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Forecasting Stock Index Volatility: The Incremental Information in the Intraday High-Low Price Range

Author

Listed:
  • Charles Corrado
  • Cameron Truong

    (University of Auckland)

Abstract

We compare the incremental information content of implied volatility and intraday high-low range volatility in the context of conditional volatilityforecasts for three major market indexes: the S&P 100, the S&P 500, and the Nasdaq 100. Evidence obtained from out-of-sample volatility forecasts indicates that neither implied volatility nor intraday high-low range volatility subsumes entirely the incremental information contained in the other. Our findings suggest that intraday high-low range volatility can usefully augment conditional volatility forecasts for these market indexes.

Suggested Citation

  • Charles Corrado & Cameron Truong, 2004. "Forecasting Stock Index Volatility: The Incremental Information in the Intraday High-Low Price Range," Research Paper Series 127, Quantitative Finance Research Centre, University of Technology, Sydney.
    • Handle: RePEc:uts:rpaper:127
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    File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp127.pdf
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    References listed on IDEAS

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    Cited by:

    1. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2008. "Volatility forecasting using threshold heteroskedastic models of the intra-day range," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2990-3010, February.

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