Information Leakage Around SEC Comment Letters
Marshall Geiger et al.
Management Science, forthcoming
We investigate whether sophisticated investors obtain information about Securities and Exchange Commission (SEC) comment letters before the public release date. Specifically, we examine mutual fund trading behavior around dates firms receive a comment letter. We find significant abnormal net selling by mutual funds immediately after a firm receives a comment letter. Additional tests find that abnormal net selling is greater when firms receive a second-round letter, where information leakage is more likely (e.g., firms with high board member connectedness and higher dedicated institutional ownership) and when comment letters address more critical issues (e.g., the need to restate prior results or related party transactions). We also find that funds with high abnormal net selling in the private phase avoid significant future share price declines. In sum, we find consistent evidence that mutual funds appear to trade on information obtained during the private phase of the SEC comment letter process.
Stock Market Stimulus
Robin Greenwood, Toomas Laarits & Jeffrey Wurgler
NBER Working Paper, March 2022
We study the stock market effects of the arrival of the three rounds of “stimulus checks” to U.S. taxpayers and the single round of direct payments to Hong Kong citizens. The first two rounds of U.S. checks appear to have increased retail buying and share prices of retail-dominated portfolios. The Hong Kong payments increased overall market turnover and share prices in Hong Kong and mainland Chinese markets, especially in large-cap portfolios. We cannot rule out that these price effects were permanent. The findings raise novel questions about the role of fiscal stimulus in the stock market.
Price revelation from insider trading: Evidence from hacked earnings news
Pat Akey, Vincent Grégoire & Charles Martineau
Journal of Financial Economics, March 2022, Pages 1162-1184
From 2010 to 2015, a group of traders illegally accessed earnings information before their public release by hacking several newswire services. We use this scheme as a natural experiment to investigate how informed investors select among private signals and how efficiently financial markets incorporate private information contained in trades into prices. We construct a measure of qualitative information using machine learning and find that the hackers traded on both qualitative and quantitative signals. The hackers’ trading caused 15% more of the earnings news to be incorporated in prices before their public release. Liquidity providers responded to the hackers’ trades by widening spreads.
Discounting Less in Bad Times: Shining the Light on Cash Flow Expectations
Constantin Charles, Cary Frydman & Mete Kilic
University of Southern California Working Paper, November 2021
Research using survey data has found that respondents report lower expectations of future stock returns in bad times. This empirical pattern conflicts with the predictions of leading rational asset pricing models, where investors demand higher returns in bad times. We hypothesize that departures from rational cash-flow expectations can help reconcile the mismatch between theory and survey data. We test this hypothesis in an experiment that enables us to precisely control information about the cash flow process. Subjects are incentivized to report a time series of expected cash flows and asset valuations, which we use to infer discount rates. We find that discount rates and perceived risk are strongly negatively correlated; in contrast, a rational risk averse agent in our experiment should exhibit a strong positive relationship. We then document a new fact: when perceived risk is higher, subjects apply lower discount rates and are also willing to pay less for future cash flows. We argue that the mechanism which generates this new fact operates through distorted beliefs about cash flows. Overall, our results point to the importance of jointly modeling subjective expectations of cash flows and subjective expected returns.
Stock Volatility and the War Puzzle
Gustavo Cortes, Angela Vossmeyer & Marc Weidenmier
NBER Working Paper, March 2022
U.S. stock volatility is 33 percent lower during wartime and periods of conflict. This is true even for World Wars I and II, which would seemingly increase uncertainty. In a seminal paper, Schwert (1989) identified the “war puzzle” as one of the most surprising facts from two centuries of stock volatility data. We propose an explanation for the puzzle: the profits of firms become easier to forecast during wartime due to massive government spending. We test this hypothesis using newly-constructed data on more than 100 years of defense spending. The aggregate analysis finds that defense spending reduces stock volatility. The sector level regressions show that defense spending predicts lower stock volatility for firms that produce military goods. Finally, an event-study demonstrates that earnings forecasts of defense firms by equity analysts become significantly less disperse after 9/11 and the invasions of Afghanistan (2001) and Iraq (2003).
Social Networks and Hedge Fund Activism
Yazhou Ellen He & Tao Li
Review of Finance, forthcoming
We study the role of social networks in hedge fund activism. Actively managed funds whose managers are socially connected to activists are more likely than unconnected managers to invest in target stocks; their investment decisions are profitable. Importantly, such effects are greater for funds facing more severe information asymmetry. Connected funds are 14.2 percentage points more likely to support activists in proxy contests and contribute to reducing proxy contest costs. Our evidence shows that social ties benefit both connected investors and activists, and suggests that social networks reduce information asymmetry around activist campaigns by facilitating information exchange and increasing trust.
The Value of (Private) Investor Relations during the COVID-19 Crisis
Daniel Neukirchen et al.
Journal of Banking & Finance, forthcoming
We investigate the value of investor relations (IR) and find firms with strong IR to experience between five and eight percentage points higher stock returns than those with weak IR during the COVID-19 crisis. Firms with better-quality IR are also associated with higher investor loyalty and appear to have attracted significantly more institutional investors over the crisis period. This suggests that a firm’s IR contributes to value generation by enhancing credibility with shareholders and by diversifying its shareholder base. After decomposing IR into public and private transmission channels, we find the private IR function to be the main driver of our results.
Twitter Information, Analyst Behavior, and Market Efficiency
Ann Marie Hibbert et al.
University of Miami Working Paper, March 2022
Using Bloomberg’s daily Twitter Sentiment data for S&P500 firms, we show that Twitter information reduces forecast optimism and improves forecast accuracy of sell-side equity analysts. Negative Twitter information is more influential, and this effect is distinct from the impact of news. Using two exogenous events that changed the information content of individual tweets, we establish a causal relation between Twitter information and analyst behavior. At the aggregate level, Twitter-sensitive firms have smaller earnings surprises and weaker stock market reaction. Collectively, these results suggest that analysts extract useful negative information from Twitter, improving their forecasting performance and market efficiency.
Data Breach Announcements and Stock Market Reactions: A Matter of Timing?
Jens Foerderer & Sebastian Schuetz
Management Science, forthcoming
Although firms’ announcement of data breaches can lead to reputational or operational damages, extant research suggests that stock markets are relatively unresponsive to such announcements. We investigate whether markets’ unresponsiveness can be explained by firms strategically timing the announcement to coincide with busy days in the media, thereby reducing attention and, ultimately, attenuating market reactions. We leverage novel data on data breach announcements in the United States between 2008 and 2018 and create a measure of busyness in the trade press—news pressure—based on the Wall Street Journal. To investigate, we conduct two complementary studies. In Study 1, we employ an instrumental variable approach to assess whether announcements coincide with days of predictably high news pressure. We find that this is the case. On days with a one-standard-deviation-higher predictable news pressure, 4.44% more data breaches are announced (or approximately 19.024 data records). Strategic timing is more prevalent for breaches that are severe, that have firm-internal causes, and that leak healthcare data or credentials. In Study 2, we utilize a stock market event study to assess market reactions conditional on news pressure on the announcement day. We find that data breach announcements are associated with negative market reactions, yet these are attenuated by higher news pressure on the announcement day. If news pressure is on its empirical mean (respectively, one standard deviation above), we estimate a median decline in market capitalization of $347 (respectively, $85) million. We conclude that firms’ strategic timing might explain inconsistent findings in prior work.
Quantum Economic Advantage
Francesco Bova, Avi Goldfarb & Roger Melko
NBER Working Paper, February 2022
A quantum computer exhibits a quantum advantage when it can perform a calculation that a classical computer is unable to complete. It follows that a company with a quantum computer would be a monopolist in the market for solving such a calculation if its only competitor was a company with a classical computer. Conversely, economic outcomes are unclear in settings where quantum computers do not exhibit a quantum advantage. We model a duopoly where a quantum computing company competes against a classical computing company. The model features an asymmetric variable cost structure between the two companies and the potential for an asymmetric fixed cost structure, where each firm can invest in scaling its hardware to expand its respective market. We find that even if: 1) the companies can complete identical calculations, and thus there is no quantum advantage, and 2) it is more expensive to scale the quantum computer, the quantum computing company can not only be more profitable but also invest more in market creation. The results suggest that quantum computers may not need to display a quantum advantage to be able to generate a quantum economic advantage for the companies that develop them.
Patent quality, firm value, and investor underreaction: Evidence from patent examiner busyness
Tao Shu, Xuan Tian & Xintong Zhan
Journal of Financial Economics, March 2022, Pages 1043-1069
This paper attempts to study the causal effect of examiner busyness on patent quality and firm value. Using a broad set of patent quality measures, we find strong evidence that patents allowed by busy examiners exhibit significantly lower quality. Further, examiner busyness of firms’ patents negatively predicts the firms’ future stock returns, which is consistent with investor underreaction to examiner busyness. Examiners’ experience helps attenuate the negative effect of examiner busyness.