Knowledge that Transforms

We propose a latent-variables approach to recover extrapolative beliefs from asset prices. We estimate a present-value model of the price–dividend ratio of the market that embeds both return extrapolation and cash-flow extrapolation, alongside discount rates and rational expectations of dividend growth. This approach allows us to measure extrapolation bias without having to rely on survey data, and it inherently guarantees that the researcher focuses on a set of beliefs that matter for price formation. We show that extrapolative beliefs extracted from prices are highly correlated with surveys and that survey-based and price-based extrapolative beliefs share similar predictive properties for future returns, with the former improving upon the latter.

This paper examines the effects of targeted credit rationing by banks on firms likely to generate negative externalities. We exploit an initiative of the U.S. Department of Justice, labeled Operation Choke Point, which compelled banks to limit relationships with firms in controversial industries. Using supervisory loan-level data, we show that, as intended, targeted banks reduced lending and terminated relationships with affected firms. However, most of these firms fully substituted credit through nontargeted banks under similar terms. Overall, we find no significant shifts in the performance and investment of affected firms, suggesting that targeted credit rationing is widely ineffective in promoting change.

Several influential studies show that transformations of implied volatilities calculated from options prices predict stock returns. This predictability is puzzling because market participants readily observe options prices. We find that this predictability is consistent with implied volatilities reflecting stock borrow fees that are known to predict stock returns. We derive a formula relating the option-implied volatility spread to the borrow fee. Motivated by this relation, we show that the return predictability from implied volatility spread and skew decreases by at least two-thirds if high-fee stocks are excluded. The patterns for other predictors computed from option implied volatilities are similar.

We analyze the trade-offs of having intermediaries originate government-sponsored enterprise (GSE) mortgages using proprietary GSE data. We first find evidence of lenders pricing for observable and unobservable default risk independently of the GSEs. We then develop and estimate a model of competitive lending in which lenders have skin-in-the-game and conduct additional screening beyond the GSEs’ criteria. Lenders reduce costs via screening but also charge markups. On net, interest rates are higher compared to a counterfactual effectively without intermediaries. In an extension, the observed differences between banks and nonbanks are more consistent with differences in their skin-in-the-game rather than screening quality.

Corporate earnings announcements unpack large bundles of public information that should, in efficient markets, trigger jumps in stock prices. Testing this implication is difficult in practice, as it requires noisy high-frequency data from after-hours markets, where most earnings announcements are released. Using a unique dataset and a new microstructure noise-robust jump test, we show that earnings announcements almost always induce jumps in the stock price of announcing firms. They also significantly raise the probability of price co-jumps in non-announcing firms and the market. We find that returns from a post-announcement trading strategy are consistent with efficient price formation after 2016.

This article investigates predictors and benefits of corporate adaptation to crisis, adding a new dimension to studies of flexibility and resilience based on ex ante characteristics. We produce a unique sample of work-from-home announcements scraped from company websites during Covid-19. The announcers’ valuations increased by 3%–5% and risk declined versus matches, consistent with real-options theory under asymmetric information. We estimate characteristics, including subtle textual topics from 10-Ks, that predicted adaptation, show faster price response following Bloomberg coverage, and real advantages in subsequent operating performance. Corporate adaptation to crisis adds value and reduces risk, beyond information in firm characteristics.

We examine the adoption rates of responsible investment (RI) policies among university endowments. Adoption rates are higher among universities that face stakeholder pressure and are donation-dependent. Policy adoption predicts greater abnormal donations totaling 12 % of endowment assets, especially from “socially conscious” donors and during periods of higher media attention to climate change. Universities also experience greater student applications following adoptions. RI endowments have greater management costs, greater return volatility, and similar overall asset growth (donations plus net-of-cost investment income) compared to non-RI endowments. We conclude that RI policies are an important part of the optimal contract between universities and their stakeholders.

Distributed ledgers promise to enable the classical vision of money as a universal transaction record. But is it ever optimal to update a ledger through decentralized consensus? Analyzing an exchange economy with credit, we show that centralized updating is optimal when long-term rewards are more valued, minimizing redundant validation costs and maximizing economic surplus. Decentralization becomes preferable under weaker intertemporal incentives and when validators are drawn from market participants. We show how competing ledgers – anonymous or identified, permissioned or permissionless – can achieve socially optimal outcomes even in low-trust environments. Our framework provides a foundation for designing robust and efficient ledger systems.

We propose a statistical methodology for jointly estimating the pricing kernel and conditional physical return densities from option prices. Pricing kernel estimates show that negative stock market returns are significantly more painful to investors in low-volatility periods. Density estimates reflect a significantly positive risk–return trade-off, suggest that Martin’s (2017) lower bound on the equity premium is violated in high-volatility periods, and provide new evidence on the variance premium’s predictive power for excess returns as well as the co-movement between higher return moments. Lastly, we show that leading macrofinance models are at odds with basic features of conditional stock market risks and risk pricing.

We use Swedish administrative data to study the role of unemployment risk in salaried employees’ decisions to become entrepreneurs. Using the 2001 relaxation of Sweden’s last-in-first-out (LIFO) dismissal rule as an exogenous shock to unemployment risk, we find that employees facing increased unemployment risk are more likely to become entrepreneurs. The effect is more pronounced for employees with longer tenure, as they were newly exposed to greater unemployment risk. When we track entrepreneurs’ income dynamics and the performance of their ventures, we find that entrepreneurs who used to face greater unemployment risk do not underperform compared to other entrepreneurs. Our results provide some of the first empirical evidence of how employees respond to increased unemployment risk.