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We propose a technique to avoid spurious detections of jumps in highfrequency data via an explicit thresholding on available test statistics



    (University of Geneva)

  • Olivier SCAILLET

    (University of Geneva and Swiss Finance Institute)


We prove that it eliminates asymptotically all spurious detections. Monte Carlo results show that it performs also well in nite samples. In Dow Jones stocks, spurious detections represent up to 50% of the jumps detected initially between 2006 and 2008. For the majority of stocks, jumps do not cluster in time and no cojump a ects all stocks simultaneously, suggesting jump risk is diversi able. We relate the remaining jumps to macroeconomic news, prescheduled company-speci c announcements, and stories from news agencies which include a variety of unscheduled and uncategarized events. The majority of news do not cause jumps. One exception are share buybacks announcements. Fed rate news have an important impact but rarely cause jumps. Another nding is that 60% of jumps occur without any news event. For one third of the jumps with no news we observe an unusual behavior in the volume of transactions. Hence, liquidity pressures are probably another important factor of jumps.

Suggested Citation

  • Pierre BAJGROWICZ & Olivier SCAILLET, "undated". "We propose a technique to avoid spurious detections of jumps in highfrequency data via an explicit thresholding on available test statistics," Swiss Finance Institute Research Paper Series 11-36, Swiss Finance Institute.
  • Handle: RePEc:chf:rpseri:rp1136

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    References listed on IDEAS

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    More about this item


    jumps; high-frequency data; spurious detections; jumps dynamics; news releases; cojumps;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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