This paper shows that high-frequency, irregularly-spaced, FX data can generate non-normality, conditional heteroskedasticity, and leptokurtosis when aggregated into ¯xed-interval calendar time even when these features are absent in the original D.G.P. Furthermore, we introduce a new approach to modeling these high-frequency irregularly spaced data based on the Poisson regression model.

Modeling High-Frequency Foreign Exchange Data Dynamics

MARCELLINO, MASSIMILIANO;
2003

Abstract

This paper shows that high-frequency, irregularly-spaced, FX data can generate non-normality, conditional heteroskedasticity, and leptokurtosis when aggregated into ¯xed-interval calendar time even when these features are absent in the original D.G.P. Furthermore, we introduce a new approach to modeling these high-frequency irregularly spaced data based on the Poisson regression model.
2003
Marcellino, Massimiliano; Jorda, O.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/51378
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