We investigate the cross-sectional return predictability of delta-hedged equity options using machine learning and big data. Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample...

Drawing upon more than 12 million observations over the period from 1996 to 2020, we find that allowing for nonlinearities significantly increases the out-of-sample performance of option and stock characteristics in predicting future option returns. Besides statistical significance, the...

In this paper we study empirically the implications of macroeconomic disagreement for the time variation in bond market risk premia. If there is a source of heterogeneity in the belief structure of the economy then differences in beliefs can affect equilibrium asset prices, and the dynamics of...

This paper documents large micro-heterogeneity and forecasting skill in the cross-section of survey based bond risk premia. We reject informationally constrained rational expectations but show a learning model distorted by sentiment is consistent with the data. Aggregating, we propose a belief...

We study an equilibrium asset pricing model with several Lucas (1978) trees subject to persistent distress events, where the agent has incomplete information about the state of an underlying common factor and learns from the events occurring to each tree. Contrary to similar asset pricing models...

We compare the implications of speculation versus hedging channels for bond markets in heterogeneous agents’ economies. Treasuries command a significant risk premium when optimistic agents speculate by leveraging their positions using bonds. Disagreement drives a wedge between marginal agent...