The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks
AbstractThe volatility information content of stock options for individual firms is measured using option prices for 149 U.S. firms and the S&P 100 index. ARCH and regression models are used to compare volatility forecasts defined by historical stock returns, at-the-money implied volatilities and model-free volatility expectations for every firm. For one-day-ahead estimation, a historical ARCH model outperforms both of the volatility estimates extracted from option prices for 36% of the firms, but the option forecasts are nearly always more informative for those firms that have the more actively traded options. When the prediction horizon extends until the expiry date of the options, the option forecasts are more informative than the historical volatility for 85% of the firms. However, the model-free volatility expectations are generally outperformed by the at-the-money implied volatilities. --
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Bibliographic InfoPaper provided by University of Cologne, Centre for Financial Research (CFR) in its series CFR Working Papers with number 09-07.
Date of creation: 2009
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Volatility; Stock options; Information content; Implied volatility; Model-free volatility expectations; ARCH models;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
- G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
- G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
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- Blair, Bevan J. & Poon, Ser-Huang & Taylor, Stephen J., 2001. "Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high-frequency index returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 5-26, November.
- Duffee, Gregory R., 1995. "Stock returns and volatility A firm-level analysis," Journal of Financial Economics, Elsevier, vol. 37(3), pages 399-420, March.
- Ser-Huang Poon & Clive W.J. Granger, 2003. "Forecasting Volatility in Financial Markets: A Review," Journal of Economic Literature, American Economic Association, vol. 41(2), pages 478-539, June.
- Cheung, Yin-Wong & Ng, Lilian K, 1992. " Stock Price Dynamics and Firm Size: An Empirical Investigation," Journal of Finance, American Finance Association, vol. 47(5), pages 1985-97, December.
- Christensen, B. J. & Prabhala, N. R., 1998. "The relation between implied and realized volatility," Journal of Financial Economics, Elsevier, vol. 50(2), pages 125-150, November.
- Lamoureux, Christopher G & Lastrapes, William D, 1993. "Forecasting Stock-Return Variance: Toward an Understanding of Stochastic Implied Volatilities," Review of Financial Studies, Society for Financial Studies, vol. 6(2), pages 293-326.
- Peter Carr & Liuren Wu, 2009. "Variance Risk Premiums," Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1311-1341, March.
- Cathy Chen & I-Doun Kuo, 2014. "Investor sentiment and interest rate volatility smile: evidence from Eurodollar options markets," Review of Quantitative Finance and Accounting, Springer, vol. 43(2), pages 367-391, August.
- Chalamandaris, Georgios & Tsekrekos, Andrianos E., 2010. "Predictable dynamics in implied volatility surfaces from OTC currency options," Journal of Banking & Finance, Elsevier, vol. 34(6), pages 1175-1188, June.
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