Tests of the information content of derivatives prices: The case of options and single stock futures

We examine the information content of derivative prices. In Chapter 1, we examine the information content of implied volatility for both future realized volatility and future returns. Previous studies have explored possible seasonal patterns in volatility (both implied and realized) and returns around the turn-of-the-year. However, we contribute to the existing literature by exploring possible seasonal patterns in the information content of implied volatility. Consistent with our hypotheses, we find a distinct seasonal pattern in the information content of implied volatility. The bias in implied volatility is largest in December and smallest in January. Moreover, the bias in implied volatility decreases in firm size, which is consistent with the idea that option traders are better able to price the options of larger firms with more available information. Additionally, we document a strong seasonal pattern in the market volatility risk premium. Further, we find a seasonal pattern in the relation between market the market volatility risk premium and future portfolio returns.;In Chapter 2, we use a sample of firms with actively traded single stock futures (SSF) to examine the information content of implied risk premiums embedded in SSF and option prices for future stock and portfolio returns. We believe this to be the first comprehensive study relating embedded risk premiums in cost-of-carry and put-call parity deviations to future stock returns. In addition, we test the possibility of a maturity dependent relation between the embedded risk premia and future returns. Overall, our results indicate that investors cannot profit from perceived mispricings in the SSF and option markets. The absence of a consistent relation between the implied risk premia and future returns implies that SSF and option markets are efficient in that any perceived mispricings in the SSF or option markets cannot be used to forecast future equity returns.