor structure.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 131 (2006)
Issue (Month): 1-2 ()
Pages: 179-215

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Handle: RePEc:eee:econom:v:131:y:2006:i:1-2:p:179-215
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