Volatility Comovement: A Multifrequency Approach

42 Pages Posted: 15 Aug 2007 Last revised: 29 Oct 2021

See all articles by Laurent E. Calvet

Laurent E. Calvet

EDHEC Business School - Department of Economics & Finance; CEPR

Adlai J. Fisher

University of British Columbia (UBC) - Sauder School of Business

Samuel Brodsky Thompson

Arrowstreet Capital, L.P.

Multiple version iconThere are 2 versions of this paper

Date Written: August 2004

Abstract

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.

Suggested Citation

Calvet, Laurent E. and Fisher, Adlai J. and Thompson, Samuel Brodsky, Volatility Comovement: A Multifrequency Approach (August 2004). NBER Working Paper No. t0300, Available at SSRN: https://ssrn.com/abstract=583421

Laurent E. Calvet (Contact Author)

EDHEC Business School - Department of Economics & Finance ( email )

France

CEPR ( email )

33 Great Sutton Street
London, EC1V 0DX
United Kingdom

Adlai J. Fisher

University of British Columbia (UBC) - Sauder School of Business ( email )

2053 Main Mall
Vancouver, BC V6T 1Z2
Canada
604-822-8331 (Phone)
604-822-4695 (Fax)

HOME PAGE: http://finance.sauder.ubc.ca/~fisher

Samuel Brodsky Thompson

Arrowstreet Capital, L.P. ( email )

44 Brattle St., 5th Floor
Cambridge, MA 02138
United States
617 349 2254 (Phone)

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