Currying favor with top venture capital firms: The role of IPO underpricing and all-star coverage Daniel Bradleya, Incheol Kimb, and Laurie Krigmanc a
Department of Finance, University of South Florida, Tampa, FL 33620, 813.974.6326,
[email protected] b Department of Finance, University of South Florida, Tampa, FL 33620,
[email protected] c Finance Division, Babson College, Babson Park, MA 02457, 781.239.4246,
[email protected]
August 24, 2011 ______________________________________________________________________________
Abstract We explore the central role that top venture capitalists play in the IPO underwriting market. We argue that underwriters curry favor with Top VCs, not necessarily issuing firms, because Top VCs have the ability to direct the most business in a repeated game sense to banks that treat them well. The relationship between VC firms and investment banks extends through time and therefore incentives extend beyond the current IPO. Consistent with this view, we find that Top VC-backed IPOs are more likely to get all-star coverage regardless of analyst bank affiliation. In turn, banks providing all-star coverage are more likely to be chosen to lead the next VC-backed deal. We find a positive relationship between underpricing and all-star coverage for Top VCs, but not non-Top VCs. Top VCs tolerate higher levels of underpricing because the information momentum generated by underpricing allows them to cash out at higher prices when the lockup expires.
Keywords: Initial public offering; all-star analyst coverage; venture capital; underpricing JEL Classification: G14; G24
_________________________________________________________________________________ We wish to thank Brian Adams, Anup Agrawal, Mike Cliff, Doug Cook, Jack Cooney, Shane Corwin, Venkata Eleswarapu, Mike Highfield, Mingsheng Li, Jim Ligon, Alexander Ljungqvist, Jim Moser, Manju Puri, Jay Ritter, Ken Roskelley, Mike Stegemoller, Donghang Zhang and seminar participants at the 2011 Kaufmann Entrepreneurial Finance and Innovation Conference at Harvard, the 2011 Boston Area Finance Symposium, Alabama, Louisiana Tech, South Carolina, and Texas Tech universities for useful comments and suggestions. This paper was previously circulated under the title, “Do co-managing all-star analysts influence IPO pricing?” We are responsible for any errors.
Currying favor with top venture capital firms: The role of IPO underpricing and all-star coverage
I.
Introduction Over the period 1994 to 2007, venture capitalists (VCs) backed close to 40 percent of all
IPOs. Over this time, several academic papers have shown that VC-backed IPOs were significantly more underpriced than their non-VC-backed counterparts (i.e., Lee and Wahal (2004)). This result is at odds with earlier research arguing that VCs are certification agents and associated with lower initial returns (Megginson and Weiss (1991). Why the sharp change? To grasp this empirical phenomenon, an understanding of the incentives of the parties involved in the IPO is necessary. Loughran and Ritter (2004) argue that underpricing has changed over time because the incentives have changed. Recent papers in the IPO underpricing literature have placed a strong emphasis on rent-seeking behavior by underwriters. Underwriters cannot directly benefit from underpricing, but through quid pro quo arrangements they can indirectly profit by allocating underpriced shares to preferred clients who pay for other services. For example, Liu and Ritter (2010a) examine the practice of “spinning” whereby underwriters allocate IPO shares to CEOs and executives as a form of bribery for future investment banking business. Hao’s (2007) paper focuses on laddering, in which underwriters require the purchase of additional shares of the IPO in the aftermarket as a condition of receiving an IPO allocation. Nimalendran, Ritter and Zhang (2008) suggest that allocations are also given to hedge funds and other investors that agree to pay excessive commissions in return for underpriced shares. All of these types of arrangements can help explain the explosive growth in initial returns during, and leading up to, the Internet boom. Each of these practices has been subject to immense scrutiny leading to fines and regulatory changes with respect to IPO allocations.1 1
Liu and Ritter (2010a) provide excellent detail on the regulatory settlements stemming from these practices.
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While rent-seeking behavior by the underwriter may explain why underwriters prefer higher underpricing, why do issuing firms and venture capitalists tolerate it? In recent years, the quality of the analyst research team has grown in importance. Issuing firms primarily seek underwriters that have Institutional Investor “all-star” analysts.2 Supporting this conjecture, Krigman, Shaw, and Womack (2001) find that IPO firms are most likely to switch underwriters in their subsequent SEO to secure better quality research coverage. In order to get this premier service, Cliff and Denis (2004) find that issuing firms accept higher levels of underpricing.3 In a similar spirit, Liu and Ritter (2010b) characterize the IPO underwriting market as an oligopoly with only the top underwriters employing all-star analysts competing for IPO mandates. They argue underwriters bundle analyst coverage with other IPO services and charge the issuing firm indirectly for this service through underpricing. Issuing firms may be at the mercy of the underwriter and have to acquiesce and accept higher underpricing, but venture capitalists are repeat players in the IPO market and thus should have bargaining power. Further, they are sophisticated investors and understand pricing decisions. Why would VCs put up with higher levels of underpricing? VCs may put up with high levels of underpricing because they care about the price at which they exit their investments, not necessarily the IPO price per se. If underpricing attracts influential analyst coverage (Rajan and Servaes (1997) and Aggarwal, Krigman, and Womack (2001)), which generates information momentum that helps support the stock price until the 2
Each year, Institutional Investor polls buy-side institutional investors and selects the Top analysts in each industry along with a runner-up. See Clarke, Khorana, Patel, and Rau (2007), Fang and Yasuda (2009), and Liu and Ritter (2010b). 3 Degeorge, Derrien, and Womack (2007) find that in France, where issuing firms have a choice between bookbuilding, with high levels of underpricing, and auctions, with low underpricing, more than half of issuing firms choose bookbuilding. They argue that analyst coverage can explain this choice. They show that under bookbuilding, issuers receive more lead underwriter recommendations that tend to be more optimistic than for auction led IPOs.
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expiration of the lockup date when they distribute shares to their limited partners, then VCs would be willing to accept higher levels of underpricing. Hoberg and Seyhun (2010) argue that underwriters and VCs collaborate. They argue that VCs agree to a lower offer price in exchange for greater post-IPO marketing including, but not limited to, more optimistic analyst research. While all VC firms should have similar incentives with respect to IPO pricing and valuation, the literature has shown that VC quality is an important consideration. For example, Chemmanur and Loutskina (2006) argue that high reputation VCs attract high quality market participants to an IPO and receive higher valuations as a result. Nahata (2008) finds that VCreputation is positively linked to the probability that a VC portfolio firm goes public. Krishnan, Ivanov, Masulis and Singh (2010) show that top-ranked VCs back better quality firms, and after controlling for this selectivity are associated with higher long-run returns. We extend this line of inquiry and provide a unified explanation for the central role played by large reputable VCs in the IPO market. During our 14-year sample period between 1994 and 2007, the average non-Top VC firm took less than 5 deals to market whereas the average Top VC firm brought over 37 deals to IPO. Thus, in a repeated game framework, underwriters need to curry favor with top venture capitalists, not necessarily the other way around. We argue that only the most active, reputable VCs, akin to top underwriters, have market power and underwriters actively court their business by providing all-star analyst coverage to IPOs backed by the Top VCs. Importantly, the relationship between venture capital firms and investment banks extends through time and therefore incentives extend beyond the current IPO. That is, an investment bank may provide all-star coverage to an IPO to curry favor with the VC firm even though they may not have a role in the current IPO. They provide all-star coverage in order to reap future underwriting mandates from the VC.
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Consistent with our hypothesis, we find that Top VC-backed firms are significantly more likely to be allocated a star analyst compared to non-Top-VC firms or non-VC firms, controlling for the inherent selection bias that not all firms can work with a Top VC firm. We also demonstrate that IPO underpricing is strongly related to Top VCs that receive all-star coverage, but not non-Top VCs. Both of these results are independent of the affiliation of the investment bank to the IPO. That is, Top VCs are more likely to get all-star coverage post-IPO from lead managers, co-managers and investment banks unaffiliated with the IPO. Further, underpricing is higher for Top VC deals that also receive all-star coverage from any type of analyst, affiliated or unaffiliated. The economic impact of this effect is large. For example, IPOs backed by Top VCs that do not receive all-star coverage are underpriced by 34.2 percent. Those that receive all-star coverage from the lead, co-manager, or unaffiliated all-stars are underpriced by 95.4 percent, 110.8 percent, and 118.2 percent, respectively. The corresponding numbers for non-Top VC backed IPOs are 24.4 percent, 36.1 percent, 43.3 percent, and 30.1 percent, for no all-star, lead, co-manager and unaffiliated all-star coverage, respectively. We interpret our evidence that underwriters are willing to allocate star analysts to Top VC firms regardless of their position in the current IPO to potentially get future IPO business from them. Consistent with this view, we find that co-managers that provide VCs all-star coverage in their previous deal are likely to get rewarded with a lead mandate for the VC’s subsequent deal. We also find evidence that IPOs backed by Top VCs receiving all-star coverage have stronger performance up to the lockup expiration, and subsequently experience a significantly larger price drop on the lockup expiration indicative of aggressively exiting their investment compared to non-top VC-backed IPOs.
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The rest of this paper proceeds as follows. Section II reviews the literature and formulates our hypotheses. Section III describes the data and gives descriptive statistics. Section IV presents empirical results and section V provides concluding remarks.
II.
Hypothesis Development Our primary objective is to examine the relationships that exist between the quality of
venture capital IPO backing, the type of all-star analyst coverage post-IPO and IPO underpricing. We hypothesize that top venture capital firms are central to the IPO process from the perspective of an investment bank. Venture capital firms have decision-making power in selecting underwriters for IPOs and thus have the potential to have repeat relationships with investment banks. Further, top venture capital firms bring the most firms public repeatedly and thus offer the greatest potential for future business to investment banks. If investment banks want to be selected as lead or co-managing underwriters on future IPOs, they must keep venture capital firms happy, especially Top VC firms. This naturally leads to the question of how one keeps venture capital firms happy. The first thing that comes to mind would not be underpriced IPOs. Underpricing “leaves money on the table.” As early stage investors in IPOs, selling shares to the public for a higher price would seem better than selling for a lower a price. So, why would Top VC firms want underpricing? The key to the relationship is that VC firms cannot sell their shares until the lockup expires. Thus, the price at the IPO is not a primary concern. What matters to a VC is the price at lockup expiration, typically six months following the IPO. Aggarwal, Krigman and Womack (2001) provide the link in their information momentum model. They show that the return to the lock-up
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expiration is increasing in information momentum (analyst coverage post-IPO). Therefore, venture capital firms want research coverage post-IPO so they can cash out at higher prices. Cliff and Denis (2004) find evidence supportive of the notion that issuing firms pay for all-star analyst coverage through IPO underpricing. They also find that firms are more likely to switch underwriters for follow-on offerings if the lead investment bank does not provide the expected coverage post-IPO. While only the lead investment bank has a direct relationship with the issuing firm, all investment banks potentially have relationships with the venture capital firms on a deal. Thus, Cliff and Denis (2004) examined the provision of lead bank all-star analyst coverage as it related to IPO underpricing in the context of the relationship between issuing firms and lead banks. Liu and Ritter (2010b) consider the relationship between venture capital-backed IPOs and lead investment banks in providing all-star coverage post-IPO. They show that VCbacked IPOs are more underpriced when the lead underwriter provides all-star analyst coverage. We extend this line of inquiry by considering the central role of top venture capital firms. If all-star coverage is a valuable asset owned by the investment bank, then they should expect to receive something in return for providing it. This has been explored in the literature for issuing firms and investment banks in the context of future underwriting of SEOs, debt offering and mergers and acquisitions activity by Ljungqvist, Marston, and Wilhelm (2006), Ljungqvist, Marston, and Wilhelm (2009), and others. We depart from the literature and explore the notion that investment banks provide all-star coverage to curry favor with venture capital firms rather than with issuing firms. We focus on top venture capital firms because they have the ability to direct the most business in a repeated game sense to banks that treat them well. We argue that the relationship between venture capital firms and investment banks extends through time and therefore incentives extend beyond the current IPO. That is, an
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investment bank may provide all-star coverage to an IPO to curry favor with a venture capital firm even though they may not have a central role in the current IPO. They provide coverage in order to reap rewards in the future. Therefore, we go beyond the lead investment banks’ provision of all-star analyst coverage and examine all all-star coverage post-IPO, regardless of bank affiliation. We partition our sample into three categories based on the type of all-star coverage received. First, when a firm hires an investment bank, it is often with the implicit understanding that if the investment bank has an all-star analyst in the industry, it will cover the IPO. We refer to all-stars provided by the lead investment bank as “Lead-Stars.” Second, we examine the prevalence and motivations for a co-managing investment bank to provide all-star coverage (“Co-Star”). Finally we examine all-star coverage provided by an investment bank that is unaffiliated with the current IPO (“Unaffiliated-Star”). This line of thought leads to several empirical predictions. First, we predict that because of the importance of top venture capital firms in providing a continuous stream of business to investment banks, IPOs backed by top venture capital firms are likely to receive more all-star analyst coverage post-IPO from lead, co-managing and unaffiliated investment banks. In exchange for the prospect of receiving all-star analyst coverage from investment banks, our second prediction is that IPOs backed by top venture capital firms will be more underpriced. However, under this hypothesis, not all affiliated banks are treated equal. The pay-for-coverage hypothesis only applies to the lead underwriter as they control the offer price. Co-managers may influence the offer price at the margin, but it is unlikely that they have much say in the pricing process. Unaffiliated banks have no direct influence over underpricing. In the context of information momentum, VCs will naturally want more underpricing, which will in turn attract
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more coverage. Thus, while unaffiliated analysts (and possibly co-managers) may not influence underpricing, they will be attracted to more underpriced deals, consistent with Rajan and Servaes (1997). Third, investment banks are more willing to provide all-star coverage to VC-backed IPOs regardless of their affiliation in the current IPO, because they hope to secure future underwriting mandates from the venture capital firm. Thus, we predict that the probability of becoming a lead underwriter is positively related to the past provision of all-star coverage to IPOs backed by venture capital firms, particularly the most reputable ones. Prediction 1: IPOs backed by top venture capital firms have a higher probability of receiving all-star analyst coverage post-IPO. Prediction 2: IPOs backed by top venture capitalists will have higher underpricing Prediction 3: The probability of becoming a lead investment bank is related to the past provision of all-star coverage on IPOs of venture capitalists These predictions have certain implications for the relationship between post-IPO performance, all-star analyst coverage and type of venture capital backing. Our hypotheses regarding the central role of top venture capital firms, all-star analyst coverage and IPO underpricing are all choice-based. That is, top venture capital firms choose which firms they invest in; the lead investment bank chooses the offer price and thus, to a large extent, the level of underpricing; and investment banks choose whether or not to provide all-star coverage to IPOs. These choices imply certain outcomes in the market. We test two such implications. First, if allstar coverage is considered valuable in boosting the stock price post-IPO, we expect that performance to the lock-up expiration will be positively related to top venture capital backing and all-star analyst coverage. Second, if venture capital firms are primarily concerned with the stock price at the lock up expiration when they can cash out, we should find evidence of 8
significant selling by venture capital firms around the lockup expiration. The two specific implications we test are: Implication 1: Performance to the lockup expiration is related to Top VCs and all-star coverage. Implication 2: The price drop around the lockup expiration will be higher for Top VC-backed IPOs.
III.
Data and descriptive statistics To test the importance of the relationship between Top VC firms and all-star analyst
provision, we collect data from several sources. We identify IPOs through Thompson Financial’s Securities Database Corporation (SDC) New Issues Database over the period 1994-2007. We delete unit offers, spinoffs, ADRs, closed-end funds, REITs, financial institutions, and issues with offer prices below $5.00. Analyst data are gathered from I/B/E/S. The main advantage of using the I/B/E/S database in this study is that it identifies the specific analyst making the recommendation. Therefore, we are able to determine whether or not the analyst in question is an all-star. Consistent with Dunbar (2000), Cliff and Denis (2004) and others, we use Institutional Investor’s all-star research team to define all-stars. Stock price data are from the Center for Research in Security Prices (CRSP). We hand-collect data on venture capitalists from the IPO prospectus. We collect the names of each venture capitalist participating in each deal, the amount invested, and the dates of each round of financing. For data pre-1996 that is not captured on the SEC’s Edgar database, we use hardcopies of each firm’s S-1 filing.4 Insert Table 1 about here 4
We are very grateful to Jay Ritter for providing us access to this data.
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Panel A of Table 1 presents firm and offering characteristics. Of the 3,981 firms in the sample, the average IPO has assets of $745 million and raises $107.4 million. The average firm is about 15 years old at the time of its public debut. The average price revision, the percentage difference from offer price to the midpoint of the file range (Hanley (1993)), is 2.2 percent and the average IPO is underpriced by 26 percent. Finally, half of the sample is tech-related. We separate IPOs in three time periods as many recent studies document significant changes through time, particularly for underpricing. Our sample confirms that the unusually large initial returns during the Internet bubble of 1998 through 2000 skews the mean underpricing upwards for the entire sample. The average price revision is negative in the pre- and post-bubble periods, but over 10 percent during the bubble period. Firm age declines during the bubble period, but rises significantly in the post-bubble period. Nominal assets and proceeds rise with time. Panel B of Table 1 provides descriptive statistics on underwriter, VC and all-star analyst coverage characteristics. CM-rank is a ranking measure of underwriter prestige, developed by Carter and Manaster (1990) and updated by Loughran and Ritter (2004). Over 65 percent of issuing firms hire an investment bank with a CM-rank of 8 or above on a 9-point scale. We use the top 25 VC firms identified in Table 3 of Gompers, Kovner, Lerner, and Scharfstein (2010) to define Top VCs. For each VC-backed deal, we identify all of the venture capitalists participating and if a Top VC has more than a 5 percent ownership stake, we code it as a Top VC deal.5 About
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We also follow Krishnan, Ivanov, Masulis and Singh’s (2010) definition of Top-ranked VCs. They measure VC reputation based on a venture investor’s past market share of completed venture-backed IPOs for where they are the lead investor. The measure is similar to the Megginson and Weiss (1991) underwriter reputation measure and captures a VC’s IPO success rate relative to other VCs. However, with this measure, we lose the first two years of our sample. Nonetheless, our results are similar throughout the paper regardless of the definition of Top VC. We also use the top 20, 30 and 40 VC firms in Gompers, Kovner, Lerner, and Scharfstein (2010). Our results remain unchanged.
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40 percent of IPOs are VC-backed and Top VCs bring approximately 15 percent of firms to market. The final variables in Table 1 are related to all-star coverage. Lead Star Analyst is the percentage of IPOs that hire an investment bank in which an all-star analyst ultimately covers the firm within the first year of going public. As shown, approximately 20 percent of IPOs have a lead all-star covering them after the IPO. This is similar to the 22 percent reported in Cliff and Denis (2004). Interestingly, about 15 percent of IPOs have an all-star covering their firm that was a co-manager. Further, 8 percent of IPO firms receive all-star coverage from an unaffiliated investment bank. We view these high participation frequencies as economically meaningful and not considered in previous studies. Interestingly, we find that while most of the variables increase through time, VC-backing, Top VC-backing, Co-Manager Star coverage and Unaffiliated Manager Star coverage all peaked in the bubble period and subsequently fell. Perhaps not coincidentally, this pattern mirrors underpricing. Insert Table 2 about here In Table 2 we partition the data by VC representation and time period. As can be seen in the table, large differences exist between VC categories. The average underpricing for Top VCbacked IPOs is 56%, compared to 27% for non-Top VC-backed IPOs and 17% for non-VC IPOs. Medians, while lower, reveal the same pattern. Not only are these results economically significant, but in unreported results, we find that these differences are statistically significant (based on means and medians). The price revision pre-IPO is significantly higher for Top VC IPOs as well. Top VCs are more likely to match with top underwriters. This is consistent with Fernando, Gatchev, and Spindt (2005) who argue that high quality issuers naturally pair with high quality firms. The
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magnitude of the lockup expiration return increases monotonically as we move from no VC to Top VC-backed IPOs. Top VC-backed IPOs have the largest negative abnormal return at lockup expiration, suggesting that Top VCs are exiting their positions more aggressively than other VCs or insiders in non-VC-backed IPOs. Consistent with Hypothesis 1, all-star coverage is highest for Top VCs regardless of affiliation. Interestingly, all-star coverage is the lowest for non-Top VCs no matter the affiliation of the analyst. Insert Figure 1 about here An examination of IPO underpricing by time period reveals that IPOs of top venture capitalist firms are significantly more underpriced. Figure 1 illustrates this point. As can be seen, average underpricing for Top VC-backed IPOs is over 104% (median 65%) during the bubble period compared to only 53% and 31% (median 29% and 11%) for VC-backed and non-VC-back IPOs, respectively. We point out one last interesting result from Table 2. Focusing on the time series nature of all-star coverage, non-VC-backed IPOs experienced a linear increase in lead star coverage through time: 14.8 percent, 21.6 percent, and 33.3 percent during the pre-bubble, bubble, and post-bubble periods, respectively. For Top VC-backed IPOs, the corresponding lead-star coverage percentages are 12.8, 37.8 and 28.8. Thus, only during the internet bubble period were Top VCs more likely to receive lead star coverage.
IV.
Empirical Results
A.
Are Top VCs related to all-star coverage? Our first empirical prediction is that Top VC-backed IPOs should garner more all-star
analyst coverage than other IPOs. Consistent with our prediction, simple statistics in Table 2
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show that Top VC-backed IPOs have significantly more all-star analyst coverage than other IPOs. However, the means do not control for other factors that would reasonably be expected to determine the level of analyst coverage. In Table 3, we present a series of two-stage regressions modeling all-star analyst coverage post-IPO as a function of type of VC backing. We recognize that not all firms will have access to capital from a Top VC firm. Thus, we control for the endogeneity of Top VC-backing using the Inverse Mills Ratio calculated from a probit model capturing the probability of being Top VC-backed. We instrument Top VC-backing using an indicator variable equal to “1” if the firm is located in California. Firm location has been used as an instrument variable in other studies (i.e., Krishnan et al. (2010)). In the context of our paper, we are in need of a variable(s) that is related to the probability of receiving financing from a Top VC, but unrelated to the probability of receiving all-star coverage. Since many technology-related firms that receive VCbacking are located in Silicon Valley as are many Top VCs, it is likely that Top VC status is correlated with firms headquartered there. However, the location of the issuing firm is unlikely to determine all-star coverage.6 Consistent with these arguments, we find that the California dummy is highly correlated with Top VC status, but uncorrelated with all-star coverage. Likewise, we believe that an internet dummy has the same qualities and find that it indeed does. Finally, an F-test that the instruments are jointly equal to zero is 83, supporting our choice of instruments. Insert Table 3 about here In addition to our instruments in the first stage model, we also include an indicator variable for internet-related firms, a size-related variable (Log Assets), an indicator for tech 6
Although Malloy (2005) shows that analysts geographically closer analysts have an informational advantage over more distant analysts, location is unlikely to impact the choice of coverage by all-star analysts. That is, even if distance influences the coverage decision, it is likely to impact stars and non-star analysts equally.
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status, a top underwriter dummy, and firm age. We find that Top VC status is positively related to being headquartered in California, being internet and tech-related, and associated with a top underwriter yet negatively related to firm age and assets. In the second stage, the dependent variable is equal to one if the IPO received any type of all-star coverage (“lead”, “co-manager” or “unaffiliated”), and zero otherwise. The independent variables of interest are two indicator variables. The first, “VC-backed” is equal to 1 if the firm is backed by a non-Top VC and zero otherwise. The second, “Top VC-backed” is equal to 1 if the IPO is backed by a Top VC and zero otherwise. In addition to the variables in the first stage, we also control for proceeds raised, underpricing, and include the Inverse Mills Ratio calculated from the first stage estimation to control for endogeneity. The model is estimated for the full sample and is also estimated by sub-period. As can be seen in Table 3, the coefficient on VC-Backed, which represents non-Top VCbacked IPOs is negative. This is consistent with the univariate results shown in Table 2. In fact, during the bubble period, the coefficient is negative and statistically significant. In contrast, representation by a Top VC is significantly positively related to the likelihood of receiving allstar analyst coverage post-IPO in the full sample model and during the bubble period. Our results show that all-star status is also positively related to firm size, underwriter quality, underpricing and negatively related to technology status. B.
The relationship between VC status, all-star coverage and underpricing Liu and Ritter (2010b) put forth and test the Analyst Lust Theory of IPO underpricing.
They find that VC-backed IPOs are significantly more underpriced during the bubble period. They also show that IPOs that subsequently receive all-star analyst coverage from a bookrunner
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in the 12 months following the IPO are more underpriced. We extend their results and examine the quality of the venture capital firms as well as the source of the all-star analyst coverage. In Table 4 we build on Liu and Ritter’s (2010b) model of IPO underpricing. We are interested in how VC quality and all-star analyst coverage independently and jointly are related to IPO underpricing. Since all-star analyst coverage is not known at the time of the IPO, we use a two-step procedure and use estimates of the probability of receiving “lead”, “co-manager” or “unaffiliated” all-star analyst coverage in our model of IPO underpricing. Panel A of Table 4 presents three logistic regressions used for calculating an estimate of the probability of receiving all-star analyst coverage from either a “Lead”, “Co-Managing”, or “Unaffiliated” investment bank. The independent variables were described previously.7 Insert Table 4 about here In the first stage of Table 4, we confirm the results in Table 3 that the probability of receiving all-star coverage (Lead, Co-Manager or Unaffiliated) is significantly related to being backed by a Top-VC firm, but not to a VC firm in general. We use the estimated probabilities from these models as inputs into the models of IPO underpricing in Panel B of Table 4. The independent variables of interest in the underpricing regressions are the type of VC-backing (VC and Top VC), the estimated probabilities of receiving all-star analyst coverage (Pr(Lead AllStar), Pr(Co-Mgr All-Star), and Pr(Unaff All-Star)), and interactions among the two sets of variables. Due to the high correlation between the estimated probabilities of receiving lead, comanager and unaffiliated all-star coverage, we run separate models for each type of all-star coverage. We also control for the IPO price revision, underwriter quality, proceeds raised, technology and Internet firms, and time period. 7
In unreported results, we also use an indicator for actual all-star coverage instead of predicted values for all-star coverage. The results are qualitatively the same.
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As shown in Panel B of Table 4 Model (1), consistent with Liu and Ritter (2010b), IPOs that have VC-backing are significantly more underpriced. Model (2) demonstrates that if we limit VC coverage to Top VCs, Top VC-backed IPOs are also significantly more underpriced. However, when we include both VC and Top VC in Model (3), we find that only the indicator for Top VC-backed IPOs is significant. Thus, after controlling for Top-VC backed IPOs, nonTop VC-backed IPOs are not significantly more underpriced than other IPOs. Thus, venture capital firm quality is an important determinant in IPO underpricing. When we add the probability of lead all-star coverage to the regression in Model (4), we find that it is significant and it eliminates the significance of having a top underwriter. Finally, in Model (5), we consider the interaction of VC type (Top or non-Top) and the probability of receiving lead all-star coverage. We find that IPOs that have a high probability of receiving lead all-star coverage post-IPO and have Top VC-backing are significantly more underpriced than other IPOs. Non-Top-VCs interacted with the probability of receiving all-star coverage are not significantly more underpriced. The results for co-manager and unaffiliated all-star analysts are presented in Models (6) through (9) and are comparable. Overall, we find that controlling for other IPO characteristics and time, Top-VC backed IPOs with a high probability of receiving lead, co-manager or unaffiliated all-star coverage are significantly more underpriced. Insert Figure 2 about here Figure 2 displays this result graphically. Two results are apparent. First, holding star status constant, Top VCs have the highest underpricing. Second, despite the literature focusing only on lead all-star coverage and underpricing, our results indicate underpricing is higher for IPOs that receive all-star coverage from any underwriter.
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C.
Do relationships change through time? Loughran and Ritter (2004) and Ritter and Liu (2010b) suggest that the incentives
between firms and underwriters have changed through time. For many of the same reasons, we expect this to be true for venture capitalists and underwriters. Our conjecture is that the relationship between investment banks and venture capital firms is a repeated game. We also believe that the incentives for this game have changed over time as the IPO market and financial regulations have changed. Therefore we test the robustness of these relationships across time. We partition our underpricing regressions into three time periods: pre-bubble (1994-1997), bubble (1998-2000) and post-bubble (2001-2007). To conserve space, we only report the coefficients of interest from the same model in Table 4. Insert Table 5 about here Panel A of Table 5 contains the underpricing regressions for the pre-bubble period. The interactions between Top VC and the corresponding probabilities of all-star coverage for each type of underwriter are positive and significant. We also find that the interactions between VC and the probabilities of lead and co-manager all-star are significant. Panel B contains the results for the bubble years 1998-2000. This table mimics the full sample results. The explanatory power of the regression models for explaining IPO underpricing jumps from an average adjusted r-squared of 27% to over 44% during this time period. Top VCs and all-star coverage appear to have a central role in IPO pricing during the pre-bubble and bubble period. The significance of VC with the probability of all-star coverage disappears during the bubble period. Again, we find that underpricing is related to Top VC status and not VCbacking in general.
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Finally, in Panel C we present the results for the post-bubble years. The importance of Top-VC backing interacted with all-star analyst coverage disappears. It appears that regulatory changes and market scrutiny diminished the ability of investment banks to barter all-star analyst coverage to top venture capital firms in exchange for business.
D.
Post-IPO performance, lockup expiration and VC and all-star status To recap, we have shown that Top VC status is related to all-star coverage and IPO
underpricing is strongly related to Top VC-backed firms that receive all-star coverage. Both of these results are independent of the affiliation of the investment bank. If venture capital firms have relationships with investment banks that garner them all-star coverage on their IPOs regardless of who is the lead underwriter, the question we address is “Why would Top VCs who seem to have all of the power be willing to accept high levels of underpricing?” The answer lies with the work of Aggarwal, Krigman and Womack (2001). They demonstrated that firms with the highest levels of underpricing were most likely to receive analyst coverage. In turn, analyst coverage was shown to influence and increase the return to the lock-up expiration when venture capital firms are allowed to cash-out. We now examine the relationship between post-IPO performance, type of VC-backing and type of all-star analyst coverage. We start by providing summary statistics on analyst coverage and stock performance post-IPO. We partitioned the data by type of VC-backing and source of analyst coverage (Lead, Co-manager and Unaffiliated) as well. Multiple refers to cases where an IPO firm receives all-star coverage from more than one analyst.8 We measure 8
We do not provide the average time to initiate or the recommendation level for multiple all-star recommendations because they are not meaningful. In most of these cases, an affiliated all-star analyst initiates coverage with an unaffiliated all-star. Because affiliated analysts tend to initiate coverage significantly earlier than unaffiliated analysts, averaging the time to initiate coverage would be misleading because it would appear as if multiple all-stars
18
performance as the buy-and-hold abnormal return relative to the market as measured by the NYSE/Nasdaq/Amex value-weighted portfolio and only include research coverage initiations in the first 180 days post-IPO. As such, the number of unaffiliated all-star coverage initiations is small because unaffiliated analysts typically take longer to initiate coverage than affiliated analysts. The average rating is about a “buy,” consistent with other research examining research coverage of IPOs. Insert Table 6 about here Examining the performance measures in the last two columns, there are three things worth noting. First, holding VC-backing constant, all-star coverage seems to be related to postIPO performance. That is, IPOs that receive all-star coverage seem to have better performance than those that do not. For example, within each of the four groups, “No All Star” returns range from -1.8 percent to 3.4 percent, while the range for all-stars varies from 2.4 to 72.3 percent. Second, holding research coverage constant, Top VC IPOs perform the best up to the lockup period. This result confirms the findings of Krishnan, Ivanov, Masulis and Singh (2010), which show that reputable VC-backed IPOs outperform. Finally, Top VCs take the hardest hit at lockup expiration. While several papers including Field and Hanka (2001) find large negative returns for VCs around lockup expiration, our results show there is a strong, incremental Top VC effect. Insert Figure 3 about here We graphically present the raw return to lockup expiration partitioned by type of analyst coverage and VC-backing in Figure 3. This graph clearly reiterates the results in Table 6 that Top VC-backed IPOs that receive all-star coverage outperform, but suffer the largest price
initiate coverage later than affiliated analysts. However, we do provide the impact of multiple all-stars on performance-related attributes.
19
declines around lockup expiration. To examine the returns in Table 6 more thoroughly, we estimate regressions in the next two tables. Insert Table 7 about here The dependent variable in Table 7 is the post-IPO performance leading up to the lockup expiration (calendar days [2, 177]). In the first model, we include VC and Top VC indicator variables and several other control variables. Top VC, Top Underwriter, Log (Assets) and Tech Firm are positive and significant while Underpricing and Log (Proceeds) are negative and significant. This model suggests that Top VC-backed IPOs generate an incremental 5.4 percent return up to the lockup period. In Model 2 we introduce lead, co-manager and unaffiliated all-star analyst coverage. Top VC remains significant at the 10 percent level. Unaffiliated star coverage is positive and significant and the other variables from Model 1 are essentially unchanged. In Model 3 we interact all-star coverage with VC status. Top VC loses its statistical significance, but Top VC interacted with lead-star coverage and unaffiliated coverage are positive and significant. Thus IPOs backed by Top VCs that receive all-star analyst coverage post IPO from either the lead investment bank or an unaffiliated investment bank generate stronger abnormal performance post-IPO leading up to the lockup expiration. If Top VCs want to prop the price up until they can cash out at lockup expiration, it is reasonable to assume that they are going to aggressively sell at the lockup expiration. Because venture capital firms distribute shares to limited partners that are not required to file with the SEC upon selling, it is not possible to examine directly the trading behavior of venture capital firms. Bradley, Jordan, Roten, and Yi (2001) and Field and Hanka (2001) find that VC-backed firms suffer the largest price decline on lockup expiration. This is consistent with the view that
20
these IPOs have aggressive selling. They also experience a spike in turnover. We also examine the market reaction around lockup expiration to proxy for selling aggressiveness. Taking our analysis one step further, we conjecture that Top VC-backed firms will experience an incremental impact beyond just VC-backing. Although the univariate results in Table 6 support our conjecture, we examine the robustness of this result in a multivariate framework. Insert Table 8 about here In Table 8, the dependent variable in the regression is the 5-day market adjusted return surrounding the lockup expiration. The independent variables of interest are indicators for VC backing, Top VC status, and variables related to all-star coverage. The remaining control variables have already been discussed in previous models. In the Full Sample model, the price reaction surrounding the lockup is strongly related to both VC and Top-VC backing. A Top VC exhibits an incremental -1.9 percent abnormal return over the 5-day window surrounding lockup expiration beyond the -1.7 abnormal return that VC-backed IPOs experience. Thus, holding all else constant, Top VC-backed IPOs experience approximately an incremental -4 percent abnormal return during the lockup window. Although the coefficients are negative in each subperiod, most of this effect is attributed to the bubble period. During the bubble period, Top VCbacked IPOs experience a -5.7 percentage point abnormal return relative to non-VC-backed IPOs. Analyst coverage of any type does not mitigate the price drop.9
E.
All-Star coverage in exchange for underwriting mandates? Our third prediction centers on the use of star analyst coverage as a means of gaining
future investment-banking mandates. The literature has focused on the relationship between 9
We also examine the interaction of VC and all-star status and do not find significant results. That is, all-star coverage does not mitigate the lockup period return.
21
investment banks and issuing firms. For example, Krigman, Shaw and Womack (2001) and Cliff and Denis (2004) each examine why firms switch underwriters. They find that firms are more likely to retain a lead underwriter for the first SEO if they have provided research coverage. We examine the provision of all-star analyst coverage as a “good” for the venture capital firm rather than the issuing company. Thus, when an investment bank provides all-star coverage to an IPO, they are doing so to curry favor with the venture capital firm who will likely be bringing more IPOs to market. We now test whether the provision of all-star analyst coverage to a prior VCbacked IPO increases the likelihood of being selected as a lead manager on the next IPO brought to market by the VC firm. Insert Table 9 about here In Table 9 we estimate two logistic models where the dependent variable is equal to one if the underwriter is chosen as a lead of an IPO and zero otherwise. For the lead model (Model 1), the dependent variable equals one if the VC firm stays with the same lead bank, and zero otherwise. For the co-manager model (Model 2), the dependent variable equals one if the VC firms switches, and zero otherwise. The independent variables of interest are Lag Lead Star, an indicator equal to one if the investment bank provided an all-star analyst as the lead bank on the last VC deal and zero otherwise; and Lag Co Mgr Star, an indicator equal to one if the investment bank provided an all-star analyst and was a co-managing underwriter on the last VC deal and zero otherwise. We control for top underwriter, Top VC, firm and issue size, technology status, the number of days between the VC’s last deal, industry, and include an indicator variable representing the bubble period. The model is estimated for the 1,037 VC-backed IPOs where the VC was involved in at least two IPOs.10 10
We restrict this analysis to deals where a VC is the lead VC in at least 2 deals so that the VC must choose to stay or switch underwriters in the subsequent deal. If we do not require this restriction, our results are stronger.
22
As can be seen in Table 9, the probability of becoming the lead investment bank on the next deal brought public by a venture capital firm is strongly related to the past provision of allstar coverage to IPOs of that venture capital firm. The results are significant regardless of the affiliation of the all-star analyst to the prior deal. That is, Lag Lead Star and Lag Co Mgr Star are each significant. This relationship is not restricted to Top VC firm deals. We find that for the sub-sample of VC-backed IPOs, prior all-star coverage helps gets an investment bank the lead on the next VC-backed IPO, regardless of the quality of the VC.
V.
Concluding Thoughts Our primary objective in this paper was to examine the relationships that exist between
venture capital firms and investment banks. We depart from the literature and explore the notion that investment banks provide all-star coverage to curry favor with venture capitalists rather than issuing firms. We focus on top venture capital firms because they have the ability to direct the most business in a repeated game sense to banks that treat them well. We conjecture that firms use all-star coverage either to win a current investment banking deal or to increase the likelihood of receiving future underwriting mandates from the VC firm, not the issuing firm. We argue that the relationship between venture capital firms and investment banks extends through time and therefore incentives extend beyond the current IPO. This line of thought led to several empirical predictions supported by the data. We find that because of the importance of top venture capital firms in providing a continuous stream of business to investment banks, IPOs backed by top venture capital firms are more likely to receive all-star analyst coverage post-IPO. This coverage is not contingent on bank affiliation at the time of the IPO because all banks wish to make Top VCs happy to potentially reap future business.
23
We find that IPOs backed by top venture capital firms are significantly more underpriced, regardless of the affiliation of the underwriter. We generally find post-IPO performance leading up to the lockup period is better for Top VCs that receive all-star coverage, but find Top VC backed IPOs suffer a larger price decline around the lockup expiration consistent with the view that they are selling aggressively at this time. We also demonstrate that the probability of becoming a lead underwriter is positively related to the past provision of all-star coverage to IPOs backed by venture capital firms. Overall, our results suggest that large, reputable VC firms play a critical role in the IPO market.
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References Aggarwal, Rajesh K., Laurie Krigman, and Kent L. Womack, 2002, Strategic IPOs Underpricing, Information Momentum, and Lockup Expiration Selling, Journal of Financial Economics 66, 105-137. Bradley, Daniel J., Bradford D. Jordan, Ivan C. Roten, and Ha-Chin Yi, 2001, Venture Capital and IPO Lockup Expiration: An Empirical Analysis, Journal of Financial Research 24. Bradley, Daniel J., Bradford D. Jordan, and Jay R. Ritter, 2003, The Quiet Period Goes out with a Bang, The Journal of Finance 58, 1-36. Carter, Richard, and Steven Manaster, 1990, Initial Public Offerings and Underwriter Reputation, The Journal of Finance 45, 1045-1067. Chemmanur, Thomas J., and Elena Loutskina, 2006, The Role of Venture Capital Backing in Initial Public Offerings: Certificaton, Screening or Market Power? Boston College working paper. Clarke, Jonathan, Ajay Khorana, Ajay Patel, and P. Raghavendra Rau, 2007, The Impact of Allstar Analyst Job Changes on their Coverage Choices and Investment Banking Deal Flow, Journal of Financial Economics 84, 713-737. Cliff, Michael T., and David J. Denis, 2004, Do Initial Public Offering Firms Purchase Analyst Coverage with Underpricing?, The Journal of Finance 59, 2781-2901. Degeorge, Francois, Francois Derrien, and Kent Womack, 2007, Analyst Hype in IPOs: Explaining the Popularity of Bookbuilding, Review of Financial Studies 20, 1021-1058. Dunbar, Craig G., 2000, Factors Affecting Investment Bank Initial Public Offering Market Share, Journal of Financial Economics 55, 3-41. Fang, Lily and Ayako Yasuda, 2009, The Effectiveness of Reputation as a Disciplinary Mechanism in Sell-side Research, Review of Financial Studies 22, 3735-3777. Field, Laura Casares, and Gordon Hanka, 2001, The Expiration of IPO Share Lockups, The Journal of Finance 56, 471-500. Fernando, Chitru S., Vladimir A. Gatchev, and Paul A. Spindt, 2005, Wanna Dance? How Firms and Underwriters Choose Each Other, The Journal of Finance 60, 2437-2469. Gompers, Paul, Anna Govner, Josh Lerner, and David Scharfstein, 2010, Performance Persistence in Entrepreneurship, Journal of Financial Economics 96, 18-32. Hanley, Kathleen Weiss, 1993, The Underpricing of Initial Public Offerings and the Partial Adjustment Journal of Financial Economics 34, 231-250. 25
Hao, (Grace) Qing, 2007, Laddering in Initial Public Offerings, Journal of Financial Economics 85, 102-122. Hoberg, Gerard, and Hasan Nejat Seyhun, 2010, Do Underwriters Collaborate with Venture Capitalists in IPOs? Implications and Evidence, AFA 2006 Boston Meetings Paper. Krigman, Laurie, Wayne H. Shaw, and Kent L. Womack, 2001, Why Do Firms Switch Underwriters?, Journal of Financial Economics 60, 245-284. Krishnan, C. N. V., Vladimir I. Ivanov, Ronald W. Masulis, and Ajai K. Singh, 2010, Venture Capital Reputation, Post-IPO Performance and Corporate Governance, Journal of Financial and Quantitative Analysis (JFQA), Forthcoming. Lee, Peggy M., and Sunil Wahal, 2004, Grandstanding, Certification and the Underpricing of Venture Capital Backed IPOs, Journal of Financial Economics 73, 375-407. Liu, Xiaoding, and Jay R. Ritter, 2010a, The Economic Consequences of IPOs Spinning, Review of Financial Studies 23, 2024-2059. Liu, Xiaoding, and Jay R. Ritter, 2010b, Local Underwriter Oligopolies and IPOs Underpricing, Forthcoming, Journal of Financial Economics. Ljungqvist, Alexander, Felicia Marston, and William J. Wilhelm Jr, 2006, Competing for Securities Underwriting Mandates: Banking Relationships and Analyst Recommendations, The Journal of Finance 61, 301-340. Ljungqvist, Alexander, Felicia Marston, and William J. Wilhelm Jr, 2009, Scaling the Hierarchy: How and Why Investment Banks Compete for Syndicate Co-Management Appointments, Review of Financial Studies 22, 3977-4007. Loughran, Tim, and Jay R. Ritter, 2004, Why Has IPOs Underpricing Changed over Time?, Financial Management 33, 5-37. Malloy, ChrisTopher J., 2005, The Geography of Equity Analysis, The Journal of Finance 60, 719-755. Megginson, William L., and Kathleen A. Weiss, 1991, Venture Capitalist Certification in Initial Public Offerings, The Journal of Finance 46, 879-903. Nahata, Rajarishi, 2008, Venture Capital Reputation and Investment Performance, Journal of Financial Economics 90, 127-151. Rajan, Raghuram, and Henri Servaes, 1997, Analyst Following of Initial Public Offerings, The Journal of Finance 52, 507-529.
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Ritter, Jay R., and Donghang Zhang, 2007, Affiliated Mutual Funds and the Allocation of Initial Public Offerings, Journal of Financial Economics 86, 337-368.
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Table 1 Summary statistics This table provides summary statistics for our sample of 3,981 IPOs during 1994-2007. Panel A presents total assets after the IPO (in $millions), proceeds raised in the IPO (in $millions), firm age at the IPO, pre-IPO price revision ([offer price – mid-price of original file range]/ mid-price of original file range), underpricing ([first day close – offer price]/offer price), and high-tech status. Panel B provides sample characteristics on underwriter, VC status, and all-star analyst coverage post-IPO. The percentage of IPOs that are backed by a top underwriter (as measured by the Carter-Manaster ranking of 8 or 9), VC, and top VC are presented. Also included are the percentage of IPOs that receive all-star analyst coverage post-IPO from a lead, co-manager or unaffiliated investment bank. We provide statistics for the full sample and partitioned by time period.
Full Sample (N=3,981) Mean Median
Pre-Bubble (N=1,994) Mean Median
Bubble (N=1,129) Mean Median
Post-Bubble (N=858) Mean Median
Panel A Assets Proceeds Firm Age Price Revision Underpricing High Tech Company
745.11 107.42 14.61 2.20% 25.79% 50.59%
343.78 52.75 13.61 -0.20% 15.79% 47.39%
752.7 119.63 11.22 10.57% 53.85% 59.43%
1667.8 218.41 21.41 -4.00% 12.11% 46.39%
Panel B Back by Top Underwriter Backed by VC Backed by Top VC Lead Star Analyst Coverage Co-Manager Star Analyst Coverage Unaffiliated Star Analyst Coverage
66.92% 39.36% 15.47% 20.40% 14.92% 7.79%
49.20 46.50 7.00 0.00% 11.03% 100.00%
59.28% 35.06% 12.49% 14.44% 13.34% 6.77%
46.59 31.20 7.00 0.00% 9.62% 0.00%
74.14% 50.13% 22.59% 24.27% 18.25% 9.21%
29.61 56.00 5.00 6.25% 22.73% 100.00%
75.17% 35.20% 13.05% 29.14% 14.22% 8.28%
138.54 100.78 10.00 0.00% 6.93% 0.00%
Table 2 Descriptive Statistics Partitioned by VC status This table provides sample characteristics for 3,981 IPOs during 1994-2007 partitioned by venture capital status. The data is then partitioned by time period. We include mean and median values for underpricing ([first day close – offer price]/offer price), pre-IPO price revision ([offer price – mid-price of original file range]/ mid-price of original file range), and the market adjusted 5-day CAR around the lock-up expiration (180 calendar days after the IPO). Also presented is the percentage of IPOs that receive all-star analyst coverage post-IPO from a lead, co-manager or unaffiliated investment bank and percentage of IPOs that are backed by a top underwriter (as measured by the Carter-Manaster ranking of 8 or 9). Full sample and sub-period statistics are provided. Top VC Full Sample Underpricing Price Revision Lock Up Expiration CAR Lead All Star Co-Manager All Star Unaffiliated All Star Top Tier Underwriter Pre-Bubble Underpricing Price Revision Lock Up Expiration CAR Lead All Star Co-Manager All Star Unaffiliated All Star Top Tier Underwriter Bubble Underpricing Price Revision Lock Up Expiration CAR Lead All Star Co-Manager All Star Unaffiliated All Star Top Tier Underwriter Post-Bubble Underpricing Price Revision Lock Up Expiration CAR Lead All Star Co-Manager All Star Unaffiliated All Star Top Tier Underwriter
Mean N = 614 56.14% 13.01% -4.67% 26.06% 14.33% 9.45% 86.81% N = 249 24.35% 7.03% -3.40% 12.85% 10.04% 4.82% 84.34% N = 254 104.57% 27.94% -6.55% 37.80% 20.47% 15.35% 90.16% N = 111 16.64% -7.75% -3.23% 28.83% 9.91% 6.31% 84.68%
VC
Median 23.25% 7.85% -4.43%
13.89% 6.25% -3.46%
65.56% 21.53% -6.99%
11.76% -6.67% -2.80%
Mean N= 953 27.48% 2.03% -2.63% 15.84% 10.07% 6.09% 72.19% N =450 15.51% -0.33% -2.40% 13.78% 9.56% 5.33% 66.89% N = 312 52.90% 9.30% -3.20% 17.95% 11.54% 5.77% 79.17% N = 191 14.16% -4.30% -2.26% 17.28% 8.90% 8.38% 73.30%
No VC Median 12.50% 0.00% -2.33%
7.32% 0.00% -1.82%
29.20% 7.69% -4.21%
9.78% 0.00% -2.13%
Mean N = 2,414 17.41% 0.49% -0.59% 20.75% 16.98% 8.04% 59.78% N = 1,295 14.24% -1.53% -0.81% 14.82% 15.13% 7.56% 51.26% N = 563 31.52% 4.48% -0.69% 21.67% 20.96% 8.35% 64.12% N = 556 10.51% -3.04% 0.06% 33.27% 16.91% 8.63% 73.92%
Median 8.93% 0.00% -0.64%
9.38% 0.00% -0.71%
11.11% 0.00% -1.31%
6.37% 0.00% 0.16%
Table 3 Probability of Receiving All-Star Coverage This table presents a two-stage probit analysis where the probability of receiving all-star coverage is modeled. In the first stage, the dependent variable is 1 if the IPO is backed by a top VC. Independent variables include a dummy variable equal to one if the firm is headquartered in California, a dummy variable equal to one if the IPO is internetrelated, the natural log of assets at the time of the IPO, a dummy variable equal to one if the IPO is technologyrelated, a dummy variable equal to one if the IPO is backed by a top underwriter, and firm age. In the second stage, the dependent variable is a dummy variable equal to one if the IPO firm received all-star coverage. In addition to the independent variables in the first stage, the inverse mills ratio from the first stage is included, a dummy variable equal to one if the IPO went public between 1998-2000 (Bubble), the natural log of IPO proceeds, IPO underpricing, and indicator variables equal to one if the IPO is backed by a venture capitalist (VC-backed) or a top venture capitalist (Top VC-backed). Stage 1: Pr (Top VC) Full Sample Intercept California Internet Log (Assets) Tech Top Underwriter Firm Age
-2.611 (0.0001) 1.094 (0.0001) 0.645 (0.0001) -0.153 (0.0001) 0.966 (0.0001) 1.442 (0.0001) -0.344 (0.0001)
Bubble Log (Proceeds) Underpricing VC-Backed Top VC-Backed
18.71% 3,975
Bubble
Model 1 -14.091 (0.0001)
Model 2 -14.125 (0.0001)
Model 3 -13.607 (0.0001)
Model 4 -13.683 (0.0001)
Model 5 -15.002 (0.0001)
Model 6 -15.053 (0.0001)
0.231 (0.0001) -0.240 (0.0071) 1.962 (0.0001) -0.010 (0.8280) 0.248 (0.0120) 0.599 (0.0001) 0.004 (0.0001) -0.103 (0.3298) 0.338 (0.0063)
0.243 (0.0001) -0.322 (0.0022) 1.878 (0.0001) 0.013 (0.7854) 0.229 (0.0215) 0.596 (0.0001) 0.004 (0.0001) -0.108 (0.3061) 0.912 (0.0260) -0.346 (0.1417)
0.532 (0.0001) -0.172 (0.1282) 2.235 (0.0001) 0.029 (0.5633)
0.271 (0.0001) -0.265 (0.0643) 2.159 (0.0001) 0.046 (0.3873)
0.132 (0.0180) -0.310 (0.0478) 0.003 (0.0005) -0.095 (0.3050)
0.132 (0.0178) -0.350 (0.0361) 1.804 (0.0001) -0.068 (0.4991)
0.532 (0.0001) 0.007 (0.0043) -0.022 (0.8705) 0.006 (0.9714)
0.531 (0.0001) 0.007 (0.0058) -0.026 (0.8468) 0.608 (0.3040) -0.359 (0.2896)
0.696 (0.0001) 0.003 (0.0005) -0.422 (0.0246) 0.669 (0.0004)
0.696 (0.0001) 0.003 (0.0012) -0.433 (0.0217) 1.080 (0.0645) -0.237 (0.4881)
26.24% 3,975
26.28% 3,975
27.45% 2,846
27.49% 2,846
21.28% 1,129
21.31% 1,129
Inverse Mills Ratio
Pseudo Adj R2 N
Stage 2: Pr(All-Star Coverage) Non-Bubble
Table 4 Underpricing Regressions This table provides a two-stage analysis where underpricing is modeled. In the first stage, a probit regression models the probability of all-star coverage from lead, co-manager or unaffiliated analysts. Independent variables include indicator variables equal to one if the IPO is backed by a venture capitalist (VC) or a top venture capitalist (Top VC), or a top underwriter, the natural log of IPO proceeds, the natural log of assets at the time of the IPO, a dummy variable equal to one if the IPO is technologyrelated, firm age, and indicator variables to control for the bubble and post-bubble periods. In the second stage, OLS regressions are used to model underpricing. In addition to some of the variables in the first stage, we also include the pre-IPO price revision ([offer price – mid-price of original file range]/ midprice of original file range), a dummy variable equal to one if the IPO is internet-related, a dummy variable equal to one if the lead underwriter provided all-star coverage on the VCs last IPO (Lag Star Coverage), the predicted values from the first stage model (Pr (Lead, Co-Mgr, and Unaff all-star) and interactions between VC, Top VC and the predicted all-star coverage variables. Panel A: Probit Estimation of All-Star Coverage
Intercept Top VC VC Top Underwriter Log (Proceeds) Log (Assets) Tech Firm Age Bubble Post Bubble Pseudo Adj R2 N
Pr(Lead all-star coverage) -11.361 (0.0001) 0.465 (0.0005) -0.169 (0.1569) 2.222 (0.0001) 0.426 (0.0001) 0.106 (0.0060) -0.130 (0.1744) -0.038 (0.4114) 0.322 (0.0043) 0.179 (0.1414) 25.99% 3,981
Pr(Co-manager all-star coverage) -19.729 (0.0001) 0.280 (0.0939) -0.122 (0.3881) 1.798 (0.0001) 0.887 (0.0001) 0.144 (0.0013) -0.127 (0.2567) 0.083 (0.1117) -0.103 (0.4220) -1.454 (0.0001) 31.61% 3,981
Pr(Unaffiliated all-star coverage) -14.543 (0.0001) 0.440 (0.0278) 0.188 (0.2904) 1.172 (0.0001) 0.586 (0.0001) 0.179 (0.0014) -0.275 (0.0521) -0.075 (0.2474) -0.095 (0.5541) -0.810 (0.0001) 17.96% 3,981
Panel B: OLS Regression of IPO Underpricing Variable Intercept Price Revision Top Underwriter Log(Proceeds) Tech Firm Internet Firm Bubble Post-Bubble VC
(1) 65.053 (0.0001) 0.980 (0.0001) 5.227 (0.0011) -3.303 (0.0001)
(2) 62.621 (0.0001) 0.962 (0.0001) 4.390 (0.0053) -3.111 (0.0001)
(3) 61.263 (0.0001) 0.962 (0.0001) 4.206 (0.0084) -3.038 (0.0001)
(4) 98.591 (0.0001) 0.961 (0.0001) -0.777 (0.7570) -5.311 (0.0001)
4.905 (0.0002) 23.019 (0.0001) 18.675 (0.0001) 2.110 (0.2500) 5.648 (0.0001)
4.614 (0.0004) 22.443 (0.0001) 18.567 (0.0001) 1.888 (0.3004)
4.435 (0.0008) 22.308 (0.0001) 18.522 (0.0001) 1.831 (0.3158) 1.073 (0.4885) 13.300 (0.0001)
5.263 (0.0001) 22.537 (0.0001) 17.727 (0.0001) 1.273 (0.4883) 2.473 (0.1319) 11.284 (0.0001) 28.984 (0.0102)
Top VC
13.929 (0.0001)
Pr(Lead All Star) VC * Pr(Lead All Star) Top VC * Pr(Lead All Star)
Model (5) 66.590 (0.0008) 0.923 (0.0001) 0.584 (0.8210) -3.252 (0.0064) 5.698 (0.0001) 20.273 (0.0001) 16.846 (0.0001) 0.368 (0.8409) 0.038 (0.9881) -15.290 (0.0004) 4.943 (0.6688) 11.039 (0.3959) 108.416 (0.0001)
Pr(Co-Mgr All Star)
(6) 67.510 (0.0013) 0.962 (0.0001) 3.996 (0.0180) -3.421 (0.0069)
(7) 58.817 (0.0046) 0.901 (0.0001) 3.555 (0.0353) -2.822 (0.0245)
(8) 70.916 (0.0003) 0.963 (0.0001) 4.007 (0.0136) -3.632 (0.0020)
(9) 55.271 (0.0045) 0.921 (0.0001) 3.606 (0.0267) -2.627 (0.0253)
4.506 (0.0007) 22.371 (0.0001) 18.604 (0.0001) 2.327 (0.2986) 1.215 (0.4457) 13.223 (0.0001)
5.596 (0.0001) 20.233 (0.0001) 17.627 (0.0001) 2.883 (0.1954) -1.281 (0.5482) -6.500 (0.0421)
4.656 (0.0006) 22.372 (0.0001) 18.679 (0.0001) 2.488 (0.2297) 1.107 (0.4753) 13.014 (0.0001)
5.607 (0.0001) 20.399 (0.0001) 18.058 (0.0001) 2.195 (0.2868) -0.500 (0.8213) -5.839 (0.0958)
3.037 (0.7019)
-7.901 (0.3184) 20.705 (0.1383) 141.335 (0.0001) 9.205 (0.5020)
-15.354 (0.2734) 23.904 (0.3537) 203.142 (0.0001) 43.37% 3,981
VC * Pr(Co-Mgr All Star) Top VC * Pr(Co-Mgr All Star) Pr(Unaff All Star) VC * Pr(Unaff All Star) Top VC * Pr(Unaff All Star) Adj R2 N
41.88% 3,981
42.50% 3,981
42.49% 3,981
42.58% 3,981
43.56% 3,981
42.48% 3,981
43.86% 3,981
42.49% 3,981
Table 5 Underpricing OLS Regressions by Time Period This table provides OLS regressions where the dependent variable is IPO Underpricing. Regressions are partitioned by time period. Models 1-4 in Panel A include the pre-bubble period (1994-1997), models 5-8 in Panel B include the bubble period (1998-2000), and models 9-12 in Panel C contain the post-bubble period (2001-2007). To conserve space, we only present the variables of interest. See Table 4 for a full description of the independent variables.
(1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
(10)
(11)
(12)
VC -0.387
TOPVC 4.208
(0.7132)
(0.0051)
Pr(Lead Star)
VC*Pr (Lead star)
TOPVC*Pr (Lead star)
Pr(Comgt Star)
VC*Pr(Comgt Star)
TOPVC* Pr(Comgt Star)
Pr(Unaff Star)
VC* Pr(Unaff Star)
TOPVC* Pr (Unaff Star)
Panel A: Pre-Bubble
-2.679
-7.315
14.523
24.970
49.493
(0.1085)
(0.0262)
(0.1524)
(0.0211)
(0.0044)
-1.671
-6.205
6.277
16.023
84.392
(0.2421)
(0.0167)
(0.2655)
(0.0834)
(0.0001)
-1.724
-6.281
15.087
22.532
115.692
(0.2413)
(0.0287)
(0.1761)
(0.1816)
(0.0002)
6.227
22.881
(0.1751)
(0.0001)
Panel B: Bubble
4.220
-10.448
-70.383
-7.584
132.612
(0.6395)
(0.4469)
(0.0697)
(0.8466)
(0.0085)
0.558
2.671
-59.476
12.872
120.254
(0.9390)
(0.7874)
(0.0150)
(0.7596)
(0.0238)
3.543
3.862
-76.624
23.540
185.628
(0.6270)
(0.7057)
(0.0449)
(0.7723)
(0.0574)
2.487
4.387
(0.0993)
(0.0205)
Panel C: Post-Bubble
-2.062
2.416
-11.798
20.139
3.543
(0.4258)
(0.5647)
(0.2991)
(0.0664)
(0.8191)
-0.629
5.825
-9.663
43.674
-27.772
(0.7349)
(0.0212)
(0.1840)
(0.0086)
(0.2749)
-0.468
5.696
-17.222
60.401
-34.587
(0.8153)
(0.0485)
(0.1644)
(0.0231)
(0.3610)
Adj R2 26.37%
N 1994
27.44%
1994
27.74%
1994
27.37%
1994
44.00%
1,129
44.44%
1,129
44.63%
1,129
44.45%
1,129
25.64%
858
26.03%
858
26.16%
858
25.99%
858
Table 6 Post-IPO Performance This table provides data on post-IPO performance partitioned by VC status and all-star analyst affiliation. Avg Time to initiate is the average number of days from the IPO until all-star analysts initiate research coverage, Avg Ratings is the mean recommendation rating level, where 1 is a strong buy and 5 a sell. Performance to lockup expiration is the buy-and-hold abnormal return calculated over calendar days (2,178). Lockup expiration is the market-adjusted return over the 5-day (-2,+2)-day window. Both returns use the CRSP NYSE/Nasdaq/Amex value-weighted index. We include research coverage initiations only for the first 180 days post-IPO. VC status
All-Star Affiliation
No All Star Lead
No VC
Co-manager Unaffiliated Multiple All Stars
No All Star Lead
VC
Co-manager Unaffiliated Multiple All Stars
No All Star Lead Top VC
Avg time to initiate
Avg Ratings
Performance to Lockup Expiration
Lockup Expiration (-2,+2)
1558
n.m.
n.m.
-1.78%
-0.58%
(0.1706)
(0.0130)
406
48.84
1.77
4.01%
-0.20%
(0.0757)
(0.5466)
Obs
337 78
168
683 130 83 20
30
367
49.29 85.25
n.m.
n.m. 44.19 52.10 99.75
n.m.
n.m.
1.86 2.00
n.m.
n.m. 1.79 1.89 2.00
n.m.
n.m.
146
43.39
1.95
Co-manager
75
42.88
1.80
Unaffiliated
25
101.96
1.92
Multiple All Stars
40
n.m.
n.m.
3.39%
-0.30%
(0.2668)
(0.4869)
18.07%
-0.49%
(0.0011)
(0.5539)
2.42%
0.52%
(0.4026)
(0.3104)
2.76%
-2.85%
(0.3512)
(0.0001)
3.97%
-2.58%
(0.5494)
(0.0038)
8.05%
0.79%
(0.4656)
(0.5318)
11.18%
-1.73%
(0.4777)
(0.5361)
7.11%
-1.94%
(0.4018)
(0.3200)
3.35%
-3.98%
(0.4380)
(0.0001)
19.54%
-5.49%
(0.0267)
(0.0001)
21.69%
-5.11%
(0.0917)
(0.0019)
72.28%
-4.53%
(0.0640)
(0.0624)
22.79%
-4.08%
(0.1973)
(0.0681)
Table 7 OLS Regressions of Abnormal Performance This table provides OLS regressions where the dependent variable is the performance to lockup expiration is the buy-and-hold abnormal return calculated over calendar days (2,177) using the CRSP NYSE/Nasdaq/Amex value-weighted index. Independent variables include indicator variables equal to one if the IPO is backed by a venture capitalist (VC) or a top venture capitalist (Top VC), all-star coverage provided by a lead, co-manager, or unaffiliated analyst (Lead Star Coverage, Co Mgr Star Coverage, or Unaffiliated Star Coverage), and interactions between VC and Top VC and Lead Star Coverage, Co Mgr Star Coverage, and Unaffiliated Star Coverage. We also include an indicator variable equal to one if the IPO firm has a top underwriter, underpricing ([first day close – offer price]/offer price), the natural log of proceeds raised in the IPO, the natural log of total assets at the time of the IPO, an indicator variable equal to one if the IPO is technology-related, firm age, and an indicator variable equal to one to control for the bubble period. Model (1) Coefficient p-value
Model (2) Coefficient p-value
Model (3) Coefficient p-value
Intercept
0.427
(0.7997)
0.532
(0.0079)
0.514
(0.0104)
VC
-0.021
(0.3453)
-0.019
(0.4004)
-0.018
(0.4699)
Top VC
0.054
(0.0635)
0.049
(0.0918)
0.000
(0.9968)
0.040
(0.1047)
0.025
(0.4256)
VC *Lead Star
-0.035
(0.5563)
Top VC * Lead Star
0.149
(0.0445)
-0.025
(0.4731)
VC * Co Mgr Star
0.047
(0.4985)
Top VC * Co Mgr Star
0.076
(0.4048)
0.149
(0.0142)
VC * Unaffiliated Star
-0.049
(0.7188)
Top VC * Unaffiliated Star
0.311
(0.0595)
Lead Star Coverage
Co Mgr Star Coverage
0.005
Unaffiliated Star Coverage
0.195
(0.8695)
(0.0001)
Top Underwriter
0.124
(0.0001)
0.116
(0.0001)
0.121
(0.0001)
Underpricing
-0.001
(0.0275)
-0.001
(0.0003)
-0.001
(0.0001)
Log(Proceeds)
-0.035
(0.0010)
-0.041
(0.0014)
-0.040
(0.0018)
Log(Assets)
0.021
(0.0056)
0.018
(0.0204)
0.020
(0.0117)
Tech Firm
0.090
(0.0066)
0.091
(0.0001)
0.094
(0.0001)
Firm Age
-0.007
(0.4714)
-0.006
(0.5085)
-0.005
(0.5925)
Bubble
0.022
(0.3035)
0.023
(0.2854)
0.022
(0.3032)
Adj R2 N
1.73% 3,978
2.13% 3,978
2.34% 3,978
Table 8 OLS Regressions of Lockup Expiration Return This table provides OLS regressions where the dependent variable is the 5-day market-adjusted return over the 5-day (-2,+2)-day window using the CRSP NYSE/Nasdaq/Amex value-weighted index. Independent variables include indicator variables equal to one if the IPO is backed by a venture capitalist (VC) or a top venture capitalist (Top VC), a top underwriter, and all-star coverage provided by a lead, comanager, or unaffiliated analyst (Lead Star Coverage, Co Mgr Star Coverage, or Unaffiliated Star Coverage). We also include the natural log of proceeds raised in the IPO, the natural log of total assets at the time of the IPO, an indicator variable equal to one if the IPO is technology-related, firm age, and an indicator variable equal to one to control for the bubble period.
Intercept VC Top VC Top Underwriter Lead Star Coverage Co Mgr Star Coverage Unaffiliated Star Coverage Log(Proceeds) Log(Assets) Tech Firm Firm Age Bubble Adj R2 N
Full Sample
PreBubble
Bubble
PostBubble
-0.106 (0.0033) -0.017 (0.0001) -0.019 (0.0003) -0.007 (0.0845) -0.002 (0.6094) 0.000 (0.9406) 0.001 (0.8708) 0.006 (0.0057) 0.000 (0.8314) -0.004 (0.2551) -0.001 (0.5762) -0.010 (0.0060)
-0.038 (0.4520) -0.013 (0.0037) -0.008 (0.2047) -0.006 (0.2025) -0.003 (0.5993) -0.006 (0.3414) 0.005 (0.6389) 0.001 (0.7050) 0.004 (0.0297) -0.002 (0.5980) -0.001 (0.4420)
-0.179 (0.0724) -0.024 (0.0200) -0.033 (0.0052) -0.006 (0.5902) 0.002 (0.8305) -0.002 (0.8915) 0.013 (0.5722) 0.011 (0.0778) -0.004 (0.1816) -0.006 (0.4945) 0.003 (0.5871)
-0.127 (0.0695) -0.019 (0.0058) -0.008 (0.3589) -0.011 (0.0867) -0.004 (0.5004) 0.017 (0.0384) -0.016 (0.2362) 0.009 (0.0399) -0.002 (0.3047) -0.009 (0.1411) -0.004 (0.1533)
2.55% 3,969
1.46% 1,992
2.35% 1,122
4.22% 855
Table 9 VC Underwriter Switching Models This table provides logistic regressions where the dependent variable is 1 if an investment bank is selected as lead underwriter on a deal, and zero otherwise. In model 1, the dependent variable is equal to one if the VC firm stayed with same underwriter in its subsequent IPO. In specification 2, the dependent variable is equal to one if the VC firm switched underwriters in its subsequent IPO. Independent variables include indicator variables equal to one if the IPO is backed by a top VC, if all-star coverage was provided by the lead or co-manager on the current IPO (Lead Star or Co Mgr Star) or on the VCs prior IPO (Lag Lead Star or Lag Co Mgr Star). We include an indicator variable equal to one if the IPO has a top underwriter, the natural log of total assets at the time of the IPO, the natural log of proceeds raised, an indicator variable equal to one if the IPO is technology-related, firm age, the natural log of the number of days in between the VCs current IPO and its last IPO, an indicator variable equal to one if the VCs last IPO is in the same industry as the current IPO, and an indicator variable to control for the bubble period. Model (1) Coefficient p-value -7.428 (0.5034)
Intercept
Model (2) Coefficient p-value -4.919 (0.8667)
Top VC
-0.134
(0.5425)
-0.008
(0.9743)
Lead Star
0.443
(0.0677)
-0.786
(0.0426)
Lag Lead Star
0.825
(0.0003)
Co Mgr Star
-0.156
(0.7057)
Lag Co Mgr Star
1.019
(0.0004)
Top Underwriter
0.819
(0.0356)
-0.980
(0.0006)
Log (Asset)
0.032
(0.7540)
-0.006
(0.9611)
Log (Proceeds)
0.233
(0.2189)
0.164
(0.4630)
Tech
-0.272
(0.2841)
1.022
(0.0075)
Firm Age
0.124
(0.4959)
-0.001
(0.9944)
Log (days)
0.046
(0.4914)
-0.064
(0.4038)
Same Industry
0.352
(0.1546)
-0.267
(0.3457)
Bubble
-0.385
(0.1115)
-0.090
(0.7502)
2
Pseudo Adj R N
7.06% 1,037
10.00% 1,037
Figure 1 IPO Underpricing by Time Period and VC Status This figure plots average and median underpricing by time period (pre-bubble, bubble, and post-bubble) and VC status (No VC, VC, and Top VC).
Average IPO Underpricing 120.00% 100.00% 80.00% No VC
60.00%
VC 40.00%
Top VC
20.00% 0.00% Pre Bubble
Bubble
Post Bubble
Median IPO Underpricing 70.00% 60.00% 50.00% 40.00%
No VC
30.00%
VC Top VC
20.00% 10.00% 0.00% Pre Bubble
Bubble
Post Bubble
Figure 2 IPO Underpricing by All-Star Analyst Coverage and VC Status This figure plots average and median IPO underpricing by all-star coverage received post-IPO (No star, Lead star, Co-manager star, and unaffiliated star coverage) and VC status (No VC, VC, and Top VC).
Average IPO Underpricing 140.00% 120.00% 100.00% 80.00%
No VC
60.00%
VC Top VC
40.00% 20.00% 0.00% No Star
Lead Star
Co‐Mgr Star
Unaff Star
Median IPO Underpricing 70.00% 60.00% 50.00% 40.00%
No VC
30.00%
VC
20.00%
Top VC
10.00% 0.00% No Star
Lead Star
Co‐Mgr Star
Unaff Star
Figure 3 Post-IPO Performance and Lockup Expiration Return This figure plots average post-IPO performance by all-star coverage received post-IPO (No star, Lead star, Co-manager star, and unaffiliated star coverage) and VC status (No VC, VC, and Top VC). The top graph plots the raw return calculated over calendar days (2,178). The bottom graph plots the raw lockup expiration return over the 5-day (2,+2)-day window.
Mean Raw Return to Lock Expiration 90.00% 80.00% 70.00% 60.00% 50.00%
No VC
40.00%
VC
30.00%
Top VC
20.00% 10.00% 0.00% No Star
Lead Star
Co‐Mgr Star
Unaff Star
Mean Raw Return at Lock Expiration 1.00% 0.00% ‐1.00% ‐2.00%
No Star
Lead Star
Co‐Mgr Star
Unaff Star No VC VC
‐3.00% ‐4.00% ‐5.00% ‐6.00%
Top VC
