We measure investors' short- and long-term stock-return expectations using both options and survey data. These expectations at different horizons reveal what investors think their own short-term expectations will be in the future, or forward return expectations. While contemporaneous short-term...

We theoretically characterize the behavior of machine learning asset pricing models. We prove that expected out-of-sample model performance--in terms of SDF Sharpe ratio and test asset pricing errors--is improving in model parameterization (or "complexity"). Our empirical findings verify the...

We survey the nascent literature on machine learning in the study of financial markets. We highlight the best examples of what this line of research has to offer and recommend promising directions for future research. This survey is designed for both financial economists interested in grasping...

This paper proposes a robust one-pass estimator that is easy to code: Justified by the market-model itself and using a prior that market-betas should not be less than -2 and more than +4, the market-model is run on daily stock rates of return that have first been winsorized at -2 and +4 times...

Empirical evidence shows that conditional market betas vary substantially over time. Yet, little is known about the source of this variation, either theoretically or empirically. Within a general equilibrium model with multiple assets and a time varying aggregate equity premium, we show that...

Existing research has documented cross-sectional seasonality of stock returns--the periodic outperformance of certain stocks relative to others during the same calendar month, weekday, or pre-holiday periods. A model in which stocks differ in their sensitivities to investor mood explains these...

Using a dataset of $17 trillion of assets under management, we document that actively-managed institutional accounts outperformed strategy benchmarks by 86 (42) basis points gross (net) during 2000-2012. In return, asset managers collected $162 billion in fees per year for managing 29% of...