Stage financing and syndication in the IPO underpricing of venture-backed firms: Venture capital and IPO underpricing

Abstract

The article investigates the impact of stage financing and syndication practices on the underpricing level of venture-backed firms (VBFs) undertaking their initial public offerings (IPOs). This empirical study uses a unique hand-collected data set concerning more than 260 VBFs that went public on Euronext Paris and Alternext between 1997 and 2013. Our findings suggest a lower level of underpricing for firms backed by syndicated venture capital investment. Additionally, we find that the syndicate size is negatively associated with the level of underpricing. However, there is no evidence that stage financing has a significant impact. Syndication thus appears to be the only relevant mechanism to improve IPO performance (measured by the underpricing level), as it reduces agency costs and information asymmetry between the different stakeholders in an IPO process.

Keywords

initial public offering private equity stage financing syndication underpricing

Introduction

The availability of venture capital (VC) funding is crucial for the survival and the development of high potential companies since it helps to overcome the shortage of financial resources as well as the lack of business development knowledge characterizing start-up projects. Consequently, the French authorities have supported VC industry since its late emergence in the 1990s. The government’s actions aimed to both develop private funds specialized in the VC segment and stimulate entrepreneurship, leading to a progressive increase in investment over the last decades. The Invest Europe's report (2016) indicates that French firms received €2 million during each funding round over the period 2007–2015 (the average amount of investment in Europe reaches €1.3 million). Following the financial crisis, the government scheme funding has intensified, leading to an average number of 34 funds raising money per year during the period 2010–2013 (vs. 24 funds between the years 2007 and 2009). A large part of these new funds came from government agencies, in particular the French public bank of investment (BPI France), which invested almost €2 billion in more than 130 VC funds, jointly with other private investors since 2000. According to the French Association of Private Equity, the total amount of investment represents €14.3 billion in 2017, which generates a 32% increase compared to 2016. Ranked at the second position after the UK market in Continental Europe, the French VC industry expects to have the leading position by 2020 thanks to intensive public interventions. More than 2000 start-ups and small- and medium-sized firms have been supported by VC firms (VCFs) in 2017.

As argued by Schwienbacher (2008), the attractiveness and success of the VC industry rely on the capacity of VC funds to exit their portfolio firms successfully. Indeed, the exit process is a key part of the VCFs cycle and enables a quantitative assessment of VCFs performance. Among the exit routes, the initial public offering (IPO) appears to the VCFs, as the culmination of the exit plan. Despite its lower frequency, IPO is one of the most prominent routes by amount at cost (17% of divestments) after the sale to another private equity firm and trade sale in Europe (Invest Europe's report, 2016) since it offers the best return from investment and adds to VCFs’ reputation (Lin, 1996). In France, it accounts for 5–8% of divestments over the last 5 years. The money raised by venture-backed IPOs on Euronext Paris amounts to €148 million (accounting for 7% of the IPO proceeds in 2017).

In this article, we investigate the IPO success of venture-backed firms (VBFs) which has been under-explored comparatively to other performance like accounting and financial performance or the investment exit strategy. From the standpoint of VCFs and firm managers, the degree of underpricing for the VBF’s shares at the time of the IPO may assess the transaction’s performance. Defined as the difference between the initial listed price and the offer price, as a proportion of the offer price (Chahine et al., 2007), this is a complex phenomenon, whose impact differs depending on the stakeholders involved in the operation (Beatty and Ritter, 1986).

The specific literature of VBFs on underpricing points out two explanations: the certification, hypothesis supported by Megginson and Weiss (1991), shows that VCFs involvement is a signal of quality for potential investors that enhances the conditions for IPOs by the firms financed by VCFs, thus helping to reduce underpricing. The grandstanding hypothesis discussed by Gompers (1996) suggests the opposite idea, meaning that VCFs undertake IPOs for firms in their portfolio to ‘show off’, this drives them to go public prematurely. In such a case, the presence of VCF shareholders can amplify underpricing. While many empirical studies validate the grandstanding theory (Bouzouita et al., 2015; Gompers and Lerner, 1997; Lee and Wahal, 2004), other authors like Chahine et al. (2007) show that British VCFs play more of a certification role (thus mitigating underpricing) although French VCFs have a greater tendency to grandstand (thus amplifying underpricing).

The majority of analyses explaining underpricing essentially rely on the underlying assumption of an existing information asymmetry between the IPO stakeholders, which positively associates the level of underpricing with the degree of information asymmetry that exists between the issuing firm and potential investors. To cope with uncertainty and information asymmetries, VCFs commonly use two practices: stage financing and syndication. While several studies have analysed the impact of syndication¹ and stage financing² on firm performance, measured in several ways (trading on the financial markets, time to market, accounting and financial performance of VBFs, etc.), there is relatively little research into how these practices affect underpricing. Only Tastan et al. (2013) and Tian (2012) analyse the impact of syndication on underpricing, and to the best of our knowledge, there has been no further research examining the effect of stage financing. This study aims to fill that gap in the literature by analysing how far syndication and stage financing affect IPO performance, because they reduce underpricing of VBFs.

The empirical analysis uses new, hand-collected data concerning more than 260 VBFs, which undertook an IPO on the Euronext Paris and Alternext markets between 1997 and 2013.

Our empirical results show lower underpricing for firms that benefit from syndicated investment. The tests conducted also reveal that the degree of underpricing is lower when the number of VCFs in the syndicate is higher. Stage financing, however, does not affect the level of underpricing. In the end, only syndication is an effective way of improving IPO performance (through the degree of underpricing), via a reduction in agency costs and information asymmetry between the stakeholders in the IPO.

The first part of this article outlines our theoretical positioning and formulates the hypotheses tested. The second part presents the methodology and the database. In the third part, we report the empirical results. The final part discusses the results, presents the limitations of this study and proposes avenues for further research.

Theoretical positioning and hypotheses tested

The academic research analysing stage financing and VCFs syndication mainly relies on agency and information theories (Da Rin et al., 2013).

Literature on stage financing

The potential agency conflicts between the VCF and the manager, additionally to the private information possessed by the manager about the quality of the firm, submit VCFs as victims of an opportunistic behaviour by managers. Stage financing seems to be a way to minimize agency problems, as it enables investors to collect information and monitor progress on business plans, while retaining the option to withdraw support from the entrepreneur if he fails to achieve the predefined objectives (Admati and Pfleiderer, 1994; Bergemann and Hege, 1998; Cornelli and Yosha, 2003; Dahiya and Ray, 2012; Tian, 2011). In line with this argument, Gompers (1995) shows that stage financing is more frequently used by firms with significant agency problems, particularly when they have a high level of intangible assets and significant research and development expenditure. According to Hochberg et al. (2007), approximately one-third of VBF do not survive after the first round of investment. Therefore, the probability of survival increases as the number of round of investment is high. It keeps VCFs regularly informed and leaves them the option to call off investment in projects with low chances of reaching the stock market. In this way, it allows to limit potential losses (Dieter et al., 2007). Moreover, the number of financing rounds is positively associated with the level of agency risks (Shepherd and Zacharakis, 2002). For Neher (1999), stage financing can solve commitment problems. The entrepreneur has human capital that is essential for the firm’s success, and this gives her bargaining power with equity investors. Once funding has been received, the entrepreneur can hold the VCFs hostage, threatening to leave the firm for a better career elsewhere. Stage financing reduces the amount VCFs put into an entrepreneurial firm at a given point in time, while gradually embedding the entrepreneur’s human capital in the firm’s capital. The stage financing mechanism thus minimizes any incentives for the entrepreneur to leave the firm. This control mechanism – if it is effective – leads to better firm performance (Kaplan and Strömberg, 2003; Sahlman, 1990; Tian, 2011). Dahiya and Ray (2012) conclude that stage financing improves performance because it leads investors to withdraw rapidly from low-profit firms and make greater investments in more promising ones. Wang and Wang (2009) and Wang and Zhou (2004) consider stage financing as an optimum capital allocation strategy in a situation marked by uncertainty and moral hazard issues. Hopp and Lukas (2014) study the relationship between VCFs experience and the intensity of monitoring. The more experienced the VCFs, the longer the period between two financing rounds and the lower the intensity of monitoring. Dai (2011), meanwhile, considers that stage financing reduces funding costs and has a positive impact on private investor involvement in long-term firm performance. Hsu (2010) finds that stage financing gives the VCFs a waiting option, but also mitigates agency problems by preventing the manager from being overcautious. Stage financing is costly, however, since it regularly generates bargaining and contracting costs (Witt and Brachtendorf, 2006). It can also have unwanted side effects: it may drive the entrepreneur to aim for short-term success rather than encouraging value creation over a longer time horizon. Stage financing can therefore have a negative impact on the performance of VBFs.

The performance criteria used in the empirical research confirming a positive relationship between stage financing and firm performance are the probability of an IPO, return on equity, the sales margin of VBFs (Tian, 2011) and their post-IPO survival rate (Wang and Zhou, 2004). Tian (2011) more specifically shows that when the firm is geographically distant from the VCFs funds, the number of financing rounds is positively correlated with the probability of an IPO and firms’ financial and accounting performance, both in the year of the IPO and the longer term. But to our knowledge, no research has yet established a connection between stage financing and IPO performance as measured by underpricing. As seen earlier, information asymmetry problems are central to the research on underpricing and the research on syndication and stage financing. However, these problems concern different types of actors in each of these practices. In the case of underpricing, asymmetry exists between the pre-IPO shareholders (VCs and the managers of VBFs) and potential investors. In the case of stage financing, information asymmetry is essentially between VCs and the managers of VBFs. We posit two alternative hypotheses. The first is that there is a positive association between stage financing and IPO performance: stage financing is a way for VCs to collect information and monitor the manager more closely. This monitoring reduces the costs of information-seeking for potential investors and also minimizes agency conflicts, thus ultimately improving performance. The opposite hypothesis is as follows: stage financing, because of the costs it generates for VBFs and the short-term managerial approach it implies, is detrimental to firm performance when they undertake an IPO.

H1a: IPO underpricing negatively correlates with the number of financing rounds for the VBF.

H1b: IPO underpricing positively correlates with the number of financing rounds for the VBF.

Literature on syndication

The Invest Europe report in 2016 indicates that VCFs refer to syndication in 30–40% of their deals in Europe. More particularly, on the French VCFs industry, this investment strategy is more frequently used. Approximately, 50–60% of investments were syndicated over the period 2007–2017.

A body of literature focusing on the motives for syndication identifies three rationales: (1) syndication leads to better selection for firms in the portfolio (the investment selection motive), (2) syndication improves performance through the accumulation of VCFs expertise that can benefit the firm (the expertise motive) and (3) syndication diversifies the risks (the portfolio diversification motive). Alongside, several papers empirically analyse syndication’s impact on performance. Brander et al. (2002), for instance, who conduct empirical tests on the validity of the selection and expertise motives, validate the first of these, measuring Canadian firms’ performance by the internal rate of return registered by VCFs after the lock-up period. Das et al. (2011) suggest that the two effects of syndication (the selection effect and the expertise effect) play a combined role in firm performance, measured by the probability of portfolio exit and the length of time until exit. Casamatta and Haritchabalet (2007) propose a theoretical model suggesting that syndication improves selection (and thus ultimately performance) and protects against competition between VCFs once investment opportunities have been disclosed. Hopp and Rieder (2011) show that syndication increases each partner’s incentives to use their idiosyncratic skills to improve firm selection and value added in investment monitoring. Agarwal (2012) presents a game theory model in which syndication can lead to suboptimal performance. Having a large number of members who joined the syndicate in the last rounds is particularly damaging, as such VCFs do not contribute to value creation. Applying graph theory, Hochberg et al. (2007) show how strong VCFs networking in syndicates explains the performance of the firms they finance, as measured by their IPO or sale.

Research that compares the performance of VBFs with and without syndicated financing concludes that syndication leads to a higher survival rate (Berggren et al., 2006), better profitability, better productivity, a better return on investment (Guo and Jiang, 2013), a higher probability of successful exit by the VCFs investor (Tian, 2012) and faster growth. Other empirical analyses find that there are no differences in performance, measured by VBFs’ abnormal post-IPO returns (Lehmann, 2006) or the return on equity, return on investment, Tobin’s Q and commercial value added (Hamdouni, 2011). According to Tian (2012), syndication creates value for firms because syndicate-financed firms have better terms for access to the financial markets and receive a positive response from those markets. Meuleman et al. (2009) approach syndication from the angle of the costs it generates. In line with the theoretical work by Pichler and Wilhelm (2001), they show how far the agency costs associated with syndication reduce its appeal. Agency costs are presumed to rise with agency conflicts and the level of control. Consequently, there is less probability of syndication in situations with high agency costs. This negative association is mitigated by the reputation of the syndicate’s lead investor, and his/her own network. These results may explain why syndication has a negative effect on the optimal VCFs portfolio. Agarwal (2012) shows that having a greater number of investors negatively affects performance, measured by the probability of an IPO. Nitani and Riding (2013) show that a preponderance of small VCFs funds leads to excessive syndication, compromising fund performance.

All in all, several studies empirically analyse the impact of syndication on performance, using many criteria such as VCFs performance, time in the portfolio, the probability of investor exit, the firm survival rate and so on. But there is little research examining the impact of syndication on underpricing (Tastan et al., 2013). The findings of this small body of literature are worth closer attention. Tian (2012) presents two contrasting hypotheses regarding the link between syndication and underpricing. The first posits a negative correlation between syndication and the level of underpricing. The reasoning is that the fact that two or more VCFs have decided to invest in a firm sends a positive signal to the financial market, whereas being funded by a single VCF does not send such a positive signal. The second hypothesis posits a positive correlation between syndication and the level of underpricing. The reasoning is that a VCF investing alone holds private information about a promising firm and will want to be the sole beneficiary of the return on the investment. This hypothesis argues that IPO performance will be better for firms financed by a single VCF than for syndicate-financed firms. The empirical findings reported by Tian (2012) validate the first of these hypotheses and, in line with Chemmanur and Loutskina (2007), show that VCFs acting in a syndicate are better able to reduce the degree of information asymmetry between insiders and outsiders than VCFs investing alone, leading to the conclusion that syndication helps to reduce the level of underpricing.

This leads to a second pair of hypotheses:

H2a: IPO underpricing negatively correlates with syndication.

H2b: IPO underpricing positively correlates with syndication.

When the factor under consideration is no longer syndication but size, then the following two hypotheses assumed. The first, proposing a negative correlation between the size of the syndicate and the level of underpricing, is justified by the cumulative effect of VCs’ different types of expertise and the information they provide. Alternatively, a positive correlation may result from coordination problems and agency conflicts between syndicate members. Syndication may be seen as an example of many principals controlling the same agent in a moral hazard situation where the principals have divergent objectives. Empirical research has shown the opposite association between board size and firm performance (Bennedsen et al., 2008; Yermack, 1996). Jensen (1993) considers that ‘When boards get beyond seven or eight people they are less likely to function effectively and are easier for the CEO to control’. In a similar vein, Hermalin and Weisbach (2003) conclude that ‘large boards exacerbate some free riding problems among directors vis-à-vis the monitoring of management’.

In the specific case of VBFs, Stevenot-Guery (2007), Hellmann et al. (2008), Chemmanur et al. (2011) and Du (2016) consider that large syndicates generate coordination problems and conflicting objectives. Tastan et al. (2013) are the first researchers (and the only ones to our knowledge) to conduct an empirical analysis of the impact of syndicate size on the level of IPO underpricing. Their empirical results validate the positive correlation between syndicate size and the level of underpricing, which they suggest result from coordination problems and conflicts of interest, which increase with syndicate size.

This leads to the third pair of hypotheses:

H3a: IPO underpricing is negatively correlated with syndicate size.

H3b: IPO underpricing is positively correlated with syndicate size.

In line with the famous model proposed by Leland and Pyle (1977) who argue that the proportion of the firm held by insiders signals the firm’s true value to outsiders, it is interesting to test a final measure of the impact of syndication: the impact of the percentage of capital retained by VCFs in the syndicate at the time of the IPO. Chahine et al. (2007) consider that the share of capital retained by VCFs in an IPO reflects an investment decision based on their assessment of the firm’s appeal to outside investors, and can therefore amplify the effect of VC certification. The same authors also make the opposite hypothesis, based on the grandstanding argument and the corruption argument advanced by Loughran and Ritter (2004). They claim that VCFs may want to benefit from rents and deliberately engage in underpricing in return for shares in future IPOs, which will also be underpriced.

This leads to a final pair of hypotheses concerning the link between syndication and underpricing:

H4a: IPO underpricing is negatively correlated with the percentage equity stake held by the VCs in the syndicate.

H4b: IPO underpricing is positively correlated with the percentage equity stake held by the VCs in the syndicate.

Empirical study

After presenting the sample, we present the variables and the methodology used.

Description of the sample

We constructed a new database containing information about 267 French VBFs that undertook IPOs between 1997 and 2013 on Euronext Paris (B and C compartments) and Alternext (known as Euronext growth). The information comes from the firms’ IPO prospectuses and the Thomson One Banker database. Our database differs from those used in many studies on VC funding which compile perceptual data collected through questionnaires (Manigart et al., 2006). Since this can generate significant bias, we decided to collect data primarily from IPO prospectuses. In this research, VBF performance is measured by underpricing, and thus at a very specific point of the IPO. This is an advantage, methodologically speaking, because access to information is facilitated by the obligation to disclose information on stock market operations. Until they undertake an IPO, VBFs, which by definition are unlisted, are not subject to such disclosure requirements.

There were several stages in construction of the sample. First, we selected all the firms that went public for the first time on the French stock market from the IPO listing available in the annual statistics of the Société de Bourse Française (SBF), the annual reports of the Autorité des Marchés Financiers (AMF) and the Euronext information base. This resulted in an initial sample of 700 firms that were adjusted: we eliminated financial firms and insurance companies, retaining only firms in Euronext Paris’ B and C compartments and Alternext (now Euronext growth). After analysis of the firms’ capital structure, around 300 VBFs were extracted. Data on syndication, stage financing and the IPO were then collected from the prospectuses published by the AMF and NYSE Euronext information. Due to missing data, the final sample consisted of 267 firms.

The variables used

The variables are outlined in Table 1.

Table 1.

Variable definitions.

Dependent variable
IPO performance or underpricing (UNDPRIC)	The ratio of the difference between the initial listed price and the offer price to the offer price (Chahine et al., 2007)
Independent variables
Stage financing
Intensity of stage financing (NBR_RDS)	The number of financing rounds for VBFs before their IPO
Syndication
SYNDINV	A dummy variable taking the value of 1 whenever there is VC syndication, and 0 otherwise
SYNDMEMB	The total number of VCFs in the syndicate at the IPO time (Ferretti and Meles, 2011)
SYND_SHARE	The percentage of equity stake held by VCFs in the syndicate at the IPO time (Barry et al., 1990)
Control variables
Underwriting bank’s reputation, denoted BANKREP	A categorical variable measured on a scale of 1–5. The bank’s score depends on the number of IPOs in which it was involved, from 1 for the lowest numbers of IPOs to 5 for the highest numbers of IPOs (Carter and Manaster, 1990; Coakley et al., 2009)
IPO market cycle (IPO_CYC)	A categorical value ranked from 1 to 3. The score of 1 is attributed to IPOs in a crisis period (2001–2003, 2008–2009); the score of 2 is attributed to IPOs in a post-crisis period, when IPO activity was slowly picking up again (2004, 2010); and the score of 3 is attributed to IPOs in a period of more intense stock market activity (1997–2000, 2005–2007 and 2011–2013). These three periods correspond to the market cycles (Boutron et al., 2007)
Type of IPO mechanism (TYP_PROC)	A dummy variable taking the value of 1 when there is a book-building procedure (placement) combined with another method; 0 otherwise (Faugeron-Crouzet, 2001; Jenkinson and Jones, 2004)
Size of the issue (ISS_SIZE)	The logarithm of market capitalization (Megginson and Weiss, 1991)
Business sector (BUS_SECT)	A binary variable taking the value of 1 if the firm is in the information and communications technology sectors, and 0 otherwise (Mak and Kusandi, 2002; Tanda and Anderloni, 2014)
Age of the financed firm (LOG_AGE)	The logarithm of the number of years of existence at the time of the IPO
Size of the firm (LOG_ASSTS)	The logarithm of the financed firm’s total assets (Mak and Kusandi, 2002)
Rate of return on equity for the year before the IPO (ROE_N-1)	The ratio of net income to total equity before the IPO (Guo et al., 2015)
Management’s shareholding (MGT_SHARE) at the IPO time	The percentage equity stake held by the manager at the IPO time (Broye and Schatt, 2003)

Note: IPO: initial public offering; VBF: venture-backed firm; VC: venture capital; VCF: venture capital firm.

Empirical results

The model tests the impact of stage financing and syndication on VBF performance at the IPO time through the level of underpricing. To this end, three multivariate regressions are undertaken corresponding to the three different measures for syndication.

After presenting the results of the descriptive analyses, we present the results of the multivariate tests and regressions.

Descriptive statistics

The descriptive statistics for our sample are reported in Table 2. The mean level of underpricing for VBFs between 1997 and 2013 is 5.94%. This mean is comparable to the mean observed by Le Maux (2009): 6.01% for firms undertaking IPOs between 2001 and 2006 on the French secondary market. About 72% of the firms in our sample received syndicated investments, with an average 2.1 rounds of financing. The average number of VCFs in a syndicate is 2.8, and the average shareholding owned by each VCF is 27.3%.

Table 2.

Descriptive statistics.

Variables	Mean	Standard deviation	Minimum	Maximum	N
UNDPRIC (%)	5.94	15.8	−21	135	267
SYNDINV	0.72	0.45	0	1	267
SYNDMEMB	2.8	2.5	0	14	267
SYND_SHARE (%)	27.3	20.74	1	98.98	267
NBR_RDS	2.1	1.39	1	12	267
RG_BGE	3.64	1.64	1	5	267
IPO_CYC	2.7	0.55	1	3	267
TYP_PROC	0.83	0.37	0	1	267
ISS_SIZE	17.89	0.94	15.25	21.65	267
SECT_ACT	0.31	0.46	0	1	267
LOG_ASSTS	7.11	6.75	−0.43	21.33	267
LOG_AGE	2.35	0.99	0	5.23	267
ROE_N-1 (%)	37	5.95	−37.5	69	267
MGT_SHARE	40.5%	27.8	0	97.5	267

A discriminant analysis of our sample using the SYNDINV variable reveals significant differences between the two subsamples (firms with syndicated financing and firms with non-syndicated financing), as shown in Table 3.

Table 3.

Descriptive analysis by subsample (syndicated and non-syndicated financing).

Statistics	UNDPRIC	SYND_SHARE	NBR_RDS	BANKREP	LOG_ASSTS	MGT_SHARE
SYNDINV = 0
Mean	7.98	19.9	1.641	3.97	5.49	52.3
Standard deviation	20.59	20.29	0.9	1.518	6.38	32.5
N	75	83	53	78	94	76
SYNDINV = 1
Mean	5.144	30.15	2.22	3.53	7.736	36.01
Standard deviation	13.47	20.26	1.49	1.67	6.8	24.5
N	192	184	155	189	173	191
Student’s t	1.69*	−3.6***	−2.68***	2.005**	−2.32**	−4.37***

* Significant at 10%.

** Significant at 5%.

*** Significant at 1%.

We note a significantly higher level of underpricing for the subsample without syndication (7.98% compared to 5.15%). The average percentage capital retained by VCF(s) is significantly lower in this group (19.9%, against 30.15%). In firms with syndicated financing, the number of financing rounds tends to be higher (2.22, against 1.64) and the underwriting banks tend to have a lower reputation (3.53 against 3.97). These firms are larger in size (7.73 against 5.49) and the manager’s shareholding is lower (36.01% against 52.3%). Note that for all variables, tests of differences between the means for the two subsamples are significant at the 5% threshold. The significance threshold for underpricing is 10%.

Multivariate tests

Analysis of the correlation matrix for the variables in our model (Table 4) shows no significant correlation (at 5%) above 0.5 between most variables. The variables measuring the share of equity held by the manager (MGT_SHARE) and the degree of underpricing (UNDPRIC) display a correlation coefficient of 0.51. In addition, the variable for the underwriting bank’s reputation (BANKREP) has a correlation coefficient of 0.84 with the firm size (LOG_ASSTS). This correlation justifies leaving the ‘firm size’ control variable out of our models.

Table 4.

Correlation matrix.

	UNDPRIC	SYND_SHARE	SYNDINV	SYNDMEMB	NBR_RDS	BANKREP	IPO_CYC	TYP_PROC	ISS_SIZE	BUS_SECT	LOG_ASSTS	LOG_AGE	ROE_N-1	MGT_SHARE
UNDPRIC	1.0000
SYND_SHARE		1.0000
SYNDINV		0.2224*	1.0000
SYNDMEMB		0.3833*	0.6670*	1.0000
NBR_RDS		0.2479*	0.1902*	0.1890*	1.0000
BANKREP		−0.2891*	−0.1256*		−0.1941*	1.0000
IPO_CYC		−0.1656*			−0.1497*	0.2833*	1.0000
TYP_PROC	−0.1563*	0.1095	0.1716*	0.1227*				1.0000
ISS_SIZE	0.2177*			0.1585*	0.1695*	0.2013*		0.1270*	1.0000
BUS_SECT		0.1964*			0.1449*	−0.1726*				1.0000
LOG_ASSTS	0.1269					−0.8474*					1.0000
LOG_AGE					−0.1928*		0.1302*			−0.1500*	−0.0946*	1.0000
ROE_N-1													1.0000
MGT_SHARE		−0.51*	−0.2614*	−0.3082*	−0.2726*	0.3472*	0.1380*	−0.2032*		−0.1921*				1.0000

Note: Coefficients are reported when they are significant at the 10% level.

* Significant at the 5% level.

Since the homogeneity requirements for a linear regression are not met, we transformed the UNDPRIC variable by adding the value 100, leading to a Tobit regression (TUNDPRIC). The results of the linear regression tests are reported in Table 5.

Table 5.

Tobit regressions (total sample).

TUNDPRIC	Model 1	Model 2	Model 3
NBR_RDS	−0.498	−0.660	−0.0289
SYNDINV	−7.011**
SYNDMEMB		−1.233*
SYND_SHARE			0.0184
BANKREP	−1.620*	−1.378	−1.282
IPO_CYC	2.096	1.788	2.121
TYP_PROC	−9.522**	−10.07**	−8.229**
ISS_SIZE	8.435***	8.696***	7.550***
BUS_SECT	5.392*	5.977*	6.825**
LOG_AGE	−1.841	−1.455	−1.835
ROE_N-1	0.108	0.118	0.0760
MGT_SHARE	−0.0722	−0.0784	−0.00791
Sigma
CONST	18.58***	18.58***	18.47***
N	267	267	267
LR χ²	31.78	31.85	25.54
Log likelihood	−717	−717.6	−682.07
Pro > χ²	0.0004	0.0004	0.0044
Pseudo R² (%)	21.7	21.7	18.4

Note: LR: likelihood ratio.

* Significant at the 10% threshold.

** Significant at the 5% threshold.

*** Significant at the 1% threshold.

First, no significant relationship is visible between the number of financing rounds and the underpricing of our sample VBFs in their IPOs. In other words, stage financing has no impact on firms’ IPO performance. This contradicts the results of Tian (2011), who shows that the number of financing rounds improves the performance of VBFs. He argues that when the firm is geographically distant from the VC fund, the number of financing rounds positively correlates with the likelihood of an IPO and the firms’ financial and accounting performance for the year of the IPO and in the longer term. When underpricing is used as a performance criterion, the coefficient is not significant. Consistent with our findings, Honjo and Nagaoka (2017) find that stage capital infusion is not associated with the IPO value. Several arguments can be suggested. For us, the first one relates to the counterbalance of the two opposite effects of stage financing on the level of underpricing, cancelling each other out. The number of financing rounds indicates better monitoring by VCs and less information asymmetry between insiders and outsiders, which reduces the level of underpricing. At the same time, staged injections of capital subject to achievement of intermediate milestones is costly for VBFs and leads entrepreneurs to take a short-term view, which is detrimental to firm performance. The second argument, presented by Honjo and Nagaoka (2017), suggests that stage financing may occur when the project is successful but in the same time, may occur when capital invested in the prior stage is too small because of the capital constraints of the lead VCFs. The round’s position matters as the early rounds enable the lead investor in a VC syndicate to overcome its financial constraints, letting the other VCFs to invest in the later rounds. Moreover, as suggested by Baldock and North (2015), the other equity sources alongside the VCFs during the journey of financing rounds could increase the complexities of staged capital infusion (the business angel activity precedes more frequently VC funding).

Second, the Tobit regressions reveal a significant negative relationship between syndication and IPO performance: the level of underpricing is lower when VC funding is syndicated. This result is consistent with several studies, among which, Tian (2012) confirming the role of syndication in reducing information asymmetry between insiders and outsiders.

Third, our empirical analysis shows that the size of the syndicate plays an important role, since it affects the level of underpricing of VBFs: a negative relationship is observed between the degree of underpricing and the number of VCs in the syndicate. In other words, the degree of underpricing declines as the number of VCs in the syndicate rises. This finding echoes Megginson and Weiss (1991) who report that a larger number of VCs in the syndicate increases certification of firm quality in an IPO, and thus reduces underpricing. However, our result contradicts Tastan et al. (2013), who find that having too many VCs leads to agency conflicts that ultimately harm performance.

Fourth, our empirical results cannot validate our hypothesis linking the percentage equity stake retained by the VCs and the underpricing level. The suggestion by Leland and Pyle (1977) that the share held by insiders signals the firm’s true value to outsiders is thus not confirmed for French VBFs. Our result does not confirm the findings of Chahine et al. (2007): the VCs’ retained shareholding does not amplify the certification effect of VC involvement. A potential explanation relates to the behaviour shown by VCFs participating in syndication, who have imitative behaviour of the lead VC, leading to information cascade and no adding value role. This point was supported by Filatotchev et al. (2006) who argue that there is a higher equity presence of passive private equity investors in syndicated deals.

In addition, there may be the two opposite effects of the VC’s percentage ownership on performance cancelling each other out.

Finally, the control variables give interesting results concerning the influence of the underwriting bank’s reputation, the type of listing procedure, the issue size and the business sector on the level of underpricing. Like Franzke (2004) and Nahata (2008), our regressions show a lower level of underpricing for highly reputed banks. This result is only significant at the 10% threshold, and only in model 1. The better the bank’s reputation, the more it reduces information asymmetry and stock underpricing in the event of VC syndication. Our empirical findings also show a positive link between issue size and the level of underpricing. Just like Degeorge and Derrien (2001) and Franzke (2004), we observe that a larger issue size increases underpricing. Finally, the level of underpricing is larger for firms in the information and communications technology sectors, which have higher information asymmetry.

Further robustness checks were conducted at different stages. After the Tobit regressions reported in Table 5, we run further regressions, eliminating the ‘extreme’ values identified by the Stata software. The signs of the coefficients and the significance thresholds are the same, indicating that our results are robust. In a second stage, we tested the relationship between the level of underpricing, stage financing and syndication, using a different measure for the level of underpricing. This measure incorporates the distribution of the UNDPRIC variable, indicating that 61% of firms in the sample show no underpricing and/or overpricing, and 39% have positive underpricing, that is, positive initial returns. The new dependent variable representing underpricing, coded LG_UNDPRIC, is a binary variable that takes the value of 1 when the underpricing is positive, and 0 otherwise. We conducted logistic regressions, including the three sets of syndication-related variables, using models denoted 1A, 2A and 3A. The results of these models remain substantially identical, both in sign and significance level, to our three Tobit regressions (Table 6).

Table 6.

LOGIT regressions (total sample).

LG_UNDPRIC	Model 1A	Model 2A	Model 3A
NBR_RDS	−0.0251	−0.0311	0.0342
SYNDINV	−0.29*
SYNDMEMB		−0.185**
SYND_SHARE			−0.00492
BANKREP	−0.250**	−0.238**	−0.248**
IPO_CYC	−0.304	−0.303	−0.359
TYP_PROC	−1.565***	−1.545***	−1.712***
ISS_SIZE	0.592***	0.671***	0.553***
BUS_SECT	0.424	0.499	0.551
LOG_AGE	0.0853	0.125	0.0750
ROE_N-1	0.195	0.168	0.168
MGT_SHARE	0.00210	−0.00159	0.00212
CONS	−8.028**	−9.135**	−7.289**
N	267	267	267
LR χ²	20.87	26.04	19.62
Log likelihood	−103.85	−101.27	−98.9
Pro > χ²	0.02	0.0037	0.0331
Pseudo R² (%)	9.13	11.39	9.02

* Significant at the 10% threshold.

** Significant at the 5% threshold.

*** Significant at the 1% threshold.

Finally, we repeated the Tobit regressions, this time on the subsample comprising only firms with syndicated financing. Models 4 and 5 of Table 7, respectively, test the impact of the number of financing rounds, the size of the syndicate and the percentage of capital retained by the syndicate’s VCFs on the level of underpricing. The results (signs and significance thresholds) are unchanged for stage financing, syndicate size and VCFs’ percentage shareholding. Unlike the previous results shown in Table 5, two control variables are no longer significant: the reputation of the underwriting bank and the business sector. In other words, when all firms have had syndicated financing, neither the underwriting bank’s reputation, nor the firm’s business sector significantly influence the degree of underpricing. Overall, these checks lead us to conclude that our results are robust.

Table 7.

Tobit regressions (subsample of firms with syndicated financing).

TUNDPRIC	Model 4	Model 5
SYNDMEMB	−0.264**
SYND_SHARE		−0.00370
NBR_RDS	−0.155	−0.0665
BANKREP	−0.169	−0.240
IPO_CYC	−0.00655	−0.00267
TYP_PROC	−1.629**	−1.577**
ISS_SIZE	0.646**	0.508**
BUS_SECT	0.307	0.344
LOG_AGE	0.0389	−0.105
MGT_SHARE	−0.00188	0.00249
ROE_N-1	0.185	0.200
CONS	−8.649**	−6.960*
N	192	192
LR χ²	19.83	11.88
Log likelihood	−76.402673	−76.165378
Pro > χ²	0.0309	0.2928
Pseudo R²	0.1149	0.0724

* Significant at the 10% threshold.

** Significant at the 5% threshold.

*** Significant at the 1% threshold.

Discussion and conclusion

After showing this study’s contribution to the literature, we present its limitations and consider prospects for future research.

Contributions to the research

The aim of this research is to analyse the effect of stage financing on the firms’ IPO performance. Drawing on agency and information-based theories, we analyse the impact of stage financing and syndication on underpricing of VBF. Our quantitative methodology uses a database comprising 267 French VBFs that undertook an IPO between 1997 and 2013.

Our results show that syndication and the syndicate size have a positive impact on a firm’s IPO performance. Investment through a syndicate and the number of VCs in the syndicate are negatively correlated with the level of underpricing. This finding, in line with Tian (2012), confirms the syndication’s role in reducing information asymmetry between the IPO stakeholders. Having too many VCs does not cause agency conflicts that ultimately harm performance as shown by Tastan et al. (2013). Syndication mechanism benefits the VC investors through sharing of risk of investment in a firm and preparing them for a successful exit (Mishra and Bag, 2017).

Our empirical findings do not show any impact of the shares held by VCs, unlike Chahine et al. (2007). For VBFs in our sample, the positive effect of VC certification, which is amplified by the percentage of ownership of the VCs in the syndicate, appears to be counterbalanced by a grandstanding phenomenon.

Our empirical tests show no significant impact of stage financing on firm performance, consistently with Honjo and Nagaoka (2017), the positive and negative effects cancelling each other out. Additionally, the degree of syndication in the funding journey with other equity sources could make more complex the analysis of the effect of this investment practice.

This study makes several contributions to the research. First, to our knowledge, it is the first to test the impact of stage financing on the level of underpricing. There is little research connecting syndication and underpricing. Our study aims to fill this gap in the literature by running, for the first time, a full series of tests explaining both the positive and negative impacts of syndication practices and stage financing on firm performance, in order to consider all the issues debated in the literature. Regarding syndication more specifically, our empirical analysis is more exhaustive than in the existing literature, because it is founded on three different measures: syndication or non-syndication, syndicate size and the percentage of equity share held by the VCFs in the syndicate. Finally, the geographical setting of this research – France – is unusual. Empirical research on syndication practices and stage financing of VBFs in France is rare, due to the difficulties of collecting information.

Limitations and prospects for future research

Our research has several limitations. First, it focuses on the French IPO market characterized by a lower liquidity leading to a lesser amount of money raised through venture-backed IPOs, compared to the UK and US markets. Additionally, the different institutional and legal context differing depending on the country may influence the VCFs’ and market investors’ practices, which consequently could affect the findings (Chahine et al., 2007). The smaller size of European funds and the VCFs activity scale, more particularly in France, could affect the stage financing practice, comparatively to the US counterparts (Baldock and Mason, 2015). It would also be interesting to conduct a study similar to this one on VBFs entering the NASDAQ in the Unites States or the AIM in the United Kingdom. Second, our study underestimates the different VCFs profiles (independent, corporate, government) alongside other external equity financing sources like the business angel. The work by Hochberg et al. (2007) could be further investigated to take into consideration how the profile of the VCFs (independents and otherwise) in the syndication networks affects the level of underpricing and the complementary role between the equity fund providers (business angels and VCF).

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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