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...

Average idiosyncratic volatility and firm idiosyncratic volatility increase with the number of listed firms. Average industry idiosyncratic volatility increases with the number of listed firms in the industry. We ex-plain the relation between idiosyncratic volatility and the number of listed...

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...

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 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...

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...

Different aspects of liquidity impact the performance of short-run reversals in different ways, consistent with the predictions of microstructure models. Higher volatility is associated with faster, initially stronger reversals, while lower turnover is associated with more persistent, ultimately...

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...

Browser data from an approximately representative sample of individual investors offers a detailed account of their search for information, including how much time they spend on stock research, which stocks they research, what categories of information they seek, and when they gather information...

This paper describes a process for automatically generating academic finance papers using large language models (LLMs). It demonstrates the process' efficacy by producing hundreds of complete papers on stock return predictability, a topic particularly well-suited for our illustration. We first...