The Intraday Periodicity and Long-memory Characters in High-frequency Data of China Stock Market

Li Bin TAO;Zhao Ben FANG;Wan Bin PAN

Systems Engineering - Theory & Practice ›› 2004, Vol. 24 ›› Issue (6) : 26-32.

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Systems Engineering - Theory & Practice ›› 2004, Vol. 24 ›› Issue (6) : 26-32. DOI: 10.12011/1000-6788(2004)6-26
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The Intraday Periodicity and Long-memory Characters in High-frequency Data of China Stock Market

  • Li Bin TAO,Zhao Ben FANG,Wan Bin PAN
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Abstract

By FFF regression of Andersen and Bollerslev(1997), we analysis the periodicity of Shanghai stock index 5-min high frequency data and the long memory characters in filtered absolute returns. We document that the periodicity of intraday absolute returns is stronger than that of raw intraday returns, and FFF regression is an efficient way of determining the periodicity. After comparing the previous results, we found that the long memory in high-frequency absolute returns is stronger than that of daily returns...

Key words

periodicity / long memory / high-frequency data

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Li Bin TAO , Zhao Ben FANG , Wan Bin PAN. The Intraday Periodicity and Long-memory Characters in High-frequency Data of China Stock Market. Systems Engineering - Theory & Practice, 2004, 24(6): 26-32 https://doi.org/10.12011/1000-6788(2004)6-26
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