Innovations in financing: The impact of anchor investors in Indian IPOs

Author:Arnab Bhattacharya, Chinmoy Ghosh, Milena Petrova, Binay Bhushan Chakrabarti
Publication Date:01 Sep 2020
Eur Financ Manag. 2020;26:10591106. © 2020 John Wiley & Sons Ltd.
DOI: 10.1111/eufm.12257
Innovations in financing: The impact of anchor
investors in Indian IPOs
Arnab Bhattacharya
Binay Bhushan Chakrabarti
Chinmoy Ghosh
Milena Petrova
Finance and Control Group, Indian
Institute of Management Calcutta,
Kolkata, West Bengal, India
Department of Finance, School of
Business, University of Connecticut,
Storrs, Connecticut
Department of Finance, Martin J.
Whitman School of Management,
Syracuse University, Syracuse, New York
Chinmoy Ghosh, Department of Finance,
School of Business, University of
Connecticut, Storrs, CT 06269, USA.
In 2009, the Securities Exchange Board of India allowed
qualified institutional investors to anchor initial public
offerings (IPOs) by participating in the issue at a price
and allocation publicly disclosed preceding the issue.
We study anchor investors (AIs) in Indian IPOs during
20092017. We find the share allotment and the number
of AIs separately have significant impacts on valuation
and underpricing; however, the net effect is nonsigni-
ficant. Further, AIs significantly influence other institu-
tional investorsparticipation in the IPO and induce
lower aftermarket volatility. Overall, our evidence
suggests that AIs boost demand for and mitigate ex ante
information uncertainty of IPOs.
anchor investors, certification, information uncertainty, IPOs
G14; G24
An issue of passionate and continuing debate in the literature is the underpricing of initial
public offerings (IPOs). The information asymmetry hypothesis asserts that new issues are
underpriced, on average, to induce uninformed investors to participate in the IPO. A
The authors thank John Doukas (the Editor) and an anonymous referee for their insightful comments and guidance
throughout the review process. The usual disclaimer applies.
competing hypothesis, often referred to as the discretionary allocation hypothesis, asserts that
underpricing is the reward of betterinformed investors for revealing favorable information
about the issue. The prevalent method used in most countries, including the United States, to
seek information from informed institutions, is bookbuilding, in which the underwriter
solicits offers from institutional investors and, based on the demand from active market
participants, determines the final offer price and allocation the day before the issue goes
public. The stronger the bookbuilding demand, the greater the price adjustment and the final
offer price. A critical feature of the bookbuilding process in the United States and most other
countries is that the identity and allocation to the investors participating in bookbuilding are
not public information. The rationale for the allocation to privileged institutions is that it
induces them to reveal information about the value of the firm. However, the secrecy and
significant underpricing of bookbuilding IPOs have raised concerns about whether the
allocation is indeed a reward for information revelation or quid pro quo compensation to large
institutions for participation in future IPOs and continuing brokerage business with the
underwriter. Several recent papers have reported evidence consistent with both the
asymmetric information and quid pro quo hypotheses.
Partly in response to the controversy about the bookbuilding process, alternative methods of
pricing new issues have been attempted, the most common of which, used in several countries
in Europe and Asia, is the auction. The auction process puts the power over pricing into the
hands of bidders, with a limited role for the underwriter in pricing and allocation (Chiang,
Qian, & Sherman, 2010). However, the auction method has not been widely adopted.
Jagannathan, Jirnyi, and Sherman (2015) attribute the limited success of auctions to investors
inability to design an optimal bidding strategy that requires them to not only evaluate the
quality of the issue, but also determine the optimal bid.
The inherent conflicts of interest associated with bookbuilding and the challenges of
auctions have prompted the development of other IPO offering mechanisms. Several
authors have proposed twostage issues where the offerings are restricted to informed
investors in the first stage, followed by a regular bookbuilt offering in the second stage open
to retail investors (Bonini & Voloshyna, 2013; Chiang et al., 2010; Jagannathan et al., 2015;
Mello & Parsons, 1998; Vandemaele, 2003). Our purpose in this study is to examine a two
stage process of new equity offerings introduced in India and several countries in Asia and
Europe over the last 15 years. Specifically, our focus is the role of anchor investors (AIs) in
public equity offerings, introduced in India in June 2009 by the Securities Exchange Board
of India (SEBI) by an amendment of the Disclosure and Investor Protection (DIP)
Guidelines to boost investor confidence and strengthen the public issue market.
In the first
stage, SEBI allows the discretionary allocation of IPO shares to AIs of up to 30% (increased
to 60% in 2014) of the portion available for allocation to qualified institutional buyers (QIBs)
at a predetermined price, which is made public before the issue opens for public
subscription. The identity of the AIs and the offer price and share allocation to them are
thus known before the second stage of the offering.
The idea of AIs was triggered by the global financial crisis of 20082009 and the bearish
sentiment of foreign institutional investors (FIIs), which severely impacted the Indian capital
Jenkinson, Jones, and Suntheim (2018) find that syndicate banks make favorable allocations to investors who share information that is useful in pricing. They
also find that investors, who generate higher revenues elsewhere, particularly through brokerage commissions, receive more IPO allocations. Reuter (2011)
reports a positive correlation between the brokerage commission paid by mutual funds to the lead underwriters of IPOs and their holdings in these IPOs.
Introduction of concept of anchor investor in public issues through book building route,SEBI Circular No. SEBI/CFD/DIL/DIP/36/2009/09/07, July 9, 2009.
market and had a cascading effect on the primary and secondary markets.
The volume of IPOs
therefore decreased dramatically, from 101 IPOs in 2007 to 42 IPOs in 2008, and fell further to
only 17 IPOs in 2009.
At this critical juncture, as fear and pessimism gripped the market, it was
hoped that the commitment of reputable institutional investors through the anchor mechanism
would act as a credible signal of IPO quality and increase investorsinterest in the issue.
We focus on the efficacy of the regulatory reform of introducing AIs in reviving the Indian
primary capital market and its impact on IPO valuation and performance. More specifically, we
examine whether the public knowledge of the initial price and allocation to AIs reduces ex ante
uncertainty around the IPO valuation, boosts investorsconfidence in the value of the IPO, and
enhances its marketability. We invoke IPO valuation theories to explore the impact of AIs on
the valuation and performance of IPOs in India, including the certification of IPO quality, the
discretionary allocation of IPO shares, and retail and institutional investor overreaction. Under
the certification hypothesis, which draws upon information asymmetrybased models,
knowledge of AI participation should mitigate information asymmetry, such that anchor
backed IPOs will be subject to lower underpricing than nonanchor IPOs. The greater the
number of participating AIs and their allocation, the lower the underpricing. The allocation
hypothesis posits that underwriters compensate informed investors for revealing favorable
information by allocating more shares to them. However, if the number of shares to be offered
is rationed, underwriters partially adjust the final offer price upward to allow underpricing as a
reward to informed investors. Accordingly, the greater the number of participating AIs and
their allocation, the larger the price adjustment. Finally, if the reputation of the AIs leads to
oversubscription, the resulting excess demand induces greater underpricing. The aggregate
effect of the three hypotheses is indeterminate and an empirical issue.
Using a sample of 182 IPOs listed on the National Stock Exchange/BSE between August 2009
and September 2017, including 107 anchorbacked IPOs, we examine the impact of AI
participation on underpricing, price adjustment, primary market demand, postIPO volatility
and liquidity, and the longterm performance of the issuing firm. Our analyses reveal evidence
consistent with the hypotheses: the allocation to AIs (AI share) is negatively related to
underpricing, which is consistent with the certification and allocation hypotheses; and the
number of AIs (AI number), a proxy for demand by AIs, is positively related to underpricing,
which is consistent with the overreaction hypothesis. However, in the aggregate, the net effect
of AIs on underpricing is nonsignificant. Next, we test the impact of AIs on valuation and price
adjustment. The certification of IPO quality through disclosure of the initial price, the
discretionary allocation to AIs, which induces them to reveal favorable information about the
IPO, and investor overreaction are all consistent with higher IPO valuation. Our analyses reveal
that the initial AI price is related to the final price adjustment. We further find that the number
of AIs receiving an initial allocation is positively related to price adjustment. However,
inconsistent with our expectation, the share of AIs is generally negatively related to price
adjustment, resulting in a nonsignificant net effect of AIs on valuation. Finally, we find that
The Standard & Poor's (S&P) Bombay Stock Exchange Sensitive Index, or S&P BSE 30 Sensex, the most widely followed market index in India, increased by
23% in 2007 and then fell sharply, by about 63%, in 2008. The volatility in the secondary market, the global recessionary outlook, and the consequent loss of
investor confidence were a serious deterrent to the new issues market in India.
In terms of IPO proceeds, the total volume of funds raised fell from USD 9.2 billion in 2007 to USD 4.3 billion in 2008, and further to USD 3.5 billion in 2009.
One implication of the quid pro quo hypothesis is that the AIs receiving privileged allocation will be observed offering more future business to the underwriter.
Unfortunately, we cannot directly test this prediction because of lack of data. Therefore, our main focus is the efficacy of the AI concept and the impact of the
information on the identity, price, and allocation to AIs on IPO valuation.

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