This paper estimates the effect of presentation of information on financial markets, using quasi-random variation in prominent "front page" positioning of news on the Bloomberg terminal. The front page and non-front page articles are indistinguishable by either algorithmic analysis or by the target audience of active finance professionals. Front page positioning induces 280% higher trading volumes and 180% larger price changes within the first ten minutes after publication. Front page articles also see a stronger price drift from these initial reactions for the next 30-45 minutes. Subsequently, non-front page news begins to catch up, but the incorporation of non-front page information is substantially more gradual. As a result, the initial effects of positioning persist for days after publication. The effects induced by positioning are even stronger than the differences between articles of varying editorial importance.
Job Market PaperBest Paper Award, 2018 FMA Napa Conference on Financial Markets ResearchBest Ph.D. Paper Award, 2017 European Finance Association2017 WFA Cubist Systematic Strategies PhD Candidate Award for Outstanding ResearchFinalist, 2016 Hillcrest Behavioral Finance Award
This paper explores the puzzle of increased trading volume around informational releases through the lens of canonical models of gradual information diffusion and differences of opinion. I use a unique dataset of clicks on news by key finance professionals to distinguish between trading among investors who see the news at different times and trading among investors who see the same news but disagree regarding its interpretation. Consistent with gradual information diffusion, dispersion in the timing of investors' attention is strongly predictive of daily trading volume surges around earnings announcements and volume surges within minutes of individual news articles. The differences of opinion channel, measured as heterogeneity of investors reading the news, is generally weaker in explaining trading volume surges, but plays a larger role around more ambiguous news.
Why do investors react to old information? We conjecture that it is cognitively difficult to identify old content combined from multiple sources. We use a unique dataset of news passing through the Bloomberg terminal to differentiate "recombination" stories that draw content from several sources from direct "reprints." Firms see larger price moves on days when they have more recombination stories relative to reprints. Furthermore, while overall reactions to old information have declined over time, differential reactions to recombination stories have risen. Altogether, the results point to investors' increased sophistication in discarding reprints, but continuing susceptibility to recombination of old information.
How does a firm's human capital impact financial performance? By directly observing the employment and education trajectories of a significant proportion of U.S. public company employees from 1990 to the present, we explore the relationship between performance and two aspects of human capital: turnover and skills. First, we find that firms with higher employee turnover experience significantly worse future returns. A long-short strategy based on employee turnover with a three-month lag lag generates an excess compounded annual return of 14.3%. Second, firms with a larger emphasis on sales-oriented skills show better subsequent performance, whereas firms with more focus on administrative skills underperform. The effects of skills are heterogeneous across industries, with a larger premium on web development in Information, a higher premium on insurance in Manufacturing, and no benefit from sales-oriented skills in Finance.
Best Paper on Long-Term Investments, 2018 Northern Finance AssociationWinner, 2017 Jack Treynor Prize from the Institute for Quantitative Research in FinanceSecond Place, 2017 PanAgora Asset Management Dr. Richard A. Crowell Memorial Prize
Do individuals anticipate present bias in others? This paper jointly investigates beliefs about one's own and others' present bias in two settings. First, in a classroom survey, students systematically underestimate how late they will turn in an assignment, but hold significantly more accurate beliefs about their classmates. Second, in an online experiment, participants engaged in a real-effort task display little awareness of their own present bias, but anticipate present bias in others. Structurally, I estimate a present bias parameter β of 0.82. Participants perceive others' β to be 0.87, indicating substantial sophistication, contrasted with 1.03 for themselves, indicating full naivete.
The literature finds that investors increase portfolio turnover following high returns, explaining it by either overconfidence or skilled trading. This paper develops a theoretical model and shows empirically that team-managed funds trade less after good performance than single-managed funds. The magnitude of this differential increases with team size. Moreover, the change from single- to team-management structure decreases overconfidence induced trading. In spite of more trading, the next-period risk-adjusted returns of single-managed funds are no better than those of team-managed funds. These findings indicate that team-management reduces overconfident trading. Alternative channels cannot explain the drop in excessive trading in team-managed funds.
This paper analyzes interactions between agents who are overconfident regarding their own future self-control relative to others. The paper considers the problem of incentivizing several such agents, and compares two methods: assigning work individually to each agent or jointly to pairs of agents. If the agents are homogenous in their preferences and beliefs, then the joint assignment method dominates individual assignments. In the case of heterogenous agents, the effects of the joint assignment are twofold: teamwork mitigates the efficiency loss from overconfidence, but introduces inefficiency by disincentivising the more patient members of the team. The results in the paper suggest that team-based incentives are more effective when employees are relatively overconfident and when teams are formed based on similarity in present-bias and beliefs.