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Volatility Comovement: A Multifrequency Approach

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

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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Paper provided by National Bureau of Economic Research, Inc in its series NBER Technical Working Papers with number 0300.

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Date of creation: Aug 2004
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Publication status: published as Calvet, Laurent E., Adlai J. Fisher and Samuel B. Thompson. "Volatility Comovement: A Multifrequency Approach," Journal of Econometrics, 2006, v131(1-2,Mar-Apr), 179-215.
Handle: RePEc:nbr:nberte:0300
Note: TWP
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