Kim Christensen, Roel C. A. Oomen, Mark Podolskij
arXiv 11 Feb 2026 · Econometrics
arXiv:2602.10925 · PDF · Extracted main text
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.
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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.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | S. S. Lee and P. A. Mykland (2008) Jumps in financial markets: A new nonparametric test and jump dynamics | 0.854 | 15 | 2 | 93% |
| 2 | B. Eraker and M. Johannes and N. Polson (2003) The impact of jumps in volatility and returns | 0.843 | 4 | 3 | 75% |
| 3 | Y. Aït-Sahalia and J. Jacod (2009) Estimating the degree of activity of jumps in high frequency data | 0.843 | 3 | 3 | 100% |
| 4 | M. Podolskij and M. Vetter (2009) Bipower-type estimation in a noisy diffusion setting self | 0.754 | 7 | 4 | 43% |
| 5 | Y. Aït-Sahalia and J. Jacod (2009) Testing for jumps in a discretely observed process | 0.737 | 3 | 2 | 100% |
| 6 | T. G. Andersen and L. Benzoni and J. Lund (2002) An empirical investigation of continuous-time equity return models | 0.737 | 3 | 2 | 100% |
| 7 | O. E. Barndorff-Nielsen and N. Shephard (2004) Power and bipower variation with stochastic volatility and jumps | 0.737 | 3 | 2 | 100% |
| 8 | K. Christensen and R. C. A. Oomen and M. Podolskij (2013) Appendix to Fact or friction: Jumps at ultra high frequency self | 0.737 | 3 | 2 | 100% |
| 9 | X. Huang and G. Tauchen (2005) The relative contribution of jumps to total price variance | 0.737 | 3 | 2 | 100% |
| 10 | J. 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 self | 0.737 | 3 | 2 | 100% |
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