Using text from 200 million pages of 13,000 US local newspapers and machine learning methods, we construct a 170-year-long measure of economic sentiment at the country and state levels, that expands existing measures in both the time series (by more than a century) and the cross-section. Our...

For decades credit rating agencies were viewed as trusted arbiters of creditworthiness and their ratings as important tools for managing risk. The common narrative is that the value of ratings was compromised by the evolution of the industry to a form where issuers pay for ratings. In this paper...

This study analyzes information production and trading behavior of banks with lending relationships. We combine trade-by-trade supervisory data and credit-registry data to examine banks' proprietary trading in borrower stocks around a large number of corporate events. We find that relationship...

Using a two-period model of a commodity market with a large number of atomistic consumers and two strategic sellers, we show that a speculator with access to storage can lower the market price while buying and raise the price while selling by clever use of limit, stop-loss, and market orders....

Is shareholder interest in corporate social responsibility driven by pecuniary motives (abnormal rates of return) or non-pecuniary ones (willingness to sacrifice returns to address various firm externalities)? To answer this question, we categorize the literature into seven tests: (1) costs of...

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 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...

Trading in cryptocurrencies has grown rapidly over the last decade, primarily dominated by retail investors. Using a dataset of 200,000 retail traders from eToro, we show that they have a different model of the underlying price dynamics in cryptocurrencies relative to other assets. Retail...

Using transaction data from a large non-fungible token (NFT) trading platform, this paper examines how the behavioral bias of selection-neglect interacts with extrapolative beliefs, accelerating the boom and delaying the crash in the recent NFT bubble. We show that the price-volume relationship...

Using granular data on the entire Brazilian securities lending market merged with all trades in the centralized stock exchange, we identify information leakage from short sellers. Our identification strategy explores trading execution mismatches between short sellers' selling activity in the...