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Volatility forecasting in the framework of the option expiry cycle

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Author Info

  • 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.

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File URL: http://www.tandfonline.com/doi/abs/10.1080/135184799337190
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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

Volume (Year): 5 (1999)
Issue (Month): 1 ()
Pages: 73-94

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Handle: RePEc:taf:eurjfi:v:5:y:1999:i:1:p:73-94

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Related research

Keywords: Volatility; Forecasting; Index Options;

References

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  1. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 33(1), pages 125-132.
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  3. Beckers, Stan, 1981. "Standard deviations implied in option prices as predictors of future stock price variability," Journal of Banking & Finance, Elsevier, vol. 5(3), pages 363-381, September.
  4. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-72, June.
  5. Louis O. Scott, 1992. "The Information Content of Prices in Derivative Security Markets," IMF Staff Papers, Palgrave Macmillan, vol. 39(3), pages 596-625, September.
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  8. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
  9. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-54, May-June.
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  13. Edey, Malcolm & Elliott, Graham, 1992. "Some Evidence on Option Prices as Predictors of Volatility," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 54(4), pages 567-78, November.
  14. Jorion, Philippe, 1995. " Predicting Volatility in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 50(2), pages 507-28, June.
  15. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
  16. Amin, Kaushik I. & Morton, Andrew J., 1994. "Implied volatility functions in arbitrage-free term structure models," Journal of Financial Economics, Elsevier, vol. 35(2), pages 141-180, April.
  17. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
  18. Schwert, G. William, 1987. "Effects of model specification on tests for unit roots in macroeconomic data," Journal of Monetary Economics, Elsevier, vol. 20(1), pages 73-103, July.
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Citations

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Cited by:
  1. Peter Carr & Liuren Wu, 2004. "Variance Risk Premia," Finance 0409015, EconWPA.
  2. 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.
  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.
  4. repec:ltr:wpaper:1999.01 is not listed on IDEAS
  5. 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.
  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. Bernard Bollen & Brett Inder, 1999. "Estimating Daily Volatility in Financial Markets Utilizing Intraday Data," Working Papers 1999.01, School of Economics, La Trobe University.
  8. 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.

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