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Identifying events in financial time series – A new approach with bipower variation

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  • Andor, György
  • Bohák, András

Abstract

We present a statistical test to identify significant events in financial price time series. In contrast to “jumps,” we define “events” as non-instantaneous, but nevertheless unusually fast and large, price changes. We show that non-parametric tests perform badly in detecting events so defined. We propose a new approach to explore the dependence of jump detection statistics on the sampling method used and find that our method improves the event detection rate of the standard test by a factor of three.

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  • Andor, György & Bohák, András, 2017. "Identifying events in financial time series – A new approach with bipower variation," Finance Research Letters, Elsevier, vol. 22(C), pages 42-48.
    • Handle: RePEc:eee:finlet:v:22:y:2017:i:c:p:42-48
    DOI: 10.1016/j.frl.2016.11.003
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    References listed on IDEAS

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