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How reverse merger firms raise capital in PIPEs: search costs and placement agent reputation

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Abstract

We examine the role of placement agents in private investments in public equity (PIPE) deals of firms that went public via a reverse merger (RM). We find that reputable placement agents with greater expertise (expert agents) help RM firms to complete their PIPE deals in a smaller number of financing rounds (closings) and raise funds from a larger base of private investors. In exchange for these benefits, RM firms advised by expert agents agree to more investor-friendly contract terms and pay higher cash compensation to their placement agents. Overall, our evidence indicates that, while expert PIPE agents use their superior networking capabilities to reduce the search costs of RM firms, they also exercise more bargaining power against RM firms compared to non-expert PIPE agents. Finally, compared to the PIPE offerings of IPO firms, the PIPE offerings of RM firms are more likely to involve deals with multiple closings and larger offer price discounts. This suggests that raising new capital in PIPEs entails significantly higher costs for RM firms than IPO firms.

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Notes

  1. IPO statistics are from Thomson Reuters SDC Platinum. Reverse merger statistics are from PrivateRaise.

  2. According to PrivateRaise and Thomson Reuters SDC Platinum, the total capital raised through PIPEs by RM firms during 2008–2015 is $8.01 billion, while the total capital raised through PIPEs by traditional IPO firms is $50.9 billion during the same period. In 2010, regulators started investigating RM firms traded in the U.S. and issued several alerts (PCAOB 2010, 2011a, b; SEC 2011).

  3. In our sample, about 77% of the PIPE deals are initiated within a year after the RM event, and the rest of the PIPE deals are simultaneously arranged with the RM. Since the shares of RM firms are mostly traded in OTC markets initially, public equity offerings (SEOs) are very rare. Only 10 out of 1346 RM firms in our sample conducted an SEO within a year after the RM transaction.

  4. For example, Trailblazer Resources, an RM firm, initially planned to raise $7.5 million in a private placement. The firm later increased its funding target to $10.0 million (see its PRE 14C proxy statement filed on June 27 of 2008 and DEF 14C proxy statement filed on September 24 of 2008). However, the firm managed to raise only $2.5 million and $2 million in its first and second closings, respectively. Finally, according to its 8-K filings, the firm completed its PIPE transaction by raising $6.37 million in total proceeds as of December of 2008 after four closings.

  5. We use these two complementary explanations to develop hypotheses about the benefits and costs associated with expert placement agents, respectively. In other words, they are not opposing alternatives to each other.

  6. The existing corporate finance literature also studies how the reputation of financial intermediaries affect their incentives for certification and information production about issuing firms: see, e.g., Klein and Leffler (1981), Beatty and Ritter (1986), Carter and Manaster (1990), Megginson and Weiss (1991), Chemmanur and Fulghieri (1994), and Fang (2005).

  7. Dai et al. (2010) show that reputable financial intermediaries are often able to charge a higher compensation to their issuing firm clients. Bengtsson and Dai (2014) argue that expert agents may help potentially biased PIPE issuers to understand the payoff consequences of complex (contingent) contract terms. Reputable placement agents and their investor clients may also set more stringent evaluation standards to screen good-quality RM issuers ex ante and use more investor-friendly (contingent) contract terms to provide better post-PIPE incentives to the issuers as well: see, e.g., Hertzel and Smith (1993), Gompers (1995), Kaplan and Stromberg (2003, 2004).

  8. This is consistent with previous studies documenting that reputable financial intermediaries reduce the information asymmetry between issuing firms and investors (Carter and Manaster 1990; Chemmanur and Fulghieri 1994; Logue et al. 2002; Fang 2005; Dai et al. 2010; Bengtsson and Dai 2014).

  9. Using a large sample of private placements in the U.S. market during the period of 2000-2017, Chuang (2020) shows that growth firms offer larger discounts to their investors relative to their mature and old counterparts.

  10. Our evidence suggests that, after controlling for factors that affect the endogenous matching between an RM firm and a reputable financial intermediary, the effects of an expert agent on the likelihood of a PIPE deal with multiple closings, investor base, and agent compensation still remain significant in our sample of RM firm PIPEs.

  11. Adjei et al. (2008), Gleason et al. (2008), and Lee et al. (2015) analyze the long-term performance of RM firms. Gleason et al. (2005) and Floros and Sapp (2011) study the market reaction to RM transactions. Floros and Shastri (2009) and Greene (2016) analyze differences in firm characteristics between RM firms and IPO firms.

  12. Gao et al. (2013) report that the number of initial public offerings (IPOs) in the United States dropped from an average of 310 IPOs per year during 1980–2000 to only 99 IPOs per year during 2001–2012. They attribute the low volume of IPOs during the last decade to the fact that an increasing number of small firms are acquired by large players due to economies of scope and the speed to the product market. Doidge et al. (2013) attribute the abnormally low US IPO activity to the rise of financial globalization. Ewens and Farre-Mensa (2019) argue that the deregulation of securities laws in the 1990 s has facilitated the process of raising capital privately and been a key driver of the decline in US IPOs.

  13. Consistent with an internal certification effect, Floros et al. (2019) find that insider participation in PIPE offerings is associated with lower PIPE discounts and improved future firm operating performance. Lee and Wu (2009) show that that the probability of making private placements increases with abnormal insider purchases and decreases with abnormal insider sales. See also the related study by Wu and Lee (2008) for a methodological contribution to testing the presence of asymmetric information in the private equity market.

  14. In a study of private equity placements by Taiwanese listed firms, Cheng et al. (2014) show that firms with long-term institutional investors receive significantly positive abnormal returns around the offering announcement. This suggests that private placement firms with long-term institutional investors acquire certification and monitoring-related benefits.

  15. PrivateRaise provides extensive data on PIPE deals, reverse mergers, venture capital financing, and special purpose acquisition companies.

  16. We hand-collect the information on the current exchange of these reverse merger firms by searching their 10-Ks filed to the SEC.

  17. In our sample of RM firm PIPEs, 281 deals out of 360 have only one agent, 56 have two agents, 16 have three agents, 7 have four agents.

  18. Our results do not change materially when we use alternative ranking criteria (total market share or average market share) and alternative cutoffs for identifying higher ranked agents (Expert Agent) in untabulated sensitivity analyses. Similarly, our results remain unchanged if we use rankings of placement agents in the year prior to the PIPE issue.

  19. As of 2015, the top 5 expert agents in our sample are: (1) Cowen and Company, LLC; (2) J.P. Morgan Chase & Co.; (3) Bank of America Corporation; (4) Cantor Fitzgerald & Co.; and (5) H.C. Wainwright & Co., Inc.

  20. See also the earlier studies by Brophy et al. (2009) and Chaplinsky and Haushalter (2010), who empirically analyze contract terms and returns to investors in PIPE transactions.

  21. Note that since multiple-closing deals constitute about 50% of our sample, the sample size in the regressions reported in columns (2) and (3) is reduced by about half.

  22. The PIPE offer price discount is measured as one minus the purchase/conversion price in the PIPE deal divided by the market stock price of the issuing firm prior to the PIPE closing date. See also “Appendix 1” for variable definitions.

  23. Information about investor identity is missing for 145 observations. Therefore, the sample size is smaller in this section.

  24. Our study emphasizes the other benefits RM issuers obtain when they are advised by expert agents in PIPE deals: reduced search costs of financing and greater speed of capital infusion in a smaller number of closings by having access to a larger network of accredited investors. Consistent with Bengtsson and Dai (2014), our results also suggest that, in PIPE deals with multiple closings, expert agents help to improve the pricing terms of RM issuers over multiple rounds.

  25. While the mean (median) size of the RM firms in our sample is $71.38 million ($29.76 million), the mean (median) size of the issuing firms in the sample of Bengtsson and Dai (2014) is $270 million ($90.9 million). The proportion of the sample firms trading on a national exchange (NYSE, Nasdaq, Amex) is over 50% in Bengtsson and Dai (2014), whereas the proportion of RM issuers trading on a national exchange is only 17.23% in our sample.

  26. In unreported results, we find that the average compensation for an agent advising an RM PIPE in our sample is about 6.5% of the offer size, which is similar in magnitude to the underwriter spreads of seasoned equity offerings (SEOs) and IPOs.

  27. Dai et al. (2010) who examine the PIPEs of more mature public firms have similar findings about agent compensation. Note that they require their PIPE sample to be covered by Compustat and CRSP, while the majority of our RM firms are not covered by these two databases.

  28. Ewens and Marx (2015) use a similar rationale and use the lagged number of acquisitions in a VC-backed startup firm’s industry as an instrument for executive replacement. They argue that exogenous shocks to the supply of executives in an industry might serve as a suitable instrument for executive replacements (the endogenous variable) in startups and is less likely to directly affect whether a startup can survive a struggling stage.

  29. We test hypothesis H1a only in this section, but not hypotheses H1b and H1c. This is because hypotheses H1b and H1c are only based on a subsample of multiple-closing PIPEs, and the size of the subsample is not large enough to estimate a Heckman two-stage model.

  30. The variable Lead Agent Rank is measured as the rank of the lead placement agent advising the PIPE deal based on the number of PIPE deals the agent advises in that PIPE year. The higher the value of this rank, the lower the placement agent’s reputation in the financial advisory market for PIPEs. We use the variable Lead Agent Rank instead of Expert Agent to make placement agents across all PIPE issuers comparable because of the large heterogeneity across the placement agents for RM firms and IPO firms. The PIPE placement agents of IPO firms have much higher rankings overall than those of RM firms. Therefore, we directly use the rankings of each agent in the PIPE market in our full sample.

  31. If the variable Lead Agent Rank is calculated based on the total market share or the average market share of each placement agent, our results remain similar.

  32. Conditional on the inclusion of warrants, the warrant strike price (in dollar terms) is significantly higher on average in IPO firm PIPEs than in RM firm PIPEs, suggesting a greater ownership dilution for RM firms.

  33. Crisis is a dummy variable that is equal to 1 if the firm raises PIPEs during the 2008–2009 crisis periods. Private Benefit is a dummy variable that is equal to 1 if and only if (1) the firm's industry is among top five CEO perk consumption industries (Rajan and Wulf 2006) and (2) the firm's industry has the CEO-Divisional Manager differential in the Rajan–Wulf perk consumption score that is greater than 1. The Herfindahl Index (HHI) is calculated as a sum of squares of the sales-based market share of all Compustat firms within the same three-digit SIC industry code, at the year of PIPE issuance. Mean Analyst Forecast Error is the average analyst forecast error within each three-digit industry, where analyst forecast error is calculated as the difference between analysts’ forecasted earnings (EPS) and firms’ actual earnings from IBES.

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Authors and Affiliations

  1. University of Texas at San Antonio, San Antonio, TX, 78249, USA

    Onur Bayar & Juan Mao

  2. Western University, London, ON, N6A 3K7, Canada

    Yini Liu

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  1. Onur Bayar
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  2. Yini Liu
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Appendices

Appendix 1

See Table 11.

Table 11 Variable definitions
Full size table

Appendix 2: An example of a multiple-closing PIPE deal of an RM firm

This is an example of a multiple-closing PIPE. The firm “MusclePharm Corporation” initially intended to raise up to $10 million, in later disclosed filings it adjusted this planned amount to $13.95 million. However, a week later it declared to decrease this planned amount to $13.65 million. In a press release following the final closing, the firm disclosed that it raised $12 million in total.

[Change in Funding Target]

  • In its S-1/A amended Registration Statement filed on 12/19/2012, Issuer disclosed that it is in the process of conducting a Registered Direct offering, on a “best efforts” basis through a placement agent (initially identified as Aegis Capital Corp.), of up to $10 million of its Series D Convertible Preferred Stock.

  • In its S-1/A amended Registration Statement filed on 12/26/2012, Issuer disclosed that it has UPSIZED the maximum amount it may raise under this Registered Direct offering from $10 million to $13.95 million (and intends to offer up to 1,500,000 shares of the Series D Preferred Stock).

  • In its S-1/A amended Registration Statement filed on 12/31/2012, Issuer disclosed that the Proposed maximum aggregate offering price of the offering has been slightly DOWNSIZED from $13.95 million to $13.65 million.

  • In a Form POS AM Post-Effective Amendment (to the S-1 registration described above) filed on 1/8/2013, Issuer disclosed that Aegis Capital Corp. has been removed as its placement agent and been replaced by GVC Capital (though the number of shares of Series D Preferred Stock to be offered remains at 1,500,000).

  • In its 424B4 Prospectus Supplement filed on 1/17/2013, Issuer disclosed pricing terms for this “best efforts” Registered Direct offering, indicating that a total of 1,500,000 shares of Series D Preferred Stock are to be offered at $8.00 per preferred share to raise up to $12 million in gross proceeds.

[Multiple Closings]

  • In a press release dated 1/28/2013, Issuer announced that this offering is being completed (or has been completed) in MULTIPLE Closings.

  • * Initial and 2nd Closings *

  • According to Issuer’s 8-K filing on 1/28/2013, the Initial Closing occurred on 1/22/2013 and the 2nd Closing occurred on 1/25/2013 (amounts of Preferred Stock issued at each Closing not indicated in this 8-K).

  • * Final Closing *

  • In a press release on 2/5/2013, Issuer announced that it has completed the final closing under this offering selling a total of 1,500,000 shares of its Series D Preferred Stock for $12.0 million in aggregate gross proceeds. Therefore, that issuer sold 988,375 shares of its Series D Preferred Stock in the Final Closing for gross proceeds of $7.9 million.

  • In its 8-K filing dated 2/6/2013, Issuer disclosed that the Final Closing was completed on 2/4/2013.

Appendix 3

See Table 12.

Table 12 Top 20 placement agents in the PIPE market in 2015
Full size table

Appendix 4

See Table 13.

Table 13 Descriptions of PIPE contract terms
Full size table

Appendix 5

See Tables 14, 15.

Table 14 Expert agents and long-run operating performance in RM PIPEs
Full size table
Table 15 Price discounts, and expert agents in RM PIPEs
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Bayar, O., Liu, Y. & Mao, J. How reverse merger firms raise capital in PIPEs: search costs and placement agent reputation. Rev Quant Finan Acc 56, 143–184 (2021). https://doi.org/10.1007/s11156-020-00889-7

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