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Volatility forecasting in the framework of the option expiry cycle

Author

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  • Owain Ap Gwilym
  • Mike Buckle

Abstract

The paper presents new UK evidence on the relative predictive performance of several implied and historical volatilities. The Datastream combination of historical and implied volatilities is also tested empirically for the first time. Daily observations are used to increase the power of the tests, and particular attention is paid to forecasting over the life of options. A further contribution of the paper is to examine relative accuracy for several different horizons, and matching the amount of past data to the forecast horizon is found to be effective when forecasting over longer horizons. Historical volatility estimators are found to have greater forecast accuracy than implied volatilities. Although implied volatility is a biased estimator of realized volatility, regression tests show that it contains more information than historical volatility. Also, a simple trading rule using historical volatility estimators is unable to exploit the forecast improvements since it fails to earn abnormal profits after transactions costs.

Suggested Citation

  • Owain Ap Gwilym & Mike Buckle, 1999. "Volatility forecasting in the framework of the option expiry cycle," The European Journal of Finance, Taylor & Francis Journals, vol. 5(1), pages 73-94.
  • Handle: RePEc:taf:eurjfi:v:5:y:1999:i:1:p:73-94
    DOI: 10.1080/135184799337190
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Peter Carr & Liuren Wu, 2004. "Variance Risk Premia," Finance 0409015, EconWPA.
    2. Bollen, Bernard & Inder, Brett, 2002. "Estimating daily volatility in financial markets utilizing intraday data," Journal of Empirical Finance, Elsevier, vol. 9(5), pages 551-562, December.
    3. Bent Jesper Christensen & Charlotte Strunk Hansen, 2002. "New evidence on the implied-realized volatility relation," The European Journal of Finance, Taylor & Francis Journals, vol. 8(2), pages 187-205, June.
    4. Guan Wang & Pierre Yourougou & Yue Wang, 2012. "Which implied volatility provides the best measure of future volatility?," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 36(1), pages 93-105, January.
    5. Moosa, Imad A. & Bollen, Bernard, 2002. "A benchmark for measuring bias in estimated daily value at risk," International Review of Financial Analysis, Elsevier, vol. 11(1), pages 85-100.
    6. Cifarelli, giulio, 2002. "The information content of implied volatilities of options on eurodeposit futures traded on the LIFFE: is there long memory?," MPRA Paper 28538, University Library of Munich, Germany.
    7. Yu, Wayne W. & Lui, Evans C.K. & Wang, Jacqueline W., 2010. "The predictive power of the implied volatility of options traded OTC and on exchanges," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 1-11, January.
    8. Giulio, Cifarelli, 2004. "Yes, implied volatilities are not informationally efficient: an empirical estimate using options on interest rate futures contracts," MPRA Paper 28655, University Library of Munich, Germany.

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    Keywords

    Volatility; Forecasting; Index Options;

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