Why Frequency Matters for Unit Root Testing in Financial Time Series

H. Peter Boswijk () and Franc Klaassen

Journal of Business & Economic Statistics, 2011, vol. 30, issue 3, 351-357

Abstract: It is generally believed that the power of unit root tests is determined only by the time span of observations, not by their sampling frequency. We show that the sampling frequency does matter for stock data displaying fat tails and volatility clustering, such as financial time series. Our claim builds on recent work on unit root testing based on non-Gaussian GARCH-based likelihood functions. Such methods yield power gains in the presence of fat tails and volatility clustering, and the strength of these features increases with the sampling frequency. This is illustrated using local power calculations and an empirical application to real exchange rates.

Date: 2011
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DOI: 10.1080/07350015.2011.648858

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