Testing and detecting jumps based on a discretely observed process

Yingying Fan, Jianqing Fan

Research output: Contribution to journalArticlepeer-review

16 Scopus citations


We propose a new nonparametric test for detecting the presence of jumps in asset prices using discretely observed data. Compared with the test in At-Sahalia and Jacod (2009), our new test enjoys the same asymptotic properties but has smaller variance. These results are justified both theoretically and numerically. We also propose a new procedure to locate the jumps. The jump identification problem reduces to a multiple comparison problem. We employ the false discovery rate approach to control the probability of type I error. Numerical studies further demonstrate the power of our new method.

Original languageEnglish (US)
Pages (from-to)331-344
Number of pages14
JournalJournal of Econometrics
Issue number2
StatePublished - Oct 1 2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Economics and Econometrics


  • False discovery rate
  • High frequency
  • Jump diffusion process
  • Stable convergence
  • Test for jumps


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