IPO Underpricing and Underwriter Reputation
Student Sabine Wagenaar
Number 5603978
Programme Economie & Bedrijfskunde Track Financiering & Organisatie Supervisor Dr. P.J.P.M. Versijp
Date 2 February 2016
Abstract
This paper investigates the effect of underwriter reputation on initial returns of IPOs. IPOs with a value of at least $100.000.000 are selected on the New York Stock Exchange (NYSE), American Stock Exchange (AMEX) and NASDAQ between January 1st 2005 and December 31st 2014. Results show that, contradicting previous research by Beatty and Ritter (1986), Johnson and Miller (1988), Carter and Manaster (1990) and Carter et al. (1998), underwriter reputation has an insignificant positive effect on initial returns.
Verklaring eigen werk
Hierbij verklaar ik, Sabine Wagenaar, dat ik deze scriptie zelf geschreven heb en dat ik de volledige verantwoordelijkheid op me neem voor de inhoud ervan.
Ik bevestig dat de tekst en het werk dat in deze scriptie gepresenteerd wordt origineel is en dat ik geen gebruik heb gemaakt van andere bronnen dan die welke in de tekst en in de referenties worden genoemd.
De Faculteit Economie en Bedrijfskunde is alleen verantwoordelijk voor de begeleiding tot het inleveren van de scriptie, niet voor de inhoud.
Table of contents 1. Introduction………....2 2. Literature review……….…...4 2.1 IPOs……….….4 2.2 Underpricing……….……4 2.3 Underwriting process………...5
2.4 Underwriter reputation measures……….7
2.4.1 Carter-Manaster………..…...7
2.4.2 Johnson-Miller………....…..………7
2.4.3 Megginson-Weiss………..…7
2.5 Underwriter reputation……….8
3. Data and Methodology………...9
3.1 Data………..9
3.2 Methodology………..………11
4. Results………..………13
5. Conclusion and Discussion………...18
1. Introduction
An initial public offering (IPO) occurs when a company issues common stock to the public for the first time. Initial public offerings are often issued by companies seeking capital to expand or looking to become publicly traded. If the value of the new issue turns out to be greater than the offer price set by the underwriter, the investor who purchases the offering earns the profit (Ibbotson 1975). This means the IPO is underpriced and the issuer ‘leaves money on the table’. Several studies show that initial public offerings are on average underpriced. Among these studies are Ibbotson (1975), Ritter (1984), Brau and Fawcett (2006) and Lowry et al. (2010).
Because underpricing is an opportunity cost to the issuing firm, as part of the value of the firm is earned by the investors, risk-averse firms choose investment banks with a good reputation as underwriters. This way they reveal their low risk character to the market and thereby reduce underpricing (Carter and Manaster, 1990).
Several studies confirm this relation between underwriter reputation and underpricing. Beatty and Ritter (1986) find that higher ranked underwriters underprice less in the short-run. Johnson and Miller (1988) also find that underwriter prestige is negatively related to short-run underpricing. Carter and Manaster (1990) find a negative relation between underwriter reputation and short-run underpricing as well. Carter et al. (1998) find that a better underwriter reputation causes less short-run underpricing.
This paper investigates the effect of underwriter reputation on initial returns of more recent IPOs. Initial returns are used to express the level of underpricing. For ranking the underwriting firms, an adjusted Carter and Manaster ranking is used. This is the same ranking Loughran and Ritter (2004) use in their research. Following existing literature, underwriter reputation is expected to have a negative effect on initial returns, as well as on underpricing, of IPOs.
To examine the explanatory power of underwriter reputation on the level of underpricing, an ordinary least squares regression model is used. Data is used of IPOs on the New York Stock Exchange (NYSE), American Stock Exchange (AMEX) and NASDAQ between January 1st 2005 and December 31st 2014 with a value of at least $100.000.000. The final data sample consists of 619 IPOs.
Results show no significant effect of underwriter reputation on initial returns. A positive relation between underwriter reputation and initial returns is found, but not significant. This is not what was expected from previous literature.
The structure of this paper is as follows. In chapter two, previous literature on IPOs, underpricing, the underwriting process and underwriter ranking is reviewed. Chapter 3 explains the data sample and methodology used in this research. In chapter 4, the results are presented, analyzed and compared to previous research. Chapter 5 contains a conclusion and discussion.
2. Literature review
This section reviews the most important literature on IPOs, underpricing in IPOs, the underwriting process and underwriter reputation.
2.1 IPOs
An initial public offering (IPO) occurs when a company issues common stock to the public for the first time. Initial public offerings are often issued by companies seeking capital to expand or looking to become publicly traded. In this public market, founders and other shareholders can convert some of their wealth into cash at a future date (Ritter and Welch, 2002). Other reasons for an IPO are lowering the cost of capital and the pecking order of financing. The creation of public shares for acquisitions is however identified by CFOs as the most important motivation for going public (Brau and Fawcett, 2006).
2.2 Underpricing
Several studies show that initial public offerings are on average underpriced. Among these studies are Ibbotson (1975), Ritter (1984), Brau and Fawcett (2006) and Lowry et al. (2010). Positive initial performance along with aftermarket efficiency indicates that new issue offerings are underpriced. Three groups of actors are involved in this process: the issuers, the underwriters and the investors. If the value of the new issue turns out greater than the offer price set by the underwriter, the investor who purchases the offering earns the profit (Ibbotson 1975). This means the issuer ‘leaves money on the table’.
In his paper, Ibbotson (1975) gives a few possible explanations for underpricing. First, regulations could require the underwriter to set the offer price below the expected trading value. Second, underpricing could be used to create a good name for the issuer and make future offerings easier to sell at attractive prices. A third explanation could be collusion between underwriters to exploit inexperienced issuers to favor investors. Fourth, underpricing could be a sign of risk that not all information is included. Underwriters must underprice to minimize these risks. Fifth, underpricing could be a tradition or arrangement between the issuer, investment bank and investors. Underpricing is in this case compensated by payments from investors
to underwriters to issuers. Lastly underpricing could be used as an insurance against legal suits.
One factor that could affect the level of short-run underpricing, and is of most interest in this paper, is the reputation of the underwriting firm. Underpricing is costly to the issuing firm because part of the value of the firm is earned by the investor instead of the issuer. Therefore, low risk firms attempt to reveal their low risk characteristic to the market by selecting underwriters with high prestige (Carter and Manaster, 1990). At the same time, underwriters have a reputation at stake on which it can earn a return. Whenever the underwriter cheats by underpricing too much or too little, it loses customers (Beatty and Ritter, 1986). This creates an incentive for the underwriter to not underprice for any of the previously discussed reasons.
Apart from underwriter reputation, several other characteristics of offerings are interesting when looking at underpricing, for example the size of the IPO. Larger IPOs are often done by bigger and more established firms because they are better able to handle larger equity offerings (Hayes, 1971). Therefore IPO size could have an effect on the level of underpricing. The age of the issuing firm is also interesting. Older firms are less risky, which should lead to smaller initial returns and less underpricing (Ritter, 1991). This is because it should be easier to determine the correct value of an older firm than of a young firm. The percentage of the firm’s shares offered to the public shows the percentage of the firm on offer. Aggarwal et al. (2001) find that higher ownership by managers leads to more underpricing. This would mean that a large part of the firm’s shares being on offer is a sign that not much underpricing is expected. Lastly classification as a technological firm is interesting to look at. Lougran and Ritter (2004) include this in their research because according to them it adds to the risk composition. As a result this would add to the level of underpricing.
2.3 Underwriting process
The formal process of going public starts by filing a registration statement with the Securities and Exchange Commission (SEC). Next is issuing a preliminary prospectus to detect the amount of interest from potential investors. When the SEC approves the offer, it is time to decide about the offer price and the number of shares to be sold. This is when the final prospectus is issued and at the same time the underwriter
guarantees the delivery of the proceeds to the issuing firm. The prospectus is circulated and the shares are sold to investors (Ritter, 1987).
In this process, the underwriter carries out a large number of tasks. First, it coordinates due diligence for the prospectus. Next, it advises the issuer on the design, size and timing of the offering. The underwriter also gives an advise about the price range for the shares. After that, it takes care of the marketing of the offering. This starts with a pre-marketing period in which analysts inform investors about the shares and ends in a roadshow where the underwriter collects bids form investors and forms a book of demand. This is also when the underwriter advises the issuer on the final offer price of the shares. In practice the issuer typically delegates the decision on allocations and on pricing to the underwriter. The underwriter then acts as a stabilizing manager for the shares in the aftermarket, meaning that it may buy shares if the price falls to or below the offer price. Remuneration for all these tasks comes in the form of commissions agreed in advance and paid as a proportion of issue proceeds (Jenkinson and Jones (2009).
When a company decides to go public the underwriting firm is the intermediary between the issuer and the investors (Ibbotson, 1975). In the process of an issuer and underwriter finding each other, they both look at each other’s qualities and abilities and eventually associate by mutual choice (Fernando et al., 2005). There is however a difference in selection criteria between firms with high-prestige underwriters and firms with low-prestige underwriters. CFOs in firms with high-prestige underwriters select underwriters based on reputation, quality, expertise, and institutional investor client base. By contrast, CFOs in firms that use low-prestige underwriters are more concerned with valuation promises, retail investor client base, and fee structures (Brau and Fawcett, 2006). This process, of selecting an investment bank to act as bookrunner for the transaction, typically takes place at least six months before the IPO (Jenkinson and Jones (2009).
It is clear that the underwriter plays an important part in the IPO. The underwriter is the one making decisions on among other things the offer price, which in the end determines what the initial return is. This is why selecting the right one for the offering is crucial. Several underwriter reputation measures have been developed in the past decades, which might help in deciding which underwriter to go for.
2.4 Underwriter reputation measures
In this section, several underwriter reputation measures will be discussed; first the Carter-Manaster measure, secondly the Johnson-Miller measure and lastly the Megginson-Weiss measure.
2.4.1 Carter-Manaster
One of the commonly used underwriter reputation measures is the Carter and Manaster ranking. Carter and Manaster (1990) measure underwriter prestige on a scale from zero to nine, with firms ranked nine being the most prestigious ones. This measure is based on hierarchy in the investment banking industry and underwriters defending their place in the highest bracket. Ranks are assigned to investment banks based on tombstone announcements. A tombstone announcement is a print notice of a pending public offering. Underwriters are placed in one of the ten brackets by comparing relative placement of underwriters in tombstone announcements (Carter and Manaster, 1990).
2.4.2 Johnson-Miller
Another well known underwriter reputation measure is the Johnson and Miller ranking. Johnson and Miller (1988) divide bankers over four different levels. The most prestigious bankers get a rank three which makes them part of the bulge bracket, underwriters with rank two are in the major bracket, rank one means the sub-major bracket and rank zero is for all other bankers with the least prestige. Ranks are assigned based on the role of underwriters in high-quality issues. A leading role places the underwriter in the bulge bracket and assigns him rank three.
2.4.3 Megginson-Weiss
A third measure is the Megginson-Weiss ranking. Megginson and Weiss (1991) measure the quality of underwriters as the percentage of the total dollar amount brought to the market and assume that the greater the average market share of the lead underwriters, the higher the quality. Only the lead manager of the IPO is assigned full credit for the total amount underwritten.
2.5 Underwriter reputation
Previously discussed underwriter reputation measures have been used in many researches. They were mostly used to investigate the effect of underwriter reputation on initial returns. Because the rankings indicate how much experience investment banks have in underwriting and how constant their performances are, this could give an insight in their future achievements. Therefore, this rank could have an effect on IPO underpricing resulting in an effect on initial returns. Previous research on the effect of underwriter reputation on initial returns is discussed below.
Beatty and Ritter (1986) find that underwriters with a higher reputation underprice less in the short-run. Their explanation is the fact that investment bankers have reputation capital at stake and therefore would not risk losing potential investors or potential issuers by underpricing too little or too much. In their research, they rank underwriting firms based on their absolute standardized average residuals.
Johnson and Miller (1988) also find that underwriter prestige is negatively related to short-run underpricing. However, after adjusting the initial returns for risk, they find no relationship at all. This would mean there is no need for both investors and issuers to differentiate between high and low prestige investment bankers. Johnson and Miller use two different underwriter reputation measures: Johnson and Miller and Carter and Manaster.
In line with previously discussed literature, Carter and Manaster (1990) find a negative relation between underwriter reputation and short-run underpricing as well. They explain this relation by the fact that prestigious underwriters only choose to market low dispersion firms’ IPOs to keep their high ranking. Carter and Manaster use their own underwriter reputation measure.
Carter et al. (1998) find that a better underwriter reputation causes less short-run underpricing. In their research, they use three different underwriter reputation measures: Johnson and Miller, Migginson-Weiss and Carter and Manaster. The Carter-Manaster measure is found to be the most significant, because when evaluated simultaneously with the other two measures, it remains significant.
3. Data and methodology
This section discusses data and methodology. Section 3.1 describes the data used in this research. In section 3.2 the chosen methodology is discussed and the model used for the regression is presented.
3.1. Data
In this research, data is used of IPOs on the New York Stock Exchange (NYSE), American Stock Exchange (AMEX) and NASDAQ between January 1st 2005 and December 31st 2014. This data was retrieved from the Zephyr database. Only offerings with a value of at least $100.000.000 were selected. A total of 1.163 IPOs match these criteria. After excluding offerings with incomplete data and offerings with extreme outliers, the final sample consists of 619 IPOs.
Figure I IPOs per Year
Figure I shows the distribution of IPOs over the selected years, 2005 through 2014. At the start of the financial crisis in the United States, in 2008, only eight firms within the selection criteria went public. During the following years, this number started increasing and reached 129 IPOs within the selection criteria in 2014.
0 20 40 60 80 100 120 140 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014
Data points of interest on the selected IPOs are initial returns, underwriter reputation, size, firm age, the percentage of shares offered and whether the firm is technological or not.
Initial returns are used to express the level of underpricing. Initial returns are computed as the percentage difference between the first-day closing price and the offer price at the IPO. The average underpricing in the selected sample is 16%.
Underwriter reputation is expressed in a ranking of underwriting investment banks. This reputation is determined for the lead investment bank underwriting the offering. For ranking the underwriting firms, an adjusted Carter and Manaster ranking is used. This is the same ranking Loughran and Ritter (2004) use in their research. The ranking is updated to the year 2014 and it is available on Jay Ritter’s website (2014). The Carter and Manaster (1990) ranking is used as a start, but Loughran and Ritter (2004) made several alternations and updated the ranking up to 2014. On a scale from 0 - 9, most prestigious underwriters are assigned the top ranking of 9. In the selected sample, the lowest assigned rank is 4 and the highest assigned rank is 9. The mean rank is 8.64.
IPO size is an interesting variable when looking at underpricing. The size of an IPO is measured as the gross proceeds of the offering. It is the amount of money the issuing firm brings in for offering its shares. The data sample starts with IPOs of $100.000.000 and the largest IPO has a value of $ 21.767.215.000 The average IPO size in the selected sample is $ 465.300.
Firm age, being the age of the issuing firm at the time of the offering, is determined as the interval between the offer date and the date the firm was founded. Additional data on founding dates, to supplement the data found in Zephyr, is retrieved from Jay Ritter’s (2014) website. For firms where the founding date was unavailable, the date of incorporation is used instead. The average age of the firms in the selected sample is 12.5 years.
The percentage of shares offered to the public shows the percentage of the firm on offer. In the selected sample, this percentage lies between 5.67 and 100. The average fraction of shares offered is 37%.
Whether the issuing firm qualifies as a technology firm or not is relevant. To identify IPOs of technology firms, the same criteria are used as Loughran and Ritter (2004). They define tech stocks by their SIC codes and include firms in computer
hardware, communications equipment, electronics, navigation equipment, measuring and controlling devices, medical instruments, telephone equipment, communications services and software. In the selected sample, 125 firms qualify as technology firms.
The descriptive statistics for all variables described above can be found in Table I.
Table I
Descriptive Statistics
Variable Mean Median Std. Dev. Min Max
Market-adjusted Initial Return (%) 16.06 6.36 0.27 -28.96 132.81
Underwriter Rank 8.64 9.00 0.81 4 9 Size ($ millions) 465.30 212.80 1423.41 100.00 21767.22 Age (years) 12.52 5.00 23.03 0 175 Tech dummy 0.20 0.00 0.40 0 1 Shares offered (%) 37.32 28.42 0.27 5.67 100 3.2. Methodology
To examine the explanatory power of underwriter reputation on the level of underpricing, an ordinary least squares regression model is used. The dependent variable in the regression analysis is the initial return, which determines the level of underpricing. The initial return for each IPO is regressed on the underwriter reputation (Underwriter Rank). Based on previous research by Beatty and Ritter (1986), Johnson and Miller (1988), Carter and Manaster (1990) and Carter et al. (1998), the coefficient is expected to be negative.
A number of additional independent variables are included in the model, selected based on previous research.
Most previous work includes natural logarithms of gross proceeds (LNSIZE). Larger IPOs are often done by bigger and more established firms because they are better able to handle larger equity offerings (Hayes, 1971). Initial returns of larger IPOs are thus expected to be smaller. This would result in a negative relation between the size of the IPO and the level of underpricing.
Firm age is included in the model as the natural logarithm of one plus the age of the firm at the IPO date (LNAGE). Older firms are less risky, what should lead to smaller initial returns and less underpricing. Ritter’s (1991) findings confirm this. He
finds higher initial returns for IPOs of younger firms. Therefore, a negative relation between the age of the firm and the level of underpricing is expected.
The percentage of the firm’s shares offered to the public (OFFERED) shows the percentage of the firm on offer. Aggarwal et al. (2001) find that higher ownership by managers is positively correlated with first-day underpricing. The other way around this would mean the higher the percentage of shares offered, the less underpricing they expect, so the smaller the expected initial returns.
The dummy variable for technology firms (TECH) is included based on literature as well. Lougran and Ritter (2004) include this variable because according to them it adds to the risk composition. Abrahamson et al. (2011) also find higher levels of underpricing for firms qualified as technology firms in both Europe and the United States. Value one is assigned to technology firms and value zero to non-technology firms. Because qualifying as a non-technology firm adds to the risk, initial returns are expected to be bigger.
The empirical model is shown in equation (1).
𝐼𝑅 = 𝑏!+ 𝑏!∗ Underwriter Rank + 𝑏!∗ 𝐿𝑁𝑆𝐼𝑍𝐸 + 𝑏!∗ 𝐿𝑁𝐴𝐺𝐸 + 𝑏!∗ 𝑇𝐸𝐶𝐻
4. Results
This section presents the main results of the ordinary least squares regressions. An answer to the hypotheses will also be formulated in this section. The main hypothesis is that underwriter reputation does have an effect on initial returns.
As a first examination, to see if any variables are correlated, Pearson correlation coefficients are estimated. The results are shown in the correlation matrix in table II. Table II Correlation Coefficients IR RANK LNSIZE
LNAGE TECH OFFERED
IR 1.0000 RANK 0.0780 1.0000 LNSIZE -0.1022 0.1554 1.0000 LNAGE 0.1508 0.1238 0.2158 1.0000 TECH 0.3066 0.0917 -0.0799 0.1065 1.0000 OFFERED -0.1418 -0.1354 -0.0743 -0.2126 -0.1572 1.0000
As expected, LNSIZE and RANK are positively correlated, because the more prestigious investment banks market the larger IPOs. TECH and LNAGE are also positively correlated. This is interesting because firms qualified as technology firms are often young firms, and this correlation suggests otherwise. Since there are no correlation coefficients below -0.7000 or above 0.7000, none of the variables are highly correlated so no variables have to be removed from the model.
The results of the regression on initial returns are presented in table III. Regression one is a univariate regression for the variable of most interest, underwriter reputation. Univariate regressions for the control variables IPO size, firm age, technology firms and percentage of shares offered, are found in regressions two through five. Regression six is a multivariate regression with underwriter reputation and size and the final regression presents the results with all control variables included.
Looking at previous literature, a negative coefficient for underwriter reputation was expected. It says that a higher reputation should lead to less underpricing because the underwriter has much experience and performs continuously. However, the univariate regression for underwriter reputation gives a
Table III
Regressions Explaining the Initial Returns for 619 IPOs Issued from January 1, 2005 through December 31, 2014
Rank Size Age Tech Offered Rank,Size All
(1) (2) (3) (4) (5) (6) (7) Intercept -0.0725 0.5805 0.1002 0.1185 0.1996 0.3582 0.4566 (0.62) (3.50)*** (5.17)*** (10.11)*** (13.05)*** (1.90)* (2.48)** Underwriter Rank 0.027 0.0332 0.0157 (2.00)** (2.45)** (1.20) Size IPO -0.0337 -0.0389 -0.0402 (2.54)** (2.90)*** (3.08)*** Age firm 0.0338 0.0284 (3.79)*** (3.19)*** Tech firm 0.2088 0.1819 (8.01)*** (6.91)*** % Offered -0.1629 -0.0738 (3.44)*** (1.93)* Observations 619 619 619 619 619 619 619 Adjusted R² 0 0.01 0.02 0.09 0.02 0.02 0.12 Root MSE 0.27 0.27 0.27 0.26 0.27 0.27 0.26
Constant included. Absolute value of t statistics in parentheses.
* Significant at 10%; ** significant at 5%; *** significant at 1%.
positive coefficient, significant at the 5 percent level. The coefficient is also positive in the multivariate regression with all control variables included, but is not significant. This positive coefficient would suggest that a higher reputation leads to more underpricing.
The coefficients for each of the control variables are significant in all regressions, with varying significance levels. The coefficients for firm age and technology firms are equally significant in the univariate and multivariate regressions. The coefficient for IPO size becomes more significant in the multivariate regression and the coefficient for the percentage of shares offered is more significant in the univariate regression.
The negative coefficient for IPO size was expected. Larger IPOs are often underwritten by bigger and more established firms, which according to literature leads to less underpricing. The negative coefficient in regression seven in table III confirms that lager IPOs experience smaller initial returns.
The positive coefficient for firm age is not in line with previous research. From literature, a negative relation between firm age and initial returns was expected because it is easier to correctly value older firms and thereby set the right offer price than it is for younger firms. The positive coefficient in regression seven in table III however suggests bigger initial returns for older firms.
The positive coefficient for technology firms was expected, because technology firms are often young firms that are more difficult to value correctly and therefore experience higher initial returns. The positive coefficient in regression seven in table III confirms that technology firms experience higher initial returns.
The negative coefficient for percentage of shares offered was expected. Literature suggests that a higher percentage of shares offered by current shareholders signals little expected underpricing, which eventually leads to smaller initial returns. So the negative coefficient in regression seven in table III confirms smaller initial returns for IPOs where a larger part of the shares is offered.
Table IV
Regression Explaining the Initial Returns per Year
2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) Intercept 1.2218 1.3825 -0.2055 1.4603 -3.7624 -0.5821 0.2533 0.4055 0.7839 0.7411 (0.93) (1.41) (0.38) (2.34) (1.75) (0.78) (0.49) (0.84) (1.16) (1.75)* Underwriter Rank 0.0178 0.0478 0.0680 -0.0364 0.3035 0.0302 0.0151 0.0212 0.0297 -0.0009 (0.31) (1.10) (1.86)* (0.93) (1.33) (0.57) (0.40) (0.53) (0.67) (0.02) Observations 36 40 72 8 18 57 65 73 121 129 Adjusted R² 0.08 0.09 0.07 0.61 0.02 0.04 0.19 0.19 0.14 0.06 Root MSE 0.45 0.31 0.31 0.15 0.28 0.32 0.22 0.22 0.31 0.27
Constant included. Absolute value of t statistics in parentheses. * Significant at 10%; ** significant at 5%; *** significant at 1%.
Taking a closer look at the unexpected positive coefficient for underwriter reputation, regressions per year are presented in table IV. Regressions one through ten are regressions for the ten years of the data sample separately. Negative coefficients for underwriter reputation are expected. Regressions four and ten, for respectively 2008 and 2014, give negative coefficients. These are however not significant. The remaining regressions give positive coefficients for underwriter reputation, which is in line with the results found in the regressions in table III. Regression three is the
Table V
Regression Explaining Initial Returns per Rank
Per Rank (1) Rank 4 0.6754 (2.25)** Rank 5 0.4646 (2.34)** Rank 6 0.4803 (2.83)*** Rank 7 0.5773 (3.56)*** Rank 8 0.5917 (3.62)*** Rank 9 0.5762 (3.52)*** Size IPO -0.0386 (2.94)*** Age firm 0.0276 (3.08)*** Tech firm 0.1821 (6.90)*** % Offered -0.0734 (1.91)* Observations 619 Adjusted R² 0.34 Root MSE 0.26 Absolute value of t statistics in parentheses.
* Significant at 10%; ** at 5%; *** at 1%.
only one giving a significant coefficient, at the 10 percent level. This shows that the unexpected positive coefficients are not a result of the financial crisis in the United States.
To further investigate the positive underwriter reputation coefficient, results of a regression with separate coefficients per rank are presented in table V. For this specific regression, the constant is left out. The coefficients for all ranks, as well as the control variables, are significant with significance levels varying between 1% and 10%.
In the selected data sample, the lowest assigned rank is 4 and the highest assigned rank is 9. Coefficients for ranks four through nine are presented in table V.
All six coefficients are significantly positive, again confirming the results found in the regressions in table V.
With previously discussed results, the hypothesis that underwriter reputation has an effect on initial returns can be answered. The results show that there is no significant effect of underwriter reputation on initial returns. A positive relation between underwriter reputation and initial returns is found, but not significant.
5. Conclusion and Discussion
This paper examines the effect of underwriter reputation on initial returns of IPOs. Results show no significant effect of underwriter reputation on initial returns. A positive relation between underwriter reputation and initial returns is found, but not significant. This is not what was expected from previous literature. Beatty and Ritter (1986), Johnson and Miller (1988), Carter and Manaster (1990) and Carter et al. (1998) all found a negative relation between underwriter reputation and initial returns.
A limitation of this research is the use of incorporation dates as founding dates for IPOs where founding dates were not available. This definitely effected firm ages and might be the reason for the unexpected positive coefficient. Another limitation is the sample of IPOs with a value above $100.000.000. This resulted in many IPOs using the same big investment banks as underwriters and not much diversification in underwriter reputation ranks.
A suggestion for further research is to do more research with recent data. Most literature on the subject is from last century and a lot has happened in this field the past years. The financial crisis has changed banks and investors and this affects the whole IPO process. Another suggestion for further research is to use various different underwriter reputation measures to test for an effect on initial returns. This would make the research less dependent on one particular measure and increases the chance on significant results. It also creates a possibility to compare results of different underwriter reputation measures. This would improve results and give the possibility to compare results.
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