S&P 100 Index Option Volatility




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    • Fuqua School of Business, Duke University, Durham, North Carolina and Graduate School of Business, University of Chicago; and Fuqua School of Business, Duke University, Durham; respectively. We thank Arthur Evans, Jefferson Fleming, Sunil Paremeswan, and Shrikant Ramamurthy for their research assistance. James Fazio at Standard and Poor's Corporation provided valuable help in constructing our series. The comments of Gary Gastineau are gratefully acknowledged. We also appreciate the comments of René Stulz and an anonymous referee. This research is supported by the Futures and Options Research Center at Duke University.


Using transaction data on the S&P 100 index options, we study the effect of valuation simplifications that are commonplace in previous research on the timeseries properties of implied market volatility. Using an American-style algorithm that accounts for the discrete nature of the dividends on the S&P 100 index, we find that spurious negative serial correlation in implied volatility changes is induced by nonsimultaneously observing the option price and the index level. Negative serial correlation is also induced by a bid/ask price effect if a single option is used to estimate implied volatility. In addition, we find that these same effects induce spurious (and unreasonable) negative cross-correlations between the changes in call and put implied volatility.