Long Memory and Fractional Integration in High Frequency Financial Time Series

29 Pages Posted: 15 Jul 2010

See all articles by Guglielmo Maria Caporale

Guglielmo Maria Caporale

Brunel University London - Department of Economics and Finance; London South Bank University; CESifo (Center for Economic Studies and Ifo Institute); German Institute for Economic Research (DIW Berlin)

Luis A. Gil-Alana

University of Navarra - Department of Economics

Date Written: June 2010

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.

Keywords: High frequency data; long memory; volatility persistence; structural breaks

JEL Classification: C22

Suggested Citation

Caporale, Guglielmo Maria and Gil-Alana, Luis A., Long Memory and Fractional Integration in High Frequency Financial Time Series (June 2010). DIW Berlin Discussion Paper No. 1016, Available at SSRN: https://ssrn.com/abstract=1639836 or http://dx.doi.org/10.2139/ssrn.1639836

Guglielmo Maria Caporale (Contact Author)

Brunel University London - Department of Economics and Finance ( email )

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London South Bank University ( email )

Centre for Monetary and Financial Economics
London
United Kingdom

CESifo (Center for Economic Studies and Ifo Institute)

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Munich, DE-81679
Germany

German Institute for Economic Research (DIW Berlin) ( email )

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Berlin, 10117
Germany

Luis A. Gil-Alana

University of Navarra - Department of Economics ( email )

Campus de Arrosadia
Pamplona, 31006
Spain

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