A war-related factor model derived from textual analysis of media news reports explains the cross section of expected asset returns. Using a semi-supervised topic model to extract discourse topics from 7,000,000 New York Times stories spanning 160 years, the war factor predicts the cross section...

The financial press is a conduit for popular narratives that reflect collective memory about historical events. Some collective memories relate to major stock market crashes, and investors may rely on associated narratives, or "crash narratives," to inform current beliefs and choices. Using...

In the past decade, researchers in psychology and neuroscience studying human decision-making have increasingly adopted a framework that combines two systems, namely "model-free" and "model-based" learning. We import this framework into a simple financial setting, study its properties, and use...

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...

Over the past two decades, respondents to the Shiller Investor Confidence Surveys assess the probability of a catastrophic stock market crash to be much higher that the historical frequency of such events. We decompose these crash probabilities into fundamental and subjective components and use...

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 survey the growing literature emphasizing the role that supply-and-demand forces play in shaping the term structure of interest rates. Our starting point is the Vayanos and Vila (2009, 2021) model of the term structure of default-free bond yields, which we present in both discrete and...

Sparse models, though long preferred and pursued by social scientists, can be ineffective or unstable relative to large models, for example, in economic predictions (Giannone et al., 2021). To achieve sparsity for economic interpretation while exploiting big data for superior empirical...

We study the role of risk preferences and frictions in portfolio choice using variation in 401(k) default options. Patterns of active choice in response to different default funds imply that, absent participation frictions, 94% of investors prefer holding stocks, with an equity share of...

This paper defines risk-on risk-off (RORO), an elusive terminology in pervasive use, as the variation in global investor risk aversion. Our high-frequency RORO index captures time-varying investor risk appetite across multiple dimensions: advanced economy credit risk, equity market volatility,...