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Fact or friction: Jumps at ultra high frequency

Kim Christensen, Roel C. A. Oomen, Mark Podolskij

arXiv 11 Feb 2026 · Econometrics

arXiv:2602.10925 · PDF · Extracted main text

Abstract

This paper shows that jumps in financial asset prices are often erroneously identified and are, in fact, rare events accounting for a very small proportion of the total price variation. We apply new econometric techniques to a comprehensive set of ultra high-frequency equity and foreign exchange tick data recorded at millisecond precision, allowing us to examine the price evolution at the individual order level. We show that in both theory and practice, traditional measures of jump variation based on lower-frequency data tend to spuriously assign a burst of volatility to the jump component. As a result, the true price variation coming from jumps is overstated. Our estimates based on tick data suggest that the jump variation is an order of magnitude smaller than typical estimates found in the existing literature.

Citation extraction

86
references
146
in-text mentions
86
distinct cited
10
self-citations
13,189
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1S. S. Lee and P. A. Mykland (2008) Jumps in financial markets: A new nonparametric test and jump dynamics0.85415293%
2B. Eraker and M. Johannes and N. Polson (2003) The impact of jumps in volatility and returns0.8434375%
3Y. Aït-Sahalia and J. Jacod (2009) Estimating the degree of activity of jumps in high frequency data0.84333100%
4M. Podolskij and M. Vetter (2009) Bipower-type estimation in a noisy diffusion setting self0.7547443%
5Y. Aït-Sahalia and J. Jacod (2009) Testing for jumps in a discretely observed process0.73732100%
6T. G. Andersen and L. Benzoni and J. Lund (2002) An empirical investigation of continuous-time equity return models0.73732100%
7O. E. Barndorff-Nielsen and N. Shephard (2004) Power and bipower variation with stochastic volatility and jumps0.73732100%
8K. Christensen and R. C. A. Oomen and M. Podolskij (2013) Appendix to Fact or friction: Jumps at ultra high frequency self0.73732100%
9X. Huang and G. Tauchen (2005) The relative contribution of jumps to total price variance0.73732100%
10J. Jacod and Y. Li and P. A. Mykland and M. Podolskij and M. Vetter (2009) Microstructure noise in the continuous case: The pre-averaging approach self0.73732100%

Showing the top 10 of 86 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
1Is the diurnal pattern sufficient to explain intraday variation in volatility? A nonparametric assessment1.00054
2Warp Speed Price Moves: Jumps after Earnings Announcements0.85586
3Sluggish news reactions: A combinatorial approach for synchronizing stock jumps0.73733
4Inference from high-frequency data: A subsampling approach0.64441
5The drift burst hypothesis-0.50cm0.64422
6The realized empirical distribution function of stochastic variance with application to goodness-of-fit testing0.64422
7Asymptotic theory of range-based multipower variation0.64422
8Estimating spot volatility under infinite variation jumps with dependent market microstructure noise0.40511
9Sequential Cauchy Combination Test for Multiple Testing Problems with Financial Applications0.40511
10Real-Time Detection of Local No-Arbitrage Violations0.40511