We propose a unified theory of asset price determination encompassing both "conventional" and "alternative" asset classes (private equity, real estate, etc.). The model features disruption of old by young firms and skewness in the distribution of innovative rents among the young innovators. The...

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 document that value-to-price, the ratio of Residual-Income-Model-based valuation to market price, subsumes the power of book-to-market ratio and many other value or quality measures in predicting stock returns. Long-short value-to-price portfolios hedge against momentum, revitalize the...

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 propose a new methodology to build portfolios that hedge the economic and financial risks from climate change. Our quantity-based approach exploits information on how mutual fund managers trade in response to idiosyncratic changes in their climate risk beliefs. We exploit two types of...

Investors' behavior in U.S. Treasuries - the world's safe asset - affects monetary policy transmission mechanisms, fiscal policy space, loan pricing, and international vulnerabilities. Yet it is not well understood for a simple reason: researchers, not having a clear picture of the Treasury...

We develop a new class of tree-based models (P-Tree) for analyzing (unbalanced) panel data utilizing global (instead of local) split criteria that incorporate economic guidance to guard against overfitting while preserving interpretability. We grow a P-Tree top-down to split the cross section of...

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 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 introduce artificial intelligence pricing theory (AIPT). In contrast with the APT's foundational assumption of a low dimensional factor structure in returns, the AIPT conjectures that returns are driven by a large number of factors. We first verify this conjecture empirically and show that...