Long memory and fractional integration in high frequency data on the US dollar/British pound spot exchange rate

Guglielmo Maria Caporale and Luis Gil-Alana

International Review of Financial Analysis, 2013, vol. 29, issue C, 1-9

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 10min there are several cases with values of d strictly smaller than 1, implying a 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.

Keywords: High frequency data; Long memory; Volatility persistence; Structural breaks (search for similar items in EconPapers)
JEL-codes: C22 F31 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (21)

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Related works:
Working Paper: Long Memory and Fractional Integration in High Frequency Data on the US Dollar / British Pound Spot Exchange Rate (2013)
Working Paper: Long Memory and Fractional Integration in High Frequency Data on the US Dollar / British Pound Spot Exchange Rate (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:29:y:2013:i:c:p:1-9

DOI: 10.1016/j.irfa.2013.03.011

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