Papers In Preparation
Passive Ownership and Price Informativeness (Job Market Paper, Updated 9/2020)
Abstract: This paper incorporates passive ownership into a model with endogenous learning. Passive ownership affects both how many investors decide to become informed, and what risks informed investors learn about. The model guides three new measures of price informativeness around days we know information is released: earnings announcements. Between 1990 and 2018, pre-earnings trading volume and pre-earnings drift declined, while volatility on earnings days increased. At the firm-level, there is a negative relationship between passive ownership and pre-earnings price informativeness. This result is robust to using only quasi-exogenous increases in passive ownership associated with S&P 500 additions and Russell 1000/2000 rebalancing.
Previously circulated under the title “Earnings Announcements and the Rise of Passive Ownership”
Firm Customer Bases: Churn and Networks (Updated 5/2020)
Joint with Scott Baker and Brian Baugh
Abstract: Using consumer transaction data, this paper demonstrates that it is possible to construct accurate pictures of firm revenue, growth, geographic dispersion, and customer base characteristics. We develop two new measures which characterize firms’ customer bases: the rate of churn in a firm’s customer base and a metric of the pairwise similarity between firms’ customer bases. We show that these measures provide important insights into the behavior of both real firm decisions and firm asset prices. Rates of customer churn affect the level and volatility of firm-level investment, markups, and profits. Churn also affects how quickly firms respond to shocks in the value of their growth options (i.e. Tobin’s Q). Moreover, high churn firms tended to face steeper declines in consumer spending during the recent COVID-19 outbreak. Similarity between firms’ customer bases highlights one under-explored type of predictability among stock returns – we demonstrate that significant alpha can be generated using a trading strategy that exploits our index of customer base similarity across firms.
Trade Policy Uncertainty and Stock Returns (Updated 7/2020)
Joint with Marcelo Bianconi and Federico Esposito
Abstract: We examine how trade policy uncertainty is reflected in stock returns. Our identification strategy exploits quasi-experimental variation in exposure to trade policy uncertainty arising from Congressional votes to revoke China’s preferential tariff treatment between 1990 and 2001. More exposed industries commanded a risk premium of 6% per year. The risk premium was larger in sectors less protected from globalization, and more reliant on inputs from China. More exposed industries also had a larger drop in stock prices when the uncertainty began, and more volatile returns around key policy dates. Moreover, the effects of policy uncertainty on expected cash-flows, investors’ forecast errors, and import competition from China cannot explain our results.
What Triggers National Stock Market Jumps?
New: Our data is now live
Joint with Scott Baker, Nicholas Bloom and Steven Davis
Main Findings: 1) 36% US jumps attributed to policy categories (and 41% internationally). Policy includes government spending, monetary policy and regulation. Non-policy includes macroeconomic news, corporate earnings & outlook and commodities. 2) Realized volatility is lower following policy-driven jumps, relative to non-policy jumps of the same magnitude and sign. We measure realized volatility as the sum of squared daily returns in the 22 trading days following the jump. 3) Outside the US, newspapers attribute 34% of jumps to US developments – above the US’s 11% share of global GDP. The share of jumps attributed to the US has been rising over time. 4) Volatility and trading volume are lower after jumps with high clarity. We define clarity as the first principal component of (1) agreement across newspapers describing the same jump (2) how confidently the journalist advanced their explanation (3) how easy it was to categorize the article (4) one minus the share of newspapers that did not give an explanation for the jump.
The Unprecedented Stock Market Reaction to COVID-19 (The Review of Asset Pricing Studies, July 2020)
Joint with Scott Baker, Nicholas Bloom, Steven J. Davis, Kyle Kost, and Tasaneeya Viratyosin.
Abstract: No previous infectious disease outbreak, including the Spanish Flu, has impacted the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with respect to large daily stock market moves back to 1900 and with respect to overall stock market volatility back to 1985. We also evaluate potential explanations for the unprecedented stock market reaction to the COVID-19 pandemic. The evidence we amass suggests that government restrictions on commercial activity and voluntary social distancing, operating with powerful effects in a service-oriented economy, are the main reasons the U.S. stock market reacted so much more forcefully to COVID-19 than to previous pandemics in 1918-19, 1957-58 and 1968.
Environmental, Social, and Governance Criteria: Why Investors Are Paying Attention (Journal of Investment Management, January 2018)
Joint with Ravi Jagannathan and Ashwin Ravikumar
Abstract: We find that money managers could reduce portfolio risk by incorporating Environmental, Social, and Governance (ESG) criteria into their investment process. ESG-related issues can cause sudden regulatory changes and shifts in consumer tastes, resulting in large asset price swings which leave investors limited time to react. By incorporating ESG criteria in their investment strategy, money managers can tilt their holdings towards firms which are well prepared to deal with these changes, thereby managing exposure to these rare but potentially large risks.