Anomalies in option pricing: the Black-Scholes model revisited

New England Economic Review, March-April, 1996 by Peter Fortune

The conclusion that implied volatility is a poor forecast of actual volatility has been reached in several other studies using different methods and data. For example, Canina and Figlewski (1993), using data for the S&P 100 in the years 1983 to 1987, found that implied volatility had almost no informational content as a prediction of actual volatility. However, a recent review of the literature on implied volatility (Mayhew 1995) mentions a number of papers that give more support for the forecasting ability of implied volatility.

Test 2: The Smile Test

One of the predictions of the Black-Scholes model is that at any moment all SPX options that differ only in the strike price (having the same term to expiration) should have the same implied volatility. For example, suppose that at 10:15 a.m. on November 3, transactions occur in several SPX call options that differ only in the strike price. Because each of the options is for the same interval of time, the value of volatility embedded in the option premiums should be the same. This is a natural consequence of the fact that the variability in the S&P 500's return over any future period is independent of the strike price of an SPX option.

One approach to testing this is to calculate the implied volatilities on a set of options identical in all respects except the strike price. If the Black-Scholes model is valid, the implied volatilities should all be the same (with some slippage for sampling errors). Thus, if a group of options all have a "true" volatility of, say, 12 percent, we should find that the implied volatilities differ from the true level only because of random errors. Possible reasons for these errors are temporary deviations of premiums from equilibrium levels, or a lag in the reporting of the trade so that the value of the SPX at the time stamp is not the value at the time of the trade, or that two options might have the same time stamp but one was delayed more than the other in getting into the computer.

This means that a graph of the implied volatilities against any economic variable should show a flat line. In particular, no relationship should exist between the implied volatilities and the strike price or, equivalently, the amount by which each option is "in-the-money." However, it is widely believed that a "smile" is present in option prices, that is, options far out of the money or far in the money have higher implied volatilities than near-the-money options. Stated differently, deep-out and far-in options trade "rich" (overpriced) relative to near-the-money options.

If true, this would make a graph of the implied volatilities against the value by which the option is in-the-money look like a smile: high implied volatilities at the extremes and lower volatilities in the middle. In order to test this hypothesis, our MDR data were screened for each day to identify any options that have the same characteristics but different strike [TABULAR DATA FOR TABLE 1 OMITTED] prices. If 10 or more of these "identical" options were found, the average implied volatility for the group was computed and the deviation of each option's implied volatility from its group average, the Volatility Spread, was computed. For each of these options, the amount by which it is in-the-money was computed, creating a variable called ITM (an acronym for in-the-money). ITM is the amount by which an option is in-the-money. It is negative when the option is out-of-the-money. ITM is measured relative to the S&P 500 index level, so it is expressed as a percentage of the S&P 500.