Heteroscedasticity test of high-frequency data with jumps and microstructure noise

Qiang Liu, Zhi Liu and Chuanhai Zhang

Papers from arXiv.org

Abstract: In this paper, we are interested in testing if the volatility process is constant or not during a given time span by using high-frequency data with the presence of jumps and microstructure noise. Based on estimators of integrated volatility and spot volatility, we propose a nonparametric way to depict the discrepancy between local variation and global variation. We show that our proposed test estimator converges to a standard normal distribution if the volatility is constant, otherwise it diverges to infinity. Simulation studies verify the theoretical results and show a good finite sample performance of the test procedure. We also apply our test procedure to do the heteroscedasticity test for some real high-frequency financial data. We observe that in almost half of the days tested, the assumption of constant volatility within a day is violated. And this is due to that the stock prices during opening and closing periods are highly volatile and account for a relative large proportion of intraday variation.

Date: 2020-10
New Economics Papers: this item is included in nep-ecm and nep-mst
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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2010.07659

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