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Long Memory and Fractional Integration in High Frequency Data on the US Dollar / British Pound Spot Exchange Rate

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  • Guglielmo Maria Caporale
  • Luis A. Gil-Alana

Abstract

This paper analyses the long-memory properties of a high-frequency financial time series dataset. It focuses on temporal aggregation and other features of the data, and how they might affect 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; however, for higher data frequencies the unit root null cannot be rejected. This holds for all four series examined, namely Open, High, Low and Last observations for the US dollar / British pound spot exchange rate and for different sample periods.

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File URL: http://www.cesifo-group.de/portal/page/portal/DocBase_Content/WP/WP-CESifo_Working_Papers/wp-cesifo-2013/wp-cesifo-2013-04/cesifo1_wp4224.pdf
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Bibliographic Info

Paper provided by CESifo Group Munich in its series CESifo Working Paper Series with number 4224.

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Date of creation: 2013
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Handle: RePEc:ces:ceswps:_4224

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Related research

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

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References

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  1. Uwe Hassler, 2011. "Estimation of fractional integration under temporal aggregation," Post-Print peer-00815563, HAL.
  2. Leonardo Rocha Souza, 2007. "Temporal Aggregation and Bandwidth selection in estimating long memory," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 701-722, 09.
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  13. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2002. "Fractional integration and mean reversion in stock prices," The Quarterly Review of Economics and Finance, Elsevier, vol. 42(3), pages 599-609.
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Cited by:
  1. Slim Chaouachi & Zied Ftiti & Frederic Teulon, 2014. "Explaining the Tunisian Real Exchange: Long Memory versus Structural Breaks," Working Papers 2014-147, Department of Research, Ipag Business School.
  2. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.

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