Abstract
In initial public offerings (IPOs), underpricing refers to pricing the issue at a price lower than its fair value which results in the listing price being much higher than the issue price. This higher information asymmetry results in more underpricing. To reduce such asymmetry, the Securities and Exchange Board of India (SEBI) introduced IPO grading and anchor investor participation in India. This article aims to assess the impact of these two factors on the underpricing of Indian IPOs over 2007–2017. This study uses multivariate regression analysis to compare the impact of graded versus ungraded IPOs and of anchor-backed versus non-anchor backed IPOs on underpricing; it finds that IPO grading and anchor investment do not have a significant overall impact on underpricing. These results justify the scrapping of mandatory IPO grading. Although insignificant, IPO grading has a greater influence on underpricing than anchor investor participation. Furthermore, the current study also analyses the subscription patterns of qualified institutional buyers (QIBs), non-institutional investors (NIIs) and retail individual investors (RIIs) and their influence on one another. Accordingly, it reveals that QIB subscription influences both NII and RII subscriptions.
Keywords
Introduction
Initial public offering (IPO) and follow-on public offering (FPO) constitute the two primary sources of large-scale fundraising by corporates. Until 1992, primary market issues in India were regulated by the Controller of Capital Issues (CCI) as per the Capital Issues (Control) Act, 1947. However, these fixed price issues were most often underpriced, and hence, CCI was abolished in 1992, leading to the introduction of the SEBI Act, 1992. However, this led to avaricious issuers pricing issues at a very high premium by painting a falsely positive picture of financial projections. When these premium prices never materialized, stock prices crashed.
After this came the rise of the book-building process adopted by the Securities and Exchange Board of India (SEBI) in 1999. Book building is an auction of shares. While fixed pricing allows investors to know the exact offer price before allotment, book building gives investors a price range (with a cap and floor). Under information revelation theory, Benveniste and Spindt (1989) and Benveniste and Wilhelm (1990) contend that the book-building mechanism is specifically designed to shrink the information gap between well-informed institutional investors and less informed non-institutional investors—predominantly retail investors—because the method attempts to capture market demand information, and hence, improves price accuracy.
Marisetty and Subrahmanyam (2010) and Sahoo (2014) observe that promoters have underpriced IPOs despite the introduction of the book-building mechanism in India; while the former paper reports an underpricing of more than 100% for a group of affiliated firms over 1990–2006, the latter outlines underpricing to the extent of 14.23% for Indian IPOs issued between 2007 and 2012. Underpricing is the phenomenon of pricing the issue at a lower price than the fair value. It becomes evident when the share price jumps much higher on the listing day against the issue price. Underpricing is a cost to the company as it leads to loss of capital but is a positive gain for investors hoping to buy the company’s shares. Issues are underpriced to attract a plausibly full issue subscription.
To mitigate this information asymmetry, in May 2007, SEBI introduced mandatory IPO grading by credit rating agencies which, until then, had been optional. Later, in 2014, mandatory IPO grading was scrapped. SEBI also initiated the concept of anchor investors in 2009. These investors are allotted shares on a discretionary basis and the issue opens to them 1 day before the opening of the issue for other classes of investors.
IPO is an irreversible decision made during the lifecycle of a company (Marisetty & Subrahmanyam, 2010; Mehmood et al., 2020); it is thus vital to understand IPO underpricing because when there are arbitrage activities in the secondary market, this underpricing can lead to a probable occurrence of grey market activities. In addition, competition from other firms that underprice their shares poses a threat to enterprises which cannot afford to underprice. Greater underpricing also implies higher information asymmetry. As typified by information revelation theory and signalling theory, certification measures can be expected to reduce the costs associated with an IPO. With this backdrop in mind, this study aims to assess the impact of IPO grading, anchor investor participation and firm characteristics on the underpricing of Indian IPOs as well as to analyse the subscription patterns of QIBs, NIIs and RIIs and their influence on one another. To the best of our knowledge, this is one of the first studies to provide the empirical evidence on the comparative impact of mandatory versus voluntary grading on IPO underpricing in an emerging market context. Furthermore, in terms of novelty, this study covers comprehensive decade-long data involving multiple focus factors that influence underpricing, such as grading, anchor investor participation and firm characteristics which can aid the stakeholders in making their investment decisions.
For ease of exposition, the study has been divided as follows: the second section reviews existing literature; the third section discusses research methodology, research design, scope, variables and the tests employed; the fourth section covers the results and findings of the effects of anchor investor participation and IPO grading on underpricing; and the fifth section makes concluding observations.
Literature Review
The review of literature details book building and the IPO grading mechanism, the institutional setting and SEBI guidelines for anchor investors, as well as firm characteristics which influence underpricing.
Initial Public Offering Underpricing
Rock (1986) and Beatty and Ritter (1986) argued that due to information asymmetry, issuing companies will underprice their IPOs in a bid to encourage uninformed investors to participate in them. Information asymmetry, thus, plays a crucial role in influencing IPO underpricing. Investor protection measures are likely to reduce information asymmetry by resolving problems attributable to it, thus reducing underpricing (Liu et al., 2014).
Information revelation theory (Benveniste & Spindt, 1989; Chemmanur et al., 2010) states that underpricing arises as a cost of providing compensation to institutional investors for revealing superior information to underwriters about the true value of a firm; book building is used by underwriters to extract this private information. The underlying implication is that the higher the information asymmetry between the informed investors and the underwriters, the more the price revision during the book-building process. Credit ratings reduce the information asymmetry between the underwriter and the informed investors, resulting in fewer price revisions during the book-building process (An & Chan, 2008).
Signalling theory posits certain indicators which send signals to potential investors about the future value of firms; this helps reduce information asymmetry between issuing firms and investors. Since these signals are costly, only firms with a sound business model would use them to inform investors (Allen & Faulhaber, 1989). However, when such firms fail to convince potential investors about the quality of their business, they underprice IPO to compensate them for remaining uncertainty (Engelen & Van Essen, 2010). Therefore, underpricing is a credible signal to convey firm performance to public investors (Welch, 1989).
In light of the above theories, it has been observed that positive signals such as IPO certification mechanisms increase the demand of IPO shares as they reduce the uncertainty associated with IPOs (Helbing et al., 2019), thereby reducing underpricing.
Book Building
Book building, introduced in 1999 in India, is a mechanism of price discovery and share allocation. In this mechanism, a price band is announced in which investors can place their bids; the final allotment is done using a cut-off price within the price band. There are three categories of investors in India: qualified institutional buyers (QIBs), non-institutional investors (NIIs) and retail individual investors (RIIs). The Indian book-building process ensures higher transparency than that in the USA and other developed countries, as bidding details in India can be observed by investors on the National Stock Exchange of India (NSE) and Bombay Stock Exchange (BSE) website in near real time, and all bids are legally binding (Sahoo, 2015). Furthermore, amendments to the Disclosure and Investor Protection (DIP) 2000 Guidelines, framed by SEBI, aim to alleviate information asymmetry and protect investors’ interest in the capital market.
Initial Public Offering Grading
In 2007, SEBI mandated independent quality rating by credit rating agencies for all IPOs. Its rationale for such a dramatic move was to protect the interests of retail investors from fly-by-night firms (Kashiramka et al., 2018). IPO grading did not assess the fairness of IPO prices (Jacob & Agarwalla, 2015); rather, it suggested that rational investors should use the grades as valuable and resourceful price relevant information. Grading was primarily based on the issuing firm’s quality of management, governance, financial position, its regulatory compliance, industry prospects and the clients and projects handled by the firm and the risks associated with them.
However, Smith and Walter (2001) argued that since the issuer bears the cost of grading, a plausible conflict of interest could arise in IPO grading. On 4 February 2014, mandatory IPO grading was scrapped by SEBI and its use was left to the discretion of the issuing firm.
Deb and Marisetty (2010), Dhamija and Arora (2017) and Kashiramka et al. (2018) found that IPO grading reduces the underpricing of IPOs. Khurshed et al. (2014a) reported that IPO grading leads to informed decision-making; they, therefore, found a positive correlation in the pattern of subscriptions by well-informed institutional investors. This, in turn, led to a positive correlation in the subscription pattern of retail investors. Their findings contradict the conclusion of Deb and Marisetty (2010), as the former found that retail investors’ subscription of high-grade IPOs was higher, and that high-grade issues result in better IPO pricing. The surprising discovery of well-informed institutional investors, who dominate price discovery and market demand, using IPO grading to invest, raised a question as to whether IPO grading itself was redundant. Jacob and Agarwalla (2015) found that, although institutional investors subscribe to high-grade issues, retail investors’ subscriptions are indifferent to grading. Their finding also confirms that IPO grading does not reflect pricing efficiency.
Anchor Investors
Anchor investors form up to 60% of the QIB quota. Since anchor investors are considered well informed, the final offer price is determined to be the higher of the anchor bid price (calculated before the book-building stage) or the offer price (calculated after the book-building stage).
To compensate them for voluntarily disclosing information about the quality of the issue, anchor investors are provided with an assured allocation of shares (Bubna & Prabhala, 2014). Information about the value and quantum of anchor investments is made public along with the anchor price; hence, all investors become aware of the quality of the issue based on anchor investor participation.
Numerous reasons can be attributed to studying anchor investor participation in an IPO. Anchor investors are well-informed and have their reputation at stake and, hence, would only choose good-quality IPOs in which to invest; thus, pricing efficiency is expected to increase in such a case. Furthermore, they have an extensive understanding of the market and possess sophisticated private information about firms, which is not generally available. They are also expected to be impartial as they are not associated with any of the issuing firms. Thus, information asymmetry between institutional and non-institutional investors is markedly reduced. Anchor investors are prohibited from selling their allotted stocks during the lock-in period of 1 month post-listing, so as to provide an assurance to retail investors that the contracts of anchor investors are bona fide.
In the Indian context, the introduction of anchor investors is a relatively new phenomenon. Previously, international studies (Chemmanur, 1993; Chemmanur et al., 2010; Rock, 1986) illustrated the impact of institutional investors on IPO pricing. Rock (1986) and Chemmanur et al. (2010) found that since institutional investors are aware of private information about the issuing firm—such as its long-term prospects—due to their close association with merchant bankers or financial analysts, they tend to invest in undervalued shares. Additionally, Samdani (2019) found that anchor investment improves both the efficiency of financial reporting and promptness in price discovery.
Khurshed et al. (2014b) contend that while bidding for IPO stocks, RIIs and NIIs sequentially follow institutional investors’ (QIB) subscription levels. Retail investors are influenced by their observation of prior investors’ subscriptions (Neupane & Poshakwale, 2012). Sahoo (2017) suggests that IPOs with anchor backing are better endorsed than non-anchored IPOs as qualified institutional investors, and that private individuals are more attracted to the former. These results suggest that investors find credibility in the quality of an issue because of the presence of anchor investors, which aids in reducing information asymmetry. Sahoo (2017) also posits that anchor participation decreases short-term volatility post-listing and increases after market liquidity.
According to various studies, in addition to IPO grading and anchor investment, an issuing firm’s characteristics and institutional developments also tend to influence underpricing. Madhusoodanan and Thiripalraju (1997) studied 1922 IPOs issued during the period 1992–1995 to identify the determinants of underpricing; they found listing delays and offer size to be the key determinants. Ranjan and Madhusoodanan (2004) examined 92 IPOs between 1999 and 2003 and concluded that issue size and issue mechanism influenced underpricing; this is because small IPOs gained 80% but large IPOs only 3%; gains by fixed-price issues were 78%, and by book-built IPOs −2%. Nandha and Sawyer (2002) concluded that the promoters’ holdings in post-issue capital and issue size are significant factors that influence underpricing in India, thus indicating the influence of issue characteristics on underpricing.
Our study adds to the literature on underpricing of IPOs in several ways. Firstly, the extant literature on the underpricing of IPOs in the Indian stock market has confined its sample to the mandatory IPO grading period, that is, to 2014. As such, the difference in the effects of voluntary and mandatory grading on IPO underpricing has not been yet explored. Hence, this study becomes particularly relevant as it gauges significance both from the perspective of regulators and market participants in India. The novelty of our study emerges from the fact that it provides empirical evidence comparing the impact of mandatory versus voluntary IPO grading, which has not been explored by the academic community. Furthermore, as India is the first country in the world to have mandatory certification, such kind of evidence becomes relevant. The study also provides a perspective to the investors to focus on IPO-related, firm-related and market-related factors and make their decisions accordingly. Furthermore, the identification of variation in the impact of certification mechanisms on various categories of investors remains largely scarce. The role of anchor investors in India in reducing information asymmetry, and eventually, mitigating underpricing has also been largely neglected. Based on the gaps identified in the existing literature, this study tries to assess whether participation by anchor investors and grading in IPOs provides credibility to the quality of IPO issue without any significant costs being incurred by the company. Evolving financial systems such as those of emerging markets like India call for comprehension and evaluation of regulatory changes as these can serve as inputs for decision-making by the various stakeholders in the market in the future.
Data and Methodology
Data
The sample period of the study is 2007–2017, covering 360 IPOs and capturing three different time frames, as illustrated in Table 1.
Sample Period of Study and the Significance of the Period of Study.
Data were sourced from the PRIME© Database which provides comprehensive data on all public offers in India from 2007–2017. The sample chosen indicates changes in the IPO market since 2007, predominantly of mandatory versus voluntary IPO grading and the introduction of anchor investors. Out of the 360 companies that went public during the period understudy, 237 were new issues, 35 offers for sale and 88 offers for sale cum fresh capital. Table 2 comprehensively outlines the data collected for the study.
Summary of Sample Data.
Variables Understudy
where UPi represents the underpricing or first-day return on a listing day, Ri represents the stock return on the listing day and Rm represents the market return on listing day. The market return is computed as the percentage difference between the closing price of the index value on the listing day and the closing price of the index on the issue open date divided by the closing index value (on issue open date). The return on the market index is calculated using S&P CNX Nifty 100 index data. Undervaluation of shares is reflected by a positive value in UP on listing day and overvaluation is reflected by a negative value. Table 3 describes the independent variables used in the study.
Details of Independent Variables Used in the Study.
Research Methodology
The hypotheses below have been formulated to conduct the study.
IPO grading is expected to provide investors with a comprehensive perspective of IPO based on various rating variables. Hence, in line with information asymmetry theory and information revelation theory, underpricing in the voluntary grading regime may be higher than in the mandatory grading regime.
Consistent with the signalling theory framework, high-grade IPOs signal the sound business practices of a firm; thus, IPOs with high grades (4 and 5) are expected to have higher subscriptions than low-graded IPOs. Hence, to attract more investors, low-graded IPOs are more underpriced than high-graded IPOs.
Under information revelation theory, underwriters reward informed investors for disclosing useful information to them. Thus, as QIBs have more access to information and better skills at analysing an IPO, it is proposed that they would be less dependent than RIIs on the IPO grading for decision-making.
Participation by anchor investors provides a positive signal to potential investors as the former are considered well-informed institutional investors. Therefore, in a transparent bidding process, it is rational to expect that both NIIs and RIIs subscribe more to anchor-backed issues as per signalling theory.
Under information asymmetry theory and signalling theory, anchor investors are assumed to possess a broad spectrum of knowledge regarding IPO parameters; this might reduce information asymmetry and, in turn, reduce underpricing of IPOs.
To test the above hypotheses, multivariate regression analysis was conducted using the following regression models:
Furthermore, the following models are used to test whether IPO grading and anchor investment affect IPO underpricing and subscription patterns of various investor categories:
where
Results and Discussion
Descriptive Statistics
Tables 4 and 5 provide the descriptive statistics of the variables under the study.
Descriptive Statistics of Variables.
IPO Data: Yearwise Analysis.
The entire sample represents a total issue size of ₹2,307.04 billion where the average issue size per annum amounted to ₹209.73 billion, while the average per IPO issue size equals ₹6.41 billion. The largest IPO issue size of ₹151.99 billion was that of Coal India Ltd. in 2010. The average underpricing during the entire sample period is 17.9% for the 360 IPOs. An industry-wide analysis indicates that financial services/investments and housing finance companies have an average underpricing of 23.12%, while that of non-financial firms is lower at 17.04%. Categorically, the average underpricing of 21 fixed-price issues of the sample indicates a heavy underpricing of nearly 35.87%, while that of all 339 book-built issues is only 16.83%; it, thus, makes a strong case for the introduction of the book-building mechanism to reduce underpricing in IPOs (Bansal & Khanna, 2013). Furthermore, underpricing of anchor-backed IPOs has been noted at 12.35% on an average, whereas the corresponding value for non-anchor backed IPOs post-May 2009 is 11.26%. Moreover, the average underpricing of graded issues during the mandatory grading regime is 13.25%, while the same for the 39 ungraded issues has been observed to be a much larger 42.86%.
The subscription levels, as described in Table 5, show that in 2017, there was a maximum mean oversubscription of 42.9 times, followed by 2007 (at 29.4 times). Notably, there were just five issues in 2014, yet the same statistics accrued to 28.3 times; this could be due to the end of the mandatory IPO grading regime.
Characteristics of Graded and Ungraded Initial Public Offerings
Out of the total 360 IPOs during the sample period, there are 198 graded issues, of which 46 had the highest grades of 4 or 5 and 11.6% received the lowest grade of 1. A large percentage of IPOs in 2007 were rated at the lowest grade; this could plausibly be because, in the year of introducing mandatory IPO grading in 2007, firms may not have fully complied with all requirements and necessary background checks of IPOs. It has been observed that, upon the introduction of mandatory IPO grading in April 2007 until September 2007, there were 37 ungraded IPOs; these firms would have obtained SEBI approval before the implementation of the mandatory grading regime.
Additionally, 90% of the average issue size and 85% of the pre-IPO average asset size pertain to firms with high gradings (as described in Table 6). This skewness could probably be due to a relationship between grading and firm size. Similar to the findings of Kashiramka et al. (2018), it has been noted that larger issuers having relatively lower leverage and a higher return on equity tend to be awarded with the highest grading, while large issuers having a high financial risk despite high return on equity are awarded a low grading. The findings conform to expectations as the primary focus of grading is on the fundamentals of the company.
Comprehensive Profile of Graded IPOs (198).
Moreover, IPOs graded at 4 or 5 seem to receive a higher overall subscription. The median subscription levels of all three investor categories are higher for the high-grade IPOs. It is evident from Table 6 that the median QIB subscription of ‘Grade 4’ IPOs is 12 times, while it is 0.72 times for ‘Grade 1’. It can be further noted that retail demand is higher than QIB demand in the ‘Grade 1’ to ‘Grade 3’ IPO categories. While the NII and RII median subscriptions are 2.75 and 3.58, respectively, for ‘Grade 2’ IPOs, the same figure is just 0.75 times for the QIB category. These attributes of the investor subscription pattern make it noteworthy that the IPO demands by RIIs, NIIs and QIBs are necessarily the same.
Characteristics of Initial Public Offerings Based on Anchor Investment
Of the 129 anchor-backed IPOs, in only 10 cases it was noted that the bidding price of anchor investors was higher than the offer price. Apart from these, in 119 IPOs (i.e., 92.25% of cases), the bidding price of anchor investors was equal to the final offer price; this indicates an accurate evaluation of the potential value of the IPO company by the anchor investors. They are more diligent in valuing the IPO than others. On average, there are 12 anchor investors per issue in our sample.
Regression Analysis
Impact of Initial Public Offering Grading on Underpricing
This section analyses the influence of IPO grading and anchor investor participation on underpricing (Equation 2). The Durbin–Watson test conducted for autocorrelation for every regression equation in the study is in the acceptable range of 1–5. The presence of multicollinearity of variables, examined through variance inflation factor (VIF) is around 2, which is admissible as per the literature (Neter et al., 1985). Table 7 provides the pairwise correlation between the variables used in the study. All correlations 1 are less than 0.8 and do not pose a multicollinearity problem (Gujarati, 2009; Kennedy, 2008).
Correlation Matrix.
Multiple regression is adopted to examine the impact of IPO grading and anchor investment participation on underpricing. The regression results of Equation (2) are presented in Tables 8 and 9. Regression has been conducted using a dummy variable having the value 1 for graded and 0 for ungraded issues for: (a) the entire sample period of 2007–2017 and (b) three different sample periods, as described in Table 1.
Impact of Grading on IPO Underpricing (2007–2017).
Impact of Grading on IPO Underpricing Under Different Time Periods.
The regression results for the entire sample and graded IPOs are presented in Panels A and B of Table 8, respectively. The results show a negative relation between IPO grade and underpricing, and the corresponding dummy variable (IPO_grade_D) is not significant; this indicates that IPO grading reduces underpricing but does not have a significant impact on the pricing of IPOs. This result concurs with findings of Khurshed et al. (2014b) but contrasts with those of Deb and Marisetty (2010) and Kashiramka et al. (2018) who observe that IPO grading leads to more efficient IPO pricing and, thus, aids in significantly minimizing IPO underpricing in India.
The results suggest that the key factors that significantly influence underpricing are issue size (Madhusoodanan & Thiripalraju, 1997; Ranjan & Madhusoodanan, 2004) and the total subscription of IPOs (Dhamija & Arora, 2017). The significance of these results is similar for both Panels A and B. Incurring larger costs is expected to obtain better IPO prices, perhaps due to reduced information asymmetry. The market demand for IPOs indicates that those with higher market demand lead to higher underpricing. Plausible reasons for this could be that IPOs with high demand during a ‘hot market’ period are often listed at high prices. In highly active markets, there is a greater tendency among investors to own assets regardless of their price.
The results of the analysis of underpricing over the different sample periods (Table 9) are revealing; this is because, even though the sample sizes were considerably large, only IPO findings from April 2014 to December 2017 were consistent with those in Table 8. Even though the variables are not significant, IPO grading has a higher impact on underpricing than anchor investors across all three sample periods; this implies that underpricing is influenced to a lesser extent by anchor investor participation than by IPO grading (Dhamija & Arora, 2017). Thus, reduced information asymmetry due to IPO grading helps reduce underpricing; however, since the results are not significant, they do not conform to information asymmetry and signalling theories.
Impact of IPO Grading and Anchor Investment on IPO Subscription
This sub-section discusses the results of the regression analysis based on Equations (3)–(7). It presents an analysis of the influence of IPO grading and anchor investor participation on subscription across the QIB, NII and RII investor categories.
The results (Tables 10–12) show that size and PIP emerge as significant factors that positively influence demand in IPOs (Nandha & Sawyer, 2002). Large companies with substantial assets are assumed to be financially sound and capable of enhancing future firm value. PIP boosts investor confidence when promoters hold a higher percentage stake in the company post-IPO, which is an indicator of the confidence of promoters in the IPO firm’s future performance. Although the other variables (age, RONW, IPO grade and AI_D) are insignificant, the positive relationship indicates that the more favourable these factors are, the greater is the demand for such stock. Thus, positive signalling factors such as promoters’ holdings, IPO grade and anchor investment play a role in increasing demand, as posited by signalling theory.
Impact of IPO Grading and Anchor Investment on Overall Subscription.
Impact of IPO Grading and Anchor Investment on IPO Subscription (Categorywise: 2007–2017).
Impact of Anchor Investors on IPO Subscription (Categorywise: April 2009–2017).
Table 11 provides a summary of factors that influence subscription across various investor categories. The results indicate that the predominance of institutional investors’ demand drives demand from NIIs and RIIs. These results are intuitively appealing because well-informed institutional investors are assumed to be relatively more stringent in their investment approach vis-à-vis their counterparts (retail investors) (Khurshed et al., 2014b; Neupane & Poshakwale, 2012). The other variables that have a significant impact on IPO demand are issue-related fundamentals—issue size and PIP—that carry the expected signs.
Although the IPO-grade dummy variable is insignificant for all investor categories (Table 11), its negative sign for the RII category merits an explanation. It can be observed from Table 6 that the average issue size of the complete sample is about ₹10.66 billion and that the mean size of ‘Grade 4’ and ‘Grade 5’ is approximately ₹23.78 billion. It can, thus, be noted that the high-grade IPOs consist of the larger issue sizes which are marginally oversubscribed by RIIs compared to the average issuance volume due to the limited investable resources available to them. However, QIBs have considerably larger investment funds and can, therefore, invest more aggressively in high-quality IPOs.
These results, congruent with the findings of Dhamija and Arora (2014) and Jacob and Agarwalla (2015), comprehensively suggest that IPO grading has almost no impact on investor demand. Our results contrast with those of Deb and Marisetty (2010) who found that grading significantly reduced underpricing. The difference can be attributed to the coverage of only mandatory grading in their study, while the current study covers both mandatory and voluntary grading. However, the impact on investor demand seems to be stronger with institutional investors, as indicated by their coefficient (Khurshed et al., 2014a). Even though the statistical significance of the IPO grade dummy variable is missing, it has been observed that across the years across all three investor categories, QIBs seem more influenced by IPO grades, followed by NIIs; IPO grading has a higher impact on QIB demand than the retail group. Therefore, the relationship between IPO grades and demand from the QIB category can also reflect the independent IPO investment valuation made by these institutions based on the fundamentals of the issue. Lastly, NII demand is highly influenced by QIB subscription and, in turn, RII subscription is affected by both QIB and NII subscription (Khurshed et al., 2014b; Neupane & Poshakwale, 2012).
Table 12 shows the regression results for Equation (3) using the complete sample. The results demonstrate that N_AI is significant in explaining the subscription pattern of QIB. While N_AI and QIB subscriptions influence NII subscriptions, RII subscriptions are influenced by N_AI as well as the subscriptions of other two investor categories (NII and QIB).
The coefficient for the anchor dummy is positive (although insignificant), which indicates that anchor-based IPOs are perceived positively by the investor classes (as shown in Table 12). It is further observed that the N_AI has a significantly positive effect on demand from almost all categories of investors. Thus, investment by AI in an IPO stimulates demand. This result aligns with that of Sahoo (2017) in the Indian context. If a higher subscription reflects a better quality of issue, then the positive association between AI and SUB lends credence to the notion that anchor investors make their investment decisions based on fundamentals and the quality of issue. It also shows the improvement in the credibility of the firm’s IPO due to anchor participation. This provides a positive signal to potential investors, thereby leading to higher demand.
The insignificance of the anchor dummy variable may be because their bid constituted only 30% of the institutional investor portion (15% of the total issue size) for most of the period considered by this study. However, N_AI’s significance is intuitively appealing because these anchor investors strengthen the confidence of the public as their investment remains locked in for 30 days from listing. Therefore, the larger the number of such investors, the more it may enhance the reputation of IPO. This may also lead to higher NII and RII subscription.
Table 12 further shows that both TA and RNW affect subscriptions in IPOs positively because large and profitable companies instil greater confidence, citing higher demand from potential investors.
The study also analysed the effects of anchor investments on retail and institutional subscriptions. As expected, the coefficients for the anchor investors are both positively and significantly related to the RII and QIB subscriptions. This supports the argument that anchoring plays a vital role in influencing other investors (Sahoo, 2017).
In terms of the impact of anchor investor participation in the RII, NII and QIB subscriptions, the coefficients for anchor investors are positive but not significant for all three categories; this supports the argument that the role played by anchor investors during the subscription period might not be substantially important. Furthermore, as expected, NII demand is highly influenced by QIB subscriptions and, in turn, RII subscriptions are affected by both QIB and NII subscription demand.
Concluding Observations
This article has examined the impact of IPO grading and anchor investor participation on pricing efficiency and subscription in the context of India. IPO grading, introduced in April 2007, seeks to provide investors with comprehensive information using an easy-to-understand symbol. On 4 February 2014, mandatory IPO grading was scrapped by SEBI and a voluntary grading system was implemented.
The results of this article indicate that rating has a positive impact on demand for high-grade IPOs; however, it is worth emphasizing that IPO grading was initially introduced with the aim of reducing information asymmetry, but that, in practice, this has not been completely effective (Dhamija & Arora, 2014). This is due to several reasons. Firstly, grading was conceptualized to help retail investors, but evidence does not suggest the translation of high IPO grading to higher demand. However, average underpricing is lower for graded issues over the entire sample than the ungraded issues but there is no statistical significance for the same. Moreover, the undervaluation of high-quality issues is lower than the low-value issues. Furthermore, the article finds no overall impact of IPO grading on underpricing; this also justifies the rationale of scrapping mandatory IPO grading in March 2014. The insignificance of IPO grading suggests that the rationale of providing a certificate of quality for the underlying issue through grading was not fulfilled. Thus, the findings of the study do not conform to signalling theory.
The study further assesses the influence of anchor investor participation on underpricing and subscription. It is noteworthy that a significant proportion (57.84%, a considerable increase from Sahoo, 2017 of 39.25%) of IPOs listed on the stock exchange are backed by anchor investors. Total anchor investment during the period 2009–2017 amounts to approximately 19% of overall issue size in this period. Furthermore, underpricing during the sample period (2007–2017) seemed to reduce from nearly 28% to 23%; minimum underpricing was observed during 2009–2013 (average underpricing over this period is 7%).
As with IPO grading, anchor investor participation also had an insignificant contribution to underpricing and the subscription pattern. Therefore, anchor investment may not reduce information asymmetry as expected. However, based on statistical coefficients, it was found that IPO grading negatively influences underpricing more than anchor investors. The findings could be attributed to the fact that most of the anchor investors (nearly 85% of 129 anchor-backed IPOs) bid at the maximum price in the price band; this may be an already expected outcome, and hence, overall, anchor investors may not have influenced underpricing. It has been further observed that across investor groups, the number of anchor investors significantly influences the investor subscription pattern.
The underpricing of anchor-backed IPOs has been noted at 12.35% on an average, whereas the corresponding value for non-anchor backed IPOs post-May 2009 is 11.26%. Moreover, the average underpricing of graded issues during the mandatory grading regime was 13.25%, while the same for the 39 ungraded issues was a considerable 42.86%. Accordingly, it has been observed throughout the analysis that IPO grading had a greater influence on underpricing than anchor investor participation. Also, in both the cases of IPO grading and anchor investor participation, there is a significant influence of QIB subscription on NII subscription as well as of QIB and NII subscription on RII subscription.
The findings imply that IPO grading and anchor investor participation do not play a significant role in reducing underpricing in the Indian stock market. On the other hand, it has been observed that QIB subscription significantly influences the NII and RII subscription; therefore, regulatory authorities should leverage this to reduce underpricing. These results can be useful to stock market regulators in emerging economies that have a similar economic environment and institutional structure to India.
This study considers a comprehensive view of anchor investors’ influence on IPOs; however, we must acknowledge the limitation that the analysis of the investment pattern of anchor investments in various IPOs, based on firm characteristics, management quality and firm reputation, remains underexplored. Therefore, future researchers should focus on the comprehensive impact of these aspects on IPO underpricing and the long-term performance of IPOs.
Footnotes
Acknowledgement
The authors would like to thank the editor, Professor Arindam Banik, and the anonymous reviewers for their time and extremely valuable suggestions to improve the quality of the article. The authors are solely responsible for any errors that might yet remain.
Declaration of Conflicting Interests
The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.
Funding
Juhi Gupta receives Junior Research Fellowship from University Grant Commission (UGC) India as part of her Ph.D. program. However, UGC had no involvement in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
