Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/36744
Authors: 
Caporale, Guglielmo Maria
Gil-Alana, Luis A.
Year of Publication: 
2010
Series/Report no.: 
DIW Discussion Papers 1016
Abstract: 
This paper analyses the long-memory properties of high frequency financial time series. It focuses on temporal aggregation and the influence that this might have on the degree of dependence of the series. Fractional integration or I(d) models are estimated with a variety of specifications for the error term. In brief, we find evidence that a lower degree of integration is associated with lower data frequencies. In particular, when the data are collected every 10 minutes there are several cases with values of d strictly smaller than 1, implying mean-reverting behaviour. This holds for all four series examined, namely Open, High, Low and Last observations for the British pound/US dollar spot exchange rate.
Subjects: 
High frequency data
long memory
volatility persistence
structural breaks
JEL: 
C22
Document Type: 
Working Paper

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