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What is the source of different levels of time-series return volatility? the intraday U-shaped pattern or time-series persistence

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  • Michael Hughes
  • Drew Winters
  • Jerry Rawls

Abstract

We use the NYSE industrial index, the NYSE utility index, and the NASDAQ industrial index to examine the relationship between short-run and long-run volatility. We establish that the NASDAQ index has substantially more daily volatility than the NYSE indices. The initial examination shows that the individual U-shaped intraday patterns of the two NYSE indices are roughly similar in both position and shape, while we find that NASDAQ U-shaped pattern is distinctively different in both position and shape. However, after controlling for conditional volatility in a GARCH model, the U-shaped intraday volatility patterns of all three indices are similar. Copyright Springer 2005

Suggested Citation

  • Michael Hughes & Drew Winters & Jerry Rawls, 2005. "What is the source of different levels of time-series return volatility? the intraday U-shaped pattern or time-series persistence," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 29(3), pages 300-312, September.
    • Handle: RePEc:spr:jecfin:v:29:y:2005:i:3:p:300-312
    DOI: 10.1007/BF02761576
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    References listed on IDEAS

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    1. Lockwood, Larry J & Linn, Scott C, 1990. "An Examination of Stock Market Return Volatility during Overnight and Intraday Periods, 1964-1989," Journal of Finance, American Finance Association, vol. 45(2), pages 591-601, June.
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    3. Ito, Takatoshi & Lin, Wen-Ling, 1992. "Lunch break and intraday volatility of stock returns : An hourly data analysis of Tokyo and New York stock markets," Economics Letters, Elsevier, vol. 39(1), pages 85-90, May.
    4. Chou, Ray Yeutien, 1988. "Volatility Persistence and Stock Valuations: Some Empirical Evidence Using Garch," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(4), pages 279-294, October-D.
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    Cited by:

    1. Jang Hyung Cho & Robert T. Daigler, 2012. "An unbiased autoregressive conditional intraday seasonal variance filtering process," Quantitative Finance, Taylor & Francis Journals, vol. 12(2), pages 231-247, October.

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