Trying to forecast the future direction of markets is as old as markets themselves. Many investment strategies are predicated on scoping macroeconomic expectations and then taking a view on the future direction of markets.

Investment managers employ a variety of methods to gauge the likely direction of markets, most of which rely on long-established quantitative methods. Analysis of options forms part of these quantitative methods on the basis that option prices have been shown to provide valuable forward-looking information. But while options have been modelled extensively to create options-based investment strategies, fewer resources have been devoted to extracting information from options that could help to predict the future direction of stocks and stock markets.

So, the authors set out to deepen existing analysis of the predictive ability of options and then use this analysis to generate a portfolio of stocks with superior risk-adjusted returns.

Ever since the seminal work of Fischer Black, Myron Scholes, and Robert Merton in the 1970s, investment practitioners have recognised that option prices contain valuable information. The authors build on this idea by modelling options to obtain better estimates of systematic equity risk.

They sought to address the incompleteness of the existing academic literature by considering not only volatility but also skewness. Skewness, as many practitioners are aware, is a measure of deviation from the normal distribution. Existing research often makes the assumption that the skewness of individual stocks is zero, whereas it is well known that idiosyncratic skewness not only exists but also significantly affects asset prices. Stock prices have either positive or negative skew and do not often exhibit the balanced normal distribution.

The authors considered both the skewness of stock returns and cross-sectional stock prices of 3,484 companies. The companies were sorted into five portfolios according to their option-implied beta—that is, the systematic risk implied from the company’s observed option prices. The authors then calculated monthly returns to compare the performance of the portfolios.

The authors found that option-implied beta is a strong predictor of future stock returns and of stock market returns. Their findings provide support for the widely accepted idea that forward-looking information is embedded in option prices.

The authors discovered that as a portfolio’s implied beta increases, so does the portfolio’s return. The return from a long–short portfolio with long positions in stocks with high implied betas and short positions in stocks with low implied betas amounts to some 1.21% a month. In contrast, under the assumption that stocks have zero idiosyncratic skewness, the return from a similarly constructed portfolio is just 0.17% a month.

The implied market risk premium also provides forward-looking information about macroeconomic variables, including the market dividend yield, the term spread, and short-term interest rates. In particular, the findings suggest that when dividend yields are expected to rise, an individual stock—or the stock market—should rise too.

The findings will provide comfort for fund managers who incorporate option analysis into their investment processes. In particular, this study provides support for the notion that there is useful and under-used forward-looking information embedded in option prices.

Fund managers, whether they already incorporate option analysis or not, will find the approach used in the article directly applicable, enabling them to more accurately predict both individual stock and aggregate stock market returns.

Finally, the findings may change how practitioners view the capital asset pricing model (CAPM), which has been brought into question as the result of studies focusing on realized stock returns. The authors’ evidence that options are valuable forward-looking instruments will enhance the validity of the CAPM in the eyes of many.