Testing the volatility jumps based on the high frequency data

Guangying Liu, Meiyao Liu and Jinguan Lin

Journal of Time Series Analysis, 2022, vol. 43, issue 5, 669-694

Abstract: This article tests volatility jumps based on the high frequency data. Under the null hypothesis that the volatility process is a continuous semimartingale, our test statistic converges to a normal distribution, and under the alternative hypothesis where the volatility has jumps, the statistic diverges to infinity. Compared to the test statistic of Bibinger et al. (Bibinger et al. (2017). Annals of Statistics 45, 1542–1578), our proposed statistic diverges to infinity at a faster rate, and has a better power. Simulation studies confirm the theoretical results, and an empirical analysis shows that some real financial data possess volatility jumps.

Date: 2022
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https://doi.org/10.1111/jtsa.12634

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:43:y:2022:i:5:p:669-694

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