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Modeling foreign exchange rates with jumps

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Author Info

  • John M Maheu
  • Thomas H McCurdy

Abstract

We propose a new discrete-time model of returns in which jumps capture persistence in the conditional variance and higher-order moments. Jump arrival is governed by a heterogeneous Poisson process. The intensity is directed by a latent stochastic autoregressive process, while the jump-size distribution allows for conditional heteroskedasticity. Model evaluation focuses on the dynamics of the conditional distribution of returns using density and variance forecasts. Predictive likelihoods provide a period-by-period comparison of the performance of our heterogeneous jump model relative to conventional SV and GARCH models. Further, in contrast to previous studies on the importance of jumps, we utilize realized volatility to assess out-of-sample variance forecasts.

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File URL: http://www.economics.utoronto.ca/public/workingPapers/tecipa-279-1.pdf
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Bibliographic Info

Paper provided by University of Toronto, Department of Economics in its series Working Papers with number tecipa-279.

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Length: 34 pages
Date of creation: 02 Feb 2007
Date of revision:
Handle: RePEc:tor:tecipa:tecipa-279

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Related research

Keywords: jump clustering; jump dynamics; MCMC; predictive likelihood; realized volatility; Bayesian model average;

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References

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  3. John M. Maheu & Thomas H. McCurdy, 2004. "News Arrival, Jump Dynamics, and Volatility Components for Individual Stock Returns," Journal of Finance, American Finance Association, vol. 59(2), pages 755-793, 04.
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Citations

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Cited by:
  1. Peter Christoffersen & Kris Jacobs & Chayawat Ornthanalai, 2009. "Exploring Time-Varying Jump Intensities: Evidence from S&P500 Returns and Options," CIRANO Working Papers 2009s-34, CIRANO.
  2. Park, Beum-Jo, 2010. "Surprising information, the MDH, and the relationship between volatility and trading volume," Journal of Financial Markets, Elsevier, vol. 13(3), pages 344-366, August.

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