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

• Author: Arnab Bhattacharya,Chinmoy Ghosh,Milena Petrova,Binay Bhushan Chakrabarti
• Published date: 01 September 2020
• DOI: http://doi.org/10.1111/eufm.12257
• Date: 01 September 2020

Eur Financ Manag. 2020;26:1059–1106. wileyonlinelibrary.com/journal/eufm © 2020 John Wiley & Sons Ltd.

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DOI: 10.1111/eufm.12257

ORIGINAL ARTICLE

Innovations in financing: The impact of anchor

investors in Indian IPOs

Arnab Bhattacharya

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Binay Bhushan Chakrabarti

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Chinmoy Ghosh

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Milena Petrova

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1

Finance and Control Group, Indian

Institute of Management Calcutta,

Kolkata, West Bengal, India

2

Department of Finance, School of

Business, University of Connecticut,

Storrs, Connecticut

3

Department of Finance, Martin J.

Whitman School of Management,

Syracuse University, Syracuse, New York

Correspondence

Chinmoy Ghosh, Department of Finance,

School of Business, University of

Connecticut, Storrs, CT 06269, USA.

Email: chinmoy.ghosh@uconn.edu

Abstract

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

2009–2017. 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 investors’participation 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.

KEYWORDS

anchor investors, certification, information uncertainty, IPOs

JEL CLASSIFICATION

G14; G24

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INTRODUCTION

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

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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 better‐informed 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.

1

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 two‐stage 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.

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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 2008–2009 and the bearish

sentiment of foreign institutional investors (FIIs), which severely impacted the Indian capital

1

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.

2

‘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.

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BHATTACHARYA ET AL.

market and had a cascading effect on the primary and secondary markets.

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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.

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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 investors’interest 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 investors’confidence 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 asymmetry‐based models,

knowledge of AI participation should mitigate information asymmetry, such that anchor‐

backed IPOs will be subject to lower underpricing than non‐anchor 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.

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Using a sample of 182 IPOs listed on the National Stock Exchange/BSE between August 2009

and September 2017, including 107 anchor‐backed IPOs, we examine the impact of AI

participation on underpricing, price adjustment, primary market demand, post‐IPO volatility

and liquidity, and the long‐term 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

3

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.

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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.

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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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