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Title:Forecasting Future Variance From Option Prices
Author(s):Poteshman, Allen M.
Subject(s):SPX option prices
Monte Carlo simulations
Abstract:Although it is widely believed that option prices provide the best possible forecasts of the future variance of the assets which underlie them, a large body of empirical evidence concludes that option prices consistently yield biased forecasts of future variance. The prevailing interpretation of these findings is that option investors may be forming unbiased forecasts of the future variance of underlying assets but that these unbiased forecasts fail to get impounded into option prices because of either (1) the difficulty of carrying out the necessary arbitrage strategies that would force the prices to their proper levels, or (2) the availability to market makers of lucrative alternative strategies in which they simply profit from the large bid-ask spreads in the options markets. This interpretation has significant consequences for nearly the entire range of option pricing research, since it implies that non-continuous trading, bid-ask spreads, and other market imperfections substantially influence option prices. This implication is important, both because incorporating these types of market imperfections into option pricing models is much more difficult than, for example, altering the dynamics of the underlying asset and also because it suggests that researchers cannot learn about option investor expectations by filtering option prices through available option pricing models. The present paper studies the variance forecasting ability of SPX option prices against the backdrop of the prevailing interpretation of the findings in the variance forecasting literature. The paper presents two main empirical findings. First, approximately one third of the usual bias is eliminated when high frequency futures data rather than daily closing data is used to construct measures of realized variance. Second, roughly another third of the bias disappears when forecasts of future variance are extracted from option prices via an option pricing model that – unlike the commonly employed model – permits a non-zero market price of variance risk and a non-zero correlation between innovations to the level and variance of the SPX index. Furthermore, the remaining bias is no longer significant. In addition to the empirical results, Monte Carlo simulations are performed to study the impact on the results of model misspecification and errors in the futures and options data. The simulations indicate that failure to account for a non-zero market price of variance risk produces a forecasting bias similar to that found in the previous literature when the conventional option pricing model is employed but that errors in the variables do not produce appreciable bias.
Issue Date:2000-09
Publisher:Office for Futures and Options Research, Department of Agricultural Economics, College of Agricultural, Consumer, and Environmental Sciences at the University of Illinois at Urbana-Champaign
Series/Report:OFOR Working Paper Series, no. 00-07
Genre:Working / Discussion Paper
Publication Status:published or submitted for publication
Peer Reviewed:not peer reviewed
Date Available in IDEALS:2008-03-17

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