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

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Tác giả: Qiang Liu, Zhi Liu, Chuanhai Zhang

Ngôn ngữ: eng

Ký hiệu phân loại: 616.862 Diseases

Thông tin xuất bản: 2020

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Bộ sưu tập: Metadata

ID: 165389

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.
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