Abstract:

The three chapters of this dissertation examine return predictability and volatility estimation. The first chapter shows that flows from contrarian investors reveal information about the representative agent's risk aversion in a model in which the representative agent displays time varying risk aversion and investors have heterogeneous preferences. The key result, consistent with theory, is that the flows of contrarian investors predict market returns. The second chapter studies the information content of the call (put) Early Exercise Premium, or EEP . The call EEP specifically captures investors' expectations about future lump sum dividend payments as well as other state variables such as conditional volatility and interest rates. From that perspective, the EEP should also be related to future returns of the underlying security. Interestingly, we find that the EEP is a good forecaster of returns at daily horizons. Importantly, we find that the predictability stems primarily from the ability of the EEP to forecast innovations in dividend growth, rather than other components of unexpected returns. The third chapter examines a volatility estimation bias that may be commonly exhibited by all option pricing models. Black and Scholes (1972) were the first to illustrate the bias by showing that their model under priced options on relatively low variance stocks and over priced options on relatively high variance stocks. The bias is always observed in cross section among individual stocks. We show that alternative variance estimators that use "shrinkage" techniques can eliminate the bias.