Long Memory and Fractional Integration in High Frequency Financial Time Series

Guglielmo Maria Caporale and Luis Gil-Alana

No 1016, Discussion Papers of DIW Berlin from DIW Berlin, German Institute for Economic Research

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 (search for similar items in EconPapers)
JEL-codes: C22 (search for similar items in EconPapers)
Pages: 25 p.
Date: 2010
New Economics Papers: this item is included in nep-cba, nep-ets, nep-ifn and nep-mst
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:diw:diwwpp:dp1016

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