Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/36744 
Year of Publication: 
2010
Series/Report no.: 
DIW Discussion Papers No. 1016
Publisher: 
Deutsches Institut für Wirtschaftsforschung (DIW), Berlin
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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