Blankespoor, Hendricks, And Miller (20150527)_Final_SSRN

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Perceptionsandprice:EvidencefromCEOpresentationsatIPOroadshows

RESEARCH·MAY2015

DOI:10.13140/RG.2.1.3906.3204

3AUTHORS,INCLUDING:

ElizabethBlankespoor

StanfordUniversity

5PUBLICATIONS18CITATIONS

SEEPROFILE

GregoryMiller

UniversityofMichigan

25PUBLICATIONS1,038CITATIONS

SEEPROFILE

Availablefrom:ElizabethBlankespoor

Retrievedon:21August2015

Perceptions and price:

Evidence from CEO presentations at IPO roadshows

Elizabeth Blankespoor

Stanford University

Graduate School of Business

Bradley E. Hendricks

University of North Carolina at Chapel Hill

Kenan-Flagler Business School

Gregory S. Miller

University of Michigan

Stephen M. Ross School of Business

May 2015

Abstract

This paper examines the relation between rapidly formed basic cognitive impressions of

management and firm valuation. We develop a composite measure of investor perception using

30-second content-filtered video clips of initial public offering (IPO) roadshow presentations.

We show that this measure, designed to capture viewers’ impressions of a CEO’s competence,

trustworthiness, and attractiveness, is positively associated with an IPO firm’s secondary market

value. The result is robust to controls for traditional determinants of firm value. We also show

that firms with highly perceived management are more likely to be matched to high-quality

underwriters. Finally, we examine components of IPO price formation and find that our

composite measure of perception is positively associated with both the price proposed for the

offering and the price revision that occurs from this proposed price to the firm’s secondary

market valuation. Taken together, our results provide evidence that investors’ instinctive

impressions of management are incorporated into investors’ assessments of firm value.

We thank Bill Baber, Mary Barth, Bob Libby, Bill Mayew, Eddie Riedl, and workshop participants at the 2014

Duke/UNC Fall Camp, Georgetown University, London Business School, MIT Sloan School of Management, the

2015 Penn State Accounting Conference, Temple University, the University of Arizona, and the Victor L. Bernard

Memorial Conference for helpful suggestions. We also thank Schinria Islam and the Stanford Graduate School of

Business Behavioral Lab for excellent research assistance and support with survey creation and administration.

Blankespoor ([email protected]) received financial support from the Michelle R. Clayman Faculty Fellowship,

Hendricks ([email protected]) from the Kenan-Flagler Business School and the Deloitte

Foundation, and Miller ([email protected]) from the Michael R. and Mary Kay Hallman Fellowship and Ernst and

Young.

1

1. Introduction

In this study, we examine the relation between investors’ impressions of management and

firm valuation. The psychology literature indicates that basic impressions of others are formed

rapidly and “provide the anchor from which subsequent judgments are made” (Ambady,

Bernieri, and Richeson, 2000). This “thin-slice” literature highlights the wealth of information in

expressive, dynamic behavior, which individuals observe unconsciously and with little effort.

We predict that the impressions created from these observations impact investors’ assessment of

firm value. Following the thin-slice approach, we ask viewers to provide their perceptions of

CEOs after watching 30-second content-filtered video clips of a CEO’s initial public offering

(IPO) roadshow presentation. Consistent with our prediction, we find a positive association

between basic cognitive impressions and measures of firm value from the IPO process. By using

perceptions formed during the first major exposure of management to investors, we have a

unique setting to better understand the capital market consequences of investors’ rapidly formed

impressions.1

A body of research suggests that investors find value in meeting with management.

Surveys of investor relations firms and of analysts document that direct interactions with

management are highly sought after (Bushee and Miller, 2012; Brown, et al., 2015). Empirical

studies find that individual meetings with management are valuable for analysts and investors,

despite the Regulation Fair Disclosure (Reg FD) restrictions around selectively releasing

information (Bushee, Jung, and Miller, 2013; Green, et al., 2014; Soltes, 2014). There is also

evidence of the capital market responding to managers’ affect or emotion as revealed by vocal

cues during conference calls (Mayew and Venkatachalam, 2012). Specific to our setting, Ann

Sherman testified to the U.S. Senate in 2012 that investors primarily attend IPO roadshows “to

1 We use perception, impression, judgment, and assessment interchangeably throughout the draft.

2

get a feel for [management], because [investors] are not just investing in the idea or the product;

[investors] are investing or betting on the management team” (Sherman, 2012). Overall,

investors desire to meet management and appear to respond to the interactions with management.

This evidence, combined with the psychology literature’s documentation of individuals forming

intuitive impressions, suggests that investors could be forming perceptions of management

during these interactions and incorporating the perceptions into firm value.2

However, given the amount of verifiable information about firms and management

available to investors, it is not clear whether investors’ rapid, unreflective impressions of

management influence their valuation judgments. Firm financial reports describe the historical

performance of the firm under management and include detailed manager biographies that

discuss the manager’s prior experience, education, and general background. This information-

rich environment may suggest there is no role for basic cognitive assessments of management.

That is, investors might focus solely on the “hard” information provided in regulatory filings and

other disclosures to form expectations of future cash flows and assess the importance of

management in these expectations. Thus, the impact of basic impressions on firm valuation is an

empirical question.

Regardless of whether the market does use these basic impressions, it is interesting to

consider whether these impressions should rationally be incorporated into firm value. Manager

ability is often cited as one of the most important determinants of firm value (Drucker, 1954). If

the basic impressions of management provide accurate information on managers’ ability, the

impressions should be incorporated into firm valuations. The psychology literature provides

2 Investors could be hoping that managers will provide some additional “hard” information or disclosure beyond

those in the written documents, either knowingly in violation of Reg FD or on accident. In fact, it is likely that

investors hope to get both as these are not mutually exclusive. As discussed later in the document, we have designed

our impressions construct to remove all potential “hard” information.

3

evidence in other settings that rapid, unreflective impressions have accurately predicted

outcomes such as educational, sales, and medical evaluations, as well as political voting and

personal loan funding and default outcomes, especially when the observations involve dynamic

behavior rather than static photos (e.g., Ambady, Bernieri, and Richeson, 2000; Ambady,

Connor, and Hallahan, 1999; Todorov, et al., 2005; Duarte, Siegel, and Young, 2012).

On one hand, the connection between CEOs’ expressive behavior and firm outcomes may

not be as direct as for teaching or sales, implying that these rapid impressions may not be

accurate in the executive setting. In this case, any correlation between impressions and firm

value in the short term would be a result of investors applying a metric that is inappropriate in

this setting. Accordingly, there would be future stock reversal.

On the other hand, a primary component of the CEO’s task is to interact and

communicate with stakeholders such as employees, customers, suppliers, or investors. In this

role, they need to persuade others of their vision and motivate the necessary actions to be taken.

This suggests that rapid impressions of a CEO could predict the abilities of the CEO in a variety

of firm activities and thus be relevant for firm value. Our primary question in this paper is

whether rapid impressions are associated with price, but we also provide initial evidence of

whether the market treatment of this information appears to be rational.

We begin our empirical analysis by examining the association between basic perceptions

of management and secondary market firm valuation for a sample of 224 IPOs filed from 2011

through 2013 on U.S. exchanges. To estimate investors’ perception of management, we asked

naïve participants to view 30-second content-filtered thin slices of CEOs’ roadshow

presentations and assess each CEO’s competence, trustworthiness, and attractiveness on a seven-

4

point Likert scale.3 We use video clips because impressions formed from observing expressive

behavior are more accurate than perceptions based on still photos (Ambady, Connor, and

Hallahan, 1999). In addition, video clips are more representative of the roadshow experience,

which is likely the basis for IPO investors’ impressions of management. Each video clip is rated

by at least 40 participants, and we use the mean rating for each of the CEO’s characteristics to

estimate CEO-specific impressions of competence, trustworthiness, and attractiveness. The mean

of these three characteristics is our summary CEO-specific measure of perception, and it is

designed to capture investors’ overall impression of the CEO at the time of the firm’s IPO.

Our focus on information-rich expressive behavior captured from CEO presentations at

IPO roadshows provides several useful features for creating a clean research design. First, the

IPO roadshow is the first major, and often the only, exposure of management to IPO investors

prior to the market’s initial valuation of the firm, resulting in a clear link between investor

perceptions in that period and valuation (Ernst & Young, 2008).4 Second, the IPO roadshow is an

event common to all IPO firms, mitigating concerns about sample bias due to management

choosing whether and when to interact with shareholders. Third, the use of content-filtered video

clips allows us to base perceptions on rich, dynamic information about CEOs while controlling

for the content of what is being said. Fourth, because these are fundamental human judgments of

individuals, a generated instrument from a general population is a reasonable proxy for investors’

3 Each of these traits is a classic construct used extensively in the psychology and economics literature. A number of

studies find a relation between perceived competence and/or trustworthiness and economic outcomes, such as

political elections (Todorov, et al., 2005), teaching evaluations (Ambady and Rosenthal, 1993), company profits

(Rule and Ambady, 2008, 2011), and personal loan funding and payment outcomes (Duarte, Siegel, and Young,

2012). A manager’s general attractiveness may also impact investors’ assessment of the manager’s value to the firm,

given the evidence of a relation between attractiveness and compensation, confidence, perceived ability, and market

reaction to firm events (Hamermesh and Biddle, 1994; Mobius and Rosenblat, 2006; Halford and Hsu, 2014). 4 The Ernst & Young 2008 survey of institutional investors reports that more than 88% of institutional investors cite

the quality of the roadshow as a key nonfinancial measure in their buying decisions and that the roadshow is

generally “the only time a company’s senior management meets the investor.”

5

judgments of CEOs.5 Fifth, the IPO setting allows us to focus on younger firms where financial

performance is seen as less informative and assessment of management is considered more

important, increasing the power of our tests of the impact of perceptions of management (Kim

and Ritter, 1999; Chemmanur, Simonyan, and Tehranian, 2012).6

Using our summary measure of perception, we find a positive relation between

perceptions of management and the IPO firm’s secondary market value. The relation is robust to

the inclusion of important determinants of price (i.e., firm, offer, and CEO characteristics). These

results imply that investors’ intuitive impressions of management are relevant for firm valuation

independent of specific impacts previously studied.

In addition to the secondary market valuations, we examine how these impressions of

management relate to other portions of the IPO process. One of the first major decisions in the

issuance process is the matching of underwriter and issuer. Fernando, Gatchev, and Spindt

(2005) describe this as a mutual choice based on firm and underwriter characteristics. To the

extent that underwriters use their perceptions of an issuing firm’s management as information

about firm quality, we would expect these perceptions to impact the issuer-underwriter match,

with more positive perceptions of management increasing the likelihood of the issuer being

represented by high-quality underwriters. We find results consistent with this prediction.

Specifically, controlling for the size of the offering and other observable factors associated with

underwriter selection, we find that managers perceived more positively are more likely to be

represented by high-quality underwriters.

5 Consistent with this assumption, we find similar results using subsets of ratings based on rater characteristics. See

additional tests in Section 5. 6 In support of this, Kaplan and Stromberg (2004) examine venture capital firms’ reasons for investing in a given

company and find that 60% cite managerial quality as a reason, while only 27% cite performance to date. Note,

though, that while the IPO setting increases the power of the tests, the findings are less generalizable to other

settings.

6

We then turn to the IPO price-formation process, examining the impact of perceptions of

management on both the price proposed by underwriters prior to the beginning of the roadshow

and the price revision that occurs from the proposed price to the closing price on the firm’s first

day of trading on the secondary market. Similar to the issuer-underwriter matching, we predict

that impressions of management are positively related to the price proposed by underwriters.

However, if reputational concerns constrain underwriters to focus on more objective, verifiable

information when valuing issuers (Roosenboom 2007, 2012), underwriters’ impressions of

management would have a smaller or no impact on the proposed price. In the latter case, we

would expect investors to then impound this soft information into firm valuations during the

book building process (Benveniste and Spindt, 1989). Further, even if underwriters attempt to

include these less objective measures in their initial prices, the roadshow and book building

process likely result in additional information about general impressions of management. This

additional information would then be reflected in the secondary market price. We find a positive

relation between perception and both the proposed price and the price revision. These results

imply that underwriters incorporate their impressions of management into their assessment of

firm value but that this assessment is modified once underwriters get more feedback on the

perceptions from a broad set of investors.7

Finally, we perform several additional analyses and robustness tests. First, we examine

the association between our composite measure Perception and firms’ post-IPO stock

performance to provide descriptive evidence of whether the inclusion of these perceptions in

firm value was a rational decision. In both univariate and multivariate regressions, we fail to find

7 As part of the book building portion of the IPO process, investors that attend IPO roadshows are invited to submit

a series of limit orders for the IPO firm’s shares to the underwriters. Underwriters then use this information to

update the proposed IPO price to better reflect the actual level of demand for the offering, as indicated by these

investors.

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a statistically significant relationship between Perception and IPO firms’ buy-and-hold abnormal

returns. These results are not conclusive, but they suggest that investors acted rationally when

incorporating their perceptions of management into their valuations. Second, we re-estimate each

of the main regressions in our paper after excluding rater observations in which the rater either

recognized the CEO or exhibited suspicious behavior (e.g., providing the same response to each

request) and find that the results remain qualitatively similar.8 Third, we also re-estimate the

main regressions using ratings from specific demographics to ensure that the relation is not

driven by rater characteristics. Specifically, we sequentially restrict raters to: male raters, female

raters, raters under 30 years old, raters 30 years of age or greater, Caucasian raters, non-

Caucasian raters, raters who have attended at least some college or have a college degree, and

raters who have not attended college. In all cases, we draw similar inferences to those

documented when using the full sample of raters.9 These findings suggest that we are capturing

fundamental human judgments that are not unique to any particular observable demographic.

Our study contributes to several literature streams. First, our study brings additional

evidence to the literature examining whether and how management impacts firm market value. It

is difficult to disentangle management from the firm. A number of studies approach the issue by

testing for changes in investor behavior around a change in management, such as event studies of

abnormal stock returns following unexpected CEO turnover, death, or hospitalization (e.g.,

Johnson, et al., 1985; Bennedsen, Perez-Gonzalez, and Wolfenzon, 2012). Other studies model

the characteristics or skills of management (e.g., education, gender, founder-status, etc.) to see

8 We continue to find a positive relation between investor perceptions of managers and firm valuation (final and

proposed), underwriter matching, and price revision, significant at the 10% level or better in all cases. These

analyses are further discussed in Section 5.2 and tabulated in Table 9. 9 Specifically, we continue to find a positive relation between investor perception of managers and final firm

valuation (market value and book-to-market), underwriter matching, proposed firm valuation (market value and

book-to-market), and price revision across all subsamples, with 28 out of 32 specifications significant at the 10%

level or better.

8

whether these are correlated with firm value (e.g., Cohen and Dean, 2005; Hendricks and Miller,

2013). Our study turns instead to basic investor perceptions of management, in the tightly linked

setting of IPO roadshows, finding evidence of a relation between intuitive impressions of

management and firm value.

Second, our study makes a significant contribution to the IPO literature by being the first

to examine how information learned during the IPO roadshow influences IPO pricing. While

practitioners have suggested that investors learn valuable, nontangible information from

attending an IPO firm’s roadshow (NYSE/NASD, 2003; Sherman, 2012), our study is the first to

provide empirical evidence of the value of roadshow information, focusing on qualitative

information. Our results suggest that investors use roadshows as opportunities to learn important

information about a firm and its management.

Third, our study contributes to the disclosure literature by examining a disclosure channel

that includes a variety of nonverbal components. Prior research has shown the impact of firm

information and management disclosure choices in regulatory filings, press releases, conference

calls, and investor and industry conferences (e.g., Botosan, 1997; Li, 2008; Bushee, Jung, and

Miller, 2011; Blankespoor and deHaan, 2015). Several studies find evidence of an impact of

investors’ and analysts’ one-on-one meetings with management, implying that information may

be conveyed through multiple channels (Bushee, Jung, and Miller, 2013; Solomon and Soltes,

2013; Green, et al., 2014). Consistent with the potential importance of nonverbal behavior,

managerial affect conveyed through vocal cues in conference calls contains information about

financial misreporting and future performance (Hobson, Mayew, and Venkatachalam, 2012;

Mayew and Venkatachalam, 2012). Our study turns to the sensory-rich channel of roadshow

9

video presentations and finds evidence that valuable information about management is conveyed

through their nonverbal behavior.

2. Setting and motivation

2.1. Impressions

A stream of psychology literature examines social perception and the accuracy of

judgments using “thin slices,” or brief excerpts of expressive, dynamic behavior. Expressive

behavior and movements are seen as providing important information about the individual,

including affect, personality, and internal goals and motivations. Nonverbal behaviors

specifically are potentially very valuable for assessments because they are more difficult to

control or suppress but are easily observed (DePaulo, 1992). Essentially, these behaviors

represent a relatively unmanipulated signal about the individual’s true disposition.

Judgments of thin slices of expressive behavior are typically described as automatic or

intuitive processes that require little effort or awareness. For example, there is no evidence of

rater fatigue over time or due to increased cognitive load, and requiring explicit justification for

ratings can often reduce the accuracy of the judgments (Ambady, Bernieri, and Richeson, 2000).

These basic judgments are akin to System 1 thinking processes (Kahneman and Frederick, 2002;

Evans, 2008), which are described as more rapid, intuitive, and universal, rather than System 2

thinking processes that are slower, controlled, and logical. System 1 processes are described as

the primary response in a given situation, which is consistent with the automatic, unconscious

nature of thin-slice judgments.

Although thin-slice judgments are intuitive and unconscious, they are often predictive of

longer-term judgments that are arguably more logical and analytical. Using segments of behavior

ranging from as little as 10 to 60 seconds, studies find evidence that judgments of thin slices of

behavior are associated with final evaluations. For example, impressions of teachers based on

10

observation of a 30-second video clip predicted final course evaluations of teacher effectiveness

(Ambady and Rosenthal, 1993), and judgments of sales personnel based on 20-second video

clips were associated with management evaluations of the employees (Ambady, Krabbenhoft,

and Hogan 2006). In addition to predicting longer-term evaluations, there is evidence that thin-

slice judgments are also associated with performance outcomes. For instance, judgments of

physicians’ expression of concern based on 20-second audio clips were associated with their

history of malpractice (Ambady, et al., 2002), and perceptions of medical and occupational

therapy students based on 15-second video clips predicted clinical performance and final grades

(Rosenblum, et al., 1994; Tickle-Degnen, 1998; Tickle-Degnen and Puccinelli, 1999).10

Overall, this literature provides strong evidence that individuals form instinctive

impressions based on brief segments of human behavior, and that these impressions capture a

fundamental aspect of the perception of others that is associated with longer-term judgments and

outcomes.11 For the setting of firm valuation, the thin-slice findings imply that investors are

likely to form impressions of management based on brief interactions, such as a roadshow

presentation, and that these impressions have the potential to impact assessments of firm value.

2.2. Management impact on firm performance and valuation

Many studies find evidence of managers affecting firm performance and valuation.

Bertrand and Schoar (2003) find that manager fixed effects are related to firm practices and

performance, and Bennedsen, Perez-Gonzalez, and Wolfenzon (2010) show that CEO deaths are

10 We focus here on the literature examining perceptions of expressive behavior because this behavior provides a

richer information set. However, numerous studies also show evidence that instinctive impressions can be formed

based on brief exposure to still photos (e.g., Willis and Todorov, 2006) and that these impressions are predictive for

a variety of outcomes such as political voting, personal loan funding and default, and firm financial success

(Todorov, et al., 2005; Duarte, Siegel, and Young, 2012; Rule and Ambady, 2011). 11 This implies that first impressions remain influential even when subsequent information from repeated

interactions is incorporated (e.g., Lord, Ross, and Lepper, 1979; Rabin and Schrag, 1999). This implication

reinforces the usefulness of examining first impressions since they are shown to persist through repeated

interactions. However, our study does not attempt to answer whether or to what extent first impressions impact later

perceptions.

11

correlated with changes in firm profitability, investment, and growth. Focusing on valuation,

Johnson, et al., (1985) find a relation between executive characteristics and market reaction to

their unexpected deaths, implying that manager talent and responsibility are associated with firm

valuation, and Hayes and Schaefer (1999) find variation in the market reaction to managers’

movements to different jobs that is consistent with managerial characteristics being incorporated

into stock price. Similarly, Adams, Almeida, and Ferreira (2005) find that returns are more

variable for more powerful CEOs, supporting the theory that CEO characteristics can influence

performance and firm valuation.

The impact of management on valuation may be even higher for younger firms, such as

IPO and pre-IPO firms. Management characteristics like education and experience (e.g., Cohen

and Dean, 2005; Higgins and Gulati, 2006), gender (Bigelow, et al., 2014), and founder-status

(Hendricks and Miller, 2013) impact IPO investor interest and valuation. Bernstein, Korteweg,

and Laws (2014) provide further evidence that investors place significant value on information

about the human capital of young firms by using a randomized field experiment to show that

investors respond more strongly to information about the founding team than they do to

information about firm traction or existing lead investors.

An underlying assumption of this literature is that investors somehow observe and

incorporate manager ability into firm valuation, but it is difficult to directly identify investors’

assessments and match them with the relevant firm valuation because investor perception of

management is typically not observable. In addition, even if investor perceptions are observable

at a given point in time, firm values at that given moment are generally the result of repeated

interactions and assessments. To overcome these difficulties, we use basic human impressions

12

from thin slices of managers’ nonverbal behavior displayed during investors’ first major

exposure to the firm’s management.12

2.3. The role of roadshows in the IPO process

Uncertainty is pervasive throughout the IPO process. Potential investors usually know

very little about the issuer prior to the offering and the issuer knows neither the investors who

may be interested nor their level of interest. To reduce this bilateral information asymmetry, an

issuer is required to file a registration statement with the SEC that provides extensive

information about the firm (Leone, Rock, and Willenborg, 2007; Loughran and McDonald,

2013). After this document is filed, issuers enter into a designated quiet period that extends

through the completion of the offering. In the event that an issuer learns new information during

the quiet period, the issuer has a responsibility under the Securities Act of 1933 to communicate

this new information to investors by amending its registration statement. By placing the issuer in

a quiet period, and requiring that all information included in the registration statement be

accurate13, the registration process is designed to provide investors with all the information they

need to make an informed investment decision in a single document.

Having provided this information to investors, the issuing firm’s management team

travels to various financial centers to promote the offering through a series of roadshows (see

12 Several concurrent studies estimate perceptions of CEOs based on photos of the CEO and examine their relation

to a variety of measures, including CEO compensation, firm performance, and market reponse to various events

such as job, earnings, and merger announcements (Graham, Harvey, and Puri, 2014; Halford and Hsu, 2014). In

contrast, our study examines perceptions based on a rich information set that better represents the information

underlying investor perceptions (dynamic videos rather than static photos) within the IPO setting that enables a tight

link between perceptions and firm valuation. 13 While the SEC requires that the information provided be accurate, it does not guarantee it. However, investors

who purchase securities and suffer losses have important recovery rights if they can prove that there was incomplete

or inaccurate disclosure of important information.

13

Fig. 1).14 This process typically involves the firm’s management giving multiple presentations a

day to institutional investors over the final two to three weeks of the registration period. In these

presentations, management is counseled to only make factually accurate statements that coincide

with the registration statements filed with the SEC (Arcella, 2011). Despite the information

being repetitive, Ann Sherman testified to the U.S. Senate in 2012 that investors primarily attend

roadshows to observe the managers and “find value in watching them on their feet” (Sherman,

2012). This view that observing an IPO firm’s management provides investors with valuable

information was also expressed by the NYSE/NASD advisory committee formed in 2003 to

examine the fairness of the IPO process. In considering institutional investors’ selective access to

roadshows, the committee concluded:

[E]ven the opportunity to see and hear senior management may provide

significant information for an investment decision. Many potential investors, both

in the IPO and in the aftermarket, having been excluded from the roadshow, are

not privy to this information. To dispel the perception of unfairness, this must

change. (NYSE/NASD, 2003)

In November 2004, many of the recommendations provided by the NYSE/NASD

advisory committee were included in the SEC’s proposed regulation to enhance the

communication, registration, and offering process under the Securities Act of 1933. This reform,

now referred to as the 2005 Securities Offering Reform, was unanimously adopted on June 29,

2005 with only minor modifications to the proposed legislation. Included in both the proposed

and final reform, issuers that conduct roadshows in conjunction with an equity offering are

required to file an electronic copy of one of their roadshows with the SEC as a free-writing

prospectus. However, IPO firms are allowed to treat the roadshow as an oral communication

14 A roadshow is defined under Rule 433 of the Securities Act of 1933 as an offer (other than a statutory prospectus

or a portion of one filed as part of a registration statement) that contains a presentation made by one or more

members of the issuer’s management team.

14

rather than a free writing prospectus if they make a “bona fide” electronic roadshow available to

unrestricted audiences during the registration period. 15 By classifying roadshows as oral

communications, IPO firms are not required to file the roadshows with the SEC.

The roadshow is an important part of the IPO process because it allows investors to learn

valuable information about an issuing firm. However, it is also important to the underwriter

because it provides an opportunity to gauge the amount of investor demand that exists for a

firm’s offering (Rock, 1986; Benveniste and Spindt, 1989). While the underwriter proposes a

suggested pricing range for a firm’s offering at the beginning of the roadshow period, the

majority of offerings price outside of this proposed range, suggesting that investors’ indications

of interest are often significantly different from underwriters’ expectations (Cornelli and

Goldreich, 2001, 2003; Lowry and Schwert, 2004).

3. Data

3.1. IPO roadshows

We began using video capture software on April 1, 2011 to obtain IPO roadshows from

RetailRoadshow.com, a website that provides public access to online roadshow presentations for

current public offerings. As discussed in Section 2.3, firms offering securities for purchase in the

public markets use roadshows to market the offering to potential investors at the conclusion of

the registration period. To comply with the 2005 Securities Offering Reform, these firms provide

RetailRoadshow with a “bona fide” version of their roadshow during the final weeks of the

15 A bona fide electronic roadshow is defined in the final regulation as “a roadshow that is a written communication

transmitted by graphic means that contains a presentation by one or more officers of an issuer or other persons in an

issuer’s management and, if the issuer is using or conducting more than one roadshow that is a written

communication, includes discussion of the same general areas of information regarding the issuer, such

management, and the securities being offered as such other issuer roadshow or roadshows for the same offering that

are written communications. To be bona fide, the version need not address all of the same subjects or provide the

same information as the other versions of an electronic roadshow. It also need not provide an opportunity for

questions and answers or other interaction, even if other versions of the electronic roadshow do provide such

opportunities.” Refer to Rule 433, “Conditions to permissible post-filing free writing prospectuses,” for additional

details about free writing prospectuses and the criteria for a roadshow to be classified as an oral communication.

15

registration period. During this time, individuals may view the roadshow as often as they like.

However, when the offering is priced, the roadshow presentation is removed from

RetailRoadshow.com and can no longer be viewed.

3.2. Sample Selection

We use the Global New Issues Database within Thomson Financial’s SDC Platinum to

obtain a listing of all U.S. industrial firms that completed an original IPO in the United States

from April 1, 2011 to December 31, 2013. We choose April 1, 2011 to begin our study because

that is the date we began to capture IPO roadshows from RetailRoadshow.com. Consistent with

prior research on IPO firms, we exclude: firms that raised less than $10 million, firms that priced

below $5 per share, limited partnerships, and unit offerings. Our research design also requires

each firm to have historical financial information and first-day stock returns. Accordingly, we

remove firms whose information was either incomplete or missing from Compustat and/or

CRSP. Finally, we exclude firms from our sample whose roadshows did not include video, did

not feature presentations from their management team, or were not captured from

RetailRoadshow.com. As detailed in Table 1, 224 IPO filings remain in our study after applying

these criteria.

3.3. Perceptions of management

To measure perceptions of management, we follow the thin slice research in the

psychology literature and extract a brief portion of each IPO roadshow video to examine. An

underlying assumption of the literature is that each thin slice of management behavior is

representative of the entire behavioral sequence from which it is extracted. To this end, prior

research has generally extracted three samples from a behavioral sequence rather than use a

single excerpt from the behavioral sequence (Ambady, Bernieri, and Richeson, 2000). This

16

approach also enables controlling for linear trends (e.g., fatigue) observable in the behavioral

sequence. Accordingly, we follow this approach and construct a 30-second thin slice using three

10-second excerpts from the first five minutes of each CEO’s roadshow presentation.

Specifically, we take the first excerpt at the beginning of each CEO’s presentation and combine

it with two additional 10-second excerpts taken two and four minutes after the initial 10-second

excerpt has ended.16

Although we only use 30 seconds of excerpts from each video, there is still the concern

that viewers’ impressions may be shaped by factual information about the firm conveyed during

these excerpts. Because we are trying to isolate investor judgment of management independent

of firm performance, we choose to content-filter the video, following Ambady, Krabbenhoft, and

Hogan (2006). Specifically, we use both a lowpass and highpass filter to remove specific

frequencies that aid in word recognition. After this process, the actual words spoken by the CEO

are unintelligible, but the sequence and rhythm of their speech is preserved.

We use Amazon’s Mechanical Turk (MTurk) service to analyze each of the 224 thin

slices created from the roadshow presentations. This online labor market allows requesters to

post jobs to be completed from an on-demand workforce for relatively low pay. While MTurk

was created for human computation tasks, numerous studies provide evidence that MTurk is a

viable alternative to the traditional lab setting for behavioral research in a variety of fields, with

MTurk’s more diverse pool of participants creating a meaningful advantage (e.g., Paolacci,

Chandler, and Ipeirotis, 2010; Buhrmester, Kwang, and Gosling, 2011; Mason and Suri, 2012;

Crump, McDonnell, and Gureckis, 2013). In finance and accounting research, MTurk is starting

16 An alternative to this approach would be to take samples from the beginning, middle, and end of the entire

presentation, rather than just the first five minutes. However, a linear trend such as fatigue would have a more

significant impact on those clips taken from the middle and end portions of longer presentations. Our approach

removes these concerns while still capturing some of the linear trends that might appear in the manager

presentations.

17

to be used as an alternative to traditional lab experiments (e.g., Rennekamp, 2012; Koonce,

Miller, and Winchel, 2014; Asay and Hales, 2015), and there is also potential for this data source

to be used when researchers need to generate a construct not available via archival sources (e.g.,

Duarte, Siegel, and Young, 2012). Our goal is to capture basic human cognitive perceptions, and

thus MTurk’s broad, diverse pool of participants helps ensure that our tests and results are based

on measures of innate processing and not unduly influenced by characteristics of a specific group

of people.

Studies that examine the reliability of data originating from MTurk provide several

recommendations for maximizing data quality. We designed the Human Intelligence Task (HIT)

that we posted to MTurk in accordance with these recommendations. Specifically, we require

that each MTurk worker be located in the United States and have an approval rating of at least

95% on their previous assignments. We also attempt to ensure software compatibility by

including a sample thin-slice video at the beginning of the survey and asking whether the MTurk

worker is able to see and hear the video. MTurk workers that indicated that they were unable to

either see or hear the video were not allowed to complete the HIT. Finally, we included an

attention-check question at both the beginning and the end of the HIT and perform robustness

tests in Section 5 using only responses from MTurk workers that correctly answered these

attention-check questions.17

Table 2 Panel A provides demographic information about the MTurk workers in our

sample. Of the respondents, 87% are between 18 and 50 years old, and slightly over half (53%)

17 Prior to undertaking our data collection on MTurk, we performed a pilot survey in the Stanford GSB Behavioral

Lab to pretest our approach. We had 100 students view a sample of videos and fill out a prototype questionnaire.

This allowed us to observe individuals completing our survey and to ask them questions about the experience as

they left. The insights from the pilot test allowed us to adjust our process to reduce misunderstandings and thus

enhance the validity of the information collected from the MTurk system. The pretest was not designed to generate

usable observations, and accordingly, none of the data is used in this paper.

18

are male; 74% identify themselves as Caucasian, and 81% have at least some college education

(with 51% having college or graduate degrees). As shown in Fig. 2, we ask the MTurk workers

to use a seven-point Likert scale to provide their impressions about a CEO’s competence,

trustworthiness, and attractiveness after watching each CEO’s roadshow presentation. As Table 2

Panel B describes, the full rating scale is utilized by respondents, with 64% of ratings falling in

the range of 3 to 5, 17.5% below 3, and 18.5% above 5.

Each CEO is rated by at least 40 MTurk workers, and we take the average MTurk worker

rating for each of the CEO’s characteristics to create the following three CEO-specific variables:

Competent, Trustworthy, and Attractive.18 We then calculate the average of these three variables

to create a summary CEO-specific variable, Perception.19 Our motivation for creating Perception

is based on our belief that investors’ perceptions are likely to be formed by more information

than can be encompassed by any single trait. Accordingly, we view Perception as the overall

impression about a CEO at the time of a firm’s IPO.20

Table 2 Panel C provides the distribution of average CEO ratings. Perception ranges

from 3.00 to 5.00, with 79% of the observations falling between 3.50 and 4.50. For the individual

characteristics, Competent (Attractive) has a higher (lower) mean, and Attractive has a larger

standard deviation, ranging from below 2.25 through 5.00. Table 3 Panel A confirms these

statistics, showing a mean Perception of 4.05, mean Competent of 4.72, and mean Attractive of

3.28. Panel B also shows that the different perceptions about CEOs are highly correlated. This

observation is consistent with prior studies showing that perceptions about an individual’s

18 See the Appendix for more details about survey design and implementation, and see Section 5 for robustness tests

related to rating quality. 19 Results for our main tests using the quartile rank of Perception rather than the continuous measure yield the same

inferences. 20 Given this belief, the majority of the commentary included in our empirical analysis is focused on the associations

identified between Perception and the various empirical outcomes examined in this paper.

19

attractiveness are positively related to perceptions about that individual’s competence and

trustworthiness (Eagly, et al., 1991; Etcoff, et al., 2011). Table 3 Panel A also provides

information about the personal characteristics of the CEOs included in our sample. We find that

the average age for a CEO is 51 years old. We also observe that only 4% are female, 14% earned

a degree outside the United States, 59% earned a postgraduate degree, and 36% are founder-

CEOs. This panel also provides information about the roadshow characteristics, revealing that

65% of the retail roadshows are captured from live presentations to investors and that 8% of the

CEOs are seated during their presentations.

4. Empirical results

4.1. Determinants of perception

We begin our empirical analysis by examining the determinants of Perception. Our

motivation for this analysis is to investigate how CEO, roadshow, and firm characteristics

influence perceptions of senior management. To do so, we estimate the following pooled OLS

model:

Perceptioni = β0 + β1 CEO_Agei + β2 Femalei + β3 Foreigni + β4 Grad_Schooli

+ β5 Founderi + β6 Experiencei + β7 Livei + β8 Sittingi + β9 Backgroundi

+ β10 Assetsi + β11 Profitabilityi + β12 R&D_Inteni + β13 Firm_Agei

+ β14 VCi +Fixed Effects + εi (1)

in which Perception is the average of Competent, Trustworthy, and Attractive as described in

Section 3.3. CEO_Age is the natural log of the CEO’s age. Female is an indicator variable that

takes the value of one if the CEO is female. Foreign is an indicator variable that takes the value

of one if the CEO completed a degree from a university outside the United States. Grad_School

is an indicator variable that takes the value of one if the CEO earned a postgraduate degree.

Founder is an indicator variable that takes the value of one if the CEO is also the founder for the

20

IPO firm. Experience is an indicator variable that takes the value of one if the CEO’s prior

employer was a publicly traded firm.

In addition to these CEO-specific characteristics, we also include variables relating to the

roadshow presentation that could influence investor perceptions. Live is an indicator variable and

takes the value of one if the retail roadshow appears to be recorded from an actual presentation

made to institutional investors. Sitting is an indicator variable that takes the value of one if the

CEO is sitting during the presentation. Background is an indicator variable that takes the value of

one if an investment bank’s logo is visible in the background during the CEO’s roadshow

presentation.

Finally, we also include several firm characteristics in our model. If higher-quality CEOs

match with higher-quality firms then it is possible that firm characteristics will be informative

about Perception. Assets is the natural log of the firm’s total assets prior to IPO. Profitability is

the firm’s trailing twelve months net income divided by its total assets prior to IPO.

R&D_Intensity is the firm’s trailing twelve months R&D expenditures divided by its total assets

prior to IPO. Firm_Age is the natural log of the firm’s age at the time of its IPO. VC is an

indicator variable that takes the value of one if the firm has venture backing at the time of IPO.

Finally, we winsorize continuous variables at 1% and 99%, and we include both calendar-year

and industry fixed effects (based on the Fama French 12-industry classifications) in several of

the specifications, as noted in the tables.

Table 4 provides the results of estimating Eq. (1). Columns 1 through 3 of Table 4

present the results of regressing Perception on the CEO-specific, roadshow presentation, or firm

characteristics, respectively. Consistent with impressions about an individual being primarily

determined by individual-specific information, we observe that the adjusted R-squared is much

21

larger in Column 1 than it is for Columns 2 and 3. Further, Column 4 includes all the variables

outlined in Eq. (1) and indicates that five of the six variables that are statistically significant

indicators of Perception are CEO-specific variables. Specifically, CEO_Age, Foreign, and

Founder are all negatively associated with Perception whereas Female and Grad_School are

both positively associated with Perception. Overall, Table 4 provides new insight into how a

CEO’s personal characteristics influence investor perception. In addition, the adjusted R-squared

of only 0.253 highlights the fact that investor perception encompasses more than just observable

characteristics. Because we are interested in fundamental investor perception not explained by

these observable characteristics, we include the CEO and firm characteristics as control variables

in subsequent analyses.

4.2. Perception and firm value

Our main prediction is that impressions of a firm’s CEO are positively associated with firm

value. The underlying premise of this prediction is that if manager ability has the potential to impact

firm value, then perceptions about a firm’s manager should be impounded in that firm’s market

valuation. However, it is possible that investors choose to ignore these rapid System 1 assessments

and focus on more analytical System 2 assessments of management and financial performance,

resulting in no relation between firm valuation and intuitive impressions of managers. Thus, we turn

to regression analysis to empirically estimate the relation.

We use the log of the firm’s market value to proxy for firm value. Value-relevance studies of

IPO firms generally use the total market value of equity or a log transformation of that amount as the

dependent variable. 21 Comparing models that use these two measures, those that use the log

21 While value-relevance studies often use a firm’s price per share as the dependent variable, the IPO literature has

generally used alternative measures to examine questions of value-relevance since underwriters prefer to price each

offering around $15 (Fernando, Krishnamurthy, and Spindt, 2004). This clustering around a single price forces the

explanatory power to come through the correlation between the variable of interest and the number of shares

22

transformation generally provide the best fit (Beatty, Riffe, and Thompson, 2000; Hand, 2003).

Further, its distribution more closely resembles that of a normal distribution, providing it with

attractive econometric properties. Thus, we follow prior research and use the log transformation of

each firm’s total market value of equity as the dependent variable for our tests and estimate the

following pooled OLS regression:

L(MVE_Final)i = β0 + β1 Impressioni + β2 L(Book_Value)i + β3 L(Revenues)i

+ β4 L(Net_Income)i + β5 L(R&D_Expense)i + β6 Firm_Agei + β7 Underwriteri

+ β8 VCi + β9 Big4i + β10 Secondary_Sharesi + β11 Insider_Retentioni

+ β12Mkt_Cond_Leveli + β13-18CEO_Characteristics + Fixed Effects + εi (2)

in which L(MVE_Final) is the natural log of a firm’s market value of equity calculated at the close of

its first day trading on a public exchange. Impression is our primary variable of interest and takes the

value of Perception, Competent, Trustworthy, or Attractive as defined in Section 3.3.

We include several control variables in our model that have been shown to be important

indicators of IPO firm value. Following Aggarwal, Bhagat, and Rangan (2009), we include the log

transformations of each firm’s book value of equity, revenues, net income, and R&D expense for the

12 months prior to their IPO date.22 We also include other nonfinancial measures of firm quality as

suggested by prior research. Specifically, we include Firm_Age calculated as the natural log of 1 plus

the firm’s age at IPO (Fernando, Gatchev, and Spindt, 2005), Underwriter calculated as the average

Carter-Manaster ranking of the firm’s lead underwriters (Leland and Pyle, 1977; Carter and

Manaster, 1990), VC as an indicator variable that takes the value of one if the firm has venture-

capital backing (Barry, et al., 1990; Megginson and Weiss, 1991), Big4 as an indicator variable that

takes the value of one if the firm has a Big4 auditor at the time of IPO (Titman and Trueman, 1986),

outstanding. As a result, value-relevance studies of IPO firms that use a traditional price per share measure generally

provide highly unstable results and offer very little explanatory power (Beatty, Riffe, and Thompson, 2000). 22 Consistent with prior studies, we make the log transformation to these variables by taking the natural log

(1+value) when the original value is positive and –log (1-value) when the value is negative. This transformation is

able to retain the negative values included in the original data while also maintaining the monotonic relationship

among the actual realized values.

23

Secondary_Shares as the percentage of a firm’s shares being offered that are owned by existing

shareholders (Brau, Li, and Shi, 2007), Insider_Retention as the percentage of a firm’s total shares

that are retained by executives and directors after the offering (Jain and Kini, 1994), and

Mkt_Cond_Level as the NASDAQ level at the time of a firm’s IPO (Ritter, 1984; Ljungvist and

Wilhelm, 2003). 23

Table 5 presents the results from estimating Eq. (2). Consistent with our main prediction,

Column 1 shows that the estimated coefficient for Perception is 0.4340 (p-value < 0.01). 24

Importantly, the model includes the six CEO characteristics discussed in Eq. (1), suggesting that our

finding is not simply driven by these other CEO-specific qualities.25 Rather, this finding is consistent

with the NYSE/NASD (2003) IPO Advisory Committee’s statement that “even the opportunity to see

and hear senior management may provide significant information for an investment decision.”

Columns 2 through 4 of Table 5 provide the results of regressing the log of market value on

the components of Perception. As shown, the coefficients for Competent, Trustworthy, and Attractive

are all positive, providing evidence of a positive relation between perceptions of management and

firm valuation. Competent and Attractive are both significantly different from zero at the 0.023 level

or better, while Trustworthy is not significantly different from zero. One possible explanation for the

weaker results for Trustworthy is that investors might rely on monitoring mechanisms, such as

regulators and auditors, to ensure that management is not undertaking inappropriate or fraudulent

activities.

4.3. Perception and underwriter matching

23 We thank Jay Ritter for providing the Carter-Manaster rankings and each IPO firm’s founding date on his website

(http://bear.warrington.ufl.edu/ritter/ipodata.htm). 24 Note that since we have a directional prediction for the relation between perception of management and firm

value, we report one-tailed statistical significance for the various impression variables in the firm value, underwriter

matching, and proposed price tests. 25 For brevity, we do not report the coefficients for these CEO characteristics. However, for Column 1 of Table 5,

none of these variables are estimated to be statistically significant determinants of firm value when using

conventional significance levels (p-value < 0.10).

24

We next examine how impressions of a firm’s manager influence underwriter matching and

the IPO price-formation process. Examining relations at these earlier stages of the IPO process

allows us to both validate our primary results of an association between price and investor

perceptions and to better understand how these perceptions enter into price.

IPO firms and underwriters associate by mutual choice, with prior research providing

evidence that the quality of issuing firms is positively associated with underwriter quality

(Chemmanur and Fulghieri, 1994; Fernando, Gatchev, and Spindt, 2005). To the extent that

underwriters rely on their perceptions about a firm’s manager as valuable information about firm

quality or as expectations of the market’s likely assessment of the firm, then these perceptions should

be useful in understanding the underwriter matching that occurs between firms and underwriters.26

Accordingly, we examine this relation by estimating the following pooled OLS regression:

Underwriteri = β0 + β1 Impressioni + β2 Filing_Sizei + β3 Assetsi + β4 Revenuesi

+ β5 Profitabilityi + β6 R&D_Intensityi + β7 Firm_Agei + β8 VCi + β9 Big4i

+ β10 Insider_Retentioni + β11-16CEO_Characteristics + Fixed Effects + εi (3)

in which Underwriter is the average Carter-Manaster ranking of the firm’s lead underwriters,27

Filing_Size is the natural log of the size of the offering, and the remaining variables are as previously

defined.28

Table 6 provides the results from estimating Eq. (3). Consistent with impressions about a

firm’s manager being used by underwriters as an indicator of firm quality, Column 1 reports that the

coefficient for Perception is estimated to be 0.2746 (p-value = 0.017). The importance of this benefit

26 Underwriter assessment of quality and underwriter prediction of market assessments are related concepts. In the

former, the underwriter provides an honest personal assessment of firm quality. In the latter, they assess whether the

market will be interested in the firm at a higher price. Both assessments should help an underwriter predict both

eventual price and the value of being involved in the IPO. 27 We repeat the analysis using the market share of the firm’s lead underwriters, and find very similar results. 28 We model Eq. (3) following the model employed in Fernando, Gatchev, and Spindt (2005). In their model, they

examine how the filing size, firm age, venture backing, profitability, market value of equity, five-year survival

indicator, secondary equity offering indicator, and number of analysts influence underwriter matching. However, we

exclude the final four variables from our model since they are not known at the time of matching. We then

supplement the model with additional variables known at the time of IPO and believed to be important indicators of

firm quality. Specifically, we include Assets, Revenues, R&D Intensity, Big4, and Insider_Retention.

25

is evident when considering that more prestigious underwriters provide issuing firms with all-star

analyst coverage, more reputable syndicates, and higher valuations (Fernando, et al., 2012). In

addition, consistent with the earlier results, Columns 2 through 4 report positive and significant

coefficients for Competent and Attractive (p-values < 0.01 and = 0.081). While prior research has

primarily focused on how a firm’s financial information influences underwriter matching (Fernando,

Gatchev, and Spindt, 2005), our result suggests that an IPO firm’s management team also plays an

important role in attracting prestigious underwriters.29

4.4. Perception and IPO price formation

Section 4.3 provides evidence that underwriter behavior is influenced by the underwriter’s

impressions about a firm’s manager. If true, then we would expect underwriters to include this

information in the valuations that they propose at the beginning of the IPO price-formation process.

However, Roosenboom (2007, 2012) provides evidence that underwriters primarily use financial

models (e.g., dividend discount model, comparable multiples) for their proposed valuations and then

apply an additional discount due to reputational concerns. This valuation methodology may restrict

soft information from being fully reflected in the underwriter’s proposed valuation. In this case, we

would then expect investors to impound this soft information into firm valuations during the

book building process. In addition, predicting market participants’ perceptions is more difficult than

observing them; even if underwriters do incorporate their perceptions of management into the

proposed price, the roadshow and book building process is likely to provide additional information

29 We assume that the perception of management captured during the roadshow is correlated with or representative

of the perception of management that occurs during the underwriter matching. However, it is possible that

underwriter training of management during the IPO process improves the perception of management. If high-quality

underwriters provide better communication training for management than low-quality underwriters, the positive

relation between the perception of the management team and underwriter quality could be partly due to underwriter

training rather than underwriter matching. We control for pre-IPO training possibilities, such as interaction with

venture capital firms and the prior public firm experience of the CEO. In addition, given the inherent, subconscious

nature of the expressive behavior being assessed, it is unlikely that individuals could learn to completely control or

influence their behavior (Ambady, et al. 2000), much less learn this in the few months of underwriter interactions

before an IPO.

26

about investors’ basic perceptions of managers. This information would then be incorporated into

price adjustments during the book building process.30 Accordingly, we examine how investors’

perceptions about a firm’s manager are related to both the underwriter’s proposed valuation and the

revision that occurs to the proposed valuation to arrive at the firm’s secondary market value.

4.4.1. Perception and IPO price formation – proposed valuation

We begin this analysis by examining how Perception is associated with underwriters’

proposed valuations. To do so, we modify Eq. (2) by substituting the underwriter’s proposed

valuation (L(MVE_Proposed)) as the dependent variable in place of the firm’s market value at the

close of its first day of trading on the secondary market (L(MVE_Final)). Table 7 provides the results

from estimating this regression. Consistent with underwriters proposing valuations that reflect

information about their impressions of management, Column 1 of Table 7 reveals that β1 is estimated

to be 0.2906 (p-value = 0.009). Columns 2 through 4 show that the coefficients on Competent,

Trustworthy, and Attractive are also all positive, with Competent and Attractive significantly

different from zero (p-values = 0.031 and < 0.01). Overall, our results suggest that underwriters

incorporate various types of information about the issuing firm, including perceptions of

management, into the proposed price (Kim and Ritter, 1999).

4.4.2. Perception and IPO price formation – price revision

The previous section suggests that underwriters reflect at least some information about

their perceptions of management into the valuations they propose for issuing firms. However, as

previously noted, underwriters face reputational and other pricing pressures that may influence

the extent to which they reflect this information. Further, the incorporation of numerous market

30 This idea is similar to the concept of using multiple raters when the variable of interest involves considerable

judgment, which is what motivates us to use more than 40 raters per video. To show empirical support in our setting

for the benefit of many judges, we re-estimate our main tests using only one randomly selected rater for each CEO

video (rather than 40 raters). Consistent with the concept that more raters improve the average estimation, we do not

find a significant relation between the one randomly selected CEO rating and firm value.

27

participants during the roadshow and book building process may result in additional information

about market perceptions of management. Accordingly, we investigate whether the perceptions

of a firm’s manager are differentially weighted by investors relative to underwriters by

examining the price revision that occurs from the proposed price to the closing market price on

firms’ first day of trading.31 To do so, we estimate the following pooled OLS regression:

Revisioni = β0 + β1 Impressioni + β2 Filing_Size + β3 Assetsi + β4 Revenuesi

+ β5 Profitabilityi + β6 R&D_Intensityi + β7 Firm_Agei + β8 Underwriteri

+ β9 VCi + β10 Big4i + β11 Secondary_Shares + β12 Insider_Retentioni

+ β13 Mkt_Cond_Changei + β14-19CEO_Characteristics + Fixed Effects + εi (4)

in which Revision is defined as the percentage change between an issuing firm’s closing price

per share on its first day of trading on the secondary market and the price per share initially

proposed by the underwriter. Mkt_Cond_Change is the average daily change on the NASDAQ

stock exchange between the date when a price is initially proposed for an offering and the offer

date. This variable captures new information about the macroeconomic conditions that arise

during this period and has been shown to be a powerful determinant of the price revision (Lowry

and Schwert, 2004). All other variables are as previously defined.

Table 8 Panel A provides the results from estimating Eq. (4). β1 is our primary variable of

interest in this equation. Consistent with investors providing additional information about

perceptions of management during the book building process that is incorporated into firm value,

Column 1 indicates that the coefficient for Perception is estimated to be 0.2275 (p-value =

0.027). Turning to the components of Perception, all three (Competent, Trustworthy, and

Attractive) coefficients are estimated to be positive, but only Attractive is significantly different

31 Note that this prediction is two-sided, rather than one-sided like the final market value, underwriter, and proposed

price predictions. Information about investors’ perception of management relative to the underwriters’ estimate

could potentially modify the proposed price upward or downward. Thus, two-tailed p-values are reported for the

Perception variables in this test.

28

from zero (p-value < 0.01). Taken together, these results provide further evidence that investors

use their perceptions of management as significant indicators of firm value.

To gain further insight into this result, we decompose Revision into two components: the

change from the proposed offer price to the final offer price (Price_Update) and the change from

the final offer price to the closing price on the firm’s first day of trading on the secondary market

(Initial_Returns). As shown in Table 8 Panel B, the coefficient between Perception and each of

these two subcomponents (Price_Update and Initial_Returns) is positive, but the relation is only

significantly different from zero for Price_Update (p-value = 0.055). Thus, the positive relation

between Perception and Revision is concentrated in the time period surrounding the roadshow,

which is consistent with roadshow participants forming intuitive impressions during the CEO

presentation and incorporating these impressions into the estimate of firm valuation as part of the

book building process.

5. Additional analyses and robustness tests

5.1. Post-IPO performance

Our finding that perceptions of management are positively associated with firm value

raises the question of whether investors are rationally pricing this information about firms. This

is a difficult question to answer for several reasons. First, there is not an obvious time horizon to

examine whether an unraveling of the valuation premium occurs via poor stock performance.

Further, to determine that the initial valuation was irrational, a research design would need to

show that the unravelling was not driven by changes in investors’ perception of management, an

extremely difficult construct to capture empirically.

Despite these limitations, we examine the association between Perception and the post-

IPO stock performance of our sample of firms. Specifically, we regress firms’ one-year buy-and-

29

hold abnormal returns (BHAR) on Perception.32 While admittedly ad hoc, we choose a one-year

time horizon for two reasons. First, our sample concludes at the end of 2013, making one-year

the longest horizon we are able to examine for the entire sample. Second, using a one-year

horizon allows two prominent features that impact the secondary market pricing of IPOs to

expire, namely, insiders’ lockup provisions (Field and Hanka, 2001) and underwriters’

overallotment options (Lewellen, 2006). By allowing sufficient time for these features to expire,

we remove concerns that the final price is not a true market price. The results from this

univariate regression (untabulated) fail to identify a statistically significant relationship between

Perception and BHAR (coefficient = 0.014, t-stat = 0.16). When including other known

determinants of post-IPO performance in the model (e.g., underwriter quality, VC backing,

revenues, market conditions), the point-estimate remains close to zero (coefficient = 0.035, t-stat

= 0.36). Similar results are found when examining one-month, three-month, or six-month time

horizons. Thus, our tests fail to find any evidence that investors acted irrationally when

incorporating their perceptions of management into firm value.

5.2. Data quality

Prior research indicates several data-quality concerns may arise when using MTurk to

perform behavioral research (Mason and Suri, 2012; Crump, McDonnell, and Gureckis, 2013).

In this section, we examine whether these concerns are present in our data and investigate their

impact on our results.

We used every rating that we received from the MTurk workers in our calculation of

Perception, Competent, Trustworthy, and Attractive. However, some of the MTurk worker

ratings may be compromised either because the rater recognized the CEO, wasn’t paying close

32 To determine each firm’s BHAR, we determine the gross buy-and-hold stock returns for each IPO firm and

subtract the returns earned by that firm’s Fama-French 10x10 portfolio (i.e., the matrix of 100 portfolios formed on

deciles for the market value of equity and the book-to-market ratio) over the same one-year period.

30

attention, or was engaged in otherwise suspicious behavior (Crump, McDonnell, and Gureckis,

2013). This suspicious behavior may include providing the same response to each request or

providing responses that are uncorrelated with the group average. Accordingly, we exclude the

data observations that manifest these behaviors from the data and re-estimate each of the main

regressions in our paper.

Table 9 provides the results of re-estimating the main regressions in our paper after

excluding abnormal ratings provided by MTurk workers. Panel A provides the results after

excluding all ratings where an MTurk worker indicated having recognized the CEO in the video.

Panel B provides the results after excluding all ratings where MTurk workers failed to answer

our two attention-check questions correctly. Panel C provides the results after removing all

ratings where MTurk workers indicated the same value for a characteristic for each of the videos

that they rated. Panel D provides the results after excluding all raters whose ratings were not

positively correlated with the group average (p-value < 0.10). Panel E provides the results after

removing all ratings that were excluded in Panels A-D. In each panel, we note that the qualitative

inferences made when using the restricted set of ratings are identical to those made when using

the complete set of ratings. While the statistical inferences are similar, we note that the

coefficients estimated for Perception_Net (Panel E) are slightly lower than those estimated for

Perception (Tables 5–8) in each of the regressions.

5.3. Rater characteristics

Thin-slice judgments (and System 1 thinking processes in general) are described as

unconscious assessments made without effort or awareness, independent of intelligence or

working memory (Ambady, Bernieri, and Richeson, 2000; Evans, 2008). Because these are

fundamental, universal perceptions, we don’t expect results to be driven by rater characteristics.

31

In addition, we follow the content analysis literature’s recommendation to use a large number of

raters when capturing variables that involve judgment (Neuendorf, 2002), with the goal of

estimating a common perception. Thus, we are hesitant to estimate perceptions using

significantly smaller groups of raters. Nevertheless, we repeat our analyses using ratings from

various subsamples of raters to examine whether we observe this fundamental assumption in our

setting. We find qualitatively similar inferences for our main tests when using subsamples

limited to any of the following demographics: male raters, female raters, raters under 30 years

old, raters 30 years of age or greater, Caucasian raters, non-Caucasian raters, raters that have

attended at least some college or have a college degree, and raters that have not attended college.

These findings provide support that we are capturing fundamental human judgments that are not

unique to any particular demographic.

6. Conclusion

This study examines how investors’ perceptions of management are associated with firm

valuation. Specifically, we examine whether basic judgments of management, formed from

watching 30-second content-filtered video excerpts of a CEO’s IPO roadshow presentation, are

correlated with investors’ assessment of firm value, controlling for known determinants of firm

value. We find that a composite measure of perception based on competence, trustworthiness,

and attractiveness is positively associated with an IPO firm’s secondary market value and

underwriter quality. We also examine how this information influences IPO price formation and

show that our composite measure of perception is positively associated with both the price

proposed for the offering and the price revision that occurs from this proposed price to the

closing price on the firm’s first day of trading on the secondary market.

We contribute to the existing literature in several areas. First, we provide evidence that

impressions of management are associated with timely measures of firm value. Second, we

32

contribute to the IPO literature by providing the first empirical evidence that investors learn

valuable, non-tangible information from attending an IPO firm’s roadshow. Third, our study

contributes to the disclosure literature by providing evidence that valuable information about

management is conveyed through visual and audial nonverbal behavior.

Although we have a unique setting that allows us to match perception with concurrent

valuation, two limitations remain. First, when obtaining ratings of management, we remove

contextual information about the firm, firm performance, the history of the CEO, and even the

fact that the presentation is part of an IPO. Our goal is to focus on the most basic human

judgments, irrespective of additional information. However, this means that we are not able to

capture a measure of investor perception that is influenced by the content of conversations or

historical information about management. Second, we rely on prior literature’s findings that thin-

slice judgments are intuitive, automatic, and not easily influenced by outside factors such as

cognitive load or intelligence. However, to the extent that these inherent judgments could be

influenced by financial incentives, our measure of perception would be incomplete because our

raters are not making investment decisions based on their assessments.

33

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38

Appendix. Survey design and implementation

When creating the MTurk survey, we employ several techniques common in survey design to

reduce concerns about bias in the responses. First, we organize CEO videos by randomly

assigning each video to one of twenty groups or cells, and we then randomly assign each of our

respondents to view and rate one cell or group of videos. In this way, each video is watched by at

least 40 respondents (and on average, 45).33 In addition, respondents are only allowed to view

and rate one group of videos, reducing concerns about rater fatigue or differences in rater

learning over time. Second, within each group of videos, we randomize the order of the videos’

appearance to the respondent to minimize the potential for different responses based on when

CEO videos are viewed during the rating exercise. Third, we randomize the order of the three

characteristic questions (Competent, Trustworthy, and Attractive) for each rater to avoid

systematically different responses due to the ordering of the traits. (We do, however, leave the

question order the same for all videos rated by a given rater to avoid unnecessary confusion

during a series of videos and questions.) Fourth, we provide a practice video and questions

before the sample videos to familiarize respondents with the format, and we require raters to

confirm their ability to see and hear the practice video before allowing the survey to begin. In

addition, during the survey, we do not allow the rater to progress to the questions until the time

required to view the video has elapsed. In this way, we minimize the risk that respondents ignore

the video and respond with random ratings.34

33 Respondents are required to view and rate all videos in the group to obtain credit for completing the survey, and

we receive only complete responses. Thus, the difference in raters per cell is a result of the random assignment of

raters. On average, each cell will be assigned 45 raters. However, in practice, cells were assigned between 43 and 47

raters. Accordingly, all cells (and thus videos) were rated by at least 43 respondents. 34 Also see robustness tests in Section 5.2 eliminating ratings that are potentially of lower quality.

39

Figure 1. IPO Timeline

Figure 2. Survey question

t-2 t-1 t t+1

Firm files registration

statement with SEC

Initial pricing range

is announced

The final offer price

is announced

Price observed on

secondary market

IPO Roadshow

40

Table 1. Final sample

Notes: Panel A details our sample selection process and reports the final number of firms included in our

empirical analyses. Section 3.2 provides additional information about our sample selection process.

Notes: Panel B details the distribution of our final sample reporting both the issuing year and Fama-French

12-industry classification.

Panel A: Sample Selection Process

Observations

360

(55)

(41)

(18)

(22)

224

SDC Platinum listing of U.S. Industrials that completed an original initial public

offering between April 1, 2011 - December 31, 2013.

Details

Less: Firms that raised proceeds less than $10 million or have a final offer price

below $5 per share

Final Sample

Less: Audio-only roadshows, roadshows without manager presentations, or

roadshows that were not captured from RetailRoadshow

Less: IPOs with incomplete financial information (CRSP/Compustat)

Less: Limited Partnerships or Unit offerings

Panel B: Sample Distribution

Industry 2011 2012 2013 Total

Consumer Non-Durables 1 3 2 6

Consumer Durables 0 1 2 3

Manufacturing 2 5 3 10

Oil & Gas 4 5 4 13

Chemicals 1 0 3 4

Business Equipment 19 28 23 70

Telecommunications 1 1 2 4

Wholesale 7 10 11 28

Healthcare 5 11 36 52

Other 5 8 21 34

Total 45 72 107 224

41

Table 2. Mechanical Turk workers

Notes: Panel A provides the demographic and background characteristics of the MTurk workers

that analyzed the CEO presentations in our study. Section 3.3 provides additional information about

our use of Amazon’s Mechanical Turk system.

Panel A: Characteristics of Mechanical Turk Workers

Frequency Percent

Gender

Male 473 52.6%

Female 427 47.4%

Total 900 100%

Age

18-29 406 45.1%

30-49 378 42.0%

50+ 116 12.9%

Total 900 100%

Education

Some high school or less 9 1.0%

High school graduate or equivalent 112 12.4%

Trade, technical, or vocational training 49 5.4%

Some college credit, no degree 274 30.5%

College graduate 350 38.9%

Some postgraduate work 25 2.8%

Post graduate degree 81 9.0%

Total 900 100%

Ethnicity

Caucasian 662 73.6%

African American 76 8.4%

Asian 66 7.3%

Hispanic 60 6.7%

Other 36 4.0%

Total 900 100%

42

Table 2. Mechanical Turk workers, continued

Notes: Panel B provides the distribution of ratings provided by Mechanical Turk workers. The Appendix

provides additional information about the survey techniques used in obtaining these responses.

Notes: Panel C provides the distribution of rating averages of the 224 CEO presentations included in our

sample. Each CEO is rated by at least 40 MTurk workers, and we take the average MTurk rating for each of the

CEO’s characteristics to create Competent, Trustworthy, and Attractive. Perception is the average of

Competent, Trustworthy, and Attractive.

Panel B: Distribution of ratings provided by Mechanical Turk Workers

Rating Competent Trust Attractive Combined

1 209 468 1,555 2,232

2 438 914 1,699 3,051

3 1,073 1,656 2,146 4,875

4 2,396 2,769 2,573 7,738

5 2,947 2,421 1,366 6,734

6 2,191 1,440 590 4,221

7 822 408 147 1,377

Total 10,076 10,076 10,076 30,228

Panel C: Distribution of rating averages by CEO

Value Perception Competent Trustworthy Attractive

Less than 2.25 0 0 0 6

2.25 - 2.50 0 0 0 24

2.75 - 2.50 0 0 0 20

2.75 - 3.00 0 0 0 34

3.00 - 3.25 5 0 0 37

3.25 - 3.50 12 0 11 24

3.50 - 3.75 39 0 24 28

3.75 - 4.00 41 5 50 17

4.00 - 4.25 57 20 50 13

4.25 - 4.50 41 39 43 8

4.50 - 4.75 21 55 27 8

4.75 - 5.00 8 53 13 5

5.00 - 5.25 0 44 6 0

Greater than 5.25 0 8 0 0

Total 224 224 224 224

43

Table 3. Descriptive statistics

Notes: Table 3 provides descriptive statistics for our sample of firms. The data used in this study is

collected from a variety of sources including Compustat, CRSP, the SEC EDGAR database, and

Jay Ritter’s IPO database. The motivations and descriptions for all variables appear in Section 4 of

this paper.

Variable Obs Mean Std. Dev Q1 Median Q3

Perception 224 4.05 0.39 3.76 4.09 4.32

Competent 224 4.71 0.35 4.47 4.73 4.98

Trustworthy 224 4.16 0.41 3.86 4.13 4.47

Attractive 224 3.28 0.66 2.80 3.18 3.73

L(MVE_Proposed) 224 6.54 0.97 5.81 6.31 7.15

Revision 224 0.23 0.52 -0.16 0.12 0.51

Price_Update 224 -0.01 0.22 -0.17 0.00 0.13

Initial_Returns 224 0.21 0.29 0.01 0.14 0.32

L(MVE_Final) 224 6.67 1.11 5.94 6.58 7.34

Filing_Size 224 5.01 0.8 4.4 4.78 5.42

Assets 224 5.25 1.71 4.03 4.90 6.40

Revenues 224 1.01 0.81 0.41 0.86 1.47

Profitability 224 -0.27 0.68 -0.30 -0.03 0.04

R&D_Intensity 224 0.26 0.42 0.00 0.09 0.34

Firm_Age 224 2.62 0.89 2.08 2.48 3.16

Underwriter 224 8.27 0.77 8.00 8.50 8.75

VC 224 0.48 0.50 0.00 0.00 1.00

Big4 224 0.88 0.32 1.00 1.00 1.00

Secondary_Shares 224 0.15 0.26 0.00 0.00 0.20

Insider_Retention 224 0.41 0.25 0.17 0.45 0.59

Mkt_Cond_Level 224 3,120 421 2,754 2,998 3,481

Mkt_Cond_Change 224 0.08 0.09 0.04 0.08 0.14

CEO_Age 224 3.93 0.15 3.84 3.95 4.04

Female 224 0.04 0.19 0.00 0.00 0.00

Foreign 224 0.14 0.35 0.00 0.00 0.00

Grad_School 224 0.59 0.49 0.00 1.00 1.00

Founder 224 0.36 0.48 0.00 0.00 1.00

Experience 224 0.48 0.50 0.00 0.00 1.00

Live 224 0.65 0.48 0.00 1.00 1.00

Sitting 224 0.08 0.27 0.00 0.00 0.00

Background 224 0.15 0.36 0.00 0.00 0.00

44

Table 4. Determinants of Perception

Notes: Table 4 presents the results from an OLS regression of Perception on several CEO, firm, and

offering characteristics. Perception is defined as the average of Competent, Trustworthy, and Attractive.

See Section 4 for all other variable definitions. *** designates two-tailed statistical significance at 1%, **

at 5%, and * at 10%.

VARIABLES (1) (2) (3) (4)

CEO_Age -1.2286*** -1.1941***

(0.000) (0.000)

Female 0.5141*** 0.4761***

(0.000) (0.000)

Foreign -0.1111* -0.1332**

(0.064) (0.042)

Grad_School 0.0724 0.0902*

(0.144) (0.097)

Founder -0.1375*** -0.1311**

(0.004) (0.012)

Experience -0.0451 -0.0467

(0.338) (0.344)

Live -0.0084 0.0666

(0.881) (0.218)

Sitting -0.1717 -0.0964

(0.139) (0.369)

Background -0.0716 -0.1699**

(0.324) (0.017)

Assets -0.0020 0.0196

(0.929) (0.331)

Profitability -0.0827 -0.0491

(0.210) (0.454)

R&D_Inten -0.0188 0.0505

(0.882) (0.695)

Firm_Age 0.0363 0.0235

(0.289) (0.448)

VC 0.0890 0.0727

(0.267) (0.260)

Industry Fixed Effects Excluded Excluded Included Included

Observations 224 224 224 224

Adjusted R-squared 0.238 0.009 0.018 0.253

Perception

45

Table 5. Perception and firm value

Notes: Table 5 presents the results from an OLS regression of L(MVE_Final) on several CEO, firm, and

offering characteristics. L(MVE_Final) is defined as the natural log of the firm’s market value of common

equity calculated at the end of its first day trading on the secondary market. Perception is our primary

variable of interest and is defined as the average of Competent, Trustworthy, and Attractive. See Section 4

for all other variable definitions. *** designates one-tailed statistical significance at 1%, ** at 5%, and * at

10% for Perception, Competent, Trustworthy, and Attractive, and two-tailed significance for control

variables.

VARIABLES (1) (2) (3) (4)

Perception 0.4340***

(0.002)

Competent 0.3187**

(0.023)

Trustworthy 0.1620

(0.141)

Attractive 0.3216***

(0.000)

L(Book_Val_Post) 0.0647*** 0.0646*** 0.0624*** 0.0626***

(0.005) (0.005) (0.008) (0.007)

L(Revenues) 0.3278*** 0.3324*** 0.3315*** 0.3358***

(0.000) (0.000) (0.000) (0.000)

L(Net_Income) -0.0205 -0.0235 -0.0223 -0.0206

(0.375) (0.316) (0.348) (0.369)

L(R&D_Expense) 0.1375** 0.1330** 0.1380** 0.1414**

(0.028) (0.034) (0.030) (0.024)

Firm_Age -0.0771 -0.0836 -0.0750 -0.0636

(0.350) (0.321) (0.374) (0.441)

Underwriter 0.1825*** 0.1833** 0.2041*** 0.1898***

(0.010) (0.011) (0.005) (0.007)

VC 0.0016 0.0193 0.0110 0.0088

(0.990) (0.887) (0.935) (0.945)

Big4 0.3448** 0.3543** 0.3207** 0.3070**

(0.017) (0.015) (0.027) (0.030)

Secondary_Shares 0.3820* 0.3817* 0.3702* 0.2984

(0.068) (0.069) (0.087) (0.143)

Insider_Retention -0.1119 -0.1137 -0.1207 -0.1019

(0.610) (0.611) (0.590) (0.636)

Mkt_Cond_Level 0.0007*** 0.0007*** 0.0007*** 0.0006***

(0.003) (0.003) (0.003) (0.004)

CEO Characteristics Included Included Included Included

Fixed Effects Time, Industry Time, Industry Time, Industry Time, Industry

Observations 224 224 224 224

Adjusted R-squared 0.564 0.555 0.549 0.571

L(MVE_Final)

46

Table 6. Perception and underwriter matching

Notes: Table 6 presents the results from an OLS regression of Underwriter on several CEO, firm, and

offering characteristics. Underwriter is calculated as the average Carter-Manaster IPO ranking for the

firm’s lead underwriters. Perception is our primary variable of interest and is defined as the average of

Competent, Trustworthy, and Attractive. See Section 4 for all other variable definitions. *** designates

one-tailed statistical significance at 1%, ** at 5%, and * at 10% for Perception, Competent, Trustworthy,

and Attractive, and two-tailed significance for control variables.

Panel A:

VARIABLES (1) (2) (3) (4)

Perception 0.2746**

(0.017)

Competent 0.3673***

(0.007)

Trustworthy 0.1511

(0.119)

Attractive 0.1151*

(0.081)

Filing_Size 0.1696 0.1584 0.1889 0.1792

(0.166) (0.183) (0.138) (0.156)

Assets 0.1069 0.1083 0.1011 0.1105

(0.170) (0.161) (0.205) (0.157)

Revenues 0.0064 0.0059 0.0135 0.0181

(0.924) (0.929) (0.842) (0.783)

Profitability 0.4418*** 0.4483*** 0.4329*** 0.4360***

(0.002) (0.002) (0.003) (0.003)

R&D_Intensity 0.3810 0.3942 0.3782 0.3865

(0.164) (0.146) (0.170) (0.168)

Firm_Age 0.0252 0.0119 0.0256 0.0346

(0.700) (0.857) (0.701) (0.597)

VC 0.2743** 0.2763** 0.2761** 0.2844**

(0.020) (0.018) (0.023) (0.017)

Big4 0.4822*** 0.5056*** 0.4781*** 0.4619***

(0.006) (0.003) (0.007) (0.010)

Secondary_Shares 0.1289 0.1573 0.1304 0.0804

(0.400) (0.313) (0.396) (0.593)

Insider_Retention 0.4174** 0.4102** 0.4119** 0.4217**

(0.041) (0.042) (0.048) (0.041)

CEO Characteristics Included Included Included Included

Fixed Effects Time, Industry Time, Industry Time, Industry Time, Industry

Observations 224 224 224 224

Adjusted R-squared 0.340 0.351 0.330 0.331

Underwriter

47

Table 7. Perception and proposed IPO price

Notes: Table 7 presents the results from an OLS regression of L(MVE_ Proposed) on several CEO, firm,

and offering characteristics. L(MVE_ Proposed) is defined as the natural log of the firm’s market value of

common equity calculated at the midpoint of the initial pricing range proposed for the offering. Perception

is our primary variable of interest and is defined as the average of Competent, Trustworthy, and Attractive.

See Section 4 for all other variable definitions. *** designates one-tailed statistical significance at 1%, **

at 5%, and * at 10%.

Variables (1) (2) (3) (4)

Perception 0.2906***

(0.009)

Competent 0.2369**

(0.031)

Trustworthy 0.1048

(0.181)

Attractive 0.2065***

(0.004)

L(Book_Value) 0.0369* 0.0370* 0.0351* 0.0354*

(0.071) (0.070) (0.090) (0.086)

L(Revenues) 0.3312*** 0.3339*** 0.3346*** 0.3360***

(0.000) (0.000) (0.000) (0.000)

L(Net_Income) -0.0124 -0.0142 -0.0141 -0.0133

(0.551) (0.498) (0.511) (0.524)

L(R&D_Expense) 0.1178** 0.1147** 0.1184** 0.1211**

(0.034) (0.041) (0.035) (0.029)

Firm_Age -0.0038 -0.0084 -0.0029 0.0010

(0.956) (0.905) (0.968) (0.989)

Underwriter 0.1172* 0.1164* 0.1316** 0.1202*

(0.064) (0.067) (0.045) (0.060)

VC 0.0214 0.0323 0.0299 0.0277

(0.857) (0.788) (0.804) (0.812)

Big4 0.1915 0.1998* 0.1730 0.1659

(0.102) (0.088) (0.136) (0.153)

Insider_Retention -0.3506** -0.3512** -0.3577** -0.3529**

(0.047) (0.050) (0.045) (0.042)

Mkt_Cond_Level 0.0006*** 0.0006*** 0.0006*** 0.0006***

(0.003) (0.002) (0.003) (0.003)

Remaining Variables Included Included Included Included

Time Fixed Effects Included Included Included Included

Industry Fixed Effects Included Included Included Included

Observations 224 224 224 224

Adjusted R-squared 0.598 0.595 0.589 0.601

L(MVE_Proposed)

48

Table 8. Perception and IPO price revision

Notes: Table 8 Panel A presents the results from an OLS regression of Total_Revision on several CEO,

firm, and offering characteristics. Revision is defined as the percentage change between the price per share

initially proposed for the offering and the IPO firm’s closing price per share after its first day of trading on

the secondary market. Perception is our primary variable of interest and is defined as the average of

Competent, Trustworthy, and Attractive. See Section 4 for all other variable definitions. *** designates

two-tailed statistical significance at 1%, ** at 5%, and * at 10%.

Panel A: Determinants of the Total Revision

VARIABLES (1) (2) (3) (4)

Perception 0.2275**

(0.027)

Competent 0.1387

(0.190)

Trustworthy 0.0893

(0.358)

Attractive 0.1812***

(0.005)

Filing_Size 0.1871** 0.1918** 0.2009** 0.1857**

(0.031) (0.026) (0.020) (0.033)

Assets -0.1798*** -0.1793*** -0.1845*** -0.1753***

(0.000) (0.000) (0.000) (0.000)

Revenues -0.0544 -0.0449 -0.0454 -0.0523

(0.252) (0.351) (0.350) (0.265)

Profitability 0.1953** 0.1889** 0.1805** 0.1970**

(0.027) (0.037) (0.040) (0.024)

R&D_Intensity -0.2385* -0.2317 -0.2437* -0.2364*

(0.089) (0.104) (0.086) (0.083)

Firm_Age -0.0495 -0.0513 -0.0479 -0.0404

(0.218) (0.217) (0.243) (0.318)

Underwriter 0.0577 0.0622 0.0715 0.0593

(0.213) (0.196) (0.136) (0.192)

VC 0.0193 0.0222 0.0182 0.0291

(0.836) (0.815) (0.850) (0.751)

Big4 0.2730*** 0.2714*** 0.2598*** 0.2541***

(0.001) (0.001) (0.001) (0.001)

Secondary_Shares 0.0230 0.0099 0.0103 -0.0146

(0.855) (0.937) (0.935) (0.908)

Insider_Retention 0.2946* 0.2910* 0.2861* 0.2990*

(0.054) (0.058) (0.065) (0.053)

Mkt_Cond_Change 1.0101** 0.9430** 0.9739** 1.1216**

(0.032) (0.044) (0.038) (0.015)

CEO Characteristics Included Included Included Included

Fixed Effects Time, Industry Time, Industry Time, Industry Time, Industry

Observations 224 224 224 224

Adjusted R-squared 0.260 0.245 0.242 0.273

Revision

49

Table 8. Perception and IPO price revision, continued

Notes: Table 8 Panel B presents the results from an OLS regression of Price_Revision and Underpricing on several CEO, firm, and offering characteristics.

Price_Revision is defined as the percentage change between the price per share initially proposed for the offering and the final offer price. Underpricing is

defined as the percentage change between the final offer price and the IPO firm’s closing price per share after its first day of trading on the secondary

market. Perception is our primary variable of interest and is defined as the average of Competent, Trustworthy, and Attractive. See Section 4 for all other

variable definitions. *** designates two-tailed statistical significance at 1%, ** at 5%, and * at 10%.

Panel B: Determinants of the Price Revision and IPO Underpricing

VARIABLES (1) (2) (3) (4) (5) (6) (7) (8)

Perception 0.0729* 0.0710

(0.055) (0.223)

Competent 0.0198 0.0709

(0.611) (0.246)

Trustworthy 0.0078 0.0500

(0.831) (0.360)

Attractive 0.0773*** 0.0363

(0.002) (0.254)

Other Controls Included Included Included Included Included Included Included Included

Time Fixed Effects Included Included Included Included Included Included Included Included

Industry Fixed Effects Included Included Included Included Included Included Included Included

Observations 224 224 224 224 224 224 224 224

Adjusted R-squared 0.255 0.244 0.243 0.279 0.314 0.314 0.312 0.312

Price_Update Initial_Returns

50

Table 9. Robustness tests using alternative measures of Perception

Notes: Panel A presents the results from running Eq. (2), (3), and (4) modified to include Perception_Recognized rather than Perception.

Perception_Recognized is defined as the average of Competent, Trustworthy, and Attractive after excluding all ratings that indicated to recognize the CEO. See

Section 4 for all other variable definitions. *** designates one-tailed statistical significance at 1%, ** at 5%, and * at 10% for all but the Revision test, where

two-tailed significance is designated.

Notes: Panel B presents the results from running Eq. (2), (3), and (4) modified to include Perception_Attention rather than Perception. Perception_Attention is

defined as the average of Competent, Trustworthy, and Attractive after excluding all raters that did not correctly answer the two attention-check questions

included in the survey. See Section 4 for all other variable definitions. *** designates one-tailed statistical significance at 1%, ** at 5%, and * at 10% for all

but the Revision test, where two-tailed significance is designated.

Notes: Panel C presents the results from running Eq. (2), (3), and (4) modified to include Perception_Constant rather than Perception. Perception_Constant is

defined as the average of Competent, Trustworthy, and Attractive after excluding all raters from MTurk workers that indicated the same value for a

characteristic for each of the videos that they rated. See Section 4 for all other variable definitions. *** designates one-tailed statistical significance at 1%, ** at

5%, and * at 10% for all but the Revision test, where two-tailed significance is designated.

Panel A: Robustness - Recognized the speaker

VARIABLES L(MVE_Final) BTM_Final Underwriter L(MVE_Proposed) BTM_Proposed Revision

Perception_Recognized 0.4409*** -0.1354*** 0.2727** 0.2976*** -0.1101*** 0.2272**

(0.002) (0.003) (0.018) (0.009) (0.002) (0.028)

Ratings Retained 99.3% 99.3% 99.3% 99.3% 99.3% 99.3%

Adjusted R-squared 0.565 0.191 0.340 0.599 0.207 0.260

Panel B: Robustness - Incorrectly answered the attention check questions

VARIABLES L(MVE_Final) BTM_Final Underwriter L(MVE_Proposed) BTM_Proposed Revision

Perception_Attention 0.3956*** -0.1131*** 0.2847** 0.2660** -0.0889*** 0.2217**

(0.004) (0.006) (0.015) (0.014) (0.007) (0.027)

Ratings Retained 84.4% 84.4% 84.4% 84.4% 84.4% 84.4%

Adjusted R-squared 0.562 0.181 0.342 0.597 0.197 0.260

Panel C: Robustness - Provided a constant rating

VARIABLES L(MVE_Final) BTM_Final Underwriter L(MVE_Proposed) BTM_Proposed Revision

Perception_Constant 0.4132*** -0.1254*** 0.2748** 0.2805*** -0.1031*** 0.2083**

(0.003) (0.003) (0.015) (0.010) (0.003) (0.034)

Ratings Retained 94.2% 94.2% 94.2% 94.2% 94.2% 94.2%

Adjusted R-squared 0.564 0.188 0.341 0.598 0.205 0.258

51

Table 9. Robustness tests using alternative measures of Perception, continued

Notes: Panel D presents the results from running Eq. (2), (3), and (4) modified to include Perception_Uncorrelated rather than Perception.

Perception_Uncorrelated is defined as the average of Competent, Trustworthy, and Attractive after excluding all raters whose responses were uncorrelated with

the group average (p-value < 0.10). See Section 4 for all other variable definitions. *** designates one-tailed statistical significance at 1%, ** at 5%, and * at

10% for all but the Revision test, where two-tailed significance is designated.

Notes: Panel E presents the results from running Eq. (2), (3), and (4) modified to include Perception_Net rather than Perception. Perception_Net is defined as

the average of Competent, Trustworthy, and Attractive after excluding all ratings that were excluded in Panels A-D. See Section 4 for all other variable

definitions. *** designates one-tailed statistical significance at 1%, ** at 5%, and * at 10% for all but the Revision test, where two-tailed significance is

designated.

Panel D: Robustness - Uncorrelated to the average rating

VARIABLES L(MVE_Final) BTM_Final Underwriter L(MVE_Proposed) BTM_Proposed Revision

Perception_Uncorrelated 0.4105*** -0.1268*** 0.2317** 0.2774*** -0.1014*** 0.2083**

(0.002) (0.003) (0.026) (0.008) (0.003) (0.027)

Ratings Retained 93.3% 93.3% 93.3% 93.3% 93.3% 93.3%

Adjusted R-squared 0.564 0.190 0.337 0.599 0.205 0.259

Panel E: Robustness - Violated criteria specified in Panels A-D

VARIABLES L(MVE_Final) BTM_Final Underwriter L(MVE_Proposed) BTM_Proposed Revision

Perception_Net 0.3518*** -0.1043*** 0.2406** 0.2434** -0.0811*** 0.1890**

(0.006) (0.008) (0.021) (0.015) (0.009) (0.034)

Ratings Retained 74.5% 74.5% 74.5% 74.5% 74.5% 74.5%

Adjusted R-squared 0.561 0.181 0.340 0.597 0.197 0.257