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Forecasting Stock Index Volatility: The Incremental Information in the Intraday High-Low Price Range. (2004). Corrado, Charles ; Truong, Cameron.
In: Research Paper Series.
RePEc:uts:rpaper:127.

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  1. Volatility forecasting using threshold heteroskedastic models of the intra-day range. (2008). Lin, Edward ; Chen, Cathy W. S. ; Lin, Edward M. H., ; Gerlach, Richard.
    In: Computational Statistics & Data Analysis.
    RePEc:eee:csdana:v:52:y:2008:i:6:p:2990-3010.

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References

References cited by this document

  1. Alizadeh, S., Brandt, M.W., and Diebold, F.X. (2002). Range-based estimation of stochastic volatility models. Journal of Finance, 57, 1047-1091.

  2. Andersen, T.G., Bollerslev, T. (1998). Answering the skeptics: Yes, standard volatility models do provide accurate forecasts. International Economics Review, 39, 885-905.

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  6. Areal, N.M.P.C. and Taylor, S.J. (2002). The realized volatility of FTSE-100 futures prices. Journal Futures Markets, 22, 627-648.
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  7. Bai, X., Russell, J.R. and Tiao, J.C. (2001). Beyond Mertons Utopia: effects of nonnormality and dependence on the precision of variance estimates using high-frequency financial data. Working Paper, University of Chicago.
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  8. Ball, C.A. and Torous, W.N. (1984). The maximum likelihood estimation of security price volatility: Theory, evidence, and application to option pricing. Journal of Business, 57, 97-112.

  9. Blair, B.J., Poon, S.H., and Taylor, S.J. (2001). Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns. Journal of Econometrics, 105, 5-26.

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  13. Bollerslev, T., Chou, R.Y., and Kroner, K.F. (1992). ARCH modeling in finance: a review of the theory and empirical evidence. Journal of Econometrics 52, 559.

  14. Bollerslev, T., Engle, R.F., and Nelson, D.B. (1994). ARCH Models, Chapter 49 of Handbook of Econometrics, Vol. 4, North-Holland.
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  15. Britten-Jones, M. and Neuberger, A. (2000). Option prices, implied price processes, and stochastic volatility. Journal of Finance 45, 839866.

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