The information content of implied volatilities and model-free volatility expectations: Evidence from options written on individual stocks

Arbeitspapier

The 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.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: CFR working paper ; No. 09-07

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Single Equation Models; Single Variables: Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities ; Contingent Pricing; Futures Pricing; option pricing ; Information and Market Efficiency; Event Studies; Insider Trading
• Subject: Volatility ; Stock options ; Information content ; Implied volatility ; Model-free volatility expectations ; ARCH models ; Volatilität ; Aktienoption ; Informationswert ; ARCH-Modell ; USA

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Taylor, Stephen J. ; Yadav, Pradeep K. ; Zhang, Yuanyuan
• Event: Veröffentlichung
• (who): University of Cologne, Centre for Financial Research (CFR)
• (where): Cologne
• (when): 2009

Further information

• Handle: http://hdl.handle.net/10419/41359
• Last update: 10.03.2025, 11:44 AM CET