How do macro-financial shocks affect investor behavior and market dynamics? Recent evidence suggests long-lasting effects of personally experienced outcomes on investor beliefs and investment but also significant differences across older and younger generations. We formalize experience-based...

We build a model of the law of small numbers (LSN)--the incorrect belief that even small samples represent the properties of the underlying population--to study its implications for trading behavior and asset prices. In our model, a belief in the LSN induces investors to expect short-term price...

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 develop an analytical solution to the dynamic portfolio choice problem of an investor with power utility defined over wealth at a finite horizon who faces an investment opportunity set with time-varying risk premia, real interest rates and inflation. The variation in investment opportunities...

How should long-term investors form portfolios in our time-varying, multifactor and friction-filled world? Two conceptual frameworks may help: looking directly at the stream of payments that a portfolio and payout policy can produce, and including a general equilibrium view of the markets'...

This paper tests models of mutual fund market timing that (1) allow the manager's utility function to depend on returns in excess of a benchmark; (2) distinguish timing based on lagged, publicly available information variables from timing based on finer information; and (3) simultaneously...

We study sources and implications of undiversified portfolios in a production-based asset pricing model with financial frictions. Households take concentrated positions in a single firm exposed to idiosyncratic shocks because managerial effort requires equity stakes, and because investors gain...

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...