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ISSUER OPERATING PERFORMANCE AND IPO PRICE FORMATION

Michael WillenborgUniversity of [email protected]

Biyu WuUniversity of Connecticut

[email protected]


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ISSUER OPERATING PERFORMANCE AND IPO PRICE FORMATION

ABSTRACT

We extend the study of the association between public information and IPO price formation byexamining Brau and Fawcetts (2006) chief financial officer survey response that having stronghistorical earnings is the most important signal of quality an IPO issuer can convey to investors.For a sample of 20012012 IPOs, we find measures of pre-IPO operating performance explain asubstantial portion of the variation in the revision from the mid-point of the initial price range to

the IPO offer price. Moreover, for these recent IPOs, the partial adjustment phenomenonconcentrates among issues with strong performance; whereas for those with weak performance,the downward price adjustment is nearly full. As for why issuers with strong performance seemto acquiesce to a partial increase in offer price, these IPOs have the largest wealth gains fromshares sold / retained upon going public. Overall, our results are consistent with Loughran andRitters (2002) agency / prospect theory explanation for IPO partial adjustment and suggest animportant role for historical accounting information in the pricing of book-built IPOs.

Keywords: Operating performance, initial public offerings, partial adjustment, underpricing

Data Availability: Public sources


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I. INTRODUCTION

When a company files to go public in a firm commitment initial public offering (IPO), ineither its initial registration statement or a subsequent amendment, it must provide an initial price

range within which it expects to sell its shares. Following this disclosure, representatives of the

company and its lead underwriters meet with select investors to obtain feedback and indications

of interest to price and pre-sell the offering. Subsequent to this road-show period, the offer price

decision is made the day before the shares begin to trade. Then, as is well known, on average,

the offer price is lower than the first-day closing price. This price formation of IPOs, from initial

price range to offer price to closing price on the first trading day, is a topic of longstanding

interest. While the latter return (underpricing) garners the majority of attention, understanding

the former (price revision) is arguably the key. For example, Ritter and Welch (2002, p. 1803)conclude the solution to the underpricing puzzle has to lie in focusing on the setting of the offer

price, where the normal interplay of supply and demand is suppressed by the underwriter.

In an influential paper that links setting the offer price with underpricing, Benveniste and

Spindt (1989) propose a book-building theory of IPO pricing and allocation by underwriters. In

their model, to induce regular (e.g., road-show) investors to divulge indications of strong

demand, underwriters only partially revise the range upward to arrive at the offer price. As a


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assert issuers bargain hard over the offer price in a bad state of the world, whereas they are

pushovers in bargaining over the offer price in a good state of the world. Importantly, their

explanation makes no distinction between private and public information. In support of this,

they show that market returns during the 15 days pre-IPO are positively associated with both the

price revision and initial returns and that this association is considerably stronger when returns

are negative (i.e., they document partial (nearly full) adjustment to favorable (unfavorable)public information). In his discussion of Loughran and Ritter (2002), Daniel (2002, p. 453)

poses [s]ome questions that merit further investigation include [t]o what extent are revisions

predictable using information available as of the preliminary prospectus date?

From an empirical standpoint, one way to address Daniels (2002) question, and further

our understanding of IPO price formation, is to focus on the price revision and advance proxies

that plausibly surrogate for favorable or unfavorable public information. In Brau and Fawcetts

(2006) survey of chief financial officers (CFOs), all categories of respondents chose having

strong historical earnings as the most important positive signal issuers convey to investors

regarding the value of a firm going public. In this paper, we study the relation between pre-IPOoperating performance and IPO price formation, with a focus on the revision from the mid-point

of the initial price range to the offer price We report evidence of a strong positive association


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these measures is strongly positively associated with both the price revision and underpricing,

particularly in the tails of the distribution (e.g., whereas IPOs in the lowest decile of operating

income, net income or operating cash flow have mean (median) price revisions of 22% (21%)

and mean (median) underpricing of 5% (1%); those in the highest decile have mean (median)

price revisions of +5% (+8%) and mean (median) underpricing of +22% (+19%)). This suggests

an asymmetric association between operating performance and IPO offer price formation, in thatdownward (upward) price adjustments for IPOs with weak (strong) operating performance are

almost full (partial). Within Loughran and Ritters (2002) framework, this is consistent with the

view that weak (strong) pre-IPO operating performance represents unfavorable (favorable)

public information that engenders weak (strong) demand and motivates issuers to bargain

aggressively (passively) with the underwriter over the IPO offer price at the pricing meeting.

The positive association between pre-IPO operating performance and offer price revision

is robust to controlling for other determinants (e.g., book-building market returns, ownership

retention, selling shareholders and whether the issuer is in a high technology industry).

Moreover, specification of each of our operating performance variable of interest substantiallyincreases the explained variation in price revision over-and-above that of a baseline estimation.

We also adopt an identification strategy to assess whether our results weaken upon


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To refine our test of Brau and Fawcetts (2006) CFO survey response, which specifically

references strong historical earnings as a signal of quality, we also parse our continuous pre-

IPO operating performance variables into a series of indicator variables based on decile ranking.

Upon regressing price revision on these indicators, we find a near-monotonic increase in the

coefficients on these indicator variables of interest as they ascend decile ranks.

The association between pre-IPO operating performance and initial returns, while alsopositive and significant, is much weaker than with the price revision. For example, when we

supplement a benchmark underpricing regression, which controls for the price revision, with

operating income to assets the adjusted R-squared increases from 39.2% to 40.0%. We conclude

that to the extent pre-IPO operating performance influences IPO price formation, it is primarily

with respect to the revision from mid-point of initial price range to offer price.

To examine why issuers with strong performance seem to acquiesce to a partial upward

adjustment of offer price, we follow Loughran and Ritter (2002) and compute the change in pre-

IPO shareholder wealth. Two components comprise this revaluation: the change from mid-point

of the initial price range to offer price for the shares insiders sell at the IPO; and the change frommid-point of the initial price range to closing price on the first trading day for the shares that

shareholders retain For issuers in the highest decile of pre IPO performance the revaluation in


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vis--vis the mid-point of the initial range, acquiesce to this partial adjustment at the pricing

meeting. In contrast to this, the unfavorable scenario, issuers bargain aggressively at the pricing

meeting and, as such, little money is left on the table.

Overall, our paper contributes by providing evidence suggestive of an important role for

historical accounting information in the price formation of book-built IPOs. Previous papers

focus on the valuation of IPOs, oftentimes by studying subsets of the population, and generallyfind historical accounting information to be of relatively little importance (e.g., Kim and Ritter

1999; Bartov, Mohanram and Seethamraju 2002; Berger 2002). We extend the study of the

importance of accounting information in the context of IPOs by focusing on the price formation,

from mid-point of the initial range to offer price to first closing price.

II. BACKGROUND AND MOTIVATION

In this section, we discuss the literature on partial price adjustment and underpricing of

book-built IPOs. Two primary streams comprise this literature: one emphasizes informational

issues and book building and another emphasizes agency issues and bargaining incentives. We

then discuss the role of accounting information in the valuation and price formation of IPOs.


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allows the underwriter to more-accurately price the issue. Underpricing therefore results from

the partial offer price adjustment necessary to ensure the revelation of strong demand from

regular investors is incentive compatible. Among Benveniste and Spindts (1989, p. 353)

implications is that [u]nderpricing is directly related to the level of interest in the premarket. 1

Several empirical papers provide results consistent with this dynamic, information-based

view of IPO pricing. Hanley (1993) reports a strong, positive relation between the IPO price

revision (from mid-point of the initial price range to offer price) and first-day returns. Based on

a small, yet detailed sample of international equity issues, Cornelli and Goldreich (2001) find

that investors providing bids with both share and price information receive favorable allocations

from underwriters. Ljungqvist and Wilhelm (2002) study a large, worldwide sample for which

they have share allocation data and conclude the data more strongly support the view that

allocations promote price discovery, as opposed to representing discriminatory practices.

Issuers, underwriters and public information

A second stream focuses on agency issues between issuers and underwriters, such as the

formers bargaining incentives or non-price aspects of their objective function.

Loughran and Ritter (2002) apply a prospect theory framework (Kahneman and Tversky


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days pre-IPO are positively associated with both the price revision and initial returns and that

this association is stronger when market returns are negative. 2 Loughran and Ritter (2002)

interpret the asymmetric association between book-building market returns and price revision as

consistent with a theory of bargaining, as they assert that issuers will aggressively (passively)

bargain over the offer price when roadshow demand is unfavorable (favorable).

Habib and Ljungqvist (2001) and Ljungqvist and Wilhelm (2003) posit that underpricing

is partly a function of the extent to which owners care about it. These papers focus on the

relation between proxies for issuer incentives to bargain for a higher offer price and IPO pricing.

For example, Ljungqvist and Wilhelm (2003) examine a sample of domestic IPOs from 1996 to

2001 and conclude that decreases in CEO ownership and insider selling along with an increase in

directed-share programs (i.e., allocation of shares to friends and family) explain a large portion

of the variation in underpricing during the internet bubble.

For a sample of domestic IPOs from 1980-2003, Loughran and Ritter (2004) test three

non-mutually exclusive explanations for the time-series variation in underpricing: 1) a change in

issuer risk composition (Ritter 1984); 2) realignment of issuer bargaining incentives (Ljungqvistand Wilhelm 2003); and 3) a change in issuer objective function away from maximizing IPO

proceeds They conclude the latter specifically issuer desire to garner coverage from top stock


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revision to positive returns is much less than this. They also question the significance of publicly

available variables prior to disclosure of the initial price range to explain the price revision and

conclude the IPO market is almost efficient with respect to public information.

Because IPO failure is costly, Edelen and Kadlec (2005) conclude partial adjustment to

public information, and its asymmetric response to good and bad news, is partly an artifact of the

selection bias inherent in using samples of successful IPOs. They argue that firms proceed with

IPOs when positive market responses occur but, to ensure a successful offering and the issuer

surplus it entails, only partially adjust price upward; in contrast, when negative market responses

occur, because of the costs of withdrawal, firms more-fully adjust price downward.

Accounting information and the pricing of IPOsSeveral papers examine the relation between accounting information in the prospectus

and the pricing or valuation of IPOs. In general, this literature documents little role for historical

accounting measures of operating performance.

Klein (1996) studies the valuation usefulness of prospectus financial statement variables

for a sample of 193 IPOs from 1980 to 1991 with positive pre-IPO income. She documents a

positive association between the offer price and the market price one week after the offering and


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flows by whether they are positive or negative. For Internet IPOs, their findings provide no

support for an association between earnings and IPO prices but rather strong evidence that

negative operating cash flows are associated with higher offer prices. For non-Internet IPOs,

they find offer prices are positively related to earnings and cash flows, but only for issuers for

which these variables are non-negative. Akin to Kim and Ritters (1999) conclusion, Berger

(2002, page 348) summarizes Bartov et al.s (2002) findings as [t]he results point to a very

limited pricing role for the financial statement data contained in the IPO prospectus.

A recent paper by Brau and Fawcett (2006) motivates re-visiting the relation between

accounting measures of operating performance and IPO pricing. They survey three categories of

chief financial officers, those with companies: that went public; that began to go public but

withdrew; large enough to go public but have not done so. Among their questions is [w]hat

type of signal do the following actions convey to investors regarding the value of a firm going

public? (italics in original) All groups of respondents chose having strong historical earnings

as the most important positive signal issuers convey to investors regarding the value of a firm

going public. We extend the study of the association between public information and IPO priceformation, as Loughran and Ritter (2002) theorize, by examining this CFO survey response.


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are unit investment trusts), and 113 unit IPOs, because they are mostly small offerings by small

companies. We eliminate 71 IPOs without necessary financial statement information in their

registration statement, most of which are issuers that do not provide two balance sheets to

calculate average assets for the year before going public. Since our interest is price formation of

book-built IPOs, we eliminate 15 IPOs sold via auction (Degeorge, Derrien and Womack 2010). 4

We also eliminate 7 IPOs for which the time between the date of the registration statement with

the initial price range and the IPO date exceeds one year (Edelen and Kadlec 2005) and 6 IPOs

with a mid-point of their initial price range of $5 or less. Our final sample consists of 824 IPOs.

Variable specification and descriptive statistics

Panel B of Table 1 presents descriptive statistics and Table 2 presents correlations for all

dependent and independent variables. Mean (median) PriceRevision (change from the midpoint

of the initial price range to the IPO offer price), in percentage terms, is 5.2% (0.0%). This

average is more negative than the 1.4% Lowry and Schwerts (2004) report for their pre-bubble

period sample, and much less than the +5.8% Ljungqvist and Wilhelm (2003) report for their

bubble period sample.5

Mean (median) InitialReturn (change from the IPO offer price to theclosing price on the first trading day), in percentage terms, is 13.2% (8.3%). This average is

i il t L h d Ritt (2002) 14 1% d L d S h t (2004) 12 3% b t t


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income taxes, average (median) OI/Assets is less negative (more positive) than average (median)

NI/Assets . Of note, all three of these measures have a considerable amount of dispersion; for

example, NI/Assets has a standard deviation of 0.998 around a mean of 0.241. Not surprisingly,

this dispersion is particularly evident at the negative tail of each variables distribution. 6

In terms of covariates, we specify two spillover variables for public information during

book building (Ljungqvist and Wilhelm 2003). The first is MktReturn , the equally-weighted

return on all companies in CRSP residing in the issuers Fama and French (1997) industry from

the date of the registration statement with the initial price range to IPO date. When specifying

our regressions, we allow for the likelihood that positive secondary market returns affect the

price revision differently than negative market returns (Loughran and Ritter 2002; Lowry and

Schwert 2004; Edelen and Kadlec 2005). The second is IPOReturn , the average initial return for

all IPOs during the period from the date of the first registration statement to IPO date. 7

We also control for ownership retention and insider selling. The average (median) issuer

retains 71.0% (73.5%) ownership (i.e., Retain% , one minus the number of shares sold in the IPO

divided by the number of post-IPO shares outstanding). While the majority of our IPOs do nothave secondary shares, the average SellingShr% (number of selling shareholder shares divided

by number of total shares in the IPO) is 16 7% Leland and Pyle (1977) theorize that higher


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The motivation for our other covariates (e.g., UW , VC , Proceeds , Age , HighTech , Assets )

is extant IPO papers on price revision and initial returns, notably Ljungqvist and Wilhelm (2003)

and Lowry and Schwert (2004). Following Lowry and Schwert (2004), we adjust Proceeds and

Assets for inflation, converting them to 1983 dollars with the Consumer Price Index.

Table 2 shows correlations, Pearson (Spearman) below (above) the diagonal. Each

operating performance measure is positively correlated with PriceRevision and InitialReturn .

The measure with the highest Pearson (Spearman) correlation with PriceRevision is OI/Assets

(OCF/Assets ). Of note, consistent with the dispersion in these measures, Spearman correlations

between dependent variables ( PriceRevision or InitialReturn ) and independent variables of

interest ( OI/Assets , NI/Assets , OCF/Assets ) are more positive than their Pearson counterparts

(e.g., the Pearson (Spearman) correlation between PriceRevision and NI/Assets is 0.175 (0.309)).

Because of extreme values, particularly in the left tail of the distribution, we winsorize OI/Assets ,

NI/Assets and OCF/Assets at + / 1% for our regression estimations.

Table 3 provides descriptive sorts of our sample by: OI/Assets (panel A), NI/Assets (panel

B) and OCF/Assets (panel C). For each panel, we sort the variable of interest by decile and showmean and median values of PriceRevision and InitialReturn . It is interesting to compare the

extremes of these sorts For issuers in Decile 1 IPOs with very negative operating income net


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Taken together, these findings suggest the association between pre-IPO operating

performance and IPO price formation is asymmetric. That is, for those issuers with very weak

(very strong) performance that go public, the downward (upward) price adjustment is almost full

(partial). This asymmetry is akin to that between book-building market returns and the price

revision (Loughran and Ritter 2002; Lowry and Schwert 2004; Edelen and Kadlec 2005) in that

bad (good) news is nearly fully (partially) associated with downward (upward) price revision.

IV. EMPIRICAL ANALYSIS

Issuer operating performance and price revision

We begin by regressing each measure of pre-IPO operating performance on the IPO price

revision.8

These estimations supplement the Table 2 correlations by clustering standard errors byIPO year. 9 Given the presence of extreme values among these measures, we impart a winsor of

+1% and 1%. Because successful IPOs comprise our sample, the coefficients we report are

contingent upon the offering being completed (Loughran and Ritter 2002; Ljungqvist and

Wilhelm 2003; and Lowry and Schwert 2004)

PriceRevision = ! 0 + ! 1 OI/Assets + " (1a)

PriceRevision = ! 0 + ! 1 NI/Assets + " (1b)


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Columns 1 3 of Table 4 panel A report the results of estimating equations (1a), (1b) and

(1c). The coefficient for each operating performance measure is positive and highly significant

and their specification explains a substantial portion of the variation in PriceRevision .

To specify a benchmark to assess the effect of issuer operating performance, we estimate

equation (2) by regressing the PriceRevision on determinants from the literature. To control for

public information that arises during book building, we follow Ljungqvist and Wilhelm (2003)

and Edelin and Kadlec (2005) and specify MktReturn and IPOReturn as spillover, from

secondary and primary markets, respectively. With regard to the former, because Loughran and

Ritter (2002) and others document an asymmetric revision to positive versus negative market

returns, we also specify MktReturn+ , which equals MktReturn when it is positive, and zero

otherwise. To control for the positive signal issuers convey by ownership retention (Leland and

Pyle 1977; Brau and Fawcett 2006) or, alternatively, for lower issuer incentives to bargain for a

higher IPO price (Loughran and Ritter 2002), we specify Retain% . To control for the negative

signal issuers convey by selling secondary shares or, alternatively, for higher issuer incentives to

bargain to increase the offer price, we specify SellingShr% (Ljungqvist and Wilhelm 2003).

Following Lowry and Schwert (2004), we specify Ln( Proceeds ) and NYSEAMEX as transaction

characteristics To control for effects associated with professional advisors / intermediaries we


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MktReturn = Average return on all companies in CRSP in issuers Fama-French (1997) industry for theperiod from the date of issuers prospectus with the initial price range to IPO date

MktReturn + = MktReturn when it is positive, and zero otherwise IPOReturn = Average initial return of IPOs from the date of issuers first prospectus to IPO date Retain% = One less (number of shares sold in IPO number of post-IPO shares outstanding)SellingShr% = Number of shares sold by selling shareholders number of shares sold in IPOUW = Underwriter rank (Carter, et al., 1998; and Loughran and Ritter 2004)

BigN = One if IPO issuer has a BigN audit firm, and zero otherwiseVC = One if IPO issuer has venture capital backing, and zero otherwiseLn(Proceeds) = Natural logarithm of IPO proceeds (inflation adjusted to 1983 dollard) per issuers prospectus

with the initial price range (i.e., midpoint of initial price range times number of shares filed) NYSE/AMEX = One if IPO is listed on the NYSE or AMEX, and zero otherwiseLn(Age) = Natural logarithm of one plus the number of years from year of company founding or

incorporation, if founding date is unavailable, to IPO year HighTech = One if IPO issuer is a high technology company per SDC, and zero otherwiseLn(Assets) = Natural logarithm of issuers pre-IPO total assets, in millions (inflation adjusted)

Column 4 of Table 4 panel A reports the results of estimating equation (2). The

explanatory power, an adjusted R 2 of 12.7%, is between the 11% for Lowry and Schwerts

(2004) 1985-1997 sample and the 22% for Ljungqvist and Wilhelms (2003) 1996-2000 sample.

As for covariates, consistent with the extant literature, the price revision to book-building market

returns is more complete when they are negative. MktReturn s coefficient of 0.918 implies that a

market return during bookbuilding of 10% corresponds to a price revision of 9.18%. In

contrast, the coefficient on MktReturn + of 0.752 suggests a book-building market return of

+10% corresponds to a price revision of +1.66% (0.918 0.752). 10 Consistent with Habib and

Ljungqvist (2001) and Ljungqvist and Wilhelm (2003), the price revision to public information


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We then augment equation (2) by specifying our three pre-IPO operating performance

variables in equations (3a), (3b) and (3c).

PriceRevision = ! 0 + ! 1 OI/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) + " i,t (3a)

PriceRevision = ! 0 + ! 1 NI/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +

! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) + " i,t (3b)

PriceRevision = ! 0 + ! 1 OCF/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) + " i,t (3c)

Columns 5 7 of Table 4 panel A present the results of estimating equations (3a), (3b)

and (3c). In each case, the coefficient on the pre-IPO operating performance variable remains

positive and significant and their specification substantially increases the explanatory power

above that of equation (2) (e.g., specifying OCF/Assets in equation (3c) increases the adjusted R 2

from 12.7% for equation (2) to 19.5%). 11. As with the univariate regressions, the coefficient on

OCF/Assets is the largest and most significant; and, at 0.147, implies a one standard deviation

change in OCF/Assets is associated with a 6.8% increase in PriceRevision (0.147 * 0.460 12).13


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December 31 year-end, this occurs at the close of business on May 14 th). Given the strength of

OCF/Assets in Table 4, we table the results of estimating equations (1c), (3c) and (1d), (3d); the

latter two specify OCF/AssetsStale , which we compute using the older, year-end statements.

PriceRevision = ! 0 + ! 1 OCF/AssetsStale + " (1d)

PriceRevision = ! 0 + ! 1 OCF/AssetsStale + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) + " i,t (3d)

Table 4 panel B reports the results. For both univariate and multivariate estimations, the

coefficient on OCF/AssetsStale is smaller than that on OCF/Assets . For the multivariate

regressions, the coefficient on OCF/Assets is 0.150 (column four) whereas on OCF/AssetsStale

it is 0.117 (column five); a decrease of 22%. In addition, the regressions R 2 decreases from18.9% to 15.7% upon substituting OCF/AssetsStale in place of OCF/Assets ; a decrease of 16%.

A Vuong (1989) likelihood ratio test to assess the incremental R 2 of Equation (3c) over that of

(3d) yields a z-statistic of 1.89, with a p-value of 0.059. These weaker results from specifying a

stale version of pre-IPO operating performance in place of the most-recent version provide

additional assurance of the positive association between operating performance and the revision

from mid-point of the initial price range to IPO offer price.


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PriceRevision = ! 0 + ! 1 NI/AssetsDecile2 + ! 2 NI/AssetsDecile3 + ! 3 NI/AssetsDecile4 +

! 4 NI/AssetsDecile5 + ! 5 NI/AssetsDecile6 + ! 6 NI/AssetsDecile7 +! 7 NI/AssetsDecile8 + ! 8 NI/AssetsDecile9 + ! 9 NI/AssetsDecile10 +! 10 MktReturn + ! 11 MktReturn + + ! 12 IPOReturn + ! 13 Retain% +! 14 SellingShr% + ! 15 UW + ! 16 BigN + ! 17 VC + ! 18 Ln(Proceeds) +! 19 NYSE/AMEX + ! 20 Ln(Age) + ! 21 HighTech + ! 22 Ln(Assets) + " i,t (4b)

PriceRevision = ! 0 + ! 1 OCF/AssetsDecile2 + ! 2 OCF/AssetsDecile3 + ! 3 OCF/AssetsDecile4 +

!4

OCF/AssetsDecile5 + !5

OCF/AssetsDecile6 + !6

OCF/AssetsDecile7 +! 7 OCFI/AssetsDecile8 + ! 8 OCF/AssetsDecile9 + ! 9 OCF/AssetsDecile10 +! 10 MktReturn + ! 11 MktReturn + + ! 12 IPOReturn + ! 13 Retain% +! 14 SellingShr% + ! 15 UW + ! 16 BigN + ! 17 VC + ! 18 Ln(Proceeds) +! 19 NYSE/AMEX + ! 20 Ln(Age) + ! 21 HighTech + ! 22 Ln(Assets) + " i,t (4c)

Table 5 reports the results of estimating equation (4a) in panel A, equation (4b) in panel

B and equation (4c) in panel C. For presentation purposes, we show the results of the Table 4

panel A regression with the continuous version of each variable of interest (i.e., equations 3a, 3b

and 3c). We suppress the control variables results, though they are consistent with Table 4. In

general, across all three panels, the coefficients on the operating performance indicator variables

increase with decile rank. In addition, consistent with Brau and Fawcetts (2006) CFO survey

response that strong historical earnings is the most important signal of quality an IPO issuer

can convey, for all estimations the coefficient on OCF/AssetsDecile10 is the most positive.


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Where: InitialReturn = (Closing price on the first day of trading IPO price) IPO price

Columns 1 3 of Table 6 reports the results of estimating equations (5a), (5b) and (5c).

As with the PriceRevision regressions in Table 4 Panel A, he coefficient for each measure of

issuer pre-IPO operating performance is positive and significant. However, in contrast to the

price revision estimations, the explanatory power of these underpricing regressions is

considerably lower. For example, whereas the adjusted R-squared from regressing OCF/Assets

on PriceRevision is 12.3%, it is just 4.3% upon regressing OCF/Assets on InitialReturn .

To specify a benchmark to assess the effect of issuer pre-IPO operating performance, we

estimate equation (6) by regressing the InitialReturn on the covariates in equation (2) plus the

price revision. As with regard to the relation between secondary market returns during book

building and the price revision, following Ljungqvist and Wilhelm (2003), we allow for an

asymmetric relation between the IPO price revision and initial returns.

InitialReturn = ! 0 + ! 1 MktReturn + ! 2 MktReturn + + ! 3 IPOReturn + ! 4 Retain% +! 5 SellingShr% + ! 6 UW + ! 7 BigN + ! 8 VC + ! 9 Ln(Proceeds) +! 10 NYSE/AMEX + ! 11 Ln(Age) + ! 12 HighTech + ! 13 Ln(Assets) +

!14

PriceRevision + !15

PriceRevision+

+ " i,t

(6) Where:PriceUpdate = (IPO price mid-point of initial filing range) mid-point of initial filing range


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on PriceRevision + of 0.768 implies an IPO price adjustment of +10% corresponds to

underpricing of +9.22% (0.154 + 0.768).

We then augment equation (6) by specifying our three pre-IPO operating performance

variables of interest in equations (7a), (7b) and (7c).

InitialReturn = ! 0 + ! 1 OI/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +

! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) +! 15 PriceRevision + ! 16 PriceRevision + + " i,t (7a)

InitialReturn = ! 0 + ! 1 NI/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) +! 15 PriceRevision + ! 16 PriceRevision + + " i,t (7b)

InitialReturn = ! 0 + ! 1 OCF/Assets + ! 2 MktReturn + ! 3 MktReturn + + ! 4 IPOReturn +! 5 Retain% + ! 6 SellingShr% + ! 7 UW + ! 8 BigN + ! 9 VC + ! 10 Ln(Proceeds) +! 11 NYSE/AMEX + ! 12 Ln(Age) + ! 13 HighTech + ! 14 Ln(Assets) +! 15 PriceRevision + ! 16 PriceRevision + + " i,t (7c)

Columns 5 7 of Table 6 present the results of estimating equations (7a), (7b) and (7c).

While the coefficients on OI/Assets , NI/Assets and OCF/Assets remain positive and significant,

specifying these variables results in small increases in explanatory power versus the equation (2)


23/34

comprise this wealth revaluation: the change from mid-point of the initial price range to offer

price for secondary shares that shareholders sell at the IPO; plus the change from mid-point of

the initial price range to closing price on the first trading day for shares that shareholders retain.

Table 7 sorts our sample by decile of pre-IPO operating cash flow to average assets

(OCF/Assets ).15 In addition to mean and median PriceRevision and InitialReturn (which we

repeat from Table 3 panel C), Table 7 shows underwriter rank ( UW ) and the fraction of IPOs in

each decile with an IPO offer price: below the minimum of the initial price range (Below Min);

between the minimum and mid-point of the initial price range (Min to Mid); at the mid-point of

the initial price range (At Mid); between midpoint and maximum of the initial price range (Mid

to Max); and above the maximum of the initial price range (Above Max). Overall, 36.4% and

24.2% of our 20012012 IPOs have offer prices below the minimum and above the maximum of

the initial price range, respectively; versus 27.3% and 24.3%, respectively, for Loughran and

Ritters (2002) 19901998 IPOs. Lastly, Table 7 also shows the final IPO proceeds (this differs

from our Proceeds variable, which is inflation-adjusted proceeds per the initial prospectus), as

well as the amount of money left-on-the-table and pre-issue shareholder wealth revaluation.

The majority (57.3%) of IPOs in Decile 1 (i.e., lowest pre-IPO operating cash flow to

assets) have offer prices below the minimum of the initial price range On average (median)


24/34

million (i.e., the revaluation in pre-issue shareholders wealth exceeds the money left on the table

by four-to-five orders of magnitude). In the context of Loughran and Ritter (2002), this is

consistent with issuers agreeing to a partial price adjustment because the wealth gains they enjoy

leave them willing to acquiesce to underpricing. As such, one explanation for why issuers go

along with a partial adjustment in response to strong demand is they anchor on the mid-point of

the initial price range and offset the companys loss of proceeds with their psychic wealth gain. 16

V. SUMMARY

In this paper, we extend the study of the association between public information and IPO

price formation by examining Brau and Fawcetts (2006) CFO survey response that having

strong historical earnings is the most important signal of quality an issuer can convey. For asample of 20012012 IPOs, we find measures of pre-IPO operating performance explain a

substantial portion of the variation in the revision from the mid-point of the initial price range to

the offer price. That is, post-bubble, the partial adjustment phenomenon concentrates among

issuers with pre-IPO strong performance; whereas for issuers with weak performance, the

downward price adjustment is nearly full. As for why issuers with strong performance seem to

acquiesce to a partial increase in offer price, these IPOs have the largest wealth gains from shares


25/34

REFERENCES

Baron, D. 1982. A model of the demand for investment banking advising and distributionservices for new issues. The Journal of Finance 37, 955-976.

Bartov, E., Mohanram, P. and C. Seethamraju. 2002. Valuation of Internet stocksAn IPOperspective. Journal of Accounting Research 40, 321-346.

Benveniste, L. M. and P. A. Spindt. 1989. How investment bankers determine the offer priceand allocation of new issues. Journal of Financial Economics 24, 213-232.

Benveniste, L. M. and W. J. Wilhelm. 1990. A comparative analysis of IPO proceeds underalternative regulatory environments. Journal of Financial Economics 28, 173-207.

Berger, P. G. 2002. Discussion of Valuation of Internet stocksAn IPO perspective. Journal of Accounting Research 40, 321-346.

Bradley, D. and B. Jordan. 2002. Partial adjustment to public information and IPO underpricing. Journal of Financial and Quantitative Analysis 37, 595-616.

Brau, J. C. and S. Fawcett. 2006. Initial public offerings: An analysis of theory and practice. The Journal of Finance 61, 399-436.

Chemanmanur, T. J. 1993. The pricing of initial public offerings: A dynamic model withinformation production. The Journal of Finance 48, 285-304.

Cornelli, F. and D. Goldreich. 2001. Bookbuilding and strategic allocation. The Journal ofFinance 56, 2337-2369.

Daniel, K. 2002. Discussion of Why dont issuers get upset about leaving money on the table inIPO ? i f i i l S di 15 445 454


26/34

Kahneman, D. and A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47, 263-291.

Kim, M. and J. R. Ritter. 1999. Valuing IPOs. Journal of Financial Economics 53, 409-437.

Klein, A. 1996. Can investors use the prospectus to price initial public offerings? The Journal ofFinancial Statement Analysis 2, 23-39.

Leland, H. and D. Pyle. 1977. Informational asymmetries, financial structure and financialintermediation. The Journal of Finance 32, 371-387.

Loughran, T. and J. R. Ritter. 2002. Why dont issuers get upset about leaving money on thetable in IPOs? Review of Financial Studies 15, 413-443.

Loughran, T. and J. R. Ritter. 2004. Why has IPO underpricing changed over time? Financial Management 33, 5-37.

Lowry, M. and W. Schwert. 2004. Is the IPO pricing process efficient? Journal of Financial Economics 71, 3-26.

Ljungqvist, A. P. and W. J. Wilhelm, Jr. 2002. IPO allocations: Discriminatory ordiscretionary? Journal of Financial Economics 65, 167-201.

Ljungqvist, A. P. and W. J. Wilhelm, Jr. 2003. IPO pricing in the Dot-com bubble. The Journalof Finance 58, 723-752.

Ritter, J. R. 1984. The hot issue market of 1980. Journal of Business 57, 215-240.

Ritter, J. R. and I. Welch. 2002. A review of IPO activity, pricing, and allocations. The Journalof Finance 57, 1795-1828.


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TABLE 1Sample and descriptive statistics

Panel A: SampleFirm commitment IPOs by stand-alone domestic companies: January 2001 December 2012 1,826Less:

Financial registrants (SIC 6xxx) 790Unit IPOs 113Necessary financial statement information not available 71IPOs issued via auction mechanism 15IPOs with # days from initial filing range date to IPO date exceeds 365 7IPOs with initial filing range mid-point ! $5.00 6

Sample 824

Panel B: Descriptive Statistics (n = 824)Variable Mean Median MidQRange Standard Deviation

PriceRevision 0.052 0.000 0.056 0.219 InitialReturn 0.132 0.083 0.113 0.193OI/Assets 0.144 0.053 0.071 0.655

NI/Assets 0.241 0.006 0.122 0.998OCF/Assets 0.091 0.049 0.004 0.757

MktReturn 0.017 0.012 0.012 0.079 IPOReturn 0.116 0.111 0.114 0.047 Retain% 0.710 0.735 0.725 0.139SellingShr% 0.167 0.000 0.141 0.253UW 8.220 9.000 8.500 1.485

BigN 0.859 1.000 1.000 0.348VC 0.527 1.000 0.500 0.500Proceeds 82.175 44.285 58.798 182.945

NYSE/AMEX 0.296 0.000 0.500 0.457

Age 18.740 10.000 12.750 23.539 HighTech 0.278 0.000 0.500 0.448 Assets 234.082 45.413 92.313 694.186Variables are as follows:


28/34

26

TABLE 2

Correlations

Price Revision

Initial Return

OI/ Assets

NI/ Assets

OCF/ Assets

Mkt Return

IPO Return Retain%

SellingShr%

UW Rank BigN VC

LnProceeds

NYSE/ AMEX

Ln Age

HighTech

Ln Assets

PriceRevision 0.557 0.291 0.309 0.323 0.153 0.105 0.142 0.232 0.187 0.057 0.005 0.133 0.102 0.010 0.212 0.130 InitialReturn 0.529 0.203 0.211 0.221 0.122 0.079 0.195 0.137 0.126 0.056 0.124 -0.000 -0.013 -0.045 0.171 -0.002

OI/Assets 0.275 0.165 0.930 0.690 0.057 -0.052 -0.105 0.437 0.111 0.005 -0.369 0.313 0.229 0.388 0.058 0.393

NI/Assets 0.175 0.120 0.835 0.682 0.067 -0.076 -0.045 0.438 0.113 0.013 -0.316 0.270 0.216 0.340 0.094 0.363

OCF/Assets 0.238 0.140 0.808 0.904 0.037 -0.025 0.016 0.369 0.173 0.060 -0.213 0.255 0.193 0.227 0.175 0.329

MktReturn 0.113 0.081 -0.008 -0.028 -0.028 0.015 -0.103 -0.026 -0.087 -0.029 -0.095 -0.034 0.042 -0.025 -0.039 -0.013

IPOReturn 0.121 0.094 -0.039 -0.014 -0.007 0.083 0.085 -0.092 0.027 0.004 0.110 0.001 -0.041 -0.042 0.039 -0.004

Retain% 0.113 0.221 -0.056 -0.008 0.020 -0.114 0.092 -0.128 0.204 0.066 0.269 -0.044 -0.011 -0.188 0.207 -0.002

SellingShr% 0.158 0.048 0.293 0.201 0.196 -0.037 -0.091 -0.170 0.179 0.033 -0.189 0.314 0.193 0.246 0.126 0.271

UWRank 0.137 0.142 0.284 0.312 0.258 -0.115 -0.013 0.089 0.187 0.371 0.066 0.539 0.282 0.065 0.081 0.449

BigN 0.047 0.043 0.054 0.116 0.094 -0.019 -0.011 0.026 0.057 0.473 0.175 0.214 -0.005 0.022 0.064 0.163

VC -0.016 0.158 -0.229 -0.102 -0.103 -0.089 0.112 0.275 -0.246 0.125 0.175 -0.362 -0.349 -0.430 0.176 -0.453

Ln Proceeds 0.117 -0.023 0.326 0.277 0.238 -0.039 -0.024 -0.148 0.335 0.572 0.274 -0.293 0.476 0.301 -0.144 0.811

NYSE/AMEX 0.114 -0.024 0.188 0.120 0.136 0.024 -0.024 -0.063 0.245 0.154 -0.005 -0.349 0.438 0.269 -0.100 0.514

Ln Age 0.018 -0.096 0.296 0.202 0.168 -0.029 -0.073 -0.170 0.240 0.114 0.040 -0.443 0.317 0.289 -0.080 0.397

HighTech 0.212 0.185 0.101 0.077 0.110 -0.070 0.068 0.183 0.046 0.073 0.064 0.176 -0.116 -0.100 -0.120 -0.142

Ln Assets 0.144 -0.035 0.478 0.403 0.356 -0.010 -0.033 -0.095 0.104 0.491 0.208 -0.400 0.827 0.512 0.440 -0.132

Observations are 824 firm-commitment share IPOs by non-financial, domestic companies from January 1, 2001 to December 31, 2012. See Table 1 for sampledetails and variable definitions. Pearson (Spearman) correlations are below (above) the diagonal. To accord with our regression specifications, we show correlationsfor the natural log of Proceeds , Age and Assets. However, in contrast to our regression specifications (for which we winsorize, at +0.5% and 0.5%, our operatingperformance variables of interest), we show correlations for un-winsorized versions OI/Assets , NI/Assets and OCF/Assets .


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27

TABLE 3IPO price revision and initial return by decile of pre-IPO operating performance measure

Panel A: Panel B: Panel C:Decile sort by OI/Assets Decile sort by NI/Assets Decile sort by OCF/Assets

DecileOI /

Assets

Price

Revision

Initial

Return

NI /

Assets

Price

Revision

Initial

Return

OCF /

Assets

Price

Revision

Initial

Return

1mean

median 1.581 1.306

0.229 0.218

0.0450.005

1.976 1.349

0.212 0.200

0.0640.011

1.406 0.960

0.232 0.218

0.0420.005

2mean

median 0.619 0.595

0.133 0.077

0.1220.036

0.668 0.626

0.135 0.083

0.1000.020

0.512 0.510

0.147 0.176

0.0990.035

3mean

median 0.286 0.291

0.042 0.065

0.1380.100

0.325 0.324

0.0490.000

0.1590.100

0.185 0.167

0.074 0.073

0.1350.093

4mean

median 0.061 0.047

0.062 0.067

0.1540.063

0.100 0.092

0.100 0.125

0.1060.051

0.044 0.043

0.0280.000

0.1460.121

5mean

median

0.027

0.027

0.054

0.068

0.129

0.077

0.011

0.007

0.050

0.043

0.103

0.033

0.025

0.026

0.046

0.000

0.120

0.0646

meanmedian

0.0700.070

0.0140.000

0.0930.044

0.0180.019

0.0150.000

0.1270.122

0.0680.068

0.052 0.037

0.0860.045

7mean

median0.1060.107

0.0030.000

0.1180.087

0.0430.041

0.0050.000

0.1350.066

0.1070.105

0.0100.000

0.1550.125

8mean

median0.1500.149

0.0280.000

0.1380.131

0.0810.080

0.0060.039

0.1440.121

0.1610.159

0.0240.000

0.1220.096

9mean

median0.2330.232

0.0020.048

0.1640.119

0.1420.136

0.0040.000

0.1590.121

0.2570.255

0.0350.053

0.1710.151

10mean

median0.5160.435

0.0500.067

0.2180.188

0.3820.306

0.0460.069

0.2230.176

0.6220.498

0.0610.097

0.2420.217

Totalmean

median 0.144

0.053 0.052

0.0000.1320.083

0.2410.006

0.0520.000

0.1320.083

0.0910.049

0.0520.000

0.1320.083

Observations are 824 firm-commitment share IPOs by non-financial, domestic companies from January 1, 2001 to December 31, 2012. SeeTable 1 for sample details and variable definitions.


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TABLE 4Price revision regressions

Panel A: Full-sampleVariable Eq 1a Eq 1b Eq 1c Eq 2 Eq 3a Eq 3b Eq 3c

Constant 0.035( 2.77)b

0.030( 2.37)b

0.040( 3.25)a

0.350( 4.92)a

0.271( 3.84)a

0.272( 3.64)a

0.272( 4.11)a

OI/Assets0.130

(10.81)a0.123(6.43)a

NI/Assets0.105(9.50)a

0.092(5.58)a

OCF/Assets0.167

(14.05)a0.147

(11.85)a

MktReturn0.918(3.09)a

0.916(3.31)a

0.915(3.39)a

0.924(3.99)a

MktReturn + 0.752( 2.47)b

0.783( 2.57)b

0.762( 2.63)b

0.787( 3.06)b

IPOReturn0.524(2.58)b

0.544(2.80)b

0.541(2.88)b

0.532(2.71)b

Retain% 0.168(4.01)a0.190(4.42)a

0.185(4.08)a

0.170(4.26)a

SellingShr%0.112(4.14)a

0.064(2.02)c

0.077(2.65)b

0.068(2.73)b

UW0.008(1.16)

0.001(0.15)

0.001(0.13)

0.002(0.31)

BigN 0.008( 0.61)

0.009(0.69)

0.004(0.32)

0.003(0.24)

VC 0.001( 0.04)0.008(0.45)

0.001(0.04)

0.004(0.21)

Ln (Proceeds) 0.008( 0 36)

0.014(0 59)

0.013(0 55)

0.012(0 54)


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TABLE 4Price revision regressions

Panel B: Sub-sample of IPOs with interim financial statementsVariable Eq 1c Eq 1d Eq 2 Eq 3c Eq 3d

Constant 0.041( 2.74)b

0.041( 2.73)b

0.365( 5.29)a

0.269( 4.02)a

0.274( 3.89)a

OCF/Assets0.161(9.64)a

0.150(9.30)a

OCF/AssetsStale0.129(8.96)a

0.117(7.44)a

MktReturn0.814(2.59)b

0.799(3.11)a

0.814(2.84)b

MktReturn + 0.629( 2.35)b

0.648( 2.88)b

0.640( 2.59)b

IPOReturn0.541(2.76)b

0.548(2.81)b

0.563(2.78)b

Retain%0.166(3.95)a

0.167(4.43)a

0.175(4.70)a

SellingShr% 0.139(4.99)a0.093(3.55)a

0.096(3.52)a

UW0.007(0.98)

0.001(0.11)

0.000( 0.06)

BigN0.001(0.04)

0.011(0.82)

0.018(1.21)

VC0.003(0.11)

0.006(0.24)

0.004(0.15)

Ln (Proceeds) 0.001( 0.04)0.020(0.95)

0.016(0.78)

NYSE/AMEX0.017(0 80)

0.028(1 16)

0.025(1 05)


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30

TABLE 5Price revision regressions pre-IPO operating performance measure by decile ranking

Panel A: OI/Assets Panel B: NI/Assets Panel C: OCF/Assets Variable Eq 3a Eq 4a Eq 3b Eq 4b Eq 3c Eq 4c

Constant 0.271( 3.84)a

0.457( 6.85)a


0.453( 6.71)a


0.453( 6.51)a

OI/Assets 0.123(6.43)a

NI/Assets 0.092(5.58)a

OCF/Assets 0.147(11.85)a

OI/AssetsDecile2 0.088(2.25)b

NI/AssetsDecile2 0.064(1.64)

OCF/AssetsDecile2 0.082(2.47)b

OI/AssetsDecile3 0.160(5.06)a

NI/AssetsDecile3 0.135(4.84)a

OCF/AssetsDecile3 0.136(4.68)a


NI/AssetsDecile4 0.087(2.21)b








OI/AssetsDecile70.230(8.10)a

NI/AssetsDecile70.191(6.08)a

OCF/AssetsDecile70.204(5.03)a










Control variables Yes Yes Control variables Yes Yes Control variables Yes YesObservations 824 824 Observations 824 824 Observations 824 824

Adjusted R 2 18.4% 19.2% Adjusted R 2 16.5% 18.8% Adjusted R 2 19.5% 19.6%

Observations are 824 firm-commitment share IPOs by non-financial, domestic companies from January 1, 2001 to December 31, 2012. The dependent variableis PriceRevision . In contrast to Tables 1, 2 and 3, OI/Assets , NI/Assets and OCF/Assets are winsorized at + / 1%. For each operating performance variable(OI/Assets , NI/Assets and OCF/Assets ), we specify indicator variables for whether the IPO sorts into a given decile in Table 3 (e.g., OI/Assets-Decile2 equals oneif an IPO is in the second decile of OI/Assets in Table 3). Control variables are as in Table 4. See Table 1 for sample details and other variable definitions. OLSestimation and t-statistics with robust standard errors clustered by IPO year in parentheses.

a,b,c Significant at or beyond the 1%, 5% and 10% levels, respectively (two-sided tests).


33/34

TABLE 6Initial returns regressions

Variable Eq 5a Eq 5b Eq 5c Eq 6 Eq 7a Eq 7b Eq 7c

Constant0.140

(15.52)a0.144

(16.40)a0.138

(15.23)a 0.048( 0.76)

0.029( 0.44)

0.024( 0.36)

0.035( 0.51)

OI/Assets0.064(9.96)a

0.041(2.80)b

NI/Assets0.056

(10.45)a0.035(2.90)b

OCF/Assets0.088(8.70)a

0.038(2.08)c

MktReturn 0.182(1.05)0.202(1.14)

0.197(1.14)

0.203(1.21)

MktReturn + 0.077( 0.42)

0.104( 0.53)

0.094( 0.50)

0.102( 0.56)

IPOReturn0.069(0.62)

0.087(0.83)

0.084(0.78)

0.082(0.75)

Retain%0.128(3.78)a

0.139(4.14)a

0.138(4.08)a

0.133(3.95)a

SellingShr%0.031(1.30)

0.017(0.65)

0.019(0.77)

0.021(0.84)

UW0.015(2.10)c

0.013(1.77)

0.012(1.72)

0.014(1.85)c

BigN 0.029( 1.59)

0.024( 1.31)

0.025( 1.39)

0.027( 1.48)

VC0.018(1.20)

0.021(1.37)

0.019(1.24)

0.020(1.29)

Ln (Proceeds) 0.015( 1.34)

0.008( 0.68)

0.007( 0.60)

0.010( 0.86)

NYSE/AMEX 0.006( 0.32)

0.002( 0.11)

0.001( 0.05)

0.004( 0.21)

Ln (Age)0.000(0 04)

0.003( 0 51)

0.002( 0 31)

0.001( 0 18)


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32

TABLE 7IPO price revision, initial return, money left on the table and revaluation by decile of pre-IPO operating cash flow to assets

DecileOCF/

Assets UWBelowMin

Minto

MidAt

Mid

Midto

MaxAboveMax

Price

Revision

Initial

Return

FinalIPO

Proceeds

Moneyleft ontable Revaluation

Revaluationminus Moneyleft on table

1 meanmedian 1.406 0.960

7.1468.000

0.573 0.195 0.134 0.049 0.049 0.232 0.218

0.0420.005

59.28149.050

3.1920.163

28.611 29.420

31.803 29.922


7.8018.500

0.506 0.121 0.157 0.096 0.120 0.147 0.176

0.0980.035

69.57155.000

10.6291.225

15.599 23.549

4.970 24.591

3mean

median 0.185 0.167

8.3179.000

0.451 0.085 0.061 0.220 0.183 0.074 0.073

0.1350.093

114.35780.000

12.2166.833

17.2418.492

5.025 1.595


8.1759.000

0.349 0.096 0.121 0.133 0.301 0.0280.000

0.1460.121

115.77993.750

17.55910.000

64.1239.771

46.5645.797

5mean

median0.0250.026

8.4399.000

0.354 0.134 0.122 0.207 0.183 0.0460.000

0.1200.064

230.580146.205

25.0186.994

54.8796.074

29.861 1.526

6mean

median0.0680.068

8.3789.000

0.390 0.134 0.159 0.171 0.146 0.052 0.037

0.0860.045

244.683124.500

13.5455.190

6.3460.986

19.891 1.189

7 meanmedian0.1070.105

8.5729.000

0.301 0.121 0.084 0.169 0.325 0.0100.000

0.1550.125

212.875140.625

33.86514.188

161.77937.538

127.91421.829


8.7509.000

0.317 0.110 0.195 0.183 0.195 0.0240.000

0.1220.096

188.949113.250

25.18911.387

186.58517.471

161.3968.528


8.4169.000

0.229 0.072 0.157 0.193 0.349 0.0350.053

0.1710.151

346.18296.000

29.18011.550

320.79929.332

291.61917.809


8.2019.000

0.171 0.134 0.061 0.073 0.561 0.0610.097

0.2420.217

155.89793.424

42.74021.859

222.67094.079

179.93069.905

Total meanmedian 0.144

0.0538.2209.000

0.364 0.120 0.125 0.149 0.242 0.0520.000

0.1320.083

173.87591.000

21.3217.350

101.0654.838

79.7440.264

Observations are 824 firm-commitment share IPOs by non-financial, domestic companies from January 1, 2001 to December 31, 2012. Below Min, Min toMid, At Mid, Mid to Max and Above Max are the fraction of IPOs with an offer price below the minimum of the initial price range, between the minimumand mid-point of the initial price range, at the mid-point of the initial price range, between the mid-point and the maximum of the initial price range and abovethe maximum of the initial price range, respectively. Final IPO Proceeds are proceeds ($millions) per final prospectus. Money left on table is the first-dayclosing price minus the offer price times number of IPO shares issued ($millions). Revaluation is (the first-day closing price minus the mid-point of the initialprice range) times number of shares retained by pre-IPO shareholders plus (the offer price minus the mid-point of the initial price range) times number of sharessold by selling shareholders ($millions). See Table 1 for sample details and variable definitions.

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