Institutional Investors as Information Suppliers: Evidence from Investment Conferences

Johanna S. Shin*

The University of Chicago Booth School of Business

November, 2019

Preliminary: Please do not circulate.

Abstract This paper examines the role of institutional investors as information suppliers in shaping firms’ information environment, using a setting in which sophisticated institutional investors provide processed information to the market. Institutional investors’ presentations at investment conferences emphasize how to evaluate firms in a rich context using accounting information. These presentations can increase investors’ attention, lower their information integration costs, and change how the market analyzes the presented firms. Consistent with investment managers facilitating price efficiency, I find that prices reflect news faster after the presentations. However, bid-ask spreads increase after the conferences, suggesting that institutional investors do not benefit all traders equally. I also find, after the presentations, analysts’ forecast accuracy improves while the dispersion of forecasts decreases, indicating investment managers’ impact extends to sophisticated intermediaries. Finally, I find the market reacts more to these presentations than to financial analysts’ coverage initiations, highlighting that investment managers are distinct and significant information suppliers that influence market response. Keywords: Institutional investors, information frictions, price efficiency, information intermediaries JEL classification: G23, G14, G12, G41 *I am sincerely grateful to my dissertation committee members Phil Berger (chair), Mark Maffett, Douglas Skinner, and Abbie Smith for their guidance and support. I thank Jonathan Bonham, Hans Christensen, Raphael Duguay, John Gallemore, Lloyd Han, Sehwa Kim, Christian Leuz, Lisa Liu, Miao Liu, Yao Lu, Charles McClure, Anya Nakhmurina, Haresh Sapra, Rimmy Tommy, Anastasia Zakolyukina, and workshop participants at the University of Chicago for helpful comments. I also thank Jamie Carmell at Invest for Kids Chicago for her comments and Tim Gray (copyeditor) for his service. I gratefully acknowledge financial support from the University of Chicago Booth School of Business. All errors are my own. Email address: jsshin@chicagobooth.edu.

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1. Introduction

Institutional investors manage approximately 70% of the U.S. equity market.1 The large share

suggests they can shape firms’ information environment as primary consumers of equity market

information. They monitor, acquire, and analyze information, or collectively, process

information to make trading decisions. Research shows their ownership influences price

efficiency, firm transparency, stock liquidity, and reporting conservatism.2 However, recent

literature provides limited evidence on whether institutional investors can have a meaningful

impact on the market when they provide information to other investors.

I study the role of institutional investors in shaping firms’ information environment as

information suppliers using a unique setting where they can affect other investors’ attention as

well as their information processing capacities through the information they deliver. Institutional

investors, particularly hedge fund managers, are regarded as sophisticated market participants

who rely on their superior expertise to generate returns (Brunnermeier and Nagel, 2004; Agarwal

et al., 2013; Jiao et al., 2016). This perception has influenced market participants’ investment

decisions. The weight of their influence is evident in the immediate market reaction to hedge

fund managers’ 13F filings (Brown and Schwarz, 2011; Sun et al., 2012; Aragon et al., 2013).

More importantly, it highlights the potential impact investment managers can have if they

disclose further information to the market.

Investment conferences, organized by nonprofit organizations in major cities every year,

assemble investment professionals to share their ideas. Investment managers voluntarily explain

the details of their investment recommendations. These presentations combine, interpret, and use

1 This number is according to Institutional Investors: Power and Responsibility a speech given by Commissioner Luis A. Aguilar in 2013. 2 See, for example, Boehmer and Kelley, 2009; Piotroski and Roulstone, 2004; Jiambalvo et al., 2002; Boone and White, 2015; Agarwal, 2007; Baik et al., 2010; Ramalingegowda and Yu, 2012.

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publicly available accounting information, such as financial statements, corporate disclosures,

and analysts’ forecasts, for specific firms in a rich context by considering these firms’ business

environment, market structure, competition, regulations, etc. Another noteworthy aspect of these

conferences is the wide dissemination of information. Because these conferences attract great

interest from the market, media as well as other information outlets deliver the content of

presentations to a broad audience. These features illustrate why the setting can be used to

investigate the role of investment managers as information suppliers in the market.

Using a difference-in-differences approach on unique hand-collected data, I examine the

discovery of prices around earnings announcements to test whether the conference presentations

promote efficient price discovery. Investment managers’ presentations can influence the market

through two channels. First, they increase investors’ attention to the pitched stocks, which I refer

to as the attention effect. Second, they reduce investors’ information integration costs, which are

any efforts associated with interpreting and using a given set of information. In this setting, the

presentations lower integration costs by guiding the market to use information more effectively

through detailed case studies, and I refer to this process as the guidance effect. Together, the

attention and guidance effects decrease related information frictions and increase price efficiency

(Grossman and Stiglitz, 1980; Verrecchia, 1982; Hirshleifer et al., 2011).

If these presentations improve price discovery, the market will also improve its

incorporation of earnings news into prices. Using earnings announcements to study the price

efficiency impact of investor presentations has two advantages. Every firm experiences a similar

shock to its information environment around earnings announcements, allowing me to cleanly

compare the effect investment managers have across firms. Also, studying information

integration costs requires a measure of new information, which is easily identifiable for earnings

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announcements. To test how quickly the market incorporates earnings news into stock prices, I

compare the change in intraperiod timeliness (“IPT”), a measure of the speed at which the

market responds to earnings news, during the four quarters before and after the presentations. I

find the market becomes more efficient in reflecting earnings news in prices for the pitched firms

after conference presentations, consistent with investment managers facilitating price efficiency

through the attention and guidance effects.

I also examine the impact of these presentations on information asymmetry. If the

presentations benefit all investors, the difference in expertise between more informed and less

informed traders will decrease. Information asymmetry should then also decrease. By contrast, if

these events cater to the already informed traders more, information asymmetry among investors

may increase. I find that the bid-ask spreads increase for the presented stocks around earnings

announcements after the conferences, relative to those not mentioned, suggesting the

presentations widen the information gap between more and less sophisticated investors.

Next, I consider whether investment managers’ presentations affect sell-side analysts. If

investors’ attention to specific firms increases after the conferences, analysts may allocate more

attention to these firms (Brown et al., 2015). Also, because analysts continue to improve their

skills and expertise, they may use these presentations as a resource and reduce their integration

costs (Mikhail et al., 1999; Hong and Kubik, 2003). These considerations suggest conference

presentations can improve analysts’ forecast accuracy. In addition, some analysts may replicate

valuation analyses provided by investment managers and start to use information more similarly

in the subsequent periods to the extent they are affected by the presentations, thus decreasing the

dispersion of forecasts. Consistent with these hypotheses, I find analysts’ forecasts become more

accurate and less disperse for the firms covered at these conferences. These results suggest even

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sophisticated information intermediaries can be constrained in performing their tasks and benefit

from information provided by other sophisticated agents.

Lastly, I examine whether institutional investors differ from sell-side analysts as

information suppliers. In some ways, investment managers at these conferences resemble

analysts, who make recommendations to investors (Irvine, 2003; Crawford et al., 2012). A major

difference, however, is the degree of financial commitment. Investment managers are generally

already invested in companies when they present at conferences, but analysts are restricted in

their ability to trade due to in-house rules and exchange regulations. Another discrepancy is the

degree of independence from firms’ management. Analysts seek to maintain close ties to firms’

management for their information advantage (Brown et al., 2015; Chen and Matsumoto, 2006;

Ke and Yu, 2006). This connection, however, raises questions about potential conflicts of

interest and thus the validity of analysts’ recommendations (Barber et al., 2006; Lin and

McNichols, 1998; Malmendier and Shanthikumar, 2014). By contrast, investment managers are

less concerned about their relationships with managers at firms they discuss. These different

qualities may affect how the market assesses information provided by the two groups. I find the

market’s efficiency in incorporating news in stock prices increases more when investment

managers discuss stocks than when analysts initiate coverage. Thus, investment managers are a

distinct and valuable group of information suppliers. In addition, I extend the analysis by

focusing on financial commitment as a key characteristic for increasing market response. I find

that investment managers’ stake improves the price discovery following their presentations,

suggesting verifiable holdings are an important channel through which information providers can

enhance their impact.

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I perform several additional tests. I use Bloomberg and Google search indices to show the

information from the conferences is widely disseminated among institutional and retail investors.

I also test whether investment managers are pursuing a “pump and dump” strategy, in which case

they have little incentive to provide much information of lasting value to the market audience.

However, I find that investment managers, on average, hold their pitched stocks for 7.230

quarters following their presentations. With respect to the determinants of stock selection for the

presentations, I find that investment managers are more likely to choose stocks from their

portfolios that are slow in incorporating news. This result can be interpreted as the presenters

selecting less efficient stocks to increase their impact on the market. Finally, I examine if

changes in media coverage or firms’ voluntary disclosure can explain my results and find no

significant change in how media or firms function after the presentations.

The paper contributes to the literature investigating the role of institutional investors in

shaping firms’ information environment. Prior work shows these investors affect, for example,

price efficiency, firm transparency, stock liquidity, and reporting conservatism (Boehmer and

Kelley, 2009; Piotroski and Roulstone, 2004; Jiambalvo et al., 2002; Boone and White, 2015;

Agarwal, 2007; Baik et al., 2010; Ramalingegowda and Yu, 2012). These papers are primarily

motivated by the effect of ownership, which can be broadly interpreted as the consequences of

monitoring, acquiring, and analyzing data as information consumers. By contrast, I show

investment managers can function as information suppliers and affect various aspects of capital

markets, including price efficiency, information asymmetry, and other information

intermediaries.

In investigating how investment managers influence the market as information providers,

I also contribute to the literature examining information frictions. Specifically, my paper finds a

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novel mechanism through which investment managers lower investors’ information integration

costs. The guidance effect improves the market’s ability to analyze the discussed firms as the

presentations emphasize how to evaluate firms in a rich context using accounting information.

Therefore, holding information constant, the market improves its information integration

performance after the presentations. This also distinguishes my paper from existing literature

exploiting a decrease in information integration costs driven by changes in qualities of the

information, or, broadly, factors external to investors’ ability to use information (Miller, 2010;

Cohen and Lou, 2012; Lawrence, 2013; Blankespoor et al., 2019b). The improvement in price

efficiency in these papers will continue to hold only if the outside factors endure. Furthermore,

my paper shows institutional investors can affect how other market participants allocate attention

and resources to improve price discovery.

Finally, my paper adds to discussions about information suppliers, including information

intermediaries. I show investment managers form a distinct group of information suppliers when

benchmarked against sell-side analysts. This finding indicates different groups of information

suppliers can have varying degrees of influence on the market. It also suggests the qualities of

information suppliers may affect how investors process information. In that regard, the paper has

implications for practitioners who aim to enhance the impact of the information they provide.

Section 2 provides a summary of the institutional background, and section 3 develops

hypotheses. Section 4 describes the data and sample construction, and section 5 presents my

empirical design and results. Section 6 provides additional tests, and section 7 concludes.

2. Background: Investment Conferences

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Investment conferences, organized by nonprofits or investment firms, are held yearly in major

cities. They raise awareness and funds for each conference’s specific mission.3 The organizers

invite well-known institutional investors to discuss their stock picks and market outlooks.

In general, investment managers discuss one to two stocks and give a long or short

recommendation based on public information. They reveal how they make investment decisions.

For example, they discuss valuation multiples, such as price-to-earnings, as well as profit

margins, business segments within a firm, cost structure, and payout ratios. More importantly,

these firm-specific presentations illustrate how various accounting information could be

interpreted and used in a rich context to evaluate a firm’s business model. The strategic analyses

often examine accounting information in conjunction with a firm’s business environment, such

as competition and regulations, to identify future growth potential or detect troubling signals.

These presentations direct investors’ attention to these firms, but they also guide investors to use

information more effectively for the discussed firms and lower their information integration costs,

which are associated with investors’ efforts to analyze information. This guidance effect is a

novel channel through which investment managers can influence market investors.

Figure 1 illustrates two examples. Panel A shows slides from a presentation by David

Einhorn of Greenlight Capital on Athenahealth at Ira Sohn New York in May 2014. He uses

Morgan Stanley’s discounted cash flow analysis as a base case and adjusts the assumptions and

calculations. He discusses EBIT margins and competing peers at length to justify his revised

numbers. Every piece of information in the presentation had been publicly available, but he

explains the use of the information to derive his own estimates. Panel B shows slides from Larry

3 For example, the Sohn Investment Conference series is held annually in a number of locations, including New York, San Francisco, and London. Its goal is to support medical research and programs for children with cancer. The largest of them, hosted in New York, attracts more than 3,000 investors, and tickets to these events can cost as much as $5,000 per person.

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Robbins of Glenview Capital at the same conference. Robbins encourages people to invest in

Humana and illustrates how current demographics and Medicare Advantage will drive the

company’s growth. He also examines how the firm can improve its margins and highlights the

likelihood of a share repurchase program.

The wide dissemination of conference presentations implies these events are effectively

public.4 While it is mostly institutional investors, family offices, and financial analysts who

attend the events, many market participants follow the presentations through media outlets to

learn about investment strategies. Figure 2 shows these presentations trigger immediate market

reactions. They also attract media coverage. CNBC provides live coverage of the Sohn

conference and summarizes presentations promptly. The Wall Street Journal runs a live blog that

follows these conferences with updates on a timely basis. An example is shown in Figure 3.

Online investment communities also provide summaries of investment managers’ pitches.

I examine six investment conference series (or 26 conference events) occurring between

2011 and 2016. Table 1 provides descriptive statistics of conferences. Ira Sohn in New York is

the largest, with 37 managers presenting 92 stocks over the sample period. I note that the

maximum number of stocks covered in a year is 91. While some investment managers repeatedly

make presentations, an average investment manager appears 1.65 times and discusses 1.62 stocks

at each presentation. These numbers suggest presentations tend to be focused on a specific firm

and can deliver in-depth analyses, as illustrated in the examples discussed previously.

Finally, I discuss the significance of the setting by comparing the presentations to

alternative sets of information provided by investment managers. 13F filings are the only

regularly disclosed public information provided by hedge fund managers, but these filings have a

4 This is in contrast to disclosure milieu, such as investment conferences organized by investment banks, where firms meet current and potential institutional investors (Bushee et al., 2011). The dissemination of information is corroborated in Section 6.

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number of shortcomings. First, in contrast to the presentations that provide a detailed basis for

investment decisions, these filings contain only information about holdings and do not explain

why investment managers hold those positions. Second, the filings do not reveal investment

managers’ net position. Because many hedge fund managers often use derivatives, the positions

reported in these filings do not reflect their true exposure. Finally, the point in time nature of

these filings means investment managers may window dress their positions (Gormley et al., 2019;

Agarwal et al., 2013). Despite these limitations, the market attempts to imitate the holdings

disclosed in 13F filings (Brown and Schwarz, 2011; Sun et al., 2012; Aragon et al., 2013). The

market reaction highlights the potential impact investment managers may have if they supply

more detailed information, and investment conferences provide a setting to explore this question.

Conference presentations may also be compared to short-selling campaigns of activist

fund managers.5 While these campaigns provide in-depth analyses of target firms, they only

recommend short positions, which are more costly as investors face borrowing costs. This

suggests those involved in open campaigns may have a strong incentive to discuss their short

ideas publicly. However, given the costs, short-sellers’ investment horizon may be shorter, which

implies they may not provide any valuable information that will have a long-term impact.

Furthermore, many institutional investors as well as retail investors have limited access to short

investments, while they do not face the same restrictions on long positions. The asymmetric

access to investment opportunities indicates short-selling campaigns may have a limited market

impact. By contrast, about 85% of the conference presentations in my sample recommend long

positions in the discussed firms. These considerations suggest investment conferences provide an

5 Recent literature has investigated short-selling campaigns undertaken by activist hedge funds (Appel et al., 2019; Zhao, 2019; Kartapanis, 2019). These papers provide descriptive background about the campaigns or examine how the campaigns relate to corporate opacity and corporate fraud. However, to my knowledge, this line of research has not studied how these campaigns affect the market’s information processing capacities in the long run.

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opportunity to study the role of institutional investors as information suppliers more

comprehensively.

3. Hypotheses Development

3.1 Investment Conferences and Stock Price Discovery

Prior to examining how these presentations affect price discovery, I consider the distinction

between public and private information to understand the type of information presented at these

conferences as well as to illustrate the implications for information costs. In this paper, I use the

term “public information” to refer to any information that is obtainable by all market participants.

If an investor incurs some expense to acquire information, it is still public in that its accessibility

is not restricted. This does not necessarily imply zero information costs, because public

information is still costly to process. However, this also suggests any processed version of

publicly available information is not considered private. I use the term “private information” to

refer strictly to information that is unavailable to investors who are willing to expend their

resources and efforts. This definition suggests regulatory and litigation risks would discourage

investment managers from obtaining or sharing private information.6 Given this distinction

between public and private information, I assume investment managers’ presentations are based

on public information.7 This mitigates concerns that investment managers influence the market

because they are revealing some private information and limits the scope of the paper to

information frictions that market participants face when using publicly available information. 6 The Dodd-Frank Act required a majority of hedge fund managers to register with the SEC or a state government. As a result of registration, hedge fund managers have become subject to the SEC’s regulations for investment advisers. They must provide information on their businesses and conflicts of interest; they are expected to file Form ADV with the SEC every year. Furthermore, the SEC now has the rights to examine and audit any registered hedge fund manager. An increase in hedge fund managers’ regulatory risk prompted fund managers to strengthen internal controls, which likely resulted in avoiding acquisition of firms’ private information. 7 I hand-collect and examine conference presentations that are available online to corroborate the content of information delivered at the conferences and find that they are based on public information.

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Theoretical research has established information costs impede efficient price discovery

(Grossman and Stiglitz, 1980; Verrecchia, 1982; Hirshleifer et al., 2011). Processing information,

or the collective act of monitoring, acquiring, and analyzing information, is costly, causing

market prices to experience a delay in reflecting news. However, as sophisticated information

processors, investment managers incorporate news into prices faster than other market

participants. Their presentations demonstrate how they achieve efficient information processing,

and by presenting they may thus reduce two kinds of information frictions. First, the

presentations can increase investors’ attention to the discussed firms, which I refer to as the

attention effect. Because investors have limited resources and face cognitive constraints, they

must allocate their attention selectively to where they expect to generate greater returns (Merton,

1987; Sims, 2003). Several papers find investors’ attention is associated with their trading

decisions, affecting market efficiency (Hirshleifer et al., 2009; deHaan et al., 2015; Drake et al.,

2016). Empirical evidence also shows that some actions can draw attention to specific firms. For

example, extensive media coverage prompts investors to focus on certain stocks (Huberman and

Regev, 2001; Engelberg et al., 2012). Similarly, investment conferences attract interest from the

market, and the content of presentations is widely disseminated. Consequently, the presentations

can shift investors’ attention to the firms discussed, thus improving improve price discovery.

Second, investment managers’ presentations lower the market’s information integration

costs, and I refer to this as the guidance effect.8 Information integration costs are associated with

investors interpreting and using information to make investment decisions. Investors may be

8 I follow Blankespoor et al. (2019b) and assume investors have to be aware of, acquire, and integrate information. If the sequential steps hold, and if I do not observe any change in the first two frictions, any changes in price efficiency can be attributed to a change in how investors integrate information. Awareness costs are associated with monitoring firms’ information environment while acquisition costs are related to obtaining and extracting any subset of necessary information. The presentations are unlikely to change these two costs around future earnings announcements as earnings announcements are information shocks the market expects on a regular basis. I empirically test whether these two costs are affected in Section 6.

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aware of the discussed firms and relevant news, but they may not be effective in assessing

information. In this setting, however, investment managers are guiding investors’ use of

information through their presentations. Because these presentations demonstrate to the market

how investment managers combine and evaluate accounting information for specific firms, they

can improve investors’ integration performance. Investors can also reassess the framework they

use to value these firms by taking into consideration important factors they had neglected before

the presentations, such as regulatory risks or industry conditions.9 Therefore, the guidance effect

can lower investors’ integration costs and improves price discovery.

Equally important, the presentations can have an impact in the long run, since the

knowledge gained can be used both immediately and into the future. The guidance effect should

continue to apply when earnings news is announced. That is, the market’s ability to incorporate

earnings news into prices for given firms is improved in the subsequent periods, and any change

in the process of price discovery is likely to persist.

I acknowledge that the attention effect and the guidance effect are not mutually

exclusive.10 The two channels share some conceptual overlap and can interact with each other.

First, investors’ attention is a necessary condition for them to incur any integration costs. Second,

given investors’ limited processing capacities, if they believe their integration costs are too high

for a firm, they may choose not to allocate any attention.11 However, these presentations can

lower investors’ information integration costs by providing an example of valuation and hence

increase investors’ attention. Third, in addition to directing investors’ attention to specific firms,

9 This consideration can be interpreted as a variation of the mosaic theory. That is, collecting information from various sources on several dimensions of target firms is crucial to investors in properly evaluating firms, and the presentations illustrate examples of how such analysis can be done. In other words, investment managers highlight the factors that had widely been neglected by the market and show the significance of understanding these elements in executing valuations. 10 I consider if different tests are more consistent with either effect when I discuss my results in Section 5 and 6. 11 This notion is also consistent with the models of rational inattention (Sims, 2003; Veldkamp, 2011).

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conference presentations can increase their attention to specific elements of those companies,

such as new entrants or regulatory risks. If inefficient integration of news arises partially due to

neglecting these factors, an increase in attention to these components can improve how investors

use their information set. Therefore, the presentations can improve the speed of price discovery

in the subsequent periods, including around the release of earnings news, through these two

channels, and my first hypothesis is as follows.

H1: The speed of price discovery increases after presentations for the firms

covered in the presentations, relative to those not presented.

3.2 Investment Conferences and Information Asymmetry

If investment conferences attract a broad audience and if most investors understand the

presentation content, the market’s ability to integrate earnings news into prices will improve.

Information asymmetry among market investors will then decrease. By contrast, the

presentations may benefit only a subset of investors who grasp the materials. In this case, the

already informed traders may gain additional knowledge, whereas less informed traders may not

learn much, and the gap between the two groups may increase.12 It follows that, if investment

managers’ stock pitches improve only a subset of investors’ ability to process information,

information asymmetry among investors may increase around earnings announcements.

Therefore, I do not have a clear prediction, and I state the null hypothesis as follows.

H2: The level of information asymmetry does not change for firms covered at

investment conferences after the presentations, relative to those not presented.

3.3 Institutional Investors’ Impact on Financial Analysts

12 The impact of investment managers’ presentations might only reach the less informed traders. However, this possibility is unlikely because less informed traders are assumed to have little advantage in acquiring information, which suggests that, if anything, more informed traders are better at receiving information from investment managers’ presentations.

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As sophisticated information intermediaries, sell-side analysts follow various news sources and

collect information to provide forecasts to the market. In doing so, they often cater to their clients’

demand (Brown et al., 2015). If the presentations increase investors’ interest in the discussed

firms, analysts will prioritize these firms and devote more resources to covering them. Because

analysts’ forecast accuracy depends on their attention to the stocks, an increase in analysts’

attention suggests that their estimates become more accurate following the presentations

(Clement, 1999; Bae et al., 2008).13

The presentations can also directly influence how analysts process information. Career

concerns motivate analysts to develop their skills to enhance their forecast accuracy (Mikhail et

al., 1999; Hong and Kubik, 2003; Brown et al., 2015). The difference in their talent in predicting

earnings also indicates analysts have the incentive to use necessary means to improve their

expertise (Clement, 1999; Bradley et al., 2017; Bradshaw et al., 2013). For example, information

spillover among analysts confirms analysts continually update their knowledge (Hwang et al.,

2017). These considerations collectively imply that analysts may use the presentations as

resources to lower their integration costs. An improvement in analysts’ abilities to use

information will increase their forecast accuracy.

I also consider whether the dispersion among analysts changes after the

presentations, as could occur if different analysts replicate how the same investment

manager processes information. In this case, analysts will reach a more similar estimate

following the presentations, and the level of dispersion among them will decrease. Also,

the possibility of replication suggests analysts may expend less effort in interpreting new

13 This nature of analysts’ job suggests the presentations may not affect their attention to the stocks they cover. To the extent this is the case, my hypothesis (H3a) is more consistent with the presentations lowering analysts’ information integration costs.

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information, lowering their information integration costs. Therefore, the change in the

dispersion across forecasts can be interpreted as a consequence of the guidance effect.

These considerations suggest that even sophisticated information intermediaries

may benefit from investment managers’ presentations. They also highlight the influence

of institutional investors as information suppliers, and my hypotheses are as follows.

H3a: Sell-side analysts’ earnings forecasts improve in accuracy for firms covered

at investment conferences following investment managers’ presentations, relative

to those not presented.

H3b: Dispersion in sell-side analysts’ earnings forecasts decreases for firms

covered at investment conferences following investment managers’ presentations,

relative to those not presented.

3.4 Investment Managers vs. Sell-side Analysts as Information Suppliers

Like investment managers at these conferences, financial analysts issue recommendations to help

their clients make informed trading decisions. Their initiation of coverage resembles investment

managers’ presentations because both groups are providing information about firms that had not

been extensively discussed beforehand. Analysts’ initiation of coverage can provide firm-,

industry- and market-wide information (Crawford et al., 2012). Also, the market response is

greater to analysts’ initiation of coverage than to recommendations from those who already cover

a stock (Irvine, 2003; Li and You, 2015). The similarity between investment manager conference

presentations and analyst coverage initiations suggests that the market’s reaction to analysts’

initiation of coverage should be comparable to its reaction to conference presentations.

However, investment managers are distinct from sell-side analysts for a number of

reasons. Investment managers and sell-side analysts differ in their financial interest in the stocks

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they recommend. Analysts are constrained in their ability to trade securities. Regulations set

boundaries on their trading. The Financial Industry Regulatory Authority (FINRA), for example,

restricts analysts’ trading around the time they issue recommendations. Brokerage houses also

have strict compliance and in-house guidelines limiting analysts’ trading. The market may view

these restrictions as enhancing the objectivity of analysts’ recommendations.

Unlike sell-side analysts, investment managers generally hold a position in the firms of

interest by the time they present at conferences. It makes sense for investment managers to pitch

stocks they hold because they expend time and resources on their presentations. If they do not

hold a stake, it can be interpreted as a violation of fiduciary duty to the extent they are using

resources to serve other investors. Moreover, the market can verify their position through 13F

filings.14 These constraints create pressure for investment managers to take actions consistent

with their words and allow their words to have a meaningful impact on the market.

Another key difference is each group’s relation to the firms they discuss. In general,

investment managers do not have a strong incentive to maintain good relationships with firms’

management. Analysts, however, tend to maintain close ties to the firms’ management because

their access to management gives them an information advantage (Brown et al., 2015; Brown et

al., 2015; Chen and Matsumoto, 2006; Ke and Yu, 2006). Market investors may pay attention to

analysts if they believe the reports have some value based on analysts’ connections to firms.

However, given potential conflicts of interest, it is also likely the market relies less on analysts’

reports. For example, analysts are reluctant to issue sell ratings or downgrade their opinions, and

the market may infer that analysts are limited in providing objective valuations (Barber et al.,

2006; Lin and McNichols, 1998; Malmendier and Shanthikumar, 2014).

14 Note that institutional investors are only required to disclose their holdings for which they exercise investment discretion over $100 million or more in Section 13(f) securities. This constraint suggests that investment managers may be invested in stocks they present at the conferences although their 13F filings do not report any holdings.

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Given these different qualities of institutional investors and sell-side analysts, I predict

investment managers serve as a distinct group of information suppliers. That is, investment

managers form a separate group of information providers from the information users’ perspective

when benchmarked against sell-side analysts. However, because these characteristics raise

numerous possibilities, I do not have a prediction as to which group of information suppliers will

have a larger impact on the market. Therefore, my fourth hypothesis is the null form as follows.

H4: The change in the speed of price discovery does not differ between firms

presented at investment conferences by investment managers and firms

recommended by financial analysts for the first time.

4. Data

I hand-collect data for six conference series (26 conference events) occurring between 2011 and

2016. My original sample consists of 329 stock pitches at six major investment conferences held

in the United States.15 In constructing my sample, I collect data from the web and use a number

of sources, including The Wall Street Journal and Bloomberg. I corroborate my sample by

requiring at least two information outlets to report the stock pitches.

If a company is presented more than once during the sample period, I retain the first

instance to cleanly measure the impact investment managers have on the market. Also, any

incremental effect from later presentations may be confounded by several factors. For example, a

change in firms’ disclosures or investment policies may happen between the first and subsequent

presentations, making estimating investment managers’ true impact difficult. Excluding

subsequent presentations eliminates approximately 22% of the treatment sample.

15 My sample of 329 stock pitches excludes firms that do not trade on the U.S. stock market and ADRs.

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For all of my tests, I collect firm-specific data from Compustat, CRSP, Thomson Reuters,

and I/B/E/S. For the first three hypotheses, I match treatment firms to economically similar firms

based on size and book-to-market ratio in the same industry to construct my control sample. The

sample period is limited to earnings announcements for four quarters before and after the

presentation at investment conferences.16 My final sample is 210 treatment-control firm pairs.

To test whether investment managers’ presentations increase the speed of price discovery,

I use intraperiod timeliness (“IPT”), which estimates the speed at which prices move over a time

window (Twedt, 2015; Drake et al., 2017; Blankespoor et al., 2018; Bushman et al., 2010).17 The

measure uses the area under the curve constructed by plotting the cumulative buy-and-hold

abnormal return up to each day in the event period and scaling these returns by the cumulative

buy-and-hold abnormal return for the entire period. IPT for a six-day period [0, +5], for example,

is calculated using the following equation:

4

[0,5]0 5

0.5t

t

CumulativeBHARIPTCumulativeBHAR=

= +∑

IPT measures the speed at which new information is reflected in prices. A greater number

indicates a more efficient price response. If investors become more efficient in using information,

prices reflect news more quickly. That is, any new information should be impounded into prices

at a faster rate, and IPT will increase after the presentations. The construction of the measure

16 Cleanly measuring the impact investment managers have on the market may be difficult if earnings announcements happen close to presentations. However, such observations account for less than 3% of the sample. I also run tests after dropping these observations and find that results do not change in any significant manner. 17 I choose to use IPT to measure the speed of price discovery instead of post earnings announcement drift, which is often used in the literature, for the following reasons. First, the IPT measure has the advantage that it does not depend on specific measures generated by financial analysts. If analysts are expected to improve their forecast accuracy following the presentations, an improvement in price efficiency may not be correctly captured. Second, post earnings announcement drift requires unexpected earnings based on analysts’ forecasts, which may not be available for smaller firms in my sample. Given my small sample size, the value of decreasing the sample size further is little relative to using IPT.

19

suggests its value is sensitive to a small denominator. To reduce noise, I exclude observations if

the absolute value of the cumulative return is less than 1.5%.18

For my fourth hypothesis, I collect analyst recommendations on U.S. stocks using the

I/B/E/S detail recommendations file. I classify a recommendation as a coverage initiation if a

firm was not covered by any analyst in the previous two years.19 I eliminate IPO firms from the

sample if the coverage was initiated within six months of listing. Finally, I require that the

coverage was initiated in the six months before or after the presentation and match my treatment

sample to the sample of analyst coverage initiations based on industry, size, and book-to-market

ratio. This approach yields 224 treatment-control firm pairs in my final sample.

Table 2 reports descriptive statistics, with variable definitions in Appendix A. For the

data used to test the first three hypotheses, the mean (median) firm-quarter has a market value of

$18.617 billion ($5.224 billion), leverage of 2.607 (1.429), and a book-to-market ratio of 0.308

(0.274). For the data used to test the fourth hypothesis, the mean (median) firm-quarter has a

market value of $14.470 billion ($4.326 billion), leverage of 3.859 (1.787), and a book-to-market

ratio of 0.445 (0.354). The distributions of the main variables in Panels A and B are mostly

similar, and the IPT distribution is in line with existing papers (e.g., Blankespoor et al., 2018).

5. Empirical Design and Results

5.1 Investment Managers’ Presentations and Price Discovery

18 This eliminates approximately 20% of observations. The approach is largely consistent with the literature (Blankespoor et al., 2018). As a robustness check, I run regressions without the 1.5% filter. Although statistical significance is diminished, an untabulated analysis continues to yield similar results. 19 I count a recommendation as an initiation of coverage if there was no prior coverage in the previous two years for two reasons. First, if a firm had not been covered for two years, it is reasonable to assume that stale reports provide little value to the market. Second, limiting the sample to true initiations (i.e., where no analyst covered at all) restricts the sample size, as I am also matching control firms to treatment firms based on the date of initiation of coverage and presentation, respectively.

20

To test my first hypothesis, I examine how earnings news is impounded into prices. Specifically,

I use the [0, +5] window relative to earnings announcements for four quarters before and after

presentations. Because an earnings announcement is an information shock every firm regularly

experiences, this approach allows for a clean comparison of the effect the presentations have

across firms. In addition, I use earnings announcements to focus on the arrival of new

information. Alternatives are measures of price efficiency that capture how much of the already

available information is integrated in market prices. However, these measures are empirically

challenging to develop because they require identifying the relevant information, which could be

market-wide factors, industry-specific news, or firm-specific information.

I estimate the following difference-in-differences regression, in which the i subscripts

index firms, the t subscripts index quarters, and the k subscripts index control variables:

IPTi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (1)

IPT,i,t is the IPT measure as described in Section 4, Treatmenti,t is an indicator variable that

equals one if the firm is a treatment firm and zero otherwise, and Posti,t equals one for firm-

quarter observations after presentations and zero otherwise. Control variables include firm size,

return on assets, leverage, book-to-market ratio, stock price volatility, and an indicator variable

that equals one if the firm incurred a loss in that quarter, and the type of recommendation given

at investment conferences. I also control for factors that affect firms’ information environment

by including the number of analysts covering the stock and institutional ownership. I include

firm fixed effects to control for unobservable heterogeneity among firms and year-quarter fixed

effects to control for time-varying trends. I include conference fixed effects to alleviate concerns

that each conference attracts a unique audience, has a different level of media attention, or has

other unobservable implications for market traders. I also include industry fixed effects to

21

address potential information spillovers within industry, as information flow within an industry

may share common elements. I cluster standard errors at the firm level. A positive coefficient on

the interaction term would suggest investment managers’ presentations increase price efficiency.

Table 3 reports the results. Following the conference presentations, the speed of price

discovery improves significantly for the firms discussed by investment managers, compared with

matched control firms that are not mentioned. In terms of economic magnitude, an average

treatment firm improves its speed of price discovery by approximately 10.5% to 12.2% after the

presentations. Alternatively, if firms are ranked in deciles with respect to the speed of price

discovery, the coefficient estimate is equivalent to an average treatment firm moving up a rank

after the presentations. This finding is consistent with the hypothesis that investment managers

facilitate efficient discovery of prices through the attention and guidance effects.

The finding may be more consistent with the guidance effect. Figure 4 shows the change

in IPT for four quarters before and after the presentations. IPT is higher after the presentations

and the increase in speed of price discovery persists for four quarters. Because these

presentations demonstrate how accounting information can be used more rigorously, they

transfer knowledge and expertise to investors. Once this firm-specific knowledge is obtained,

receivers can internalize what they have learned and apply it to analyze similar issues for the

discussed firms repeatedly. Therefore, any change that arises from this decrease in investors’

integration costs should persist. In addition, existing literature finds that a sudden spike in

investors’ attention often mean reverts, which suggests any change induced by the attention

effect is unlikely to be permanent (Engelberg et al., 2012; Barber and Loeffler, 1993). Therefore,

to the extent the improvement in price discovery is persistent in the long run, the observed

change is consistent with the presentations having an impact on investors’ integration costs in the

22

subsequent periods. Furthermore, the relatively large firm size of my sample indicates that the

attention effect may have limited impact. If investors’ attention to stocks is associated with the

presence of the firms as measured by their size in the market, my finding is more consistent with

the guidance effect than the attention effect.

5.2 Investment Managers’ Presentations and Information Asymmetry

To test the second hypothesis, I use bid-ask spread around earnings announcements to measure

information asymmetry and estimate the following regression, in which the i subscripts index

firms, the t subscripts index quarters, and the k subscripts index control variables:

Spreadi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (2)

Spreadi,t is the bid-ask spread over the [0, +2] period, relative to the earnings announcement.

Control variables, standard error clustering, and fixed effects are the same as those used in the

first test. A positive coefficient on the interaction term would suggest that investment managers’

presentations increase information asymmetry among investors.

Table 4 reports the results. I find that spreads increase for treatment firms after the

presentations compared with matched control firms. The coefficient estimate suggests an average

treatment firm’s spread increases by about 15.0% to 16.5% relative to those not mentioned. The

increase can be interpreted as more information asymmetry among investors, suggesting that the

information gap between more and less sophisticated investors increases. The finding indicates

presentations do not benefit all traders equally.20

5.3 Investment Managers’ Presentations and Sell-side Analysts

20 In Section 6, I find that Bloomberg search index displays a clear spike in institutional investors’ attention after the presentations while Google search index shows a modest increase in retail investors’ attention. The difference suggests that information asymmetry between sophisticated investors and retail investors increases following the events. At the same time, if other institutional investors benefit from the presentations, it implies even sophisticated investors can be subject to information processing constraints.

23

To test how analysts’ subsequent earnings forecasts change after the presentations, I examine the

forecast accuracy and the dispersion of forecasts and estimate the following regressions, in which

the i subscripts index firms, the j subscripts index analysts, the t subscripts index quarters, and

the k subscripts index control variables:

ForecastAccuracyi,j,t = β1Posti,j,t + β2Treatmenti,j,t + β3(Posti,j,t × Treatmenti,j,t) + ∑βkControlsk,i,j,t + FE + εi,j,t (3)

Dispersioni,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (4)

ForecastAccuracyi.j,t is the absolute difference between the actual earnings and the forecast,

scaled by the first available price for the announcement quarter and then multiplied by -100, so

that a greater value indicates a more accurate forecast. Dispersioni,t is the log of the standard

deviation of analysts’ most recent earnings forecasts issued in the 45 days prior to earnings

announcements. I follow the literature and control for firm-specific characteristics, including

firm size, return on assets, leverage, book-to-market ratio, stock price volatility, stock return,

stock turnover, and analyst following (e.g., Tan et al., 2011). In addition to firm, conference,

industry, and year-quarter fixed effects, I use analyst and firm-analyst fixed effects to address

unobservable analyst-specific characteristics in equation (3). I cluster standard errors at the

analyst level in equation (3) and at the firm level in equation (4). A positive coefficient on the

interaction term in equation (3) would suggest investment managers’ presentations increase

analysts’ forecast precision. A negative coefficient on the interaction term in equation (4) would

suggest these presentations decrease forecast dispersion.

Table 5 reports the results. I find that analysts’ forecast accuracy improves for firms

covered at investment conferences following the presentations relative to those not mentioned.

The result is equivalent to an improvement of 0.02 to 0.05 percent of price. For a company with

24

price-to-earnings ratio of 20, an improvement in forecast accuracy of 0.05 percent of price equals

an improvement of 1% of actual earnings in forecast accuracy. The finding suggests the attention

effect as well as the guidance effect benefit sell-side analysts. It also indicates processing

information is costly even for sophisticated information intermediaries. Furthermore, I find a

decrease in the dispersion across analysts’ forecasts for treatment firms, relative to control firms,

after the presentations, which is more consistent with the guidance effect than the attention effect.

If investment managers induce analysts to use information in a more similar fashion to each

other in the subsequent periods, these presentations are effectively lowering analysts’

information integration costs.

5.4 Investment Managers vs. Sell-side Analysts as Information Suppliers

To test my hypothesis about the differing impact of investment managers versus financial

analysts on price discovery, I use the same specification as in the first test, in which the i

subscripts index firms, the t subscripts index quarters, and the k subscripts index control

variables, as follows:

IPTi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (5)

While most of the empirical design remains similar to the previous tests, a key difference is the

control group, which consists of firms that were covered by analysts for the first time around the

time of the presentations. A positive coefficient on the interaction term would suggest investment

managers’ presentations increase price efficiency more than analysts’ initiation of coverage.

Table 6 reports the results. Consistent with my prediction, the market responds more to

information provided by investment managers than to that provided by analysts. An average

treatment firm improves its speed of price discovery by 11.8% to 12.2% after the presentations

compared to control firms for which analysts initiated coverage. The finding highlights

25

investment managers are a distinct group of information suppliers that can influence the market’s

use of information. The result also suggests that the degree to which the market uses information

depends on these distinct characteristics of information suppliers.

I now focus on financial commitment as a key quality in which these two groups differ

and investigate if verifiable financial interest enhances information providers’ influence.

Specifically, I test if investment managers’ holdings affect the market response to their

presentations. Prior to these presentations, whether disclosed stakes should affect price efficiency

is unclear given the lack of explanation for why they invested in these firms. After the events,

however, investors learn investment managers’ reasoning and can also confirm the presenters’

ownership. Holdings will signal to the market that the presenters have exerted considerable

efforts in their analyses and add weight to their recommendations. Thus, the presentations may

receive extensive use, and investment managers can make a meaningful impact on the market.

For observations that have data for investment managers’ holdings, I estimate the

following regression to assess the effect of disclosed stakes on price discovery in the market,

with the i subscripts indexing firms, the t subscripts indexing quarters, and the k subscripts

indexing control variables:

IPTi,t = β1Posti,t + β2ExposureRanki,t + β3(Posti,t × ExposureRanki,t) + ∑βkControlsk,i,t + FE + εi,t (6)

ExposureRanki,t is the tercile ranking of managers’ exposure to their holdings by year. Controls,

fixed effects, and standard error clustering are identical to equation (5).

Table 7 reports the results. I find investment managers’ financial commitment increases

the speed at which the market discovers prices after their presentations. The finding suggests

verifiable holdings can improve the impact investment managers have on the market audience.

5.5 Additional Tests in Progress

26

To further separate the guidance and attention effects, I am in the process of implementing

additional tests. First, I examine analysts’ coverage set in relation to their forecast accuracy

before and after the presentations. Existing literature finds analysts’ abilities to issue accurate

forecasts partially depend on their attention to the firms they cover, and a common proxy used is

the inverse of the number of firms covered (Clement, 1999). Analysts covering more firms than

average, for example, can likely reallocate more attention to the discussed firms if they now

expect more demand for information from investors. An increase in their attention will

consequently improve their forecast accuracy after the presentations. However, those who cover

fewer companies likely experience little difficulty in allocating attention. If even these analysts

improve their forecast accuracy, analysts are then likely benefiting from the presentations

lowering their information integration costs, or the guidance effect.

An alternative approach considers analysts’ experience as measured by the number of

prior quarters spent covering the firm (Clement, 1999; Mikhail et al., 1997). Analysts with little

experience following firms and have thus developed relatively little expertise are more likely to

benefit from the guidance effect of the presentations. By contrast, analysts who have more

experience are less likely to learn from investment managers’ discussions at the conferences.

Finally, I am in the process of implementing textual analysis of analysts’ reports to test if

the presentations influence how analysts interpret new information and integrate news into their

forecasts. I investigate if reports published after the conferences mention these events and if

these reports contain key words used in the presentations. I note a limitation is that analysts may

be reluctant to admit they learn from investment managers. They have reputation and career

concerns which could discourage them from acknowledging that their information processing

capacities were somewhat limited prior to observing these presentations.

27

6. Additional Tests

In this section, I perform additional validation tests and consider alternative explanations.21

6.1 The Dissemination of Information and Search Indices

For investment managers to have an impact on firms’ information environment, investors must

be aware of and acquire information from the presentations. The content of conference

presentations should thus be widely disseminated to increase investors’ attention to the pitched

stocks. To corroborate the dissemination of information from the presentations, I use search

indices provided by Bloomberg and Google, which are frequently used to proxy for investors’

attention (Ben-Rephael et al., 2016; Da et al, 2011; Drake et al., 2012; deHaan et al., 2015).

To measure the flow of information to institutional investors, I use the Bloomberg search

index. Institutional investors subscribe to Bloomberg to access timely market data. Bloomberg’s

coverage of financial instruments is comprehensive, and users can easily access data for their

independent analyses. Another primary function is chat rooms set on terminals, which allow

institutional investors to talk to their brokers at any time. With the subscription fee running at

more than $20,000 per terminal per year, retail investors are unlikely to subscribe to the service.

Also, with approximately 320,000 subscriptions worldwide, 80% of users are in the financial

industry (Ben-Rephael et al., 2016).

Institutional investors can either initiate a search for a specific company or browse and

read articles that relate to a company, and Bloomberg constructs a measure of investor attention

based on these activities. When users actively search for news relevant to companies of interest

21 The sample used in this section can be larger than that used in my main tests, which requires matching based on firm characteristics and drops some treatment firms. When an analysis requires only treatment firms, I base my test on a more comprehensive sample to increase sample size for a higher power of my tests. I note the results do not change significantly when my analyses are based on the sample for my main tests.

28

by using the function “CN” (Company News), Bloomberg assigns a score of 10. By contrast,

when users read news about firms without first initializing specific searches, Bloomberg assigns

a score of 1. To generate an attention score, Bloomberg then aggregates the hourly counts to

calculate the average score during the last eight hours and compares this number to all hourly

counts in the last 30 days for the same company. Bloomberg assigns a score of 0 if the rolling

average of the last eight hours is in the lowest 80 percent, relative to the score over the last 30

days. A score of 1, 2, 3, or 4 means the rolling average is between 80% and 90%, 90% and 94%,

94% and 96%, or over 96%, respectively, relative to the previous month’s hourly attention

counts.

To verify the flow of information to retail investors, I use Google’s search index

following the literature (Da et al., 2011; Drake et al., 2012; deHaan et al., 2015). Google

provides daily search volume indices through Google Trends (http://trends.google.com/). This

measure is based on a proprietary algorithm which divides the search volume by some average of

time-series data. I focus on searches for tickers because they are less ambiguous than the names

of firms. I also require searches be made under the finance category in the United States. I drop

observations with “noisy” tickers such as “A” or “GPS,” which removes about 7% of the tickers.

Figure 5 plots how investors’ attention to stocks changes during the [-10, +10] window

around investment managers’ presentations.22 As depicted in Panel A, treatment firms show a

sharp increase in interest from institutional investors on the day of the presentation. The index

jumps approximately 125%, relative to the average of the prior 10 days. Control firms do not

show any distinct change in investor attention. The figure suggests institutional investors’

22 Because both Bloomberg and Google use a rolling average to capture the market’s attention, cleanly measuring investors’ interest after the presentations in the long run is difficult. If presentations increase the level of investors’ attention permanently, the indices calculated after the presentations are not directly comparable to those calculated before.

29

interest in treatment firms spikes on the day of the presentation and the following day, while

their attention to control firms does not change much during the same period.

Panel B shows the Google search index movements around the time of presentations. The

overall trend for treatment and control firms is largely similar during the period, but investors’

interest in treatment firms increases for the [0, +2] period immediately after the presentations.

This effect for retail investors is weak compared with that for institutional investors.

Collectively, the figures show both institutional and retail investors’ attention to

treatment firms increases after the presentations. The increase in investors’ attention ensures the

dissemination of information in the market. The figures also show institutional investors exhibit

a clear spike in interest, compared to retail investors, whose interest increases modestly. This

finding suggests an increase in information asymmetry following the presentations is driven by

an increase in information gap between institutional and retail investors.

6.2 Investment Managers’ Exit Strategy

Investment managers may opportunistically present stocks they wish to “pump and dump” at

these conferences. They are likely aware their presentations move prices in the direction of their

recommendations, particularly in the short term, as illustrated in Figure 2. By directing investors’

attention to these firms, they can induce a temporary spike in interest and trading. If so, they

could quickly exit their position following their presentations to realize gains.

This motive, however, raises questions about whether investment managers can have a

meaningful impact on firms’ information environment. If they are solely interested in shifting

investors’ attention for a short period to generate returns, they are unlikely to provide materials

that contain much insight. This possibility weakens the validity of the guidance effect improving

market investors’ abilities to use information. Furthermore, if such opportunism is repeated, the

30

market will likely infer the managers’ motive and disregard their presentations. To mitigate the

concern they give presentations that have little value, I examine when they exit their positions.

Table 8 reports the results. In Panel A, I find that, on average, investment managers hold

the stock they pitch for 7.230 (5.363) quarters following (preceding) the presentations. This

finding suggests their motive to participate in conferences is not to generate short-term profits.

This explanation is reasonable as the market can easily detect opportunism from publicly

available13F filings. In other words, managers are limited in their ability to quickly sell their

stocks because of the possibility of verification and the resulting reputational costs. Figure 6 also

confirms investment managers, on average, increase their stake in the firms they present at these

conferences following their presentations.

I also examine investment managers’ holdings in the most recent 13F filings prior to their

presentations and compare their holding period for presented stocks to their other holdings. In

Panel B, I find that the holding period for treatment firms is not significantly different from that

for other firms in their portfolios. This result strengthens the argument that their motive for

presenting is unlikely to be creating a temporary hype and lends support to the guidance effect.

6.3 Determinants of Investment Managers’ Stock Selection

Presumably, investment managers are aware the conferences receive wide media coverage and

publicity. Also, when they recommend stocks at these events, they are implicitly suggesting

prices are not efficiently reflecting news. These considerations together imply they understand

they could be facilitating price efficiency through the attention effect and the guidance effect of

their presentations. In addition, if they view investment conferences as a venue to showcase their

talent in hopes of attracting more capital or investors or to build their reputations, they are likely

to choose stocks on which they can have a significant effect. As a result, investment managers

31

are more likely to discuss stocks that less efficiently reflect news to maximize their impact on

firms’ information environment.23

I examine managers’ portfolio holdings prior to presentations to explore whether price

efficiency is associated with investment managers’ stock selection. I estimate the following

probit and logit regressions, with the i subscripts indexing firms, the t subscripts indexing

quarters, and the k subscripts indexing control variables:

Pr(Select = 1)i,t = β0 + β1IPTRanki,t + ∑βkControlsk,i,t + εi,t (7)

IPTRanki,t is the quintile ranking of IPT for the [0, +5] window for the most recent earnings

announcements prior to managers’ presentations within their portfolios. Controls include

investment managers’ stake, firm size, return on assets, leverage, book-to-market ratio, stock

price volatility, a loss indicator, analyst following, institutional ownership, and an indicator for

the direction of the presenting manager’s recommendation. A negative coefficient on IPTRanki,t

would suggest that stocks that are slow in reflecting news are more likely to be presented.

Table 9 reports that the likelihood of investment managers selecting a stock is negatively

associated with the firms’ price efficiency around its earnings announcement before their

presentations. The presenters are more likely to present stocks that are less efficient in

incorporating news. Under the assumption that they are aware of the impact their presentations

have, the result is consistent with managers seeking to increase their impact on the market. I also

note that investment managers’ stake in these firms is positively associated with the likelihood of

their stock selection. This perhaps suggests investment managers understand their financial

commitment can increase their influence on market investors and confirms the notion that

verifiable holdings influence the impact of information suppliers.

23 Investment managers may believe a stock is mispriced due to the market’s limited attention, its lack of ability to integrate information into prices, or both. By helping stocks to realize what they believe to be the correct value through their presentations, they may be able to generate higher returns and benefit from presenting.

32

6.4 Media Coverage

To provide further evidence that my findings are consistent with the guidance effect, I

investigate whether media change how they cover the discussed firms after the presentations.

The presentations may change how other information intermediaries provide news to the market.

In particular, media outlets have the incentive to adjust their behavior as they often cater to

investors’ attention-driven demand for information (Barber and Odean, 2007; deHaan et al.,

2015; Peress, 2016). If media coverage can proxy for investor attention, a lack of change in

media coverage after the presentations would suggest the guidance effect, or a reduction in

investors’ integration costs, can better explain my findings compared to the attention effect.24

Also, an increase in the synthesis and dissemination of information through media

enables investors to recognize and obtain information more effectively and hence lower their

awareness and acquisition costs (Blankespoor et al., 2018; Twedt, 2015; Drake et al., 2014). This

implies a change in information integration costs can no longer explain the observed changes in

Section 5. However, if I find no significant change in how media cover the firms, I can then

attribute the documented changes in the main tests to the guidance effect to the extent that media

coverage correctly captures investors’ awareness and acquisition costs.25

I note that examining media coverage can address endogeneity concerns about

investment managers’ selection of stocks as well. Investment managers may select stocks based

on unobservable factors related to the outcome variables in my main tests. If these underlying

concurrent factors shift investors’ demand for information for these firms, media coverage will

also change after the presentations. For example, an investment manager may choose to present a

24 However, I caution that media coverage is likely an imperfect measure of investors’ attention and therefore cannot definitively eliminate investors’ attention as an explanation for my findings. 25 In reality, media coverage is a rough proxy that captures some subset of information awareness and acquisition costs. In this regard, I cannot definitively link the observed changes in the market following the presentations to the change in integration costs.

33

specific firm because he or she believes the firm’s recent acquisition will generate synergy and

provide a growth opportunity. The acquisition will likely draw investors’ attention, and media

outlets will also increase coverage. This endogeneity concern, in turn, suggests that the

conference presentations may not be responsible for the observed changes in various dimensions

of firms’ information environment, and I address this issue by testing if media coverage changes.

I obtain media coverage data from Ravenpack, a data provider that aggregates business

media articles. I use the Dow Jones edition which includes news from Dow Jones Newswires,

regional editions of The Wall Street Journal, Barron’s, and Marketwatch. Ravenpack classifies

the type of news story into “news flashes” or “full articles.” A news flash is an article with a

headline and no significant body text, so the category broadly captures the dissemination of news.

By contrast, a full article contains both a headline and at least one paragraph of textual material

and is more closely associated with the amount of news delivered.

To test whether the manner in which media cover the treatment and control firms changes

after the conference presentations, I estimate the following regression, with the i subscripts

indexing firms, the t subscripts indexing quarters, and the k subscripts indexing control variables:

Mediai,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (8)

Mediai,t is the count of news flash articles or full articles during the quarter.26 While the

specification of the regression remains largely unchanged from prior tests, I also control for S&P

500 index membership, as these firms are likely to draw more media attention.

Table 10 reports the results. I find that there is no significant change in how media cover

firms after conference presentations. The result suggests that my main findings are likely to be

26 I also consider alternative definitions of media coverage. Using the count of full articles and news flash articles during the quarter and during the three days following earnings announcements, I still find no significant change in how media cover treatment firms after the presentations.

34

driven by investment managers’ guidance effect. However, I caution that this finding does not

completely eliminate the attention effect as a plausible explanation. Consistent media coverage

also mitigates to some extent endogeneity concerns related to the presenters’ selection of stocks.

6.5 Firms’ Disclosure Behavior

An alternative explanation for the observed changes in the speed of price discovery, information

asymmetry, and analysts’ forecasts is that firms change their disclosures in response to the

conference presentations. They have the incentive to increase voluntary disclosure following

these events. If a manager provides positive information, firms may want to use the opportunity

to try to increase their valuation. For example, if a manager shares the opinion that a recent

investment in a plant will propel a firm’s future growth, that firm may want to further justify the

project to benefit from the positive spotlight. By contrast, if a manager presents negative

information, firms may try to refute comments to protect the stock price.

If firms provide more information to the market, a subset of investors can enhance their

understanding of these firms. This implies the speed of price discovery may also improve while

information asymmetry among investors increases. This supplementary information can also

assist analysts’ efforts to generate better estimates. That is, the documented changes may not be a

direct consequence of investment managers’ presentations. To address this concern, I examine

whether firms change their voluntary disclosures following investment conferences.

I collect data on management forecasts from the I/B/E/S guidance database and retain

annual and quarterly forecasts, and I use two measures. First, I consider the bundled forecast,

which is management’s forecast guidance issued within five days of earnings announcements,

including guidance issued concurrently with earnings announcements. However, the sticky

nature of voluntary disclosure suggests counting management guidance around earnings

35

announcements may not capture any meaningful change in firms’ disclosures (Field et al., 2005;

Billings et al., 2015; Lang and Lundholm, 1993; Botosan and Harris, 2000). To mitigate this

concern, I follow the literature and consider unbundled forecasts, which represent management’s

guidance issued within 60 days of earnings announcements but excluding any issued within five

days of the announcements. Unbundled forecasts tend to be less sticky and can better capture any

change in firms’ voluntary disclosures (Rogers and Buskirk, 2009).

I estimate the following regression to test whether firms change their disclosure practice

after the presentations, with the i subscripts indexing firms, the t subscripts indexing quarters,

and the k subscripts indexing control variables:

Disclosure,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t (9)

Table 11 reports the results. Panels A and B test whether firms increase bundled and

unbundled forecast guidance following the presentations, respectively. I find no evidence they do

so. Firms might not respond to the presentations for a number of reasons. Increasing disclosure

to underscore a positive analysis may put future pressure on them. To manage investors’

expectations and market pressure, these firms may choose not to change disclosures. If firms

receive unfavorable comments from the presenters, they may remain silent to avoid any further

negative publicity.

7. Conclusion

Investment managers share their stocks picks at investment conferences. Exploiting this unique

setting, I document an improvement in price efficiency after the presentations. The finding is

consistent with investment managers increasing the market’s attention to specific firms through

the attention effect and lowering its information integration costs through the guidance effect. I

36

provide evidence that information asymmetry among investors increases after the presentations,

indicating that the presentations do not benefit traders equally. I also show sell-side analysts

improve their earnings forecasts and reduce their forecast dispersion, suggesting investment

managers’ influence extends to sophisticated information intermediaries. Last, I find the market

responds more to investment managers’ presentations than to analysts’ coverage initiations,

indicating investment managers are a distinct and significant group of information suppliers.

The paper is subject to a number of limitations. The nature of the presentations may raise

concerns about the generalizability of the role of institutional investors as information suppliers.

Only a handful of investment conferences occur. Investment managers pick the stocks to present

and expend considerable time and resources to prepare for these presentations, which are made

public. Since institutional investors do not regularly deliver information of this caliber to other

investors, the findings may not be generalizable in other settings. Nevertheless, the unique

setting sheds light on the influence institutional investors can have in capital markets as

information suppliers. Specifically, presentations containing thorough analyses of specific firms

and the wide dissemination of information among market investors make the setting a good

laboratory to examine the attention and guidance effects.

Another caveat is that the paper does not directly address why investment managers

choose to present their investment ideas. However, their motives do not have differing

implications for key assumptions or interpretations of this paper.27 Whatever the motive may be,

the presenting investment managers presumably understand their presentations will influence

27 The only case in which investment managers’ motive may become relevant is if they are seeking to dump their stocks immediately after the presentations, in which case they may be reluctant to provide any valuable information. However, Section 6 finds this is unlikely, given the long holding period of the pitched stocks. Also, in any case, reputation concerns discourage them from pitching ideas unless they are confident in their information.

37

market prices. The role of institutional investors in improving the information environment

through their presentations remains unchanged.

I contribute to the literature that studies the role of institutional investors in capital

markets. This paper shows how they can influence various aspects of firms’ information

environment when they act as information suppliers. In doing so, the paper identifies the

guidance effect as a new channel through which they can affect other investors while also

confirming that investors’ attention is another significant factor in the information environment.

My paper also informs discussions about measures to level the playing field for investors.

The influence investment managers have on other market participants suggests they have

superior information processing capacities, and differences in these abilities may contribute to

the information gap. While many regulations that are intended to reduce information

disadvantage focus on information awareness and acquisition costs, my findings suggest

regulators could consider ways to reduce market participants’ information integration costs.

Furthermore, my paper shows how different groups of information suppliers can have different

impacts on investors. My results therefore speak to practitioners, including financial analysts,

firm management, and media, who may consider their qualities to increase their influence on the

market.

38

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Figure 1: Sample presentations These figures provide selected slides from investment managers’ conference presentations. Panel A presents sample slides from David Einhorn of Greenlight Capital’s presentation on Athenahealth at the Sohn Investment Conference in May, 2014. Panel B presents sample slides from Larry Robbins of Glenview Capital’s presentation on Humana at the Sohn Investment Conference in May, 2014. Panel A: Sample slides from David Einhorn’s presentation

Source: Greenlight Capital

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Panel B: Sample slides from Larry Robbins’s presentation

Source: Glenview Capital

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Figure 2: Market activities around investment managers’ presentations These plots present market activities around investment managers’ presentations. Panel A and Panel B plot market returns and trading volume for each of days [-20, +20] around investment managers’ presentations at time t, respectively. Market returns in the figure are normalized to 1 at t-1. Blue line shows mean returns for stocks investment managers recommended to go long, whereas red line shows mean returns for stocks investment managers recommended to short. Panel A: Market returns around investment managers’ presentations

Panel B: Trading volume around investment managers’ presentations

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Figure 3: Example of media coverage on investment conferences Figure 3 presents how the Wall Street Journal provides live updates of the Sohn Investment Conference. The website provides timely updates with a summary of each speaker’s presentation.

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Source: The Wall Street Journal

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Figure 4: Difference-in-differences plot of IPT Figure 4 plots how investment managers’ presentations affect the speed of price discovery in the market. I estimate model (1) but replace Post*Treatment indicator with treatment dummy interacted with separate event time dummies, each marking a quarter relative to investment managers’ presentations at time t. I omit the indicator for t-1, which serves as the baseline. Vertical bands represent 90% confidence intervals.

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Figure 5: Search Indices These plots present investors’ search activities around the time of investment managers’ presentations. Panel A and Panel B plot how Bloomberg and Google search indices change for each of days [-10, +10] around investment managers’ presentations at time t for treatment firms (blue) and control firms (red), respectively. Panel A: Bloomberg search index

Panel B: Google search index

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Figure 6: Investment managers’ stake in presented firms Figure 6 plots investment managers’ stake in the firms they present at investment conferences at time t by quarter for four quarters before and after the presentations.

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Appendix A: Variable Definition Variable Name Description Analysts Log of 1 plus the number of analysts. BTM Book-to-market ratio, calculated as Compustat CEQQ divided by market

capitalization, measured at the end of the quarter. Bundled Disclosure

Log of 1 plus the number of management’s forecast guidance issued within 5 days of earnings announcements, including guidance issued concurrently with earnings announcements

Dispersion Log of the standard deviation of analysts’ most recent earnings forecasts issued within the 45-day period prior to earnings announcements

ExposureRank Tercile ranking of investment managers’ exposure to a firm where exposure is calculated by the value investment divided by the total value of portfolio reported in 13F.

ForecastAccuracy Absolute difference in the actual earnings and the most recent earnings forecast issued within the 45-day period prior to earnings announcements, divided by the first available price for the announcement quarter and multiplied by -100

InstOwnership Percentage of shares held by institutional investors, calculated at the most recent file date between 100 days prior to the earnings announcement date and the earnings announcement date.

IPT Intraperiod timeliness measure of the speed with which earnings information is impounded into price, measured over the six-day earnings announcement window. IPT[0, +5] = ∑t=0,4 (CumBHARt/CumBHAR5)+0.5, where CumBHAR is the cumulative abnormal buy-and-hold return from day 0 to day t. The primary test excludes observations with an absolute CumAR_5 of less than 1%.

IPTRank Quintile ranking of IPT[0,+5] within investment managers’ portfolios relative to earnings announcements two quarters prior to managers’ presentations. A higher ranking indicates a higher IPT.

Leverage The ratio of total liabilities (Compustat LTQ) to total equity (Compustat SEQQ if available, ATQ-LTQ if SEQQ is not available), measured at the end of the quarter.

Loss Indicator variable set to 1 if net income (Compustat NIQ) is negative. LnMktcap Log of market capitalization (Compustat PRCCQ * CSHOQ), measured

at the end of quarter. FlashArticles Log of 1 plus the number of news flash articles during the quarter. FullArticles Log of 1 plus the number of full articles during the quarter. MgrStake Investment managers’ exposure to the treatment firms in their portfolio,

calculated as total dollar amount invested in the firm divided by total dollar value of portfolio as reported in the most recent filing.

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Post Indicator variable set to 0 if the reporting quarter is before investment managers’ presentations (analysts’ initiation of coverage) and 1 if the reporting quarter is after investment managers’ presentations (analysts’ initiation of coverage).

SP500 Indicator variable set to 1 if a firm belongs to S&SP 500 index. Recommendation Indicator variable set to 1 if an investment manager’s recommendation is

short and set to 0 if the recommendation is long. ROA Return on assets, calculated as Compustat NIQ divided by ATQ,

measured at the end of the quarter. Spread Average of daily effective bid-ask spread scaled by ask price, measured

over the window [0, +2] relative to the earnings announcement. StockReturn Firm’s stock return over the quarter. StockTurnover Number of shares traded in the quarter, divided by the firm’s number of

shares outstanding. Treatment Indicator variable set to 1 if a firm is discussed by investment manager at

investment conferences (if a firm is discussed by analyst for the first time) and 0 for control firms matched on industry, size, BTM.

Volatility Annualized standard deviation of returns over the quarter. Unbundled Disclosure

Log of 1 plus the number of management’s forecast guidance issued within 60 days of earnings announcements, excluding guidance issued within 5 days of earnings announcements.

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Table 1: Conference statistics These tables provide descriptive statistics for the conferences in the sample. I examine six conferences series that occurred between 2011 and 2016. Panel A presents statistics by conference, and Panel B presents statistics by year. Panel A: By conference Conference Location No. Events No. Managers No. Tickers Ira Sohn NY New York 6 37 92 Ira Sohn SF San Francisco 3 18 24 Robin Hood New York 4 34 72 SALT Las Vegas 3 17 35 Great Investors' Best Ideas Dallas 5 18 55 Invest for Kids Chicago 5 34 51 Total 26 158 329

Panel B: By year Year No. Conferences No. Managers No. Tickers 2011 2 14 20 2012 3 17 29 2013 5 41 70 2014 6 42 91 2015 4 33 66 2016 6 32 53 Total 26 179 329

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Table 2: Descriptive Statistics These tables provide descriptive statistics. Panel A reports descriptive statistics of the sample used for testing how price discovery, information asymmetry, analysts’ forecast accuracy and dispersion change around investment managers’ presentations. Panel B reports descriptive statistics of the sample used for testing whether investment managers’ presentations have a different impact on price discovery compared to the initiation of coverage by financial analysts. All variables are defined in Appendix A. Panel A: H1, H2, and H3 (1) (2) (3) (5) (6) (7) VARIABLES N Mean SD p25 p50 p75 IPT[0,+5] 2,297 4.144 1.952 3.221 4.242 5.171 Spread[0,+2] 2,887 0.0660 0.0973 0.0243 0.0367 0.0677 ForecastAccuracy 14,648 -0.241 0.370 -0.278 -0.113 -0.0421 LogDispersion 2,802 0.0304 0.0482 0 0.0135 0.0400 Market Cap 2,887 18,617 34,879 2,348 5,224 17,646 Roa 2,887 0.00814 0.0283 0.00191 0.0101 0.0212 Leverage 2,887 2.607 3.112 0.880 1.429 3.022 Volatility 2,887 0.438 0.319 0.218 0.352 0.572 Btm 2,887 0.308 0.138 0.209 0.274 0.369 Loss 2,887 0.196 0.397 0 0 0 Analysts 2,887 1.881 1.288 0 2.303 2.996 Inst. Ownership 2,887 0.702 0.329 0.618 0.838 0.935 Recommendation 2,887 0.148 0.355 0 0 0

Panel B: H4 (1) (2) (3) (4) (5) (6) VARIABLES N Mean SD p25 p50 p75 IPT[0,+5] 2,363 4.169 2.022 3.084 4.213 5.305 Market Cap 2,363 14,470 28,403 1,665 4,326 14,547 Roa 2,363 0.00601 0.0274 -0.000526 0.00756 0.0188 Leverage 2,363 3.859 6.033 0.920 1.787 4.040 Volatility 2,363 0.341 0.162 0.222 0.299 0.410 Btm 2,363 0.445 0.363 0.184 0.354 0.617 Loss 2,363 0.262 0.440 0 0 1 Inst. Ownership 2,363 0.494 0.413 0.00475 0.638 0.895 Recommendation 2,363 0.156 0.363 0 0 0

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Table 3: Investment Managers’ Presentations and Price Discovery This table presents difference-in-differences of the speed at which prices are discovered in market as measured by IPT around investment managers’ presentations at investment conferences using a following model:

IPTi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

IPT,t is the intraperiod timeliness measure that captures the speed at which earnings news is incorporated in market prices over [0, +5] window relative to earnings announcements. Treatmenti,t is an indicator variable that equals one if the firm is a treatment firm and zero if it is a control firm matched based on firm size, book-to-market ratio, and industry. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. Observations are firm-quarters. All variables are defined in Appendix A. Observations are dropped if the absolute value of the cumulative abnormal buy-and-hold return for the period used to calculate IPT is below 1.5%. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. (1) (2) (3) VARIABLES IPT[0,+5] IPT[0,+5] IPT[0,+5] Post*Treatment 0.422** 0.494*** 0.490*** (0.167) (0.168) (0.166) Post -0.155 -0.235* -0.237* (0.143) (0.120) (0.120) Treatment -0.227* -0.247** (0.125) (0.124) Observations 2,297 2,297 2,297 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.0491 0.0231 0.0323

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Table 4: Investment Managers’ Presentations, Information Asymmetry This table present difference-in-differences of information asymmetry around investment managers’ presentations at investment conferences using a following model:

Spreadi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

Spreadi,t is the bid-ask spread over the [0, +2] window relative to the earnings announcement. Treatmenti,t is an indicator variable that equals one if the firm is a treatment firm and zero if it is a control firm matched based on firm size, book-to-market ratio, and industry. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. Observations are firm-quarters. All variables are defined in Appendix A. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. (1) (2) (3) VARIABLES Spread[0,+2] Spread[0,+2] Spread[0,+2] Post*Treatment 0.00902** 0.00831** 0.00911** (0.00375) (0.00423) (0.00410) Post -0.0147** -0.00694 -0.00659 (0.00619) (0.00421) (0.00402) Treatment -0.0211*** -0.0189*** (0.00732) (0.00590) Observations 2,887 2,887 2,887 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.744 0.261 0.378

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Table 5: Investment Managers’ Presentations and Analysts’ Forecasts These tables present difference-in-differences of analyst forecast accuracy and dispersion of their forecasts around investment managers’ presentations at investment conferences using following models:

ForecastAccuracyi,j,t = β1Posti,j,t + β2Treatmenti,j,t + β3(Posti,j,t × Treatmenti,j,t) + ∑βkControlsk,i,j,t + FE + εi,j,t Dispersioni,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

ForecastAccuracyi,j,t is the absolute difference in the actual earnings and the forecast, scaled by the first available price for the announcement quarter, and then multiplied by -100 so that a greater value indicates a more accurate forecast. Dispersioni,t is the log of the standard deviation of analysts’ most recent earnings forecasts issued in the 45-day period prior to earnings announcements. Treatmenti,j,t and Treatmenti,t are indicator variables that equal one if the firm is a treatment firm and zero if it is a control firm matched based on firm size, book-to-market ratio, and industry. Posti,j,t and Posti,t are indicator variables that equal one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, stock return, stock turnover, and analyst following. Observations are firm-quarters. All variables are defined in Appendix A. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by analyst in equation (3) and by firm in equation (4). *** indicates significance at 1%, ** at 5%, and * at 10%.

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Panel A: Investment Managers’ Presentations and Analysts’ Forecast Accuracy (1) (2) (3) (4) (5) VARIABLES ForecastAccuracy ForecastAccuracy ForecastAccuracy ForecastAccuracy ForecastAccuracy Post*Treatment 0.0204** 0.0543*** 0.0310*** 0.0492*** 0.0493*** (0.00972) (0.0110) (0.0117) (0.0104) (0.0102) Post -0.00204 -0.0141* -0.0120 -0.0231*** -0.0149** (0.00758) (0.00762) (0.00883) (0.00700) (0.00681) Treatment -0.0714*** 0.429*** -0.0681*** -0.0743*** (0.00996) (0.0561) (0.00900) (0.00897) Observations 14,648 14,648 14,648 14,648 14,648 Controls Yes Yes Yes Yes Yes Fixed Effects Firm/

Year-Quarter Analyst/

Year-Quarter Analyst-Firm/Year-

Quarter Conf/

Year-Quarter Industry/

Year-Quarter Adjusted R^2 0.461 0.323 0.430 0.250 0.299

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Panel B: Investment Managers’ Presentations and Dispersion of Analysts’ Forecasts (1) (2) (3) VARIABLES Dispersion Dispersion Dispersion Post*Treatment -0.00438* -0.00520* -0.00574** (0.00257) (0.00295) (0.00283) Post 0.00312 0.00551** 0.00652*** (0.00222) (0.00219) (0.00225) Treatment 0.00891*** 0.00875*** (0.00325) (0.00295) Observations 2,802 2,802 2,802 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.561 0.143 0.210

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Table 6: Investment Managers vs. Sell-side Analysts as Information Suppliers This table presents difference-in-differences of the speed at which prices are discovered in market as measured by IPT around investment managers’ presentations at investment conferences relative to around analysts’ initiation of coverage using a following model:

IPTi,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

IPTi,t is the intraperiod timeliness measure that captures the speed at which earnings news is incorporated in market prices over [0, +5] window relative to earnings announcements, Treatmenti,t is an indicator variable that equals one if the firm is a treatment firm and zero if it is a control firm whose analyst coverage was initiated within the six-month period before or after the treatment firm was presented at a conference and is matched based on firm size, book-to-market ratio, and industry. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. Observations are firm-quarters. All variables are defined in Appendix A. Observations are dropped if the absolute value of the cumulative abnormal buy-and-hold return for the period used to calculate IPT is below 1.5%. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. (1) (2) (3) VARIABLES IPT[0,+5] IPT[0,+5] IPT[0,+5] Post*Treatment 0.492** 0.486** 0.474** (0.202) (0.208) (0.204) Post -0.584** -0.295 -0.311* (0.242) (0.180) (0.174) Treatment -0.262 -0.197 (0.172) (0.169) Observations 2,363 2,363 2,363 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.118 0.0310 0.0637

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Table 7: Investment Managers’ Holdings and Market Reaction This table presents how the IPT changes for treatment firms based on investment managers’ exposure to treatment stocks before and after their presentations using a following model:

IPTi,t = β1Posti,t + β2ExposureRanki,t + β3(Posti,t × ExposureRanki,t) + ∑βkControlsk,i,t + FE + εi,t

IPT,t is the intraperiod timeliness measure that captures the speed at which earnings news is incorporated in market prices over [0, +5] window relative to earnings announcements. ExposureRanki,t is the tercile ranking of managers’ exposure to their holdings by year. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of the rank of exposure and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. Observations are firm-quarters. All variables are defined in Appendix A. Observations are dropped if the absolute value of the cumulative abnormal buy-and-hold return for the period used to calculate IPT is below 1.5%. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. (1) VARIABLES IPT[0,+5] Post*ExposureRank 0.691** (0.310) Post -1.693** (0.743) ExposureRank -0.00557 (0.265) Observations 354 Controls Yes Fixed Effects Firm/Year-Quarter Adjusted R^2 0.0724

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Table 8: Investment Managers’ Exit Strategy These tables present investment managers’ holding period for their investments. Panel A reports investment managers’ holding period for the presented stocks before and after their presentations at investment conferences to assess how quickly they exit their positions in the presented stocks. Panel B reports investment managers’ holding period for stocks reported in their most recent 13F filings prior to their presentations to compare holding policy for stocks that are presented at conferences to those that are not presented. Panel A: Number of quarters held by investment managers before and after presentations (a)Post=0 (b)Post=1 Obs. Mean Obs. Mean Diff (a)-(b) t-statistic 91 5.363 87 7.230 -1.867 -2.453**

Panel B: Number of quarters held by investment managers for portfolio holdings prior to presentations (a)Treated=0 (b)Treated=1 Obs. Mean Obs. Mean Diff (a)-(b) t-statistic 4,799 12.625 78 13.487 -0.863 -0.730

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Table 9: Determinants of Investment Managers’ Stock Selection This table presents the determinants of investment managers’ selection of stocks to present at investment conferences using a following model:

Pr(Select = 1)i,t = β0 + β1IPTRanki,t + ∑βkControlsk,i,t + εi,t

Select is an indicator variable that equals one if the stock was presented at a conference, and zero otherwise. IPTRanki,t is the primary independent variable of interest and is the quintile ranking of IPT on [0, +5] window for the most recent earnings announcements prior to managers’ presentations for firms in investment managers’ portfolios. Controls include: investment managers’ stake, firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. All variables are defined in Appendix A. All continuous variables are truncated at 1% and 99%. Standard errors are clustered by investment manager. *** indicates significance at 1%, ** at 5%, and * at 10%. Probit Logit (1) (2) (3) (4) VARIABLES Select=1 Select=1 Select=1 Select=1 IPTRank -0.0668** -0.0636** -0.165** -0.157** (0.0290) (0.0302) (0.0709) (0.0727) MgrStake 7.307*** 17.56*** (2.421) (5.348) Observations 5,208 5,160 5,208 5,160 Controls Yes Yes Yes Yes Pseudo R^2 0.0214 0.0342 0.0209 0.0341

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Table 10: Investment Managers’ Presentations and Media Coverage These tables present difference-in-differences of media coverage as measured by the number of news flash articles in a given quarter (Panel A) and the number of full articles in a given quarter (Panel B) around investment managers’ presentations at investment conferences using a following model:

Mediai,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

Mediai,t is the count of news flash articles (Panel A) or full articles (Panel B) during the quarter. Treatmenti,t is an indicator variable that equals one if the firm is a treatment firm and zero if it is a control firm matched based on firm size, book-to-market ratio, and industry. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, stock return, stock turnover, analyst following, institutional ownership, an indicator variable for recommendation, and an indicator variable for S&P 500 index membership. Observations are firm-quarters. All variables are defined in Appendix A. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. Panel A: News flash articles (1) (2) (3) VARIABLES FlashArticles FlashArticles FlashArticles Post*Treatment 0.00656 -0.0197 -0.00578 (0.0703) (0.0781) (0.105) Post -0.0449 0.118** 0.0653 (0.0409) (0.0596) (0.0778) Treatment 0.134 0.114 (0.125) (0.0828) Observations 2,785 2,785 2,785 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.798 0.207 0.286

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Panel B: Full articles (1) (2) (3) VARIABLES FullArticles FullArticles FullArticles Post*Treatment 0.103 0.0957 0.0980 (0.0854) (0.0912) (0.106) Post -0.105* 0.00629 -0.0228 (0.0556) (0.0687) (0.0692) Treatment 0.119 0.0917 (0.135) (0.0833) Observations 2,785 2,785 2,785 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.704 0.187 0.279

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Table 11: Investment Managers’ Presentations and Firms’ Disclosure Behavior These tables present difference-in-differences of firms’ disclosure behavior as measured by bundled disclosure (Panel A) and unbundled disclosure (Panel B) around investment managers’ presentations at investment conferences using a following model:

Disclosure,t = β1Posti,t + β2Treatmenti,t + β3(Posti,t × Treatmenti,t) + ∑βkControlsk,i,t + FE + εi,t

Disclosurei,t is the count of management’s forecast guidance issued within five days of earnings announcements, including guidance issued concurrently with earnings announcements (bundled disclosure) (Panel A) and the count management’s forecast guidance issued within 60 days of earnings announcements but excluding any issued within five days of earnings announcements (unbundled disclosure) (Panel B) during the quarter. Treatmenti,t is an indicator variable that equals one if the firm is a treatment firm and zero if it is a control firm matched based on firm size, book-to-market ratio, and industry. Posti,t is an indicator variable that equals one for firm-quarter observations after investment conferences and zero otherwise. The primary independent variable is the interaction term of treatment indicator and post-conference period indicator. Controls include: firm size, return on assets, leverage, book-to-market ratio, stock price volatility, an indicator variable for loss, analyst following, institutional ownership, and an indicator variable for recommendation. Observations are firm-quarters. All variables are defined in Appendix A. All continuous variables are truncated at 1% and 99%. Year-quarter, firm, conference, and industry fixed effects are considered. Standard errors in parentheses are clustered by firm. *** indicates significance at 1%, ** at 5%, and * at 10%. Panel A: Bundled Disclosure (1) (2) (3) VARIABLES BundledDisclosure BundledDisclosure BundledDisclosure Post*Treatment -0.0143 0.0212 0.00433 (0.0313) (0.0421) (0.0391) Post 0.0264 -0.0225 -0.0274 (0.0227) (0.0352) (0.0334) Treatment 0.0610 0.0467 (0.0677) (0.0593) Observations 2,317 2,317 2,317 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.819 0.184 0.369

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Panel B:Unbundled Disclosure (1) (2) (3) VARIABLES UnbundledDisclosure UnbundledDisclosure UnbundledDisclosure Post*Treatment -0.0150 -0.00689 -0.0127 (0.0352) (0.0362) (0.0363) Post 0.00953 0.0310 0.0305 (0.0268) (0.0301) (0.0293) Treatment -0.00705 0.00491 (0.0373) (0.0369) Observations 2,320 2,320 2,320 Controls Yes Yes Yes Fixed Effects Firm/Year-Quarter Conf/Year-Quarter Industry/Year-Quarter Adjusted R^2 0.293 0.0419 0.0789

Internet Appendix

Institutional Investors as Information Suppliers:

Evidence from Investment Conferences

Johanna S. Shin The University of Chicago Booth School of Business

October, 2019

1

Table of Contents

IA.1 The Distribution of Institutional Investors

IA.2 Coordination of higher-order beliefs

Figure IA.1: Hedge fund ownership of firms presented at investment conferences

Table IA.1: Distribution of Institutional Ownership

2

IA.1 The Distribution of Institutional Investors

The level of investor sophistication may affect the extent to which available information is being

used. Examining the distribution of investors should then reveal the degree to which information

integration costs can be lowered, which is consistent with the guidance effect. For example, if a

firm’s investor pool mainly consists of less sophisticated investors, conference presentations can

aid these investors and enhance their understanding. In this case, the presentations will drive an

increase in price efficiency. By contrast, if a firm’s investor pool included more sophisticated

investors, the benefit of these presentations may be limited, because these investors may already

have sufficient capacity to process information.

I examine the distribution of stock ownership to corroborate if investment managers’

presentations lower investors’ information integration costs. I follow the literature and assume

hedge funds are sophisticated institutional investors (Brunnermeier and Nagel, 2004; Agarwal et

al., 2013; Jiao et al., 2016). I combine the list of hedge funds from TASS and Morningstar to

obtain hedge fund ownership from 13F filings. I take the remaining institutional ownership to be

held by less sophisticated investors. I also separate passive ownership because these funds do not

trade on information, and their ownership should not affect the discovery of prices in the market.

To measure passive ownership, I examine holdings of the three largest passive fund managers:

Blackrock, State Street, and Vanguard.1

Table IA.1 reports the results. I observe that hedge fund ownership is approximately 50%

less than non-hedge fund ownership for treatment firms both before and after the presentations.

That is, treatment firms’ investor pools include more of those who could benefit from these

presentations. The increase in the IPT may reasonably be attributed to the conference

1 These three fund managers account for approximately 80% of all ETF assets according to a Barron’s article of May 2019.

3

presentations lowering the market’s information integration costs, or the guidance effect.

However, given the nature of the distribution of institutional investors, I caution that hedge fund

ownership is significantly smaller than other institutional investors’ ownership across all equities

in general.

4

IA.2 Coordination of higher-order beliefs

Theoretical literature suggests that the coordination of beliefs among investors deters the market

from efficiently reflecting information in prices (Allen et al., 2006). Because transactions arise

from a mutual consent, market-clearing prices reflect both buying and selling parties’ valuation

of an asset. This process suggests prices cannot be solely determined by an investor’s belief.

Rather, prices will reflect an investor’s conjecture about counterparties’ valuations.

When investment managers present their ideas at the conferences, an open discussion of

specific stocks allows the market to learn about how other investors evaluate these firms. The

improvement in the formation of higher-order beliefs enables the market to better coordinate

beliefs, and prices can become more efficient. However, the improvement in price efficiency is

more likely to be temporary if it is driven solely by this coordination of higher-order beliefs. An

investment manager discusses his or her view at a point in time; it is unclear how his or her

belief will change in the long term. Because the presenter likely continues to update this belief,

the market may lose the ability to coordinate higher-order beliefs over time. In my setting,

because I observe a persistent improvement in price efficiency, the result cannot be attributed to

coordination alone.

I acknowledge the possibility that these presentations may homogenize investors’ use of

information as well as their beliefs, leading to a coordination of higher-order beliefs. This may

occur when investors interpret information similarly, as suggested in the conference

presentations, in the subsequent periods. Because these investors follow specific approaches to

evaluate firms, it becomes easier for the market to coordinate higher-order beliefs. Yet, the

coordination of higher-order beliefs, even if it exists in the long term, can then be interpreted as a

by-product of investment managers’ influence on investors’ information integration costs. In

5

other words, investment managers’ guidance effect is a necessary condition for the coordination

effect to arise.

Finally, I consider whether the distribution of institutional ownership across firms can be

consistent with the coordination of higher-order beliefs driving the improvement in the speed of

price discovery. Sophisticated investors may be able to coordinate their beliefs better among

themselves, because they acquire and integrate most of available information, while less

sophisticated investors may not be using the same set of information to the same degree. Table

IA.1 shows hedge funds’ ownership is approximately 1% greater for treatment firms, compared

to control firms after the presentations. A higher ownership by hedge funds indicates an

improvement in coordination efforts among sophisticated investors, which then increases price

efficiency. Figure IA.1 also shows that hedge funds’ ownership in the treatment firms increases

following the presentations, consistent with better coordination among those with superior

information processing ability. However, I question whether less than 1% of difference in hedge

fund ownership between treatment and control firms can have a meaningful impact on the

investors’ coordination efforts; I leave this question open for future research.2

2 In theory, if there were reasonable sample variation in how often other prominent investment managers presented contrarian cases to the already discussed stocks, I could test whether the coordination of higher-order beliefs can explain my findings. Public disagreement about a stock among sophisticated investors would reduce the plausibility of improving the formation of higher-order beliefs without reducing (necessarily) the plausibility of the presentations lowering investors’ information integration costs. However, given my small sample size, I leave the further investigation of the coordination of higher-order beliefs to future research.

6

Figure IA.1: Hedge fund ownership of firms presented at investment conferences Figure IA.1 plots hedge fund ownership of firms presented at investment conferences at time t by quarter for four quarters before and after the presentations.

7

Table IA.1: Distribution of Institutional Ownership These tables present the breakdown of institutional ownership of stocks before (Panel A) and after (Panel B) the presentations to assess the extent of investment managers’ impact on investors’ information integration costs. Panel A: Prior to presentations Treated=0 Treated=1 Obs. Mean Obs. Mean Diff t-stat Hedge Fund Ownership 669 0.0678 700 0.0756 -0.00781 -2.063** Passive Fund Ownership 669 0.126 700 0.126 0.000508 0.153 Other Inst. Ownership 669 0.572 700 0.576 -0.0045 -0.403

Panel B: After presentations Treated=0 Treated=1 Obs. Mean Obs. Mean Diff t-stat Hedge Fund Ownership 683 0.0702 712 0.0772 -0.00701 -1.992** Passive Fund Ownership 683 0.136 712 0.132 0.00366 1.0584 Other Inst. Ownership 683 0.572 712 0.580 -0.00823 -0.0736