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Forester joined the Leventhal School of Accounting in 2016. His research uses a combination of unique settings, big data, and emerging technology to understand the role of corporate governance and information frictions in both developed and emerging economies. He studies developed economies to understand how different corporate governance mechanisms can be used to mitigate agency conflicts. His work in emerging economies is designed to understand how information frictions are created and how they can be overcome.
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RESEARCH + PUBLICATIONS
We use novel satellite data that track the number of cars in the parking lots of 92,668 stores for 71 publicly listed U.S. retailers to study the local information advantage of institutional investors. We establish car counts as a timely measure of store-level performance and find that institutional investors adjust their holdings in response to the performance of local stores, and that these trades are profitable on average. These results suggest that local investors have an advantage when processing information about nearby operations. However, some institutional investors do not adjust for the quality of their local information and continue to rely on local signals even when they are poor predictors of firm performance and returns. This overreliance on poor local information is reduced for institutional investors with greater industry expertise and those with greater incentives to maximize short-term trading profits.
Most investor coordination remains undisclosed. I provide empirical evidence on the extent and consequences of investor coordination in the context of hedge fund activism, in which potential benefits and costs from coordination are especially pronounced. In particular, I examine whether hedge fund activists orchestrate “wolf packs,” i.e. groups of investors willing to acquire shares in the target firm before the activist’s campaign is publicly disclosed via a 13D filing, as a way to support the campaign and strengthen the activist’s bargaining position. Using a novel hand-collected dataset, I develop a method to identify the formation of wolf packs before the 13D filing. I investigate two competing hypotheses: the Coordinated Effort Hypothesis (wolf packs are orchestrated by lead activists to circumvent securities regulations about “groups” of investors) and the Spontaneous Formation Hypothesis (wolf packs spontaneously arise because investors independently monitor and target the same firms at about the same time). A number of tests rule out the Spontaneous Formation Hypothesis and provide support for the Coordinated Effort Hypothesis. Finally, the presence of a wolf pack is associated with various measures of the campaign’s success.
In this article, the authors posit a quid pro quo in economic benefits between sell-side equity analysts and large hedge fund managers. They show that large hedge funds opportunistically trade one to four days prior to the publication of a recommendation change, a finding consistent with flow of information from analysts to hedge funds. Next, the authors demonstrate that in return for the information provided, analysts benefit from (1) better external evaluations and (2) higher trading commissions and fees for their brokerage firm. Notably, pre-trading occurs only when the analyst issuing the recommendations has a high external evaluation and the analyst’s brokerage house is a prime broker to the hedge fund.
One prominent justification for the mandatory disclosure rules that define modern securities law is that these rules encourage individual investors to participate in stock markets. Mandatory disclosure, the theory goes, gives individual investors access to information that puts them on a more equal playing field with sophisticated institutional shareholders. Although this reasoning has long been cited by regulators and commentators as a basis for mandating disclosure, recent work has questioned its validity. In particular, recent studies contend that individual investors are overwhelmed by the amount of information required to be disclosed under current law, and thus they cannot—and do not—use that information to analyze the companies that they own.Using a recent change in the law that allows firms to disclose less information before their initial public offering (“IPO”), we examine whether reduced disclosure leads to less trading by individual investors. Our results show that, immediately following the IPO, individual investors are less likely to trade in the stocks of the firms that provide less disclosure—but that this difference disappears after two weeks of trading. Our findings have important implications for the lawmakers now examining whether, and how, to change the mandatory disclosure rules that have served as the basis of federal securities law for generations.
A justification for mandatory disclosure is that it encourages market participation by individual investors by giving them the same access to information that institutional investors have. Recent work has questioned this justification, arguing that individual investors do not use all of the information that the law requires firms to disclose because the overwhelming amount is too burdensome for them to process. Using a recent legal change that allows firms to disclose less information upon registering their securities, we examine whether the reduction in disclosure leads to less trading by individual investors. The results show that, immediately following pertinent initial public offerings, individual investors are less likely to trade in the firms that provide less information—but that this difference disappears after two weeks of trading. Our findings have implications for policy. First, our results indicate that individual investors can process the disclosures in question. Second, we provide evidence that regulators wishing to increase (or decrease) participation by individuals may be able to use the design of securities disclosures to accomplish this result.