Negotiation and the IPO Offer Price: A Comparison of Integer versus Non-integer IPOs*
Daniel J. Bradley University of Kentucky John W. Cooney, Jr. University of Kentucky Bradford D. Jordan University of Kentucky Ajai K. Singh Case Western Reserve University
First Draft: January 15, 2002 This Draft: March 11, 2002 Comments Welcome
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Bradley, Cooney, and Jordan are from the Gatton College of Business and Economics, University of Kentucky, Lexington, Kentucky 40506-0034. Singh is from the Weatherhead School of Management, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106-7235. Cooney is the corresponding author: (859) 2571934,
[email protected]. The authors would like to thank Lynn-Ann Gries, Susan Jordan, Alexander Ljungqvist, Tim Loughran, Jay Ritter, seminar participants at the University of Kentucky, and representatives at Goldman Sachs & Co., McDonald Investments, and William Blair & Co. for providing valuable comments and suggestions.
Negotiation and the IPO Offer Price: A Comparison of Integer versus Non-integer IPOs Abstract We investigate the pricing of 4,523 initial public offerings of common stock with offer dates between 1981 and 2000. Our study documents that approximately three-fourths of IPOs have integer offer prices. Average initial returns for IPOs with integer offer prices are significantly higher (25.5 percent) than those priced on the fraction of the dollar (8.1 percent). Higher initial returns for integer offerings are observed for 18 of the 20 years of our study and over various ranges of offer prices. Initial returns for integer and fractional IPOs are similar for the subsample of offerings priced below the original filing range. However, significant differences are found for IPOs priced within and above the filing range. For instance, the average initial return for integer offerings priced above the filing range is 65.5 percent compared to 19.9 percent for those priced on the fraction of the dollar. Similar to the arguments made by Harris (1991), we hypothesize that integer versus fractional dollar IPOs are the result of negotiations between the issuing firm and underwriter. Under the negotiation hypothesis, the frequency of integer pricing should be a positive function of the offer price and uncertainty. With greater uncertainty, the extent of underpricing for integer offerings should be higher than for fractional offerings as the investment bank seeks to manage its underwriting risk. We present evidence supportive of the negotiation hypothesis. Specifically, we observe that the frequency of integer prices for the sample of IPOs priced at $15 and above is about twenty percentage points higher than for those IPOs priced below $10 per share. We also document that both the cross-sectional standard deviation of initial returns and the ex-post standard deviation of daily stock returns is highest for offerings priced on the dollar. This higher level of uncertainty for integer offerings is consistent with their high degree of underpricing.
Negotiation and the IPO Offer Price: A Comparison of Integer versus Non-integer IPOs Financial economists have closely scrutinized many aspects of initial public offerings (IPOs), and the fact that IPOs are, on average, underpriced has been thoroughly documented. Numerous explanations for the persistence of underpricing exist, but, to date, there is a lack of consensus. Given the sheer volume of research on IPO underpricing, and the evident interest in the subject among academics and practitioners alike, it is somewhat surprising that little attention has been paid to a potentially important determinant—the precise level of the final offer price. This paper focuses on one particular aspect of IPO pricing, namely, the information content of integer versus non-integer offer prices. For a sample of 4,523 U.S. IPOs from 1981–2000, we document that 76 percent are priced on the integer (i.e., in whole dollars). More importantly, we find that the initial return for integer IPOs is much higher than for non-integer IPOs, 25.5 percent versus 8.1 percent, respectively.1 This pattern is robust. Higher initial returns for whole dollar offerings are observed for 18 of the 20 years of our sample period. The difference between the mean initial returns for the two samples is generally higher in the 1990s than in the 1980s and it is dramatically higher in the IPO bubble period of 1999 and 2000. In 1999 and 2000, the mean initial returns for whole dollar IPOs are 77.1 percent and 60.5 percent, respectively, while the corresponding mean initial returns for fractional IPOs are 7.8 percent and 2.2 percent. Greater underpricing for integer-priced issues exists within every offer price range. In fact, the average underpricing for whole dollar IPOs increases with the offer price, but the mean underpricing for fractional IPOs remains fairly constant. Thus, the difference between the underpricing of whole dollar and fractional IPOs actually rises with offer price.
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In two recent working papers, Mola and Loughran (2002) and Corwin (2001) document that seasoned equity offerings (SEOs) are often priced on integers. Similar to the findings of our study, SEOs priced on the integer are discounted more (i.e., priced lower) than fractionally priced SEOs. However, the magnitude of the SEO discount is much smaller than the degree of underpricing of IPOs found in this study.
We also examine the relation between whole dollar and fractional pricing and the wellknown partial adjustment phenomenon. Similar to results first presented by Hanley (1993), both whole dollar and fractional IPOs are the least underpriced when the offer price is set below the original filing range. For these IPOs, the mean initial returns for whole dollar and fractional IPOs are comparable (4.4 percent versus 3.5 percent, respectively). However, significant differences between integer and non-integer offerings are observed for issues priced within the file range (14.4 percent versus 7.4 percent, respectively) and above the file range (66.5 percent versus 19.9 percent, respectively). Finally, we include an integer versus fractional offer price dummy variable in a multivariate regression analysis that incorporates a wide variety of variables known to be significantly related to IPO underpricing and examine the full sample period, as well as three subperiods (1981-1990, 1991-1998, and 1999-2000). We find that the integer effect is still statistically (and economically) significant after controlling for these other influences in all four regressions. In fact, we find only three effects that are consistently observed in the full sample and in all three subperiods—IPOs are more underpriced if (1) they are priced on the whole dollar, (2) if there is a positive adjustment in offer prices (the partial adjustment phenomenon), and (3) if recent underpricing in the IPO market is high. These empirical results raise an obvious question: Why are IPOs with fractional offerings underpriced less than whole-dollar IPOs? We propose an explanation based on Harris’ (1991) costly negotiation hypothesis. In Harris’ model, buyers and sellers negotiate from a coarse set of rounded prices to reduce the time needed to arrive at a transaction price. Harris argues that the use of a rounded set of prices (as opposed to a finer set of prices) is an increasing function of the stock price and uncertainty about stock values. Similarly, we hypothesize that representatives of the issuing firm and the underwriter negotiate from a set of rounded prices (e.g., $22, $21, $20) 2
when the anticipated offer price is high and/or there is a large degree of uncertainty about the stock’s market value. In such cases, the frequency of whole dollar IPOs should be relatively high. However, with a lower stock price, and/or less uncertainty, the negotiations should revolve around a more precise set of prices (e.g., $9.50, $9.25, $9.00). Under these circumstances, more fractional IPOs should be observed. Evidence consistent with the negotiation hypothesis is presented. First, we find that the frequency of whole dollar IPOs increases with offer price. For low-priced IPOs (i.e., $5 - $9.99), 66.1 percent are priced on the whole dollar. The percentage of whole dollar IPOs increases to 76.9 percent for medium-priced offerings (i.e., between $10 and $14.99), and to 86.5 percent for high-priced offerings (i.e., those priced at $15 and above). Second, we find that issues with integer prices are associated with greater uncertainty concerning their values. We measure uncertainty in two ways. First, we calculate the crosssectional standard deviation of initial returns for samples of whole dollar and fractional IPOs. We find a consistent pattern across the three offer price ranges—the cross-sectional standard deviation of initial returns is higher for the sample of whole dollar offerings. We also find that the cross-sectional standard deviation increases with offer price for the whole dollar sample, but not for the fractional sample. Thus, the difference in uncertainty between these two samples is highest for high-priced offerings. Our second method of measuring uncertainty is the calculation of the ex-post standard deviation of daily stock returns. Similar conclusions are drawn with this second measure of uncertainty—the standard deviation of ex-post daily stock returns is highest for the sample of whole dollar IPOs and the difference in the mean standard deviation of returns between the two samples increases in offer price.
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The remainder of the paper is organized as follows. Section 1 describes the data. Section 2 reports the extent of underpricing for whole dollar and fractional offerings. We discuss our negotiation hypothesis and the results of the empirical tests of this hypothesis in section 3. Concluding remarks are made in section 4. 1. Data Description Our sample is gathered from the Securities Data Company’s (SDC) New Issues database with a sample period of January 1, 1981 through December 31, 2000. Consistent with previous IPO studies, we eliminate REITs, closed-end funds, ADRs, spinoffs, reverse LBOs, unit offers, limited partnerships and trusts, IPOs with final offer prices below $5, and IPOs with total proceeds less than $5 million. We also eliminate IPOs with missing information on the name of the lead underwriter, high or low file prices, or outstanding shares, along with firms not identified on the Center for Research in Security Prices (CRSP) database. This process results in a final sample of 4,523 IPOs of which 3,436 (76 percent) are priced at the whole dollar and 1,087 (24 percent) are priced on the fraction of the dollar. As an initial examination of underpricing for fractional and whole dollar IPOs, we calculate the market-adjusted initial return (i.e., the percentage return from the offer price to the closing stock price on the first day of trading less the contemporaneous CRSP value-weighted index return) for the two samples. We find a large difference. Whole dollar IPOs are underpriced by 25.5 percent compared to 8.1 percent for fractional IPOs. This difference of 17.4 percent is not only statistically significant (p-value ≤ .0001), but economically large as well. To explore the robustness of this result over time, Figure 1 presents the mean initial return for the two groups in each of the 20 years of our sample period. As shown, whole dollar offerings have higher initial returns for 18 of the 20 years (the exceptions are 1982 and 1984). The means for the whole dollar sample are statistically greater (at the 10 percent level or better) 4
in 11 of the 20 years. The difference between the mean initial returns for the two samples is generally higher in the 1990s than the 1980s, and it is dramatically higher in the IPO bubble period of 1999 and 2000. In these last two years, the mean initial returns for integer IPOs are 77.1 percent and 60.5 percent, respectively, compared to 7.8 percent and 2.2 percent for the noninteger sample, and these differences are highly significant.2 *** Insert Figure 1 about here *** As explored more fully later in this paper, non-integer prices are more common for lower priced IPOs. For instance, of the 1,438 offerings priced between $5 and $9.99, 448 (33.9 percent) are priced on the fraction. This proportion falls to 23.1 percent (440 out of 1,908 offerings) in the $10 to $14.99 price range and 13.5 percent (159 out of 1,177 offerings) for IPOs priced at $15 and above. Mean initial returns also increase across these three offer price zones. In other words, higher priced issues are, on average, more underpriced and more likely to be priced on the integer. Consequently, the difference in initial returns between whole dollar and fractional dollar offerings may be the result of more whole dollar offerings for high-priced IPOs and more fractional offerings for low-priced IPOs. However, as Figure 2A shows, a consistent pattern exists between whole dollar and fractional offerings over various offer price ranges. Whole dollar IPOs are more underpriced than non-integer IPOs in each offer price range, and the differences are significant at the 1 percent level. In fact, although the average amount of underpricing for whole dollar IPOs increases with offer price, mean underpricing remains fairly constant for fractional IPOs. Thus, the difference between the amount of underpricing for whole dollar and fractional IPOs actually increases with offer price. *** Insert Figures 2A and 2B about here *** 2
Although the main focus of their study is an examination of the SEO market, Mola and Loughran (2002) briefly compare price clustering on the SEO and IPO markets and find results similar to those presented in Figure 1.
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Hanley (1993) and other researchers document a strong positive relation between the initial return and the revision in offer price from the original filing range to the final offer price (i.e., the partial adjustment phenomenon). If higher-priced offerings are more likely to have been revised up than lower-priced offerings, then the positive relation between initial returns and offer price for integer offerings observed in Figure 2A may result from the partial adjustment phenomenon rather than the level of the offer price. To determine if this is the case, we present in Figure 2B mean initial returns for integer and non-integer offerings sorted by the midpoint of the original filing range. As shown, the positive relation for integer IPOs no longer appears. More importantly, mean initial returns for integer IPOs are greater than for non-integer IPOs for the samples of low-, medium-, and high-file price IPOs (significant at the 1 percent level). As a final sort, we examine differences in the mean initial return for the integer and noninteger samples for offerings priced below, within, and above the original filing range. Similar to the results presented by Hanley (1993), mean initial returns are highest for offerings priced above the original file range. Figure 3 also shows that mean initial returns are higher for integer offerings priced within and above the filing range. (The means are statistically similar for offerings priced below the filing range.) *** Insert Figure 3 about here *** 2. Integer versus Non-integer IPOs: A Closer Look The results in the previous section strongly suggest that IPOs with integer prices are more underpriced than non-integer IPOs. Of course, it could be that integer pricing proxies for some other issue characteristic(s), so our goal in this section is to expand our previous analysis to examine a wide variety of effects known to be associated with IPO underpricing.
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2.1 Univariate analyses of issue characteristics Table 1 presents some basic descriptive statistics on the two types of IPOs. First, as we previously reported, whole dollar IPOs have greater underpricing: 25.5 percent versus 8.1 percent. Integer IPOs also have a higher average offer price ($12.37) than fractional IPOs ($11.07). Consistent with the higher offer price, we find that integer IPOs have been, on average, revised 2.5 percent above the original midpoint of the filing range. Conversely, fractional IPOs are revised 4.3 percent below the filing range midpoint. Since IPOs with positive revisions are more underpriced than those with negative revisions [Hanley (1993)], the higher amount of underpricing for integer IPOs may be at least partially explained by their higher price revision. *** Insert Table 1 about here *** The next variable, CM-Rank, is the Carter Manaster (1990) and Carter, Dark, and Singh (1998) measure of underwriter prestige. We use the rankings as updated in Loughran and Ritter (2001). The rankings are based on a 0 – 9 scale with 0 representing underwriters of the lowest prestige.3 IPOs with integer prices have more prestigious lead underwriters than those with fractional prices. Habib and Ljungqvist (2001) argue that issuers care most about underpricing when they are selling a large portion of the firm—either through selling a large number of new (primary) shares, or selling existing (secondary) shares in the IPO. To evaluate this effect, we calculate Overhang, pre-IPO shares retained scaled by shares offered in the IPO, and Secondary, a dummy variable equal to one if secondary shares are sold in the IPO, zero otherwise. Bradley and Jordan (2001) find that Overhang is positively related to initial returns. Habib and Ljungqvist (2001) document a negative relation between secondary shares sold and IPO underpricing. As shown, Overhang is larger for the whole dollar sample. The percentage of non-integer IPOs with 3
These rankings can be downloaded from Jay Ritter’s website (http://bear.cba.ufl.edu/ritter/), where greater detail is provided.
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secondary shares sold (43.4 percent) is greater than the percentage for integer IPOs (39.6 percent). Lag Market is the 21-day (i.e., one-month) cumulative market return ending one day before the IPO using the CRSP value-weighted index as a proxy for the market. Lag IPO is a simple average of the market-adjusted initial return for all IPOs (within our sample) offered in the month prior to the sample IPO. Lag Market is higher for fractional offerings. However, Lag IPO is higher for integer offerings. The difference for Lag IPO is quite large; the average IPO initial return preceding integer IPOs is 25.6 percent compared to 13.7 percent for stocks that had an IPO in the month prior to a fractional IPO. Integer IPOs are larger than non-integer IPOs. The average CPI-adjusted (1982-1984 base year) offer size for whole dollar IPOs is $33.6 million compared to $27.1 million for fractional IPOs. The next two variables in the table, Venture and Tech, are dummy variables taking a value of one for venture capital-backed and “high-tech” IPOs, respectively.4,5 As shown, integer IPOs are much more likely to be VC-backed (47.7 percent versus 29.5 percent) and high-tech (44.3 percent versus 27.1 percent). Classified stock (i.e., the variable Multiple Class) is observed at about the same frequency for integer and non-integer offerings.6 However, Volatility, the standard deviation of the market-adjusted daily stock returns for the 62-day period from the close of the second day of trading to the 64th day of trading (i.e., a three-month period), is much higher
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In the SDC database, certain firms are classified as “high-tech” based on 4-digit SIC codes, but the application is somewhat inconsistent. We obtained the underlying codes from SDC and applied them to our sample. The full list of codes is available on request. 5 Venture and Tech have appeared in the literature as important determinants of the amount of underpricing. For example, earlier research argued VC-backed firms played a “certification role” in that their presence reduced asymmetric information between corporate insiders and the investing public resulting in lower initial returns and gross spreads [Barry, Muscarella, Peavy, and Vetsuypens (1990) and Megginson and Weiss (1991)]. Recent evidence suggests that this effect may have reversed or is non-existent [Bradley and Jordan (2001) and Hamao, Packer, and Ritter (2000)]. 6 Multiple Class takes on a value of one if the IPO is of classified stock (e.g., class A common), or if the SDC otherwise indicates that the stock being issued has inferior voting rights, zero otherwise.
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for the integer sample (4.5 percent versus 3.3 percent, respectively).7 NYSE/AMEX is a dummy variable taking on a value of one for NYSE/AMEX-listed IPOs. Non-integer IPOs are more likely to be NYSE/AMEX listed, 11.1 percent compared to 9.3 percent. 2.2. Multivariate analysis Our univariate sorts in Table 1 clearly indicate that significant differences exist between integer and non-integer IPOs. We therefore examine a multiple regression model to determine if the integer versus non-integer classification in Table 1 simply proxies for other issue characteristics. We model initial returns as a function of a dummy variable for fractional pricing along with a number of additional explanatory variables, most of which have been previously considered in other IPO studies. 2.2.1 Variables and specification Formally, our regression model is: Initial Return = β0 + β1 Fraction + β2-3 Offer Range + β4-6 Partial + β7-9 CM Rank + β10 Overhang + β11 Secondary + β12 Lag Market + β13 Lag IPO + β14 Log Size + β15 Venture + β16 Tech + β17 Multiple Class + β18 Volatility + β19 NYSE/AMEX + β20-38 Year Dummies + ε (1) where: Initial Return = The IPO’s initial return from the offer price to the closing price on the first day of trading as recorded on CRSP less the contemporaneous CRSP value-weighted index return; Fraction = A dummy variable equal to one if the offer price is on the fraction of the dollar, zero if on the whole dollar; Offer Range = Two dummy variables for offer price range. The first, Medium Price, takes on a value of one if offer price is in the $10 - $14.99 range, and zero otherwise. The second, High Price, equals one if the offer price is in the $15 and above range, and zero otherwise. The low range dummy is the omitted category in the regression.
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Volatility is calculated over, at most, a 62 trading day period. If CRSP reports a missing return for day t, we exclude day t and day t+1 from the analysis. (Day t+1 is a two-day return.) Also, since we use the 2000 version of the CRSP tapes, Volatility is only calculated until the last trading day of 2000. Thus, Volatility is calculated with fewer than 62 trading days for IPOs with offer dates in the last three months of 2000. There are only 33 observations with offer dates in this period. We recalculated the mean Volatility for integer and fractional IPOs without these 33 observations and find results almost identical to those reported in Table 1.
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Partial = Three variables for the offer price adjustment. The first, Above, is the percentage difference between the final offer price and the original file midpoint for issues that are priced above the original file range, and zero otherwise. The second, Within, is the percentage difference for issues that are priced within the original file range, and zero otherwise; and the third, Below, is the percentage difference for issues that are priced below the original file range, and zero otherwise; CM Rank = Three dummy variables for Carter and Manaster (1990) ranks. The first, CM9, equals one if the rank is 9 (the highest possible), and zero otherwise; the second, CM8, equals one if the rank is 8 – 8.9, and zero otherwise; the third, CM67, equals one if the rank is 6 – 7.9, and zero otherwise. The lowest ranking (0 – 5.9) is the omitted category;8 Year Dummies = One for each in the 1982 – 2000 period; 1981 is the omitted category.9 The remaining variables were defined in the previous section. A few comments about certain aspects of our specification are in order. First, we use multiple dummy variables for offer price ranges instead of a single variable equal to the offer price. The reason is that, with a single variable, the assumption is that the effect is strictly linearly increasing or decreasing, but there is evidence of a “U-shaped” relation between offer prices and underpricing [see Fernando, Krishnamurthy, and Spindt (2000)]. For our price adjustment variable, we follow Bradley and Jordan (2001) and use multiple variables to allow for the possibility of an asymmetric response to upward and downward adjustments. We also use dummy variables for the Carter-Manaster (1990) rankings. Using a single variable that takes on a value equal to the ranking makes the assumption that the rankings scale is numerically meaningful such that a move from 1 to 2, for example, has the same effect as a move from 8 to 9. Using a series of dummy variables allows the data to determine the magnitudes of the effects. Our measure of overhang is from Bradley and Jordan (2001), as is the use of lagged average IPO initial returns. We include the secondary offering dummy based on results in Habib and Ljungqvist (2001). The multiple shares class dummy is based on Smart and Zutter (2000). 8 9
This division of the underwriter rankings assigns approximately one-fourth of the observations to each dummy. To conserve space, the year of offering dummy variables are not reported in the table.
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In addition to examination of the entire sample period, we examine three subperiods: 19811990, 1991-1998, and 1999-2000.10 In our regressions that examine the two later periods, we include two additional dummy variables, High20 and Low20. The first of these, High20, is equal to one if the final offer price is within $1 of an amount equal to 20 percent above the high end of the final file range, zero otherwise. Low20 is similarly defined for offer prices that are within $1 of an amount equal to 80 percent of the low end of the final file range. Because a substantial percentage of firms amend their file ranges, we define these variables relative to the final file range, as opposed to the original file range. The reason we do not include these variables in all of our regressions is that the necessary data do not become available until the late 1980s. The motivation for these two variables stems from an SEC requirement that the final offer price must be within 20 percent of the file range, meaning no more than 20 percent above (below) the high (low) end of the final file range. Pricing an offer outside this range requires a file range amendment. In other words, conditional on an existing file range, the distribution of possible offer prices is truncated. So, if an IPO is priced at 20 percent above the final file range, there is the possibility that a higher price was sustainable, but the firm and its underwriters elected to go forward with the offer rather than file an amendment to the registration statement. Such offers may be particularly underpriced. For deals priced at the lower bound, the reverse may be true. To our knowledge, these variables have not been considered in previous studies. 2.2.2 Regression results Table 2 presents the regression results for the four samples. The first sample includes all offerings from 1981-2000 (4,512 observations). For the three subperiods, the numbers of observations are 1,396 (1981-1990), 2,305 (1991-1998), and 720 for the 1999-2000 “bubble”
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Year of offering dummies are adjusted depending on the sample period, with the first year of each period excluded.
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period.11 (As shown in Figure 1, mean initial returns, and differences between whole dollar and fractional IPOs, are higher in the 1990s than in the 1980s, and much higher in the 1999-2000 period.) *** Insert Table 2 about here *** As the first regression of Table 2 shows, the variable of interest, Fraction, is statistically significant (at the 1 percent level) with a coefficient of –0.030. Fraction is also significant (at the 5 percent level, or better) in each of the subperiods. Across the first two periods, fractional offerings are underpriced by an economically significant 2.1 percentage points and 3.1 percentage points less than whole dollar IPOs, holding other IPO characteristics constant. In the 1999-2000 period, fractional offerings are underpriced by 21.8 percentage points less than comparable whole dollar offerings. Several other aspects of our regressions are interesting in their own right. First, the overall sample regression has a relatively high adjusted R2 of 49 percent, so almost half of the variation in IPO underpricing is explained by the model. The adjusted R2 is lower in the two non-bubble subperiods, 29 percent for 1981-1990 and 30 percent for 1991-1998, but it is 48 percent for the bubble period.12 Turning to specific coefficients, the most consistently significant variable is Above. In every case, this variable has a t-statistic in excess of 13, rising to 34 for the overall sample. (We report p-values instead of t-statistics in the tables.) The companion variable Below is also highly significant, but it is consistently smaller, and there is clear evidence of an asymmetric response. In the overall sample, the next most significant variable is Overhang; however, this variable is 11
Lag IPO is not available for 11 observations, dropping the total sample size from 4,523 to 4,512. Similarly, High20 and Low20 are not available for 90 of the observations in the 1991-1998 sample and 1 observation in the 1999-2000 sample, decreasing the sample sizes in these two periods. We excluded Lag IPO, High20, and Low20 from the regression model allowing the use of all 4,523 observations. Fraction remains negative and significant with this new regression specification in the full sample and in the three subperiods (p-values = 0.014, 0.003, 0.004, and 0.057, respectively. 12 The adjusted R2 remain essentially unchanged when we removed the year dummies from the regressions.
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not significant in the 1981-1990 period. The variable Secondary, which is the dummy variable indicating whether secondary shares are offered in the IPO, is negative and significant in the overall sample, but it is insignificant in every subsample. Examination of the Carter-Manaster (1990) ranks reveals a pattern that has attracted comment in numerous recent studies. In the 1981-1990 sample, the evidence is consistent with the notion that high prestige banks are associated with lower underpricing. However, in the 1991-1998 and 1999-2000 periods, the pattern reverses. For the offer price range dummies, offers in the mid-price range are less underpriced than those in the low-price range in the overall sample and in the 1991-1998 sample. On the other hand, High Price is insignificant in all four regressions indicating that high-priced offerings are just as underpriced as low-priced offerings. The cumulative return on the overall market in the period preceding the IPO is significantly positive in the overall sample and in the 1981-1990 and 1991-1998 periods, but not the bubble years. Recent underpricing in the IPO market is positively related to underpricing the overall sample and all three subperiods. Offer size is negative and significant overall and in the 1991-1998 period. High-tech orientation is positive and significant in the 1981-1990 period, but not in the other samples, whereas VC backing has an inconsistent effect. Dual class capital structure is consistently negative, but not significant. Aftermarket volatility is positive and significantly related to the initial return in the overall sample and in the 1981-1990 and 1991-1998 periods. Whether a firm trades on the NYSE or AMEX appears to be unrelated to the initial return. High20 is positive and significant in the 1991-1998 sample. The coefficient is economically large, 0.077, suggesting that these issues are severely underpriced. Low20 is insignificant in the 1991-1998 period and both variables are insignificant in the 19992000 period.
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The fact that several of the variables we consider seem to have inconsistent effects is consistent with Ritter and Welch’s (2002) observation that many IPO phenomena are not stationary. In fact, examination of the regression results shows that only three variables have consistent effects across all three of the sub-periods: the focus of our study (Fraction), the partial adjustment phenomenon (Above, Below), and recent underpricing in the IPO market (Lag IPO). Thus, for the two decades covered by our sample, there is relatively strong and consistent evidence that fractional offerings are less underpriced, even after allowing for a wide variety of both stationary and non-stationary effects. In the next section, we explore a possible explanation for this finding. 3. The Negotiation Hypothesis In this section, we discuss a possible explanation for our results based on the costly negotiation hypothesis of Harris (1991). In Harris’ model, buyers and sellers negotiate from a set of rounded stock prices (e.g., $15, $15.25, $15.50), rather than more precise prices (e.g., $15, $15.125, $15.25, $15.375, $15.50), to reduce the time needed to settle on a transaction price. Further, Harris argues that the use of a set of rounded or precise prices depends on two factors: the level of the stock price and the uncertainty about stock prices. More precise prices (e.g., oneeighth of a dollar, per Harris’ definition) are a larger fraction of a lower-priced stock’s value relative to a higher-priced stock. Thus, the inclusion of more precise prices in the set of possible transaction prices should be decreasing in stock price. Lower uncertainty should also cause buyers and sellers to use more precise prices in their negotiation set. That is, if both buyers and sellers have a precise estimate of the stock’s value, the likelihood that they will both agree to transact on a rounded price is diminished. To increase the chance that they will find an agreeable transaction price, they will use a finer set of prices to negotiate from. Negotiation from a coarse (fine) set of prices will naturally result in a coarse 14
(fine) set of transaction prices. So, Harris predicts that the percentage of rounded transaction prices will be a positive function of stock price and stock price uncertainty.13 With IPOs, the final offer price is the result of negotiations between representatives of the issuing firm and the lead underwriter. The issuing firm and underwriter typically agree on the IPO’s final offer price less than one day before the IPO date. After several weeks (or months) spent on road shows assessing investor demand, it is likely that both parties enter this pricing meeting with an estimate of the stock’s value and also an assessment of the of uncertainty about the stock’s value. Similar to Harris’ model, we predict that the likelihood that the issuing firm and underwriter will negotiate from a coarse or fine set of prices depends on their beliefs regarding the price level and degree of uncertainty about that level. For example, say both parties enter the pricing meeting knowing that the stock value is close to $10 a share, and, for this level of uncertainty, only a small discount is needed in the offer price (e.g., 10 - 15 percent below the estimated stock value). With a precise estimate of value, they may (implicitly) agree to negotiate from a fine set of prices (perhaps $9.00, $8.75, or $8.50), rather than from a more coarse set. Holding uncertainty constant, a higher stock price should result in the use of a coarser negotiation set. For example, if the stock value is close to $20, the issuing firm and the underwriter may negotiate from $18, $17.50, or $17. Negotiating from a set with mostly rounded prices should result in more rounded offer prices. Thus, the frequency of rounded (i.e., whole dollar) offer prices should be increasing in offer price.
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Following Harris (1991), several additional papers have documented price clustering on the U.S. stock markets. Christie and Schultz (1994) observe a high percentage of even-eighth quotes for some Nasdaq stocks, but not for others. They attribute the high frequency of rounded quotes as evidence of implicit collusion. However, collusion can’t explain the general tendency of prices to gravitate to rounded numbers. Bessembinder (1999) and Chung, Van Ness, and Van Ness (2001) find price clustering for quotes on the Nasdaq and NYSE after the Nasdaq price collusion lawsuit. Cooney, Van Ness, and Van Ness (2001) document clustering on even-eighth prices among investor limit orders. Kandel, Sarig, and Wohl (2001) show that investor bids for Israeli IPOs tend to be on rounded numbers.
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Holding price constant, higher uncertainty should cause two effects to occur. According to Harris’ negotiation hypothesis, greater uncertainty should give rise to a coarser (i.e., more rounded) set of possible offer prices (e.g., $18, $17, $16). In addition, greater uncertainty should increase the extent of underpricing as the investment bank seeks to manage its underwriting risk. Therefore, the negotiation hypothesis predicts that the extent of whole dollar offer prices is increasing in offer price and uncertainty. With greater uncertainty, whole dollar offer prices should have more underpricing. A different, but related argument is made by Mola and Loughran (2002) to explain whole dollar offer price clustering for US seasoned equity offerings (SEOs). The authors suggest that price clustering in the SEO market implies a standard pricing convention. They argue that, under uncertainty, integer offer prices represent “an expected and customary option in a continuum of possible alternatives.” In fact, they relate their findings to common standardized practices in the IPO market such as a 7 percent gross spread found by Chen and Ritter (2000) and 180-day lockup restriction documented by Bradley, Jordan, Roten, and Yi (2001) and Field and Hanka (2001). Although the two effects – integer price clustering on the IPO and SEO markets are obviously related, the role of uncertainty should play a larger part in the pricing of IPOs than SEOs. 3.1 Univariate tests of the negotiation hypothesis As an initial test of the negotiation hypothesis, we calculate the percentage of whole dollar offer prices for subsamples sorted on offer price and uncertainty and present the results in Table 3. As before, we define low-priced offerings as those priced between $5 and $9.99, mediumpriced offerings are priced between $10 and $14.99, and high-priced offerings are priced at $15 and above. *** Insert Table 3 about here *** 16
Consistent with the negotiation hypothesis, the percentage of integer prices is lowest for lowpriced offerings (950 out of 1,438 offerings, or 66.1 percent). The percentage increases with offer price. For medium-priced offerings, 1,468 of 1,908 (76.9 percent) are whole dollar offerings. For high-priced offerings, 1,018 of 1,177 (86.5 percent) are whole dollar offerings. We proxy for uncertainty in two ways. First, we measure the cross-sectional standard deviation of initial returns for samples of whole dollar and fractional IPOs. For low-priced offerings, the cross-sectional standard deviation of initial returns is 30.5 percent for whole dollar offerings. For medium- and high-priced offerings, the cross-sectional standard deviation of initial returns for whole dollar offerings increases to 33.0 percent and 75.3 percent, respectively. For fractional offerings, the cross-sectional standard deviation of initial returns remains fairly constant across the three offer-price zones: 15.4 percent, 12.1 percent, and 12.8 percent, respectively. This suggests that whole dollar IPOs have greater uncertainty than fractional IPOs, and the difference in uncertainty between whole dollar and fractional IPOs increases in offer price. (Standard deviations across all three price levels are significantly different at the 0.01 percent level.) Our second proxy for uncertainty is the ex-post standard deviation of daily stock returns for the three-month period following the IPO (i.e., the variable Volatility). Consistent with our first measure, the mean Volatility is significantly higher for whole dollar IPOs than for fractional IPOs, and the differences increase in offer price. For whole dollar IPOs, the mean Volatility is 4.5 percent, 4.3 percent, and 4.7 percent, for low-, medium-, and high-priced IPOs, respectively. For fractional IPOs, the mean Volatility for the three offer price zones is 3.8 percent, 3.1 percent, and 2.7 percent, respectively. (All means are statistically different at the 0.01 percent level.)
17
In summary, the proportion of whole dollar IPOs increases in offer price. In addition, the uncertainty for the whole dollar sample is significantly higher than for the fractional sample, and the difference in uncertainty between the two samples increases with offer price. 3.2 Logistic regression results In this section we turn to a logistic regression to test the negotiation hypothesis. The dependent variable, Integer, is binary, taking on a value of one if the offer price is on the integer, zero if on the fraction. (Integer is the negative of the variable Fraction from Table 2.) Based on our previous discussion, the independent variables of interest are dummy variables for mediumand high-priced offerings (Medium Price and High Price) and our ex-post measure of uncertainty (Volatility). According to the negotiation hypothesis, Integer should be positively related to Medium Price, High Price, and Volatility. As control variables, we include the underwriter dummy variables for the Carter-Manaster (1990) rank of the lead underwriter (CM9, CM8, CM67), the partial-adjustment variables (Above, Within, and Below), the log of the CPIadjusted total proceeds of the offering (Log Size), and year of offering dummies (not reported in the tables). The Carter-Manaster (1990) rank and Log Size may serve as proxies for the bargaining power of the underwriter and issuing firm. We include the partial-adjustment variables to account for the possibility that bargaining power of the two parties might vary depending on whether the offer price has been revised up or down. Logistic regression results are presented in Table 4. As with the previous set of regressions, we present results for the full sample (regression one) and separately for the 1981-1990, 19911998, and 1999-2000 subperiods (regressions two, three, and four, respectively). As predicted by the negotiation hypothesis, there is a positive relation between the frequency of integer pricing and Medium Price and High Price. Thus, in comparison to lower-priced offerings, those offerings priced in the $10 - $14.99 or $15 and above range have more whole dollar prices. Also 18
consistent with the negotiation hypothesis, a positive relation is observed between the frequency of integer pricing and Volatility—IPOs with more risk have more whole dollar prices. Analysis by period shows similar results to those presented for the entire sample period. Medium Price, High Price, and Volatility remain positive and significant (at the 5 percent level, or better) in all three periods. No consistent pattern is observed with the control variables.14 Overall, the logistic regressions provide support for the negotiations hypothesis—the likelihood of an integer price increases when price and uncertainty are high. Further, to the extent that underpricing is related to the uncertainty of the offering’s value, then the greater degree of underpricing for whole dollar IPOs is consistent with their higher level of uncertainty. 4. Conclusion We empirically examine the pricing structure of a large sample of 4,523 U.S. IPOs from 1981-2000. We find that 76 percent of U.S. IPOs are priced on integers (whole dollars). Even more interesting is our finding that the initial return for whole dollar IPOs is 25.5 percent versus 8.1 percent for non-integer offerings, a difference that is not only economically large, but also statistically significant at any conventional level. Our results are robust after conditioning for determinants typically used to model IPO initial returns. Our results also hold regardless of the period we study. For example, this effect persists in the 1980s, 1990s, and during the “internet bubble period” of 1999 and 2000. The evidence strongly suggests that the offer price, particularly whether or not it is an integer or non-integer final price, conveys valuable information to market participants.
14
As a robustness check, we include Overhang, Secondary, Lag Market, Lag IPO, Venture, Tech, Multiple Class, and NYSE/AMEX in our four logistic regressions (and also High20 and Low20 in the logistic regressions covering the 1991-1998 and 1999-2000 sample periods). Medium Price, High Price, and Volatility remain positive and significant (at the 0.01 percent level) in the full sample. Although the level of significance drops in the three subperiods, Medium Price, High Price, and Volatility remain positive with the largest p-value equal to 13.2 percent (Volatility, 1999-2000 period).
19
The explanation for our findings revolves around the negotiations that take place between the issuing firm and underwriter in determining the final offer price. The negotiations hypothesis predicts more integer prices for high-priced IPOs and IPOs with a high degree of uncertainty. At the same time, with higher uncertainty, whole dollar offerings should have greater underpricing. Logistic regression results support this hypothesis.
20
References Barry, C., Muscarella, C., Peavy III, J., Vetsuypens, M.R., 1990. The role of venture capital in the creation of public companies. Journal of Financial Economics 27, 447-471. Bessembinder, H., 1999, Trade Execution Costs on Nasdaq and the NYSE: A Post-Reform Comparison, Journal of Financial and Quantitative Analysis, Vol. 34, No. 3, pp. 387-407. Bradley, D., Jordan, B, Roten, I., Yi, H., 2001. Venture capital and IPO lockup expiration: An empirical analysis. Journal of Financial Research 24, 465-493. Bradley, D., Jordan, B, 2001. Partial adjustment to public information and IPO underpricing. Forthcoming, Journal of Financial and Quantitative Analysis. Carter, R., Manaster, S., 1990. Initial public offerings and underwriter reputation. Journal of Finance 45, 1045-1067. Carter, R., Dark, F., Singh, A., 1998. Underwriter reputation, initial returns, and the long-run performance of IPO stocks. Journal of Finance 53, 285-311. Chen, H., Ritter, J., 2000. The seven percent solution. Journal of Finance 55, 1105-1131. Christie, W., Schultz, P., 1994, Nasdaq market makers and avoidance of odd-eighth quotes, The Journal of Finance 49, 1813-1840. Chung, K., Van Ness, B., Van Ness, R., 2001, Are Nasdaq stocks more costly to trade than NYSE stocks? Evidence after decimalization, State University of New York – Buffalo and Kansas State University working paper. Cooney, J., Van Ness B., Van Ness R., 2001, Do investors prefer even-eighth prices? Evidence from NYSE limit orders. Forthcoming, The Journal of Banking and Finance. Corwin, S., 2001. The pricing of seasoned equity offerings on the NYSE and Nasdaq. University of Notre Dame working paper. Fernando, C., Krishnamurthy, S., Spindt, P., 2000. Is the offer price in IPOs informative? Underpricing, ownership structure and performance. Tulane University and SUNYBinghamton working paper. Field, L., Hanka, G., 2001. The expiration of IPO share lockups. Journal of Finance 56, 471500. Habib, M., Ljungqvist, A., 2001. Underpricing and entrepreneurial wealth losses in IPOs: Theory and evidence. Review of Financial Studies 14, 433-458. Hamao, Y., Packer, F., Ritter, J., 2000. Institutional affiliation and the role of venture capital: Evidence from initial public offerings in Japan. Pacific-Basin Finance Journal 8, 529-558. 21
Hanley, K., 1993. The underwriting of initial public offerings and the partial adjustment phenomenon. Journal of Financial Economics 34, 231-250. Harris, L, 1991. Stock price clustering and discreteness. The Review of Financial Studies 4, 389415. Kandel, S., Sarig, O., and Wohl, A., 2001. Do investors prefer round stock prices? Evidence from Israeli IPO auctions. Journal of Banking and Finance 25, 1543-1551. Loughran, T., Ritter, J., 2001. Why has IPO underpricing increased over time? University of Notre Dame and University of Florida working paper. Lowry, M., Schwert, W., 2001. IPO market cycles: Bubbles or sequential learning? Forthcoming, Journal of Finance. Megginson, W., Weiss, K., 1991. Venture capitalist certification in initial public offerings. Journal of Finance 46, 29-48. Mola, S., Loughran, T., 2002. Discounting and clustering in the offer price of SEOs, 1991-1999. Bocconi University of Milan and University of Notre Dame working paper. Ritter, J., Welch, I., 2002. A review of IPO activity, pricing, and allocations. Forthcoming, The Journal of Finance. Smart, S., Zutter, C., 2000. Control as a motivation for underpricing: A comparison of dual- and single-class IPOs. Indiana University working paper
22
Table 1. Descriptive statistics: Integer versus non-integer IPOs This table presents descriptive statistics for the integer and non-integer samples for the following variables: 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.
13.
14.
Initial return is the percentage difference from the offer price to the stock price on the first day of trading less the contemporaneous CRSP value-weighted index return. Offer Price is the offer price of the IPO. Partial is the percentage difference from the offer price relative to the midpoint of the original file range. CM-Rank is the Carter and Manaster (1990) and Carter, Dark, and Singh (1998) underwriter ranking, as updated by Loughran and Ritter (2001), (0 = low ranking, 9 = high ranking). Overhang is measured as shares retained by existing stockholders divided by shares sold in the IPO. Secondary is a dummy variable that takes on a value of one if the IPO includes shares sold by existing stockholders, zero otherwise. Lag market is the compounded market return for the 21 trading days (i.e., one month) prior to the IPO date using the CRSP value-weighted index as a proxy for the market. Lag IPO is the average market-adjusted IPO initial return for all sample IPOs for the month prior to the IPO date. Offer size is the CPI-adjusted, 1982-1984 = 100, total proceeds to the firm in millions (excluding proceeds from the exercise of the over-allotment option). Venture is a dummy variable that takes on a value of one if the IPO firm is venture capital-backed, zero otherwise. Tech is a dummy variable that takes on a value of one if the IPO firm is in a high-tech industry, zero otherwise. Multiple class is a dummy variable that takes on a value of one if the IPO is of classified stock (e.g., class A common), or if SDC otherwise indicates that the stock being issued has inferior voting rights, zero otherwise. Volatility is the standard deviation of the market-adjusted daily stock returns for the 62-day period from the close of the second day of trading to the 64th day of trading (i.e., a three-month period). The CRSP valueweighted index return is used as a proxy for the market return. NYSE/AMEX is a dummy variable that takes on a value of one if the IPO firm is listed on the NYSE or AMEX after the IPO, zero otherwise.
The p-values are for a t-test of difference in means. IPO data are collected from the Securities Data Company (SDC) U.S. Common Stock Initial Public Offerings database and from CRSP for 4,523 offerings from January 1, 1981 to December 31, 2000. Integer Variable Initial return Offer price Partial CM-Rank Overhang Secondary Lag Market Lag IPO Offer Size Venture Tech Multiple Class Volatility NYSE/AMEX
N 3,436 3,436 3,436 3,436 3,436 3,436 3,436 3,427 3,436 3,436 3,436 3,436 3,436 3,436
Non-Integer Mean 25.5% $12.37 2.5% 7.3 3.5 39.6% 1.4% 25.6% $33.61 47.7% 44.3% 4.8% 4.5% 9.3%
N 1,087 1,087 1,087 1,087 1,087 1,087 1,087 1,085 1,087 1,087 1,087 1,087 1,087 1,087
Mean 8.1% $11.07 -4.3% 6.9 2.5 43.4% 1.7% 13.7% $27.05 29.5% 27.1% 5.6% 3.3% 11.1%
p-value 0.0001 0.0001 0.0001 0.0001 0.0001 0.0235 0.0720 0.0001 0.0178 0.0001 0.0001 0.3223 0.0001 0.0810
23
Table 2. OLS regression results This table presents OLS regression results. The dependent variable is the initial return defined as the return calculated from the offer price to the stock price on the first day of trading less the contemporaneous CRSP value-weighted index return. The independent variables are: 1. Fraction is a dummy variable that takes on a value of one if the offer price is not on the integer, zero otherwise. 2. Medium price is a dummy variable that takes on a value of one if the offer price is between $10 and $14.99, zero otherwise. 3. High price is a dummy variable that takes on a value of one if the offer price is $15 or above, zero otherwise. 4. Above is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is greater than the original high file price, zero otherwise. 5. Within is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is within the original filing range, zero otherwise. 6. Below is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is less than the original low file price, zero otherwise. 7. CM9, CM8, CM67 are dummy variables that take on the value of one if the Carter and Manaster (1990) and Carter, Dark, and Singh (1998) ranking, as updated by Loughran and Ritter (2001), is equal to 9, between 8 and 8.9, or between 6 and 7.9, respectively, zero otherwise. 8. Overhang is measured as shares retained by existing stockholders divided by shares sold in the IPO. 9. Secondary is a dummy variable that takes on a value of one if the IPO includes shares sold by existing stockholders, zero otherwise. 10. Lag market is the cumulative market return for the 21 trading days (i.e., one month) prior to the IPO date using the CRSP value-weighted index as a proxy for the market. 11. Lag IPO is the average market-adjusted IPO initial return for all sample IPOs for the month prior to the IPO date. 12. Log size is the natural log of the CPI-adjusted, 1982-1984 = 100, total proceeds to the firm in millions (excluding proceeds from the exercise of the over-allotment option). 13. Venture is a dummy variable that takes on a value of one if the IPO firm is venture capitalbacked, zero otherwise. 14. Tech is a dummy variable that takes on a value of one if the IPO firm is in a high-tech industry, zero otherwise. 15. Multiple class is a dummy variable that takes on a value of one if the IPO is of classified stock (e.g., class A common), or if SDC otherwise indicates that the stock being issued has inferior voting rights, zero otherwise. 15. Volatility is the standard deviation of the market-adjusted daily stock returns for the 62-day period from the close of the second day of trading to the 64th day of trading (i.e., a three-month period). The CRSP value-weighted index return is used as a proxy for the market return. 16. NYSE/AMEX is a dummy variable that takes on a value of one if the IPO firm is listed on the NYSE or AMEX after the IPO, zero otherwise. 17. High20 (Low20) is a dummy variable equal to one if the offer price is 20 percent above (below) the amended file range, zero otherwise. Year of offering dummy variables are included, but not reported. p-values are in parentheses. Statistical significance at the 10, 5, and 1 percent levels is indicated with *, **, and ***, respectively. IPO data are collected from the Securities Data Company (SDC) U.S. Common Stock Initial Public Offerings database and from CRSP for 4,523 offerings from January 1, 1981 to December 31, 2000.
24
Table 2 – Continued
Intercept Fraction Medium Price High Price Above Within Below CM67 CM8 CM9 Overhang Secondary Lag Market Lag IPO Log size Venture Tech Multiple class Volatility NYSE/AMEX
Full Sample Coefficient (p-value)
1981-1990 Coefficient (p-value)
1991-1998 Coefficient (p-value)
1999-2000 Coefficient (p-value)
0.0012 (0.9761) -0.0298** (0.0144) -0.0471*** (0.0014) 0.0014 (0.9475) 1.1358*** (0.0001) 0.5624*** (0.0001) 0.3168*** (0.0001) 0.0196 (0.2486) 0.0035 (0.8412) 0.0715*** (0.0004) 0.0104*** (0.0001) -0.0359*** (0.0009) 0.5411*** (0.0002) 0.1910*** (0.0001) -0.0160* (0.0925) 0.0045 (0.6985) 0.0109 (0.3529) -0.0292 (0.2077) 2.6422*** (0.0001) -0.0239 (0.1994)
0.0810*** (0.0001) -0.0211*** (0.0028) -0.0126 (0.1549) -0.0137 (0.3225) 0.6827*** (0.0001) 0.4722*** (0.0001) 0.2135*** (0.0001) -0.0296*** (0.0035) -0.0496*** (0.0001) -0.0457*** (0.0006) 0.0004 (0.7936) -0.0066 (0.3504) 0.4108*** (0.0001) 0.1538*** (0.0072) -0.0085 (0.1603) -0.0098 (0.2281) 0.0181** (0.0396) -0.0109 (0.5185) 0.8943*** (0.0019) 0.0107 (0.3827)
0.0146 (0.6456) -0.0310*** (0.0068) -0.0300** (0.0432) 0.0019 (0.9269) 0.6153*** (0.0001) 0.6725*** (0.0001) 0.2804*** (0.0001) 0.0217 (0.1942) 0.0335** (0.0495) 0.0747*** (0.0002) 0.0049*** (0.0001) -0.0052 (0.6016) 0.7992*** (0.0001) 0.2457*** (0.0001) -0.0239** (0.0136) -0.0281*** (0.0099) 0.0119 (0.2747) -0.0054 (0.7955) 2.6865*** (0.0001) -0.0128 (0.4531) 0.0773** (0.0112) -0.0270 (0.2147)
-0.1398 (0.3986) -0.2176** (0.0474) -0.1457 (0.1059) 0.0843 (0.4313) 1.2092*** (0.0001) 0.4390 (0.4486) 0.4934* (0.0788) 0.0751 (0.5290) 0.0567 (0.6225) 0.1832 (0.1101) 0.0267*** (0.0001) -0.0346 (0.6319) 0.6237 (0.2686) 0.1638* (0.0639) 0.0100 (0.8259) 0.1445** (0.0180) 0.0909 (0.1011) -0.1696 (0.1636) 1.4228 (0.1842) -0.0791 (0.5139) 0.0456 (0.6425) -0.0559 (0.6927)
4,512 0.487
1,396 0.294
2,305 0.300
720 0.484
High20 Low20
Observations Adjusted R2
25
Table 3: The frequency of integer offerings, standard deviations of initial returns and aftermarket returns, by offer price This table presents the frequency of integer offerings (Panel A), the cross-sectional standard deviation of initial returns (Panel B), and Volatility (Panel C) for low-, medium, and high-priced IPOs. Initial return is the percentage difference between the offer price and the closing stock price on the first day of trading less the contemporaneous CRSP value weighted index return. Volatility is the standard deviation of the market-adjusted daily stock returns for period from the close of the second day of trading to the 64th day of trading (i.e., a three-month period). The CRSP value weighted index return is used as a proxy for the market return. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for 4,523 offerings from January 1, 1981 to December 31, 2000. Panel A: The frequency of integer and non-integer offerings Low price Medium price ($5 – $9.99) ($10 – $14.99) Integer 950 1,468 Non-integer 488 440 Percent integer 66.1% 76.9%
High price ($15 and above) 1,018 159 86.5%
Panel B: Standard deviation of initial returns Low price ($5 – $9.99) Integer 30.5% Non-integer 15.4% Difference 15.1%
Medium price ($10 – $14.99) 33.0% 12.1% 20.9%
High price ($15 and above) 75.3% 12.8% 62.5%
0.0001
0.0001
0.0001
Low price ($5 – $9.99) 4.5% 3.8% 0.7%
Medium price ($10 – $14.99) 4.3% 3.1% 1.2%
High price ($15 and above) 4.7% 2.7% 1.9%
0.0001
0.0001
0.0001
p-value of a test of equality of standard deviations
Panel C: Volatility
Integer Non-integer Difference p-value for a t-test of the difference in means
26
Table 4. Logistic regression results: Tests of the negotiation hypothesis This table presents logistic regression results. The dependent variable is binary, taking a value of one if the IPO is priced on the integer, zero otherwise. The independent variables are: 1. 2. 3.
4. 5. 6. 7. 8.
Medium price is a dummy variable that takes on a value of one if the offer price is between $10 and $14.99, zero otherwise. High price is a dummy variable that takes on a value of one if the offer price is $15 or above, zero otherwise. Volatility is the standard deviation of the market-adjusted daily stock returns for period from the close of the second day of trading to the 64th day of trading (i.e., a three-month period). The CRSP value weighted index return is used as a proxy for the market return. CM9, CM8, CM67 are dummy variables that take on the value of one if the Carter and Manaster (1990) ranking, as updated by Loughran and Ritter (2001), is equal to 9 or higher, between 8 and 8.9, or between 6 and 7.9, respectively, zero otherwise. Above is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is greater than the original high file price, zero otherwise. Within is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is within the original filing range, zero otherwise. Below is equal to the percent difference between the offer price and the midpoint of the original filing range if the offer price is less than the original low file price, zero otherwise. Log size is the natural log of the CPI adjusted, 1982-1984 = 100, total proceeds to the firm in millions (excluding proceeds from the exercise of the over-allotment option).
Each regression includes year of offering dummy variables (not reported). Statistical significance at the 10, 5, and 1 percent levels is indicated with a *, **, and ***, respectively. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for 4,523 offerings from January 1, 1981 to December 31, 2000.
Variable
Full sample
1981-1990
1991-1998
1999-2000
Intercept
-0.1588 (0.5536) 0.7740*** (0.0001) 1.4316*** (0.0001) 16.2918*** (0.0001) 0.0053 (0.9643) 0.1969 (0.1105) -0.0268 (0.8585) 1.3746*** (0.0018) 0.5919 (0.4049) -1.5469*** (0.0001) -0.2314*** (0.0006)
0.2522 (0.4611) 0.7886*** (0.0001) 1.7436*** (0.0001) 14.1056*** (0.0071) -0.3657** (0.0376) -0.1492 (0.4283) -0.3638 (0.1220) 0.5340 (0.5652) 0.1590 (0.8764) -2.7696*** (0.0001) -0.3414*** (0.0009)
0.2927 (0.3811) 0.6180*** (0.0001) 1.2052*** (0.0001) 12.9365*** (0.0012) 0.2332 (0.1647) 0.4052** (0.0192) 0.1156 (0.5836) 1.3735** (0.0164) 0.1982 (0.8512) -0.7800 (0.1104) -0.1716* (0.0888)
-0.0374 (0.9627) 1.6895*** (0.0008) 1.3210** (0.0414) 26.3554*** (0.0010) 0.6239 (0.3368) 0.7408 (0.2316) 0.6859 (0.2550) 2.6006* (0.0599) 4.5691 (0.2042) -0.8262 (0.5704) -0.2907 (0.2058)
4523 0.0001
1402 0.0001
2397 0.0001
724 0.0001
Medium Price High Price Volatility CM67 CM8 CM9 Above Within Below Log size
N p-value of likelihood ratio
27
Figure 1. Initial returns by year: Integer versus non-integer This figure plots average initial returns by year for 4,523 IPOs priced on the integer and non-integer. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for offerings from January 1, 1981 to December 31, 2000.
90.00% 80.00%
60.00% 50.00% 40.00% 30.00% 20.00% 10.00%
99
98
97
96
95
94
93
92
00 20
19
19
19
19
19
19
19
91
19
89
90
19
19
87
86
85
84
83
82
88
19
19
19
19
19
19
19
19
81
0.00% 19
Initial return
70.00%
Year Integer
Non-integer
28
Figure 2A. Initial returns by offer price: Integer versus non-integer This figure plots average initial returns by offer price for 4,523 IPOs priced on the integer and noninteger. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for offerings from January 1, 1981 to December 31, 2000.
60.00%
Initial return
50.00% 40.00% 30.00% 20.00% 10.00% 0.00% $5 - $9.99
$10 - $14.99
$15 -
Offer price Integer
Non-integer
29
Figure 2B. Initial returns by filing range midpoint: Integer versus non-integer This figure plots average initial returns by the midpoint of the original filing range for 4,523 IPOs priced on the integer and non-integer. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for offerings from January 1, 1981 to December 31, 2000.
60.00% 50.00%
Initial Return
40.00% 30.00% 20.00% 10.00% 0.00% $0 - $9.99
$10 - $14.99
$15 -
Midpoint of Filing Range Integer
Non-Integer
30
Figure 3. Initial returns by filing range: Integer versus non-integer This figure plots average initial returns for 4,523 IPOs priced on the integer and non-integer IPOs by whether the offering is priced below, within, or above the original filing range. IPO data are collected from the Securities Data Company U.S. Common Stock Initial Public Offerings database and from CRSP for offerings from January 1, 1981 to December 31, 2000.
70.00%
60.00%
Initial Return
50.00%
40.00%
30.00%
20.00%
10.00%
0.00% Below
Within
Above
Filing Range Zone Integer
Non-Integer
31
