CrossOptions

CrossOptions - Option Returns and the Cross-Sectional...

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Option Returns and the Cross-Sectional Predictability of Implied Volatility * Alessio Saretto The Krannert School of Management Purdue University November 2005 Abstract I study the cross-section of realized stock option returns and Fnd an economically important source of predictability in the cross-sectional distribution of implied volatility. A zero-cost trading strategy that is long in straddles with a large posi- tive forecast of the change in implied volatility and short in straddles with a large negative forecast produces an economically important and statistically signiFcant average monthly return. The results are robust to different market conditions, to Frm risk-characteristics, to various industry groupings, to options liquidity charac- teristics, and are not explained by linear factor models. Compared to the market prediction, the implied volatility estimate obtained from the cross-sectional fore- casting model is a more precise and efficient estimate of future realized volatility. * I thank Raffaella Giacomini, Richard Roll, Pedro Santa-Clara, and Walter Torous for their constant support, and Laura Frieder, Robert Geske, Amit Goyal, Mark Grimblatt and seminar partecipants at UCLA for valuable suggestions. West Lafayette, IN, 47907, phone: (765) 496-7591, e-mail: asaretto@purdue.edu. The latest draft is available at: http://www.krannert.purdue.edu/faculty/saretto/.
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1 Introduction Volatility is central to the pricing of options as there is a one-to-one correspondence between the price of an option and the volatility of the underlying asset. In the context of Black and Scholes (1973), given the option price it is possible to obtain an estimate of the volatility by inverting the pricing formula. The resulting estimate is generally referred to as the implied volatility, which represents the market’s estimate of the underlying future volatility over the life of the option. Options are essentially bets on volatility because an accurate prediction of future volatility delivers important economic information to traders. It is, therefore, not surprising that there is an extensive literature on predicting volatility. Granger and Poon (2003), for instance, survey the extant literature and broadly Fnd that the market’s forecast embedded in implied volatility is the best forecast of future volatility. However, this literature focuses mainly on predicting volatility of a single asset (frequently the S&P 500 index) using time-series methods. I show that there is important information in the cross-section of stock volatilities that leads to better forecasts of future volatility than those contained in the individual implied volatility itself. To the best of my knowledge, this is the Frst paper to study the predictability of the cross-section of individual equity option implied volatilities.
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CrossOptions - Option Returns and the Cross-Sectional...

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