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Modeling High-Frequency Foreign Exchange Data Dynamics

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  • JORDÀ, ÒSCAR
  • MARCELLINO, MASSIMILIANO

Abstract

This paper shows that high-frequency, irregularly spaced, foreign exchange (FX) data can generate nonnormality, conditional heteroskedasticity, and leptokurtosis when aggregated into fixed-interval calendar time, even when these features are absent in the original DGP. Furthermore, we introduce a new approach to modeling these high-frequency irregularly spaced data based on the Poisson regression model. The new model is called the autoregressive conditional intensity model and it has the advantage of being simple and of maintaining the calendar timescale. To illustrate the virtues of this approach, we examine a classical issue in FX microstructure: the variation in information content as a function of fluctuations in the intensity of activity levels.

Suggested Citation

  • Jordà, Òscar & Marcellino, Massimiliano, 2003. "Modeling High-Frequency Foreign Exchange Data Dynamics," Macroeconomic Dynamics, Cambridge University Press, vol. 7(4), pages 618-635, September.
    • Handle: RePEc:cup:macdyn:v:7:y:2003:i:04:p:618-635_02
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    Cited by:

    1. Helmut Herwartz, 2006. "Econometric analysis of high frequency data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 90(1), pages 89-104, March.

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