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...

We propose a statistical model of differences in beliefs in which heterogeneous investors are represented as different machine learning model specifications. Each investor forms return forecasts from their own specific model using data inputs that are available to all investors. We measure...

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...

This paper studies the impact of adult prosecution on recidivism and employment trajectories for adolescent, first-time felony defendants. We use extensive linked Criminal Justice Admin- istrative Record System and socio-economic data from Wayne County, Michigan (Detroit). Using the discrete age...

Using a semi-supervised topic model on 7,000,000 New York Times articles spanning 160 years, we test whether topics of media discourse predict future stock and bond market returns to test rational and behavioral hypotheses about market valuation of disaster risk. Focusing on media discourse...

Optimal investment of firms implies that expected stock returns are tied with the expected marginal benefit of investment divided by the marginal cost of investment. Winners have higher expected growth and expected marginal productivity (two major components of the marginal benefit of...

This paper shows that shootings are predictable enough to be preventable. Using arrest and victimization records for almost 644,000 people from the Chicago Police Department, we train a machine learning model to predict the risk of being shot in the next 18 months. We address central concerns...

We develop a model of satisficing with evaluation errors that incorporates complexity at the level of individual alternatives. We test the model predictions in a novel data set with information on hundreds of millions of chess moves by experienced players. Consistent with the theory, complex...

Extremely rich data on farm households in Burkina Faso are used to test whether resource are allocated Pareto efficiently. The complexity of household structures, including multi-generation and polygynous households, is taken into account to developing tests from theoretical models of behavior....

Less developed countries tend to experience higher output volatility, a fact that is, in part, explained by their specialization in more volatile sectors. This paper proposes theoretical explanations for this pattern of specialization -- with the complexity of the goods playing a central role....