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Testing for jumps based on high-frequency data: a method exploiting microstructure noise

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  • Guangying Liu
  • Jing Xiang
  • Yuquan Cang

Abstract

This paper tests for jumps of the price process based on noisy high-frequency data. Under the null hypothesis that the price process is continuous, the test statistic converges to a normal distribution, and under the alternative hypothesis that the price has jumps, the statistic converges to infinity. Compared with the test of Aït-Sahalia et al. [Testing for jumps in noisy high frequency data. J. Econom., 2012, 168(2), 207–222], our proposed statistic uses information on the microstructure noise, tends to infinity more rapidly under the alternative hypothesis and has a better power. A simulation confirms the theoretical results and an empirical study illustrates the practical application of the method.

Suggested Citation

  • Guangying Liu & Jing Xiang & Yuquan Cang, 2020. "Testing for jumps based on high-frequency data: a method exploiting microstructure noise," Quantitative Finance, Taylor & Francis Journals, vol. 20(11), pages 1795-1809, November.
    • Handle: RePEc:taf:quantf:v:20:y:2020:i:11:p:1795-1809
    DOI: 10.1080/14697688.2020.1772497
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    Cited by:

    1. Guangying Liu & Meiyao Liu & Jinguan Lin, 2022. "Testing the volatility jumps based on the high frequency data," Journal of Time Series Analysis, Wiley Blackwell, vol. 43(5), pages 669-694, September.

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