Initial Public Offering Allocations
by
Sturla Lyngnes Fjesme
A dissertation submitted to BI Norwegian Business School
for the degree of PhD
PhD specialization: Financial Economics
Series of Dissertations 9/2011
BI Norwegian Business School
Sturla Lyngnes Fjesme
Initial Public Offering Allocations
© Sturla Lyngnes Fjesme
2011
Series of Dissertations 9/2011
ISBN: 978-82-8247-029-2
ISSN: 1502-2099
BI Norwegian Business School
N-0442 Oslo
Phone: +47 4641 0000
www.bi.no
Printing: Nordberg Trykk
The dissertation may be downloaded or ordered from our website
www.bi.no/en/Research/Research-Publications/
Abstract
Stock exchanges have rules on the minimum equity level and the minimum number of
shareholders that are required to list publicly. Most private companies that want to list
publicly must issue equity to be able to meet these minimum requirements. Most companies
that list on the Oslo stock exchange (OSE) are restricted to selling shares in an IPO to a large
group of dispersed investors or in a negotiated private placement to a small group of
specialized investors. Initial equity offerings have high expected returns and this makes them
very popular investments. Ritter (2003) and Jenkinson and Jones (2004) argue that there are
three views on how shares are allocated in the IPO setting. First, is the academic view based
on Benveniste and Spindt (1989). In this view investment banks allocate IPO shares to
informed investors in return for true valuation and demand information. Informed investors
are allocated shares because they help to price the issue. Second, is the pitchbook view where
investment banks allocate shares to institutional investors that are likely to hold shares in the
long run. It is argued, by investment banks, that buy-and-hold investors will create price
stability that is good for the issuing companies. Finally, is the rent seeking view, or profit
sharing view, where investment banks allocate shares to investors in return for kickbacks.
There are four types of IPO rent seeking that have been investigated by U.S. regulators (the
SEC and the NASD), see Liu and Ritter (2010). IPO allocations can be tied to future
corporate business for the banks (IPO spinning), after-listing purchases of the IPO shares
(IPO laddering) and stock-trading commissions. Investment banks and companies can also
agree on high underpricing in return for after-listing company share coverage from a star
analysts provided by the bank (analyst conflict of interest). Underpriced shares are then
allocated to bank clients that generate high stock-trading commission for the investment bank.
In the paper 'Laddering in Initial Public Offering Allocations' it is investigated if IPO
allocations are tied to after-listing purchases of the IPO shares (IPO laddering). In the paper
'Using Stock-trading Commissions to Secure IPO Allocations' it is investigated if IPO
allocations are tied to investor stock-trading commission.
Private companies that want to list publicly can, as an alternative to the IPO allocation,
issue shares in a negotiated private placement to a small group of specialized investors. Most
theoretical papers on equity offerings, however, show that IPOs will almost always be
preferred to the negotiated private placement by the seller, see Bulow and Klemperer (1996),
Bulow and Klemperer (2009) and French and McCormick (1984). Why some companies use
private placements has therefore been the focus of many empirical studies in finance, see
Wruck (1989), Hertzel and Smith (1993), Barclay et al. (2007), Anshuman et al. (2010) and
Cronqvist and Nilsson (2005). The research question addressed in the paper 'Initial Public
Offering or Initial Private Placement?' is whether private placements are used, instead of
IPOs, to transfer private benefits of control from sellers to buyers. A common contribution of
all papers is that we introduce new and unique data on private company share ownership. This
data allow us to investigate share allocations questions it has previously been difficult to
investigate.
Acknowledgements
I am deeply indebted to Professor Øyvind Norli, my supervisor, for all the continued support,
guidance and encouragement throughout my time as a PhD student. I would also like to thank
Professor Roni Michaely for help and guidance, and for making my stay at Cornell University
such a great experience. I am very grateful to François Derrien and Øyvind Bøhren, who gave
me many helpful and detailed suggestions on my pre-doctoral defense and who helped me
with the job market process. I am grateful to Bruno Gerard for supervising my master degree
thesis and for helping me with the job market process and my PhD thesis. I would also like to
thank Karin Thorburn, Diane Denis, William Megginson, Paul Ehling, Christopher Vincent,
David De Angelis, Alyssa Anderson, Maury Saslaff, Yelena Larkin, Gideon Saar, Jay Ritter,
Dag Michalsen and Richard Priestley for support and for commenting on the thesis. I would
like to thank my fellow PhD students, Limei Che, Christian Heyerdahl-Larsen, Morten
Josefsen, Siv Staubo, Siri Valseth, Nam Huong Dau, Ignacio Garcia de Olalla Lopez, Junhua
Zhong, and my friends, Per Helmer Thorkildsen, Henrik Hasner, Kjell Olav Dalen, Jan
Kenneth Evanger, Dag Djurovic, Martin Jensen, Per-Eilert Vierli and Øystein Larsen, for
support and many interesting economic discussions. Finally, I would like to thank my family,
Sølvi Lyngnes, Torbjørn Fjesme, Arvid Lyngnes Fjesme, Sunniva Victoria Fjesme and Hanna
Kristiansen, for all the help and support during my time as a PhD student.
Contents
1 Introduction
1.1 Laddering in Initial Public O¤ering Allocations . . . . . . . . . . . . . . .
1.2 Using Stock-trading Commissions to Secure IPO Allocations . . . . . . . .
1.3 Initial Public O¤ering or Initial Private Placement? . . . . . . . . . . . . .
3
4
4
4
2 Laddering in Initial Public O¤ering Allocations
7
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Related literature . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.3 Predictions and testable implications . . . . . . . . . . . . . . . .
2.3.1 The IPO laddering hypothesis . . . . . . . . . . . . . . . .
2.3.2 Other testable implications of IPO laddering . . . . . . . .
2.4 The listing process and the incentives to engage in IPO laddering
2.4.1 Why investment banks use IPO laddering . . . . . . . . . .
2.4.2 Why laddering investors agree to buy more shares . . . . .
2.4.3 Why IPO laddering is a problem . . . . . . . . . . . . . . .
2.5 Data description . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.5.1 The IPO sample . . . . . . . . . . . . . . . . . . . . . . .
2.5.2 The remaining IPOs . . . . . . . . . . . . . . . . . . . . .
2.5.3 Aggregate laddering . . . . . . . . . . . . . . . . . . . . . .
2.5.4 Variable explanations . . . . . . . . . . . . . . . . . . . . .
2.6 Empirical results . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.6.1 Optimal holdings . . . . . . . . . . . . . . . . . . . . . . .
2.6.2 The e¤ect of IPO laddering . . . . . . . . . . . . . . . . .
2.6.3 Robustness and aggregate IPO laddering . . . . . . . . . .
2.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
3 Using Stock-trading Commissions to Secure IPO Allocations
3.1 Introduction . . . . . . . . . . . . . . . . . . . .
3.2 Related literature . . . . . . . . . . . . . . . . .
3.3 Theoretical predictions and testable implications
3.3.1 The rent seeking view of IPO allocations
3.3.2 The pitchbook view of IPO allocations . .
3.3.3 The academic view of IPO allocations . .
3.4 Data . . . . . . . . . . . . . . . . . . . . . . . .
3.4.1 IPO allocations . . . . . . . . . . . . . .
3.4.2 After-listing ownership . . . . . . . . . .
3.4.3 Variable description . . . . . . . . . . .
3.5 Empirical results . . . . . . . . . . . . . . . . .
3.5.1 The rent seeking view of IPO allocations
3.5.2 The pitchbook view of IPO allocations . .
3.5.3 The academic view of IPO allocations . .
3.5.4 Robustness . . . . . . . . . . . . . . . .
3.6 Conclusion . . . . . . . . . . . . . . . . . . . . .
1
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
9
11
12
13
14
15
15
16
16
17
18
18
18
19
21
24
24
24
24
43
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
45
46
47
48
49
50
50
51
51
52
53
54
55
55
56
56
4 Initial Public O¤ering or Initial Private Placement?
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . .
4.2 Literature review . . . . . . . . . . . . . . . . . . . . .
4.3 The road to the listing . . . . . . . . . . . . . . . . . .
4.3.1 The formal listing process . . . . . . . . . . . .
4.3.2 A public or a private o¤ering? . . . . . . . . . .
4.4 Theoretical predictions and testable implications . . . .
4.4.1 The private bene…ts of control hypothesis . . . .
4.4.2 Alternative explanations . . . . . . . . . . . . .
4.4.3 Other control measures . . . . . . . . . . . . . .
4.4.4 Private bene…ts of control also after the listing .
4.5 Data and descriptive statistics . . . . . . . . . . . . . .
4.5.1 Descriptive statistics . . . . . . . . . . . . . . .
4.5.2 Variable description . . . . . . . . . . . . . . .
4.6 Empirical Results . . . . . . . . . . . . . . . . . . . . .
4.6.1 The private bene…ts of control hypothesis . . .
4.6.2 Alternative explanations . . . . . . . . . . . . .
4.6.3 Private bene…ts of control also after the listing .
4.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . .
5 Summary
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
73
74
75
77
77
78
79
80
81
82
83
83
84
84
85
85
86
86
87
100
2
1
Introduction
This dissertation consists of three papers; ’Laddering in Initial Public O¤ering Allocations’, ’Using Stock-trading Commissions to Secure IPO Allocations’and ’Initial Public
O¤ering or Initial Private Placement?’ The rest of this section is organized as follows. I
…rst discuss the common feature of the papers, namely the allocations of Initial Public
O¤ering (IPO) shares. I then brie‡y discuss the main results in each of the papers.
Stock exchanges have rules on the minimum equity level and the minimum number
of shareholders that are required to list publicly. Most private companies that want to
list publicly must issue equity to be able to meet these minimum requirements. Most
companies, that list on the Oslo stock exchange (OSE), are restricted to selling shares
in an IPO to a large group of dispersed investors or in a negotiated private placement
to a small group of specialized investors. Initial equity o¤erings have high expected
returns and this makes them very popular investments. Ritter (2003) and Jenkinson and
Jones (2004) argue that there are three views on how shares are allocated in the IPO
setting. First, is the academic view based on Benveniste and Spindt (1989). In this view
investment banks allocate IPO shares to informed investors in return for true valuation
and demand information. Informed investors are allocated shares because they help to
price the issue. Second, is the pitchbook view where investment banks allocate shares
to institutional investors that are likely to hold shares in the long run. It is argued, by
investment banks, that buy-and-hold investors will create price stability that is good for
the issuing companies. Finally, is the rent seeking view, or pro…t sharing view, where
investment banks allocate shares to investors in return for kickbacks. There are four
types of IPO rent seeking that have been investigated by U.S. regulators (the SEC and
the NASD), see Liu and Ritter (2010). IPO allocations can be tied to future corporate
business for the banks (IPO spinning), after-listing purchases of the IPO shares (IPO
laddering) and stock-trading commissions. Investment banks and companies can also
agree on high underpricing in return for after-listing company share coverage from a star
analysts provided by the bank (analyst con‡ict of interest). Underpriced shares are then
allocated to bank clients that generate high stock-trading commission for the investment
bank. In the paper ’Laddering in Initial Public O¤ering Allocations’it is investigated if
IPO allocations are tied to after-listing purchases of the IPO shares (IPO laddering). In
the paper ’Using Stock-trading Commissions to Secure IPO Allocations’it is investigated
if IPO allocations are tied to investor stock-trading commission.
Private companies can, as an alternative to the IPO, issue shares in a negotiated
private placement to a small group of specialized investors. Most theoretical papers on
equity o¤erings, however, show that IPOs will almost always be preferred to the negotiated
private placement by the seller, see Bulow and Klemperer (1996), Bulow and Klemperer
(2009) and French and McCormick (1984). Why some companies use private placements
has therefore been the focus of many empirical studies in …nance, see Wruck (1989),
Hertzel and Smith (1993), Barclay et al. (2007), Anshuman et al. (2010) and Cronqvist
and Nilsson (2005). The research question addressed in the paper ’Initial Public O¤ering
or Initial Private Placement?’ is whether private placements are used, instead of IPOs, to
transfer private bene…ts of control from sellers to buyers. A common contribution of all
papers is that we introduce new and unique data on private company share ownership.
This data allow us to investigate share allocations questions it has previously been di¢ cult
to investigate.
3
1.1
Laddering in Initial Public O¤ering Allocations
IPO laddering is the process where share allocations are tied to the after-listing purchases
of the company shares. IPO laddering has been known by regulators for a long time
(the SEC sent out warnings to investment banks that laddering is illegal the …rst time
in 1961), but there has been limited empirical research on IPO laddering. A potential
reason for this is that it is very di¢ cult to investigate laddering because investment banks
rarely distribute information about allocation practices. In this paper we use unique data
from the Oslo Stock Exchange (OSE) that allow us to observe the after-listing trading
of investors that are allocated IPO shares. The data consists of 16,593 combinations of
investor IPO allocations, stock-trading commission and after-listing trading on the OSE
in the period from 1993 to 2007. This data allow us to investigate laddering at the
investor level. The main contribution of this paper is that we show a strong and robust
relationship between IPO allocations and the number of shares that are purchased after
new listings at the investor level. This relationship is stronger for investors that sell all
shares again right after the listing, in underpriced IPOs and in IPOs with a positive drift
in the share price after the listing. These are the investors and the IPOs that the existing
research identi…es as the most likely laddering investors. These …ndings are consistent
with the suspicion that IPO shares are allocated to investors that buy shares dictated by
the investment bank after the listing (laddering). This …nding extends to Hao (2007) and
Gri¢ n et al. (2007).
1.2
Using Stock-trading Commissions to Secure IPO Allocations
Another concern for regulators is that IPO allocations are tied to excessively large stocktrading commissions and that such a practice is illegal kickbacks from investors to investment banks. Using the same data as in ’Laddering in Initial Public O¤ering Allocations’,
we are able to link stock-trading commission and IPO allocation at the investor level. The
main …nding of the paper is a strong and robust positive relationship between the level
of stock-trading commission generated by an investor prior to the IPO and the number
of shares the same investor receives through the IPO allocation. This …nding indicates
that investors are able to buy IPO allocations by trading excessively to generate commission. The …nding extends to Reuter (2006), Nimalendran, Ritter and Zhang (2006),
Ritter (2003) and Jenkinson and Jones (2004) who all argue that investment banks are
likely to allocate IPO shares in return for stock-trading commission.
1.3
Initial Public O¤ering or Initial Private Placement?
Companies can, as an alternative to the IPO, sell shares in a negotiated private placement.
Most theoretical research on equity o¤erings show that auctions, that are similar to IPOs,
will in most cases be preferred by the seller of a company. In practice, however, there are
many companies that use negotiated private placements to raise equity. Several studies
have proposed explanations to this private placement choice. Some papers argue that
private placements are used to attract certain investors, to keep management in control,
to reduce undervaluation or to reduce problems associated with information asymmetry
(Wruck, 1989; Hertzel and Smith, 1993; Barclay et al.,2007; Anshuman et al., 2010;
4
Cronqvist and Nilsson, 2005). Other papers suggests that private placements are used
when buyers value private bene…ts of control over the stand alone cash ‡ow value of the
company (Zingales, 1994; Zingales, 1995; Zwiebel, 1995 and Damodaran, 2005). The
main contribution of our paper is that we show a strong and robust relationship between
private bene…ts of control, before the initial o¤ering, and the use of private placements.
This indicates that private placements are used to transfer private bene…ts of control from
sellers to buyers. This …nding supports Zingales (1995) in that private placements are
used to transfer company control rights.
5
.
6
2
Laddering in Initial Public O¤ering Allocations
Sturla Lyngnes Fjesme1
BI Norwegian Business School
.
.
.
.
.
.
.
.
JEL classi…cation: G3; G24
Keywords: IPO allocations; Laddering; Tie-in agreements; Rent seeking; Equity o¤erings
1
I am very grateful to Øyvind Norli (supervisor), François Derrien, Roni Michaely, Øyvind Bøhren,
Bruno Gerard, Karin Thorburn (discussant), Diane Denis (discussant), William Megginson (discussant),
Paul Ehling, Christopher Vincent, David De Angelis, Alyssa Anderson, Maury Sasla¤, Yelena Larkin,
Gideon Saar, and seminar participants at Cornell University, BI Norwegian Business School, the Nordic
Finance Network (NFN) workshop in Lund 2010, the Financial Management Association (FMA) Doctoral Student Consortium in Hamburg 2010, Stockholm University, the University of Gothenburg, the
University of Warwick and the University of Melbourne for valuable suggestions. I thank the Oslo Stock
Exchange VPS for providing the data, the Financial Supervisory Authority of Norway (Finanstilsynet)
and the companies and investment banks that helped locate the listing prospectuses. Part of the article
was written while I was a visiting PhD student at the S.C. Johnson Graduate School of Management
at Cornell University. I also thank the American-Scandinavian-Association and the Norwegian Central
Bank for …nancial support. All errors are my own.
Correspondence: BI Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway, Email address:
[email protected], Telephone (USA): +1-607-793-6911, Telephone (Norway): +47-957-722-43.
7
Abstract
Tying Initial Public O¤ering (IPO) allocations of common stock to afterlisting purchases in the IPO shares, a process referred to as IPO laddering,
has resulted in large-scale investigations of the major investment banks by the
SEC and the National Association of Securities Dealers (NASD). This process
is claimed to drive after-listing share prices above their fundamental values,
and is illegal under the laws against market manipulation and fraud. As a
result, investment banks are reluctant to distribute information about their
allocation practices, so investigating the alleged laddering and its implications
has proven to be di¢ cult. With a new and unique data set of 16,593 IPO
allocations on the Oslo Stock Exchange (OSE), we con…rm the SEC’s suspicion
that IPO allocations are dependent on after-listing trading. Allocations to
after-listing purchasing investors has been combined with allocations to high
stock-trading commissions generating investors that can take advantage of the
IPO laddering, thereby allowing investment banks to recapture some of the
money left on the table in IPOs. Allocated IPO investors buy more shares after
new listings because they are rewarded for doing so with more IPO allocations.
8
2.1
Introduction
On December 6, 2000 the Wall Street Journal (WSJ) reported that the SEC and the
NASD were investigating some of the major investment banks for tying IPO allocations
to after-listing purchases. An investment banker interviewed for the article admits that
IPO allocations to investors with after-listing interest could occur, but explains that
after-listing interest is a signal that the investor is of the buy-and-hold type. Since banks
strive to allocate shares to buy-and-hold investors to create price stability, after-listing
purchases are related to IPO allocations. An investor con…rms that expressing an interest
in after-listing purchases is one way of obtaining more IPO allocations.
Three U.S. investment banks have been sued by the SEC over allegations of IPO
laddering after the WSJ article, though all three later settled (without admitting guilt).2
The allegations made by the SEC are that the banks promised investors that they would
receive an increased allocation in current hot IPOs if they bought additional shares after
the listing of the same IPOs.3 The banks, allegedly asked IPO applicants if they would
be interested in buying more shares after the listings and at what price and quantity.
Since IPO laddering is illegal, there are no formal records of tying IPO allocations to
after-listing trading, as agreements are likely to be made over the phone or in person
rather than in a written agreement.4 It is, however, possible to see if there is a positive
and consistent relationship between IPO allocations and after-listing trading by investors.
Such a relationship would strongly indicate that IPO allocations are tied to after-listing
buy trades, although this data is very hard to obtain in the U.S. (even for the SEC and
NASD). Using data from the Oslo Stock Exchange (OSE), we are able to observe the
after-listing trading of investors that were allocated shares in IPOs. The data consists
of 16,593 IPO allocations with stock-trading commissions and after-listing trading on the
OSE in the period from 1993 to 2007. Stock ownership by investor ID is observed for all
companies throughout the listing process, and is used to calculate actual IPO allocations.
It is, from this data that the relationship between IPO allocations, after-listing purchases,
commissions and future IPO allocations is investigated.
The main contribution of this paper is that we show a strong and robust relationship
between the number of shares that are purchased after new listings and IPO allocations
by laddering investors. This is consistent with the SEC’s suspicion that IPO shares
are allocated to investors that buy shares dictated by the investment bank. We de…ne
laddering as allocated IPO investors that continue to buy shares right after the listing
before they sell all shares within six months of the listing date. This sales requirement
is included to remove rationed investors that buy shares to reach optimal holding levels
after the listing. We also show that IPO laddering bene…ts both investors and investment
banks and that the speci…ed trading can not be attributed to other explanations such as
share rationing. In the 50% IPOs with the highest laddering there is an average aggregate
IPO allocation to laddering investors of 4%. On average these investors buy 6% more of
the aggregate IPO shares after the listing, and then sell on average 10% of the aggregate
2
See the litigation releases made by the SEC at http://www.sec.gov/litigation/litreleases/lr18385.htm,
http://www.sec.gov/litigation/litreleases/lr19050.htm, and http://www.sec.gov/litigation/litreleases/lr19051.htm.
3
There are many news articles and web pages that cover laddering and the laddering cases
in the U.S. For excellent overviews please see Deneen and Hooghuis (2001), Aggarwal et
al. (2006) and the IPO securities litigation websites at http://www.iposecuritieslitigation.com/,
http://www.dandodiary.com/articles/ipo-laddering-cases/ and the articles by Susan Pulliam and Randall
Smith, the journalists that …rst published the laddering scandal in the Wall Street Journal series in 2000.
http://www.pbs.org/wgbh/pages/frontline/shows/dotcon/interviews/pulliam-smith.html
4
In both Norway and the U.S. IPO laddering is illegal under the law against market manipulation.
9
IPO shares shortly after the listing. As a consequence of this, we are not able to reject
that IPO allocations are tied to after-listing purchases of IPO shares.
The SEC is investigating IPO laddering because laddering falsely increases the price
and demand of speci…c shares (price manipulation). In addition to being abusive and
discriminatory, IPO laddering is undesirable because it increases adverse selection problems (by deterring non-laddering investors from applying for IPO shares).5 Investment
banks use IPO laddering because this practice will boost share prices after the listings.
IPO shares that will go up in price for sure can also be allocated to bank clients that
provide high levels of stock-trading commissions, thereby ensuring a future relationship
between banks and investors that generate high levels of income for the banks. We show
that investment banks and laddering inventors earn money on IPO laddering, while most
companies with high levels of IPO laddering fall in price in the …rst six months after the
listing (8 out of 11).
IPOs generally have high …rst day returns (on average 8% in Norway in the sample
period) and IPO shares are therefore very popular investments. Most IPOs are many
times oversubscribed and few investors are allowed to buy IPO shares. Investment banks
are reluctant to distribute information about their allocation practices, and the continued
investigation by the SEC and the NASD on investment bank allocation practices has not
made data collection any easier. Ritter (2003) and Jenkinson and Jones (2004) argue
that there are three main views on how IPOs are allocated. First, the academic view
based on Benveniste and Spindt (1989) is that investors obtain IPO allocations in return
for revealing their true valuations of the IPO shares. These investors help to price the
issue. Second, the pitchbook view argues that IPO shares are allocated to buy-and-hold
investors, and long-term buy-and-hold investors will create price stability. Finally, the
rent seeking view argues that IPOs are allocated in return for kickbacks. The types of
rent seeking that have been under SEC investigation are to condition IPO allocations
on generated stock-trading commissions, future corporate business (IPO spinning) or
after-listing purchases of IPO shares (IPO laddering), see Liu and Ritter (2010). IPOs
can also be intentionally underpriced in exchange for future analyst coverage (analyst
con‡ict of interest). There are many articles that have studied both the academic and
pitchbook view, but a lack of data has limited the number of articles which have studied
the rent seeking view.6 Cli¤ and Denis (2004) show that IPO underpricing is related
to after-listing analyst coverage, Liu and Ritter (2010) reveal that IPOs are allocated in
return for IPO spinning and Fjesme, Michaely and Norli (2011) document that IPOs are
allocated in return for stock-trading commissions. No empirical papers have been able to
establish a relationship between IPO allocations and after-listing purchases of IPO shares
(IPO laddering). Hao (2007) identi…es the incentives to engage in IPO laddering and the
implications of IPO laddering theoretically. Gri¢ n, Harris and Topaloglu (2007) show
empirically that it is likely that IPO laddering is used by studying aggregate after-listing
trading at the brokerage house level. Gri¢ n et al. (2007) …nd that after-listing buy trades
primarily go through lead managers, whereas after-listing sell trades go through other
managers in the weeks after new listings. This is consistent with IPO laddering because
laddering investors will place their orders through the lead manager as evidence that the
trades have been made. Previous research has not been able to study the relationship
5
Laddering is not new. The SEC sent out warnings that laddering was illegal in 1961, 1984 and 2000
(Gri¢ n et al., 2007).
6
See, amongst others, Jenkinson and Jones (2004), Ritter (2003) and Fjesme, Michaely and Norli
(2011) for papers that summarizes studies on IPO allocations.
10
between IPO allocations and after-listing trading of the IPO shares at the investor level
due to data limitations.7 The main research question addressed in this paper is whether
investors are able to increase allocations in IPOs by committing to buy more shares after
the listing of the same IPOs. We also investigate whether future IPO allocations are tied
to after-listing purchases in past IPOs.
The rest of the paper is organized as follows: Section 2.2 describes related literature.
Section 2.3 describes predictions and testable implications. Section 2.4 describes the IPO
process and the factors that create the incentives to engage in IPO laddering. Section
2.5 describes the data set. Section 2.6 describes the empirical results, and Section 2.7
concludes.
2.2
Related literature
The two main theoretical papers that model IPO laddering are Hao (2007) and Aggarwal
et al. (2006). Hao (2007) …rst show the factors that create the incentives to engage
in IPO laddering. Then, the e¤ects of IPO laddering on companies are identi…ed. Hao
(2007) argue that IPO laddering can bene…t the underwriter from two sources. First,
IPO laddering can boost the after-listing market price. This will reduce the underwriters
expected cost of price support after the listing. From this it is expected that IPO laddering
will be stronger when there is a positive drift in the after-listing share price. Second, IPO
laddering can bene…t the underwriter through rent seeking. If some allocated investors pay
a part of their pro…t from IPO allocations back to the underwriter through stock-trading
commission payments, then a part of the laddering generated pro…ts will go back to the
underwriter. Hao (2007) argue that when the underwriter share in on the pro…t from
the underpricing, then laddering is stronger when the realized percentage underpricing is
higher. Hao (2007) also show that expected underpricing increases IPO laddering. From
this it is expected that laddering will be stronger when there is a positive underpricing.
Hao (2007) also predicts that laddering is positively related to IPO allocations to high
stock-trading commission generating investors. IPO laddering will in‡ate prices after the
listing, so investment banks use laddering to make share prices go up after the listing
(more than they otherwise would have). Shares that go up in price for sure are then
be allocated to clients that generate high stock-trading commissions. Hao (2007) …nally
predicts that laddering will increase the IPO o¤er price, the …rst day closing price, the
money left on the table and the long-run underperformance of the newly listed companies.
Aggarwal et al. (2006) predict that IPO laddering increases underpricing, turnover and
long-run underperformance of the newly listed companies. These are all e¤ects of an
increased demand of the IPO shares right after the listing that will fall in the long-run.
There are three main empirical papers that provide indirect evidence of the existence
of IPO laddering. Gri¢ n et al. (2007) look at investors who buy shares through lead
and other underwriters in the three weeks after the listing of 1,294 Nasdaq IPOs in
the period 1997 to 2002. As opposed to this study, they examine aggregate trading at
the brokerage house level. They argue that the after-listing buy trades through the lead
7
Gri¢ n, Harris and Topaloglu (2007) …nd that it is very likely that investment banks tie IPO allocations to after-listing purchases. The major di¤erence is that Gri¢ n et al. (2007) study the after-listing
trading through co and lead managers at the brokerage house level, and we study actual IPO allocations
and after-listing trading on the investor level. Gri¢ n et al. (2007) show that it is likely that laddering is
being used by investigating through what manager after-listing buy orders are placed, and we show that
after-listing buy orders are related to current and future IPO allocations by investors.
11
manager (main underwriter) in the weeks after the listings are likely to be part of laddering
agreements, while buy trades through other managers (co-underwriters that help to spread
the issue) in the same period are likely to not be part of the agreements. The paper …nds
that it is likely that IPO allocations are tied to after-listing purchases because there
are unproportional high levels of buy trades through lead managers after new listings.
Aggarwal et al. (2006) study IPOs that have been sued on laddering allegations to test
the implications of laddering. The data includes 33 IPOs sued by the SEC, 140 class
action law suits and 735 non-laddering IPOs on Nasdaq, NYSE and AMEX in the period
1998 to 2000. The main …ndings are that IPO laddering leads to underpricing and longrun underperformance. Ellis (2006) investigates the trading volume in IPO shares after
the listing for 311 Nasdaq IPOs in the period 1996 to 1997. She shows that investor buy
trades through the lead underwriter account for 22% of trading volume after IPOs, and
this is consistent with laddering being used.8
2.3
Predictions and testable implications
An IPO investor is rationed when the number of shares sought in the IPO is larger than
the allocation. Rationing will lead to a smaller IPO allocation than the applied for shares
for most investors. Rationed investors may buy more shares after the listing to get to
the desired holding level. This has similar implications as IPO laddering. Gri¢ n et
al. (2007) argue that investment banks may strategically allocate toe-holds to investors
that the bank knows have higher optimal holding levels (share rationing)9 . The bank
does this in hopes that the investor will buy more shares after the listing to reach the
optimal holding level. It is expected that most optimal holding investors will reach their
determined holding level and then hold this in the longer run. Laddering investors, on
the other hand, buy shares right after the listing to ful…ll an obligation.10 Many laddering
8
There are also three other types of IPO rent seeking that have led to investigations and subsequent
settlements with the SEC or the NASD (Liu and Ritter, 2010). IPO allocations can be dependent on
future corporate business (IPO spinning), stock-trading commissions or companies can agree to underprice
IPOs in exchange for after-listing company coverage from a star analyst provided by the investment bank
(analyst con‡ict of interest). All of these allocation practices have been investigated in empirical papers.
Liu and Ritter (2010) investigate 56 U.S. IPOs in the period 1996 to 2000 and show that IPO shares
are allocated to corporate executives in return for future corporate business (IPO spinning). Cli¤ and
Denis (2004) show that IPO underpricing is positively related to the after-listing coverage by the lead
underwriter and an all star analyst (analyst con‡ict of interest). Nimalendran, Ritter and Zhang (2007),
Reuter (2006) and Fjesme, Michaely and Norli (2011) show that IPO allocations are related to stocktrading commissions.
9
The SEC makes a big point about selling shares early in their cases. It is claimed that banks frequently
allocated shares to investors that had no plans of holding the shares in the long run. Apparently, the
banks asked the investors if they would agree to buy more shares after the listing and not if the investors
were planning to hold the shares in the long run. If the reason for the after-listing purchases is to increase
allocations, then this is laddering.
10
Allocated IPO investors that buy more shares after new listings can be explained by either IPO
laddering or by IPO share rationing. Most of the IPO …rst day return takes place between the o¤er price
and the …rst day opening price (not between the …rst day opening and the …rst day close). This means
that any additional purchased shares have an expected return commensurate with risk and nothing more.
It is therefore expected that investors that buy more shares after the listing do so because they want to
hold more of the speci…c stock in their portfolio. If there is laddering, there should then be a stronger
relation between after-listing purchases and allocations for short term investors. Short term investors are
more likely to be laddering investors than long term investors.
12
investors will therefore sell their shares when the agreement is completed. The argument
is not that laddering investors will always liquidate their holdings early. The argument
is that investors that buy more shares because of optimal holding are more likely to hold
their shares in the long-run. Some laddering investors are likely to hold their shares in the
long-run as well, but some laddering investors will also liquidate their shares early because
they have no interest in holding the shares. It is important to note that the intention of
the after-listing buyer to buy-and-hold does not remove the possibility of IPO laddering
(Gri¢ n et al., 2007).11
Optimal holding is also not a very good explanation for the observed after-listing
buying in Norway. Investment banks rank investors on A, B and C lists before the IPO
allocations.12 We do not know how investors are placed on the lists, but we believe that
it is related to the investors’past trading characteristics. Investors on the A list are likely
to be rationed less than investors on the B list, and investors on the B list are likely to be
rationed less than investors on the C list. It is therefore expected that IPO applicants on
the A list are awarded a big allocation and will buy few shares after the listing. Investors
on the C list will be allocated few shares and will therefore buy many shares to reach
their optimal holding level. This will create a negative correlation between the number of
shares allocated and the number of shares purchased after the listing for these investors.
2.3.1
The IPO laddering hypothesis
Hao (2007) argue that there are two reasons why underwriters use laddering. First, Hao
(2007) argue that banks use laddering to boost prices after the listing. Boosted prices
are good for investment banks because the expected price support cost is then reduced.
IPOs with boosted after-listing prices will also be viewed as more successful. Second,
Hao (2007) argue that when the underwriter share in on the pro…t from the underpricing,
laddering is stronger when the realized percentage underpricing is higher. Hao (2007) also
show that expected underpricing increases IPO laddering. (It is likely that the expected
underpricing is highly related to the realized underpricing). If there is IPO laddering, it is
expected that the relationship between allocations and after-listing purchases is stronger
when the realized underpricing is higher. From Gri¢ n et al. (2007) and the …rst argument
in Hao (2007) we expect that laddering is more likely when there is a positive drift in
the share price after the listing (boosted price) and after-listing investors sell their shares
soon after the listing date. This is formalized in H0.1. From Gri¢ n et al. (2007) and
the second argument in Hao (2007) we expect that laddering is more likely when there is
a positive underpricing and after-listing investors sell their shares soon after the listing.
This is formalized in H0.2. If the relationship between IPO allocations and after-listing
purchases is explained by share rationing, there is no reason why the relation should be
stronger in IPOs where investors sell their shares soon after the listing, the price increase
in the …rst week after the listing and the IPO is underpriced. This is formalized in HA.
11
Gri¢ n et al. (2007) test between IPO laddering and optimal holding by studying how the aggregate
institutional holding percentage evolves from the listing date to the …rst quarter and the …rst year after
the listing. They argue that laddering investors are mainly institutional, so the aggregate institutional
holding percentage should go down in companies with IPO laddering - since laddering investors will reduce
their holding percentage and optimal holding investors will not. In the Norwegian data we observe that
the investors are allocated IPO shares buy more IPO shares after the listing and then sell shares soon
after the listing. It is more likely that investors that follow this three stage IPO share investment process
are laddering investors than optimal holding investors.
12
Information about allocation practices are obtained from meetings with former investment bankers
in Norway.
13
H0 and HA are tested by regression equation (1).13 If the relationship between allocations
and after-listing shares is signi…cantly stronger for (After-listing shares/shares issued)%i
* D1 * D2 * D3 than for (After-listing shares/shares issued)%i , then we are not able to
reject H0. This will, however, reject HA.
H0.1: The relationship between allocations and after-listing purchases is stronger when
investors sell all shares within six months after the listing and the price after one week
exceed the …rst day closing price.
H0.2: The relationship between allocations and after-listing purchases is stronger when
investors sell all shares within six months after the listing and the …rst day closing price
exceeds the o¤er price.
HA: The relationship between IPO allocations and after-listing purchases is the same
for all investors.
(1) (Allocated shares/shares issued )%i = + 1 (After-listing shares/shares issued)%i
2 (After-listing shares/shares issued)%i * D1 * D2 * D3 + [Control variables] + i
+
2.3.2
Other testable implications of IPO laddering
There are two other testable implications of IPO laddering besides that relation between
after-listing purchases and IPO allocations. First, it can be tested if IPO laddering is
bene…cial for investors. In hot IPOs it is expected that investors that buy more shares
after the listing will earn money because they are allocated an increased portion of hot
shares. It is possible that the investors either lose or earn money on the additional shares
purchased after the listing (this is uncertain and can go both ways according to an e-mail
by Goldman Sachs referred to in the SEC release), but it is expected that buying more
shares should be pro…table overall. Money earned on the hot IPO allocations should
outweigh any loss on the additional shares. This is tested by investigating if laddering
investors earn money overall. In cold IPOs it is expected that the investors earn money
on future IPO allocations. Although investors are not enthusiastic about cold IPOs it is
expected that investors will follow through with the laddering to not be excluded from
future IPOs, see Gri¢ n et al. (2007). This is tested by regressing past laddering on future
IPO allocations.
Second, it can be tested if IPO laddering is bene…cial for investment banks. Investment
banks tie allocations to after-listing purchases partly to earn money on stock-trading
commissions. Laddering investors buy more shares after new listings so total IPOs with
laddering increase more in price than IPOs with no laddering. Investment banks can
then charge more stock-trading commissions for IPO allocations with laddering, see Hao
(2007). If this is the case, there will be a relation between stock-trading commission
generated before IPOs, by non-laddering allocated investors, and the aggregate afterlisting purchases made by laddering investors. This is tested by regressing the aggregated
13
D1: A dummy that takes the value of one if the investor have sold all allocated and after-listing shares
within six months of the listing date.
D2: A dummy variable that takes the value of one if there is a positive drift in the share price in the
week following the listing (from the …rst day closing price to the …rst week closing price).
D3: A dummy variable that takes the value of one if the IPO have a positive underpricing.
14
IPO after-listing purchases made by the laddering investors on the average commission
generated per share before the IPO (by the non-laddering allocated investors).
2.4
The listing process and the incentives to engage in IPO laddering
The OSE requires that companies have su¢ cient levels of equity to survive for 12 months
without a positive cash ‡ow after a listing. The OSE also requires that public companies
must have a minimum number of owners before they can list (500 for the main list).14
This means that most companies need to issue equity before they are able to list publicly.
Table 1 gives the annual distribution of IPOs on the OSE in the sample period. Most
companies are assisted by an investment bank in their equity issuance and in the listing
process. The investment bank makes a list with proposed IPO allocations that is given to
the board of the issuing company for approval. Anecdotal evidence suggests that this list
typically is approved without adjustments. Investment banks and investors have di¤erent
reasons for why they participate in IPO laddering. Regulators investigate IPO laddering
because it is manipulative.15
2.4.1
Why investment banks use IPO laddering
IPO laddering can be advantageous for investment banks in both hot and cold IPOs.
There are two main reasons why investment banks use IPO laddering in hot IPOs. Firstly,
investment banks can earn money on combining allocations to investors that generate high
stock-trading commission and to laddering investors. IPO laddering will boost prices
after the listing. This will give the companies attention as more successful IPOs (Hao,
2007; Aggarwal et al., 2006; Gri¢ n et al., 2007). Secondly, IPO laddering will increase
underpricing. The IPO allocations will then be valued higher by investors that are willing
to pay stock-trading commissions to obtain allocations (Hao, 2007; Aggarwal et al., 2006).
In related papers, Reuter (2006), Nimalendran et al. (2006) and Fjesme, Michaely and
Norli (2011) show that stock-trading commissions are related to IPO allocations.
Laddering can also be bene…cial for investment banks in cold IPOs. IPO laddering
will reduce the after-listing price uncertainty in cold IPOs. This is good for investment
banks because IPOs that fall in price may cause reputation damage (and price support
if used without over allotment options is potentially expensive) (Hao, 2007; Aggarwal et
al., 2006; Gri¢ n et al., 2007). Investment banks use IPO laddering to earn more money
on stock-trading commissions, to increase the likelihood of successful IPOs and to reduce
the risk of after-listing price falls.16 The after-listing purchases will also increase direct
commission from the extra trades. According to Gri¢ n et al. (2007), it is uncertain
whether laddering is more bene…cial for the investment banks in hot or cold IPOs.17
14
The information about the listing process is obtained from the seminar “The road to the listing”
November 3, 2009 by Deloitte Public Accountants and the Oslo Stock Exchange and from meetings with
former investment bankers in Norway.
15
Figure 1 describes the incentives to engage in IPO laddering for the di¤erent market participants.
16
It is probably more common that bidders will o¤er laddering than that banks require laddering.
Investors will o¤er laddering if they believe that this will increase allocations and lead to future allocations.
Hao (2007) argues that it does not matter for the e¤ect of laddering if it is bidder or investment bank
initiated.
17
Laddering in cold IPOs creates a relation between after-listing purchases and future allocations (not
necessarily between allocations and after-listing purchases). Laddering in hot IPOs will create a relation
between allocations and after-listing purchases in speci…c IPOs.
15
2.4.2
Why laddering investors agree to buy more shares
Investors agree to buy more shares after cold IPOs to get future allocations in hot IPOs.
Investors are not likely to be enthusiastic about laddering in cold IPOs, but investors who
want continued access to future hot IPO allocations are likely to follow through with the
agreements (Gri¢ n et al., 2007). Investors accept laddering in hot IPOs in order to get
more allocations in the speci…c IPOs. Laddering investors may either earn or lose money
on the extra shares purchased after the listing, but it is expected that the return of the
hot allocated shares will outweigh any loss on the additional shares.18 Investment banks
do not require laddering by all investors. Gri¢ n et al. (2007) argue that laddering is
pre arranged buying support by large institutional clients. It is easier to control that the
shares are purchased when there are only a few investors involved.
2.4.3
Why IPO laddering is a problem
The reason why the SEC is investigating IPO laddering is because laddering violates both
anti-price-manipulation and anti-fraud regulations. Laddering will falsely increase price
and demand in speci…c shares. Investors who are not aware of the laddering will buy
shares on false market demand information. Regulators (the SEC) try to ensure that the
IPO allocation process is fair and open to all investors. Any abusive allocation practices
will not be tolerated. Laddering is a problem because it is discriminatory against investors
that are not willing to engage in price manipulation to receive IPO shares. In a fair IPO
with high demand the o¤er price will increase and more money will go to the issuing
company. In an IPO with laddering the price will go up after the listing and more money
will go to the allocated investors.
Other investors can also lose money on IPO laddering. The investors that are allocated
less (or no) IPO shares because the laddering investors are allocated more hot shares are
missing out on good investment opportunities. Non-allocated investors that buy shares
after the listing lose money if the laddering investors sell their shares so that prices fall
after the listing. IPO laddering will also increase adverse selection problems. When
investors know that it is possible to buy allocations with after-listing trading, it is not
likely that investors will participate in IPOs. Investors that do not provide any form of
kickback will not want to participate in IPOs because they expect shares to be overpriced
whenever they are o¤ered allocations.
The allegation made by the SEC is that investment banks have promised investors
that they will get favorable IPO allocations if they buy additional shares after the listing
of the same IPO.19 The banks have, allegedly, asked IPO share applicants if they are
interested in buying more shares after the listings and at what prices and quantities. The
banks have also allocated shares to investors with after-listing interest -investors the banks
18
See the litigation releases made by the SEC at http://www.sec.gov/litigation/litreleases/lr18385.htm,
http://www.sec.gov/litigation/litreleases/lr19050.htm, and http://www.sec.gov/litigation/litreleases/lr19051.htm.
19
Three U.S. Investment banks that have been sued and later settled with the SEC on IPO laddering
allegations. None of the banks have admitted to the laddering charges, but all banks have agreed to pay
penalties of $40 million (Morgan Stanley), $40 million (Goldman Sachs) and $25 million (J.P. Morgan).
The charge by the SEC is that the banks have violated Rule 101 of Regulation M under the Securities and
Exchange Act of 1934. This rule is, among other things, in place to prohibit underwriters in a restricted
period, prior to their completion of the distribution of the IPO shares, from bidding for or attempting
to induce any person to bid for or purchase any o¤ered security in the aftermarket. Regulation M is
designed to prohibit activities that can arti…cially in‡uence the market and the perceived demand of the
IPO shares.
16
knew were likely to sell their shares soon after the listing (laddering investors). The banks
have made follow up calls to investors that indicated after-listing interest to make sure
the purchases are made. Arguably, the only reason investors have provided after-listing
interest is because the investors understand that this will help them get favorable IPO
allocations. Banks and investors have agreed that investors will buy after-listing shares
proportional to the allocations they receive.20
2.5
Data description
There are 403 new listings on the OSE in the period January 1993 to September 2007
(210 of the 403 companies listed through IPOs)21 . New listings are identi…ed from the
annual statistics published by the OSE. Allocation dates are collected from the IPO
listing prospectuses. One listing requirement on the OSE is that all shareholders must
be registered in the Norwegian Central Depository (VPS) before the listing. The number
of shares owned by each investor must be given to the VPS before any company can list
publicly. This database is 100% accurate, as it is not possible to list otherwise. The
VPS database includes month end ownership by all shareholders in all companies that
are publicly listed or intend to list publicly. Some companies list in the VPS database
years before the listing. Other companies list in the VPS as part of the listing process.
See Figure 3 for a detailed description of the timeline in the listing process.
IPO allocations are obtained from the VPS database by taking the di¤erence in company ownership before and after IPO allocation dates. We only investigate IPO allocations
to new shareholders. More allocations to existing shareholders, if any, are not included in
the analysis. All companies list in the VPS, sell shares in the IPO and list on the OSE.
There are three dates that are important in the listing process to determine IPO allocations,: -when companies list in the VPS ownership database, when companies distribute
shares in the IPO and when companies list on the OSE. All three dates in‡uence data on
IPO allocations. Companies do this process in di¤erent orders, and this leads to di¤erent
levels of the obtained IPO allocations.
There are 15 savings banks (PCC list) out of the 210 IPOs on the OSE in the sample
periods. In total, 14 and seven of these savings banks are in the 185 IPOs with allocation
data and in 30 exact sample respectively. These banks are owned by the bank guarantee
fund before they are publicly listed. All results remain unchanged if the banks are included
in the analysis or not. These savings banks are removed in the main analysis because it
can be argued that these banks are causing the results. The savings banks does not
have previous owners before the listing, so it can be argued that di¤erent investors try
to gain control over these companies after the listing. Investors who are not able to get
control will eventually sell their shares. This will create similar …ndings, as the laddering
hypothesis, for these savings banks.
20
In addition to these allegations, the NASD claims that J.P. Morgan tied cold IPO allocations to hot
IPO allocations and that J.P. Morgan allocated hot IPO shares to investors in the return for accepting
cold IPO allocations. This is also part of the J.P. Morgan settlement. Hao (2007) explains that IPO
order books often have investors that are marked with the number of shares that will be purchased after
the listing.
21
In total 14 savings banks listed on the PCC list of the OSE are removed from the analysis. Most of the
PCC companies are listed by the Norwegian bank guarantee fund. When including the PCC companies
the …ndings remain unchanged.
17
2.5.1
The IPO sample
When the listing in the VPS database, the IPO allocation and the listing on the OSE are in
separate calendar months, we are able to calculate exact IPO allocations (the ownership
data is in monthly observations). Group one companies list in the VPS in good time
before the IPO. These companies also list on the OSE in a separate calendar month from
the IPO (for most companies, the IPO is in the calendar month right before the listing
month). For group one companies the IPO allocations are completely accurate. There
are 16,593 IPO allocations in group one companies (23 IPOs). After-listing purchases are
the increase in the number of shares by the allocated investors from the IPO allocation
to the end of the listing month (and to the end of the month after the listing).22
2.5.2
The remaining IPOs
The data set also includes 158,789 IPO allocations in 148 IPOs that are used in robustness
tests.23 The allocations in these IPOs include either some existing owners or some afterlisting trading. Group two companies list in the VPS in good time before the IPO, but
they list on the OSE in the same calendar month as the IPO allocation month. These
companies have allocations that include the actual IPO allocations and some after-listing
trading. These IPO allocations includes from one to 30 days of after-listing trading.
The companies in group two are used to test the relationship between past and future
after-listing IPO holdings.
2.5.3
Aggregate laddering
There are 317 investors who sell all allocated and all after-listing shares within six months
of the listing date in IPOs with a positive underpricing (in the 50% IPOs with the highest
laddering). The aggregate allocations to these investors is 4% of the IPO shares. They
buy in aggregate 6% of the IPO shares after the listing. Within six months they have
sold all IPO shares (in aggregate 10% of the IPO shares). There are 174 investors who
sell all allocated and all after-listing shares within six months of the listing date in IPOs
that appreciate in price in the week after the listing (in the 50% IPOs with the highest
laddering). The aggregate allocations to these investors is 5% of the IPO shares. They
buy in aggregate 8% of the IPO shares after the listing. Within six months they have
sold all IPO shares (in aggregate 13% of the IPO shares).
22
Shares sold over the counter (OTC trading) in the period between the allocation day and the end
of the allocation month will not be detected in the data. Investors that buy shares in the OTC market
between the allocation day and the end of the allocation month will be treated as allocated investors.
OTC trading is, however, expected to be a very small issue. It is unlikely that many investors that have
been allocated IPO shares will sell these shares in the weeks before the listing. The average number of
days between payment date in the IPO (when shares are transferred) and the listing date is just below
two weeks
23
The reason it is 148 IPOs and not 172 (195-23=172) is because in 15 IPOs it has not been possible
to calculate IPO allocations from the ownership data. These companies are listed in the VPS in the
same month as the listing month. These companies are therefore removed from the sample. In 6 IPOs
it has not been possible to locate the pricing information. These IPOs are therefore not included in the
analysis. There are three privatizations in the period that are removed.
18
2.5.4
Variable explanations
IPO level characteristics are given in Table 2. Market value is the total market value
(in USD) at the listing date of the IPO company. This is calculated as the number of
outstanding shares times the …rst day closing price. Book/Market is the book to market
ratio of the IPO company at the listing date. This is calculated as the book value of
equity, after the IPO, divided by the market value. O¤er price is the IPO o¤er price (in
USD) reported in the listing prospectus or in the newspapers. VC dummy is a dummy
variable that takes the value of one for companies with venture capital backing. Hightech dummy is a dummy variable that takes the value of one for IT -companies. The IPO
company variables are used to control that the results are not driven by company speci…c
characteristics. Market value and the book to market ratio are included in the regressions
to make sure that company size is not driving the results. O¤er price is included to make
sure that it is not very high or low priced IPOs that drive the results. The VC dummy
and the high-tech dummy are included to make sure that the results are not driven by
venture capital backing or high technology companies. All regressions include IPO and
year …xed e¤ects. These are dummy variables that take the value of one for each of the
companies and sample years.
Investor characteristics, for the investors on the OSE in the period 1993 to 2007,
are described in Table 3. (After-listing shares/shares issued) % is the additional shares
purchased after the listing divided by the total number of shares issued in the IPO.24 The
after-listing shares are calculated as the share increase from the IPO allocation to the
end of the listing month for the 23 sample IPOs. (We also include the share increase to
the end of the month after the listing because some companies list late in the month and
IPO laddering may go on as long as three weeks after the listing, see Gri¢ n et al., 2007).
For the remaining IPOs the share increase is measured from the end of the listing month
to the end of the month after the listing. This is likely to underestimate the after-listing
purchases in the IPOs used for robustness. D1 is a dummy variable that takes the value
of one if the investor have sold all allocated and after-listing shares within six months of
the listing date. D2 is a dummy variable that takes the value of one if there is a positive
drift in the share price in the week following the listing (from the …rst day closing price
to the …rst week closing price). D3 is a dummy variable that takes the value of one if the
IPO have a positive underpricing. (Allocated shares/shares issued) % is allocated shares
to each investor divided by the total number of shares issued in the IPO.25 This is the
percentage allocation of shares given to each investor in each IPO. Previous laddering is
the accumulated number of times an investor has laddered divided by the accumulated
number of times the investor has participated in IPOs. This is a measure of how frequently
24
The number of shares sold in the IPO is the number of actual shares sold to new shareholders from
the VPS database. In the listing prospectuses the number of shares sold is often listed as a range. E.g. in
the Aqua Bio IPO the listing prospectus says that the number of shares sold will be between 1.2 million
and 4 million shares. It is also uncertain if Over Allotment Options (OAO) is used or not. This may
increase the number of shares sold from the listing prospectus to actual shares sold up to 20%. E.g. in
the Nutri Pharma IPO the minimum number of shares sold is 10 million. The lead manager is given 2
million extra shares in an OAO. From the prospectus it is impossible to know the exact number of shares
that will actually be sold. This number is observable in the VPS database.
25
(Allocated shares/shares issued) % is trimmed at 1% at the total 171 IPO level to remove the highest
IPO allocations. These allocations are not likely to be made to investors based on trading characteristics.
This is included to be consistent with Fjesme, Michaely and Norli (2011). This trimming has no in‡uence
on the …ndings in this article.
19
an investor engages in laddering, relative to its total participations in IPOs.26
Commission is the accumulated commission (in USD) generated by each investor in
the two years before the IPO allocation dates.27 Commission is calculated as the monthly
portfolio turnover times share prices and a …xed percentage commission rate (0.075%).
The 0.075% commission rate is the average used by 15 Norwegian brokerage houses.
Commission is calculated as buy generated commission only. Generated commission below
the minimum rate is replaced by the …xed minimum fee for one transaction ($15). Portfolio
value is the total investor portfolio value (in million USD) for each allocated investor at
31.12.xx in the year before the IPO allocation date. This is calculated as the shares held
at 31.12.xx times the appropriate share prices. Financial institution dummy is a dummy
variable that takes the value of one for investors that are either Norwegian or foreign
…nancial institutions.
Previous IPOs is the accumulated previous IPO participations by the investors divided by the accumulated number of IPOs in the sample.28 This is used to measure how
many IPOs, out of all possible in the sample, each investor has participated in. Previous buy-and-hold is the accumulated previous number of times the allocated investor
has been a buy-and-hold investor divided by all previous IPO participations. This is the
number of times, out of all previous IPO participations, the investor has held some of
the IPO allocated shares for more than six months after the listing. Previous ‡ipping is
the accumulated number of times the investor has ‡ipped previous IPOs divided by all
previous IPO participations. Flipping is when all shares are sold within one month after
a listing. This is the number of times, out of all previous IPO participations, the investor
has held all IPO allocated shares for less than one month. The previous trading variables
are used to control that the results are not driven by investor size, trading activity or
holding periods.
Other control variables includes the Percentage change in pricing range that is the
change from the midpoint in the pricing range to the o¤er price in book-building IPOs.
This variable measures price information collected in the book-building period, see Ljungqvist
and Wilhelm (2002). Number of sentiment investors is the number of allocated retail investors that buy less than 1,000 shares in the IPO. We use this as our sentiment measure
as we believe that small retail investors are more sentiment driven in their IPO applications as they spend less time on fundamental analysis, see Kumar and Lee (2006). Average
commission per share is calculated as the total commission generated by non-after-listing
purchasing investors in the 24 month period before the IPO divided by the number of
shares allocated in the IPO. This is the average dollar generated commission per share be26
An investor that has participated in one IPO and bought more shares after the listing and then sold
shares will take the value of 1 (1/1). An investor that has participated in two IPOs and bought and sold
more shares after the listing in one of these IPOs will take the value of 0.5 (1/2).
27
Commissions are generated from monthly data and not daily data.
28
Many IPOs are underwritten by more than one investment bank. If there is more than one investment
bank involved in the IPO, the bank that appears on the top left of the front page of the listing prospectus
is assumed to be the lead investment bank. Carter and Manaster (1990) use the investment bank that
appears top left on the tombstone as the lead investment bank. In most IPOs there are also co-managers
that help with spreading the shares. Co-managers will allocate shares to their own clients. Investment
banks can be co-managers in many IPOs, and this creates the situation where investors can be allocated
shares as a reward in an IPO by another lead bank. There are also some mergers between investment
banks in the period and this will also create the situation where award shares can come from other lead
banks. Because of this, we investigate past trading behavior in all past IPOs in relation to current IPO
allocations. We also study IPOs by one single bank separately. When this is done, we only investigate
past trading in the IPOs where the one bank has been the lead.
20
fore the allocation (by non-laddering investors). Combined commission % is calculated as
the commission generated by all the allocated investors in the 24 month period before each
IPO divided by the accumulated commission generated by all the allocated IPO investors
in the 24 month period before all IPOs. Average commission and Combined commission
are used to measure how important stock-trading commission is for allocations in each
speci…c IPO. These variables measure if there is a relationship between commission generated before an IPO (by the allocated investors) and the aggregated after-listing purchases
of the IPO shares.
We do not know the exact oversubscription numbers in each IPO. Normally, oversubscription numbers are used to de…ne if IPOs are hot (popular/oversubscribed) or cold
(less popular/undersubscribed). We proxy for hot/cold by a dummy that takes the value
of zero if there is negative …rst day return (cold) and one otherwise (hot). We expect that
underpriced IPOs are hot and non-underpriced IPOs are cold.
2.6
Empirical results
From Table 4 it can be seen that there is a positive relationship between IPO allocations
and after-listing purchases (regression 1). This relationship is signi…cantly stronger for
investors who sell their shares soon after the listing (regression 2). The relationship is
also signi…cantly stronger for investors that sell all shares soon after the listing in IPOs
with a positive drift in the share price in the week after the listing (regression 3). This
is consistent with H0.1. The relationship is also signi…cantly stronger when investors sell
shares soon after the listing and the IPO have a positive realized underpricing (regression
4). This is consistent with H0.2. The relationship between allocations and after-listing
purchases is also signi…cantly stronger for investors that sell all shares soon after the
listing, in IPOs with a positive underpricing, and in IPOs with a positive drift in the
share price after the listing (regression 5). The point estimate for the allocation and
after-listing purchase relationship is typically two to …ve times as large for the cases
where H0 specify that the relationship should be stronger.
The relationship is also economically signi…cant. The coe¢ cient between allocation
and after-listing purchases is about 0.25. This means that for each 1% of the issues that is
allocated these investors buy 4% more after the listing, controlling for all other variables.
The average number of shares purchased after the listing is close to 7,000 shares for the 427
laddering investors. This indicates that the allocation rule is that investors who commit
to buy 7,000 shares after the listing are allocated close to 2,000 more shares in the IPOs.
The results are robust to how many shares and how early the shares must be sold
for investors to be regarded as laddering investors. The results remain unchanged when
investors who have sold 50% of their shares within three months of the listing date are
regarded as laddering investors. The relationship between IPO allocations and afterlisting purchases is signi…cantly stronger for investors that sell 50% of total shares within
three months after the listing, in IPOs with a positive underpricing, and in IPOs with a
positive drift in the share price after the listing than for other investors (regression 6).
The relationship is also signi…cantly stronger for investors that sell 50% of total shares
within six months after the listing, in IPOs with a positive underpricing, and in IPOs with
a positive drift in the share price after the listing (regression 7). This is consistent with
H0.29 Most of the control variables are unrelated to the level of allocations. Generated
29
Both allocated shares and after-listing shares are scaled by the number of shares issued in the IPOs.
21
stock-trading commission is positively related to allocations. This indicates that laddering
investors are active investors.
To make sure that the results are not driven by the other allocations views suggested by
Ritter (2003) and Jenkinson and Jones (2004) we control for these views in all regressions.
To control for the pricing information view (the academic view) we include a dummy
variable that takes the value of one for all professional investors (…nancial institution
dummy). If there is allocation to buy-and-hold type investors, there will be a relation
between holding periods and IPO allocations (buy-and-hold view). This is controlled for
by including the past IPO holding period of the allocated investors in all regressions (past
buy-and-hold and past ‡ipping). Neither of these variables are consistently related to
allocations. It is also possible that allocations are made to commission generating investors
only (rent seeking view). This view is controlled for, and ruled out by including the
portfolio value and the generated commission before the IPOs by the allocated investors
in the regressions.30
In Table 5 the relation between past IPO laddering and future ownership of IPO shares
is investigated more closely. If there is IPO laddering, it is expected that investors may
be rewarded with allocations in future IPOs as well. Testing the relation between past
laddering and future allocations is hard in the 23 IPO sample because there may be some
time between each observed IPO. This is therefore tested on the full sample where IPO
allocations include after-listing trading. Here we test whether investors that buy more
(and then sell) shares after the listing of IPOs also hold shares after the listing of future
IPOs. In Table 5 all 171 IPOs (with 175,382 IPO allocations) are investigated. Most
of these IPOs are of group two allocations. This means that the IPO allocations may
be overestimated and the after-listing purchases may be underestimated in these IPOs.31
Therefore, we are not studying allocations. Rather, this table investigates whether past
after-listing buying leads to future after-listing holding of IPO shares.
In Table 5 we regress after-listing holdings of IPO shares on the number of times in the
past (out of all IPO participations) allocated investors have bought (and then sold) more
shares after IPOs. There is a strong relation between past IPO laddering and shares held
after future IPOs. This indicates that banks tie IPO allocations together. This indicates
that IPO shares are also rewards for past laddering in IPOs.32 There is a consistent
There are very di¤erent numbers of shares sold in each IPO. Capital raised depends on both the number
of shares and on the o¤er price in the IPO. The numbers we are interested in are therefore allocated
shares and after-listing shares in percent of issued shares. This tests the relationship regardless of the
number of shares issued in the IPO. We also regress allocated shares on after-listing shares directly
without adjusting for issued shares in all regressions. This does not alter the …ndings. There are some
changes to signi…cance levels and adjusted R –squares, but the results remain the same (not reported).
30
We are not able to control for IPO spinning. IPO spinning is when IPO shares are allocated to
company executives for future corporate business. Spinning will not generate the same implications as
IPO laddering, so we argue that this is not a problem.
31
These shares are still purchased by the investors. Aftermarket purchases for group two IPO allocations
are calculated as the share increase from the end of the listing month to the end of the month after the
listing. This means that all of these investors have an increase in the IPO shares in this period. All
of these investors are buying shares after the listing of IPOs. These investors also hold signi…cantly
more IPO shares in subsequent IPOs. Table 5 shows that investors who hold shares after the listing of
IPOs, before they buy more shares in the following month, also hold more shares of future IPOs. This is
consistent with the laddering story. We cannot show that IPO allocated investors who buy more shares
after a listing are allocated more hot IPO shares, but we show that investors who buy more (and then
sell) shares after the listing of an IPO have more IPO shares in their future portfolios.
32
Past aftermarket buying is less statistically and economically related to IPO allocations in the 20
IPOs by the least active investment banks (not reported). The tie-in agreement variables are highly
22
negative relationship between past buy-and-hold and IPO allocations. Investors are not
allocated shares because they repeatedly hold their shares in the long-run. Investors are,
however, punished for ‡ipping shares in the past. Flipping investors are kept out of future
hot IPOs. These …ndings also show that investment banks keep records of how investors
trade in IPOs. The banks use these records in their future IPO allocations. This is
consistent with the SEC releases where it is claimed that banks track investor trading
and use this in their future allocation decisions.
From Table 6 it can be seen that investors are able to earn a pro…t from IPO laddering.
For allocated shares the monetary return is calculated as the number of allocated IPO
shares times the …rst day and …rst month return. For shares purchased after the listing the
monetary return is calculated as after-listing shares times the …rst month return. It is clear
that the pro…t earned from hot IPO allocations outweighs any loss from the after-listing
purchases. Table 6A show that the average return made by the 357 investors who ladder
in IPOs with a positive realized underpricing have a positive return overall. This is also
true for the 195 investors who ladder in IPOs with a positive drift after the listing (Table
6B). The 70 investors (427 laddering investors - 357 laddering investors in hot IPOs) that
ladder in cold IPOs are earning a pro…t in their overall IPO participation. This indicates
that these investors are rewarded in future IPOs for their cold IPO laddering (Table
6C). The 23 IPO sample is also split into high and low laddering IPOs based on the 427
investors who sell all shares within six months of the listing. Non-allocated investors that
buy shares after the listing in the high laddering IPOs are losing money on average (Table
6D). This is not true in the IPOs with low laddering (Table 6E). Overall, this shows that
IPO laddering is pro…table for laddering investors. However, IPO laddering is very bad
for non-allocated IPO investors that buy shares after the listing.
From Table 7 it can be seen that there is a positive relationship between aggregate
after-listing buying in each IPO (by the investors who sell all shares within six months
of the listing) and the average commission generated by other allocated investors before
the IPO. This is an important condition for IPO laddering to take place. A main reason
why an investment bank would engage in IPO laddering is to increase revenue by sharing
in on the money left on the table. Investment banks combine IPO allocations to laddering investors and stock-trading commission investors, and thus create a positive relation
between after-listing buying and commissions generated by the allocated investors before
the IPO. Laddering investors increase prices after the listing, and commission investors
pay more stock-trading commission for shares that will increase in price for sure. The
investment banks earns more money from stock-trading commissions in the IPOs where
there are more shares purchased after the listing. The data is consistent with that investment banks combine IPO allocations to high stock-trading commission investors and
laddering investors.
related to IPO allocations in the IPOs by the most active investment bank (not reported). The results
indicate that active IPO investment banks are able to use tie-in agreements. The reason why investors go
through with the tie-in agreements, and buy more shares after the listing, is to avoid being blacklisted in
future IPOs. An active investment bank will have a more reliable threat than less active banks. There is
no relationship between IPO allocations and aftermarket purchases by Norwegian government investors.
This is also as expected. The …ndings are consistent with Pulliam and Smith (2000), Ritter (2003),
Aggarwal et al. (2006), Hao (2007) and Gri¢ n et al. (2007).
23
2.6.1
Optimal holdings
We reject the hypotheses that the relation between IPO allocations and after-listing buying is driven by optimal holding of shares. There is a stronger relationship between IPO
allocations and after-listing purchases for investors that sell all shares soon after the listing, in IPOs with a positive underpricing, and in IPOs with a positive drift in the share
price after the listing. There is also no relationship between IPO allocations and past
buy-and-hold. Investment banks do not allocate shares to investors because they are expected to be buy-and-hold based on past trading. Therefore, the after-listing purchases
are not simply a result of investors trying to reach their optimal holding levels. We reject
HA.
2.6.2
The e¤ ect of IPO laddering
We …nd indications that laddering is a¤ecting company long-run returns negatively after
the listing (not reported).33 The 11 companies with high levels of IPO laddering have a
negative price evolvement in the time after the listing on average. Non-allocated IPO investors who buy shares in this period are also losing money on average. This is consistent
with both Hao (2007) and Aggarwal et al. (2006). When comparing long-run returns of
IPOs with high laddering to a one for one matching listed …rm, the underperformance
results are very weak with zero or very low explanatory power. The matching …rm technique is also biased towards …nding long-run underperformance, see Eckbo, Masulis and
Norli (2008). We are not able to conclude that high levels of laddering leads to low longrun performance, but the results indicate that laddering is negatively related to long-run
performance.
2.6.3
Robustness and aggregate IPO laddering
The results are robust to including PCC savings banks and trimming IPO allocations at
0.1% instead of at 1%, see Table 8. The results are also robust to removing all company
speci…c control variables (Table 9). From Table 10 it can also be seen that IPO laddering
involves an economically signi…cant amount of the IPO shares. Laddering investors are
on average allocated 4% of IPO shares before they buy 6% more shares after the listing.
These investors then sell 10% of the IPO shares within six months of the listing date (in
the 50% IPOs with the highest IPO laddering).
2.7
Conclusion
There is a stronger relationship between IPO allocations and after-listing purchases when
investors sell shares soon after the listing, the IPO have a positive realized underpricing
and there is a positive drift in the share price after the listing. This …nding is not consistent
33
Long run performance is calculated as the (IPO company holding period return / matching company
holding period return) (Ritter, 1991). This long run return measure is regressed on the aggregate level
of aftermarket share buying and a set of control variables. Companies are matched on market values and
book to market ratios, see Eckbo and Norli (2005). All matching companies with a market value within
30% of each IPO company are grouped together. Only companies that have been listed for more than …ve
years are included as matching companies. The company with the book to market ratio that is closest
to the IPO company is used as the matching company. A delisted matching company is replaced by the
company with the second closest book to market ratio for the remaining years etc.
24
with HA and this hypothesis is therefore rejected. We reject that the relationship between
IPO allocations and after-listing purchases is driven by share rationing only. This …nding
is, however, consistent with H0. We are not able to reject that the relationship between
IPO allocations and after-listing purchases is driven by IPO laddering. The evidence
support IPO laddering.
We …nd that laddering investors who buy more shares after the listing are also allocated more shares in IPOs. This controls for the stock-trading commissions generated
by the investors, portfolio value, investor type, past trading characteristics and company
speci…c variables. These investors also sell their shares shortly after the listing and earn a
high pro…t from their IPO participation, which is consistent with IPO laddering. The investors that buy the most shares after the listing are also allocated the most shares. These
investors are not expected to hold the shares based on past trading characteristics. There
is also a positive relationship between the number of times investors have used laddering
after the listing in previous IPOs and after-listing ownership of future IPO shares. There
is no relationship between past buy-and-hold and future IPO share ownership, -further
indicating that this is IPO laddering. Laddering gives more shares in speci…c IPOs and
more shares in future IPOs. The aggregate laddering in IPOs is also positively related to
the average commission generated by the allocated investors before the IPOs, thus demonstrating that there is more laddering when there are more shares allocated to investors
that generate high levels of stock-trading commission. Investment banks seems to be able
to earn money on IPO laddering by combining allocations to after-listing investors and
high commission investors. The evidence is consistent with IPO laddering. We are not
able to reject that IPO laddering is being used.
There are many implications of this …nding. The main practical implication is that
investors who are not aware of IPO laddering lose money on trading in IPO shares in
comparison to more informed investors. IPO laddering is also likely to increase adverse
selection problems as many investors are likely to stay away from the IPO market when
they know they must provide kickbacks to acquire the good allocations. In the U.S. there
has been a large-scale investigation of IPO allocation practices, and this study shows that
more countries should probably start their own investigations as well. A main theoretical
implication of this …nding is that IPO allocation practices should probably be explained
more from a rent seeking perspective since most theoretical papers explain IPO allocations
from a pricing information or buy-and-hold perspective.
There are some limitations to this study. With regard to the generated stock-trading
commission, we cannot see that commission is paid from the allocated investor to the
investment bank, and can only observe that the commission has been generated. We also
calculate commissions based on monthly data, and this is likely to underestimate commissions. The study does not conduct and in-depth investigation of long-run performance
(as we only observe a limited number of companies), and we also do not know the oversubscription numbers of the IPOs. This is proxied for by using the actual …rst day return
as the oversubscription hot/cold IPO dummy. Nevertheless, we do expect this dummy to
be very accurate. In terms of future research, it would be very interesting to investigate
a sample which included the actual IPO laddering agreements in writing.
25
References
[1] Aggarwal, Rajesh K., Amiyatosh K. Purnanandam and Guojun Wu, 2006, Underwriter Manipulation in Initial Public O¤erings. Working paper. University of Virginia
and University of Michigan.
[2] Benveniste, Lawrence and Paul Spindt, 1989, How investment banks determine the
o¤er price and allocation of new issues, Journal of Financial Economics 24, 343-362.
[3] Carter, Richard B. and Steven Manaster, 1990, Initial Public O¤erings and the underwriter reputation, Journal of Finance 45, 1045-1067.
[4] Cli¤, Michael T. and David J. Denis, 2004, Do Initial Public O¤ering Firms Purchase
Analyst Coverage with Underpricing?, Journal of Finance 6, 2871-2901.
[5] Deneen, M., and J. Hooghuis, 2001, Tidal Wave of IPO ‘Laddering Litigation’
Swamps D&O Market, The Plus Journal 9.
[6] Eckbo, Espen B. and Øyvind Norli, 2005, Liquidity risk, leverage and long-run IPO
returns, Journal of Corporate Finance 11, 1-35.
[7] Eckbo, Espen B., Ronald W. Masulis and Øyvind Norli, 2000, Seasoned Public Offerings: resolution of the ’new issues puzzle’, Journal of Financial Economics 56,
251-291.
[8] Ellis, Katrina, Roni Michaely and Maureen O’Hara, 2000, When the Underwriter Is
the Market Maker: An Examination of Trading in the IPO Aftermarket, Journal of
Finance 3, 1039-1074.
[9] Ellis, Katrina, 2006, Who trades IPOs? A close look at the …rst days of trading,
Journal of Financial Economics 79, 339-363.
[10] Fjesme, Sturla Lyngnes, Roni Michaely and Øyvind Norli 2011, Using stock-trading
commissions to Secure IPO allocations, Working paper, Norwegian Business School
(BI).
[11] Gri¢ n, John M., Je¤rey H. Harris and Selim Topaloglu, 2007, Why are IPO investors
net buyers through lead underwriters?, Journal of Financial Economics 85, 518-55.
[12] Hao, Qing (Grace), 2007, Laddering in initial public o¤erings, Journal of Financial
Economics 85, 102-122.
[13] Jenkinson, Tim, and Howard Jones, 2004, Bids and Allocations in European IPO
Book-building, Journal of Finance 5, 2309-2338.
[14] Kecskes, Ambrus, Roni Michaely and Kent Womack, 2010, What drives the Value
of Analysts Recommendations: Earnings Estimates or Discount Rate Estimates?,
Working paper Cornell University.
[15] Kumar, Alok and Charles M.C. Lee, 2006, Retail Investor Sentiment and Return
Comovements, Journal of Finance 5, 2451-2486.
[16] Liu Xiaoding and Jay. R. Ritter, 2010, The Economic Consequences of IPO Spinning,
Review of Financial Studies 5, 2024-2059.
26
[17] Ljungqvist, Alexander P. and William J. Wilhelm, 2002, IPO allocations: discriminatory or discretionary?, Journal of Financial Economics 65,167-201.
[18] Loughran, Tim and Jay R. Ritter, 1995, The New Issues Puzzle, Journal of Finance
1, 23-51.
[19] Loughran, Tim and Jay R. Ritter, 2004, Why has IPO underpricing changes over
time?, Financial Management 33, 5-37.
[20] Megginson, William and Kathleen Weiss, 1991, Venture capitalists certi…cation in
initial public o¤erings, Journal of Finance 46, 879-904.
[21] Michaely, Roni and Wayne H. Shaw, 1995, The Choice of Going Public: Spin-o¤s vs.
Carve-Outs, Financial Management 24, 5-21.
[22] Nimalendran, M., Jay Ritter, and Donghang Zhang, 2007, Do today’s trades a¤ect
tomorrows IPO allocations? Journal of Financial Economics 84, 87-109.
[23] Pulliam, Susan and Randall Smith, 2000, Trade-o¤s: Seeking IPO Shares, Investors
O¤er to Buy More in the After Market, The Wall Street Journal December12, 2000.
[24] Pulliam, Susan and Randall Smith, 2000B, Linux Deal is focus of IPO-Commission
Probe, The Wall Street Journal, December 12, 2000.
[25] Reuter, Jonathan, 2006, Are IPO allocations for sale? Evidence from Mutual Funds,
Journal of Finance 5, 2289-2324.
[26] Ritter, Jay R.,1984, The ‘hot issue’market of 1980, journal of Business 32, 215-240.
[27] ____, 1987, The cost of going public, Journal of Financial Economics 19, 269-281.
[28] ____, 1991, The long run performance of Initial Public O¤erings, Journal of Finance 46, 3-27.
[29] ____, 2003, Di¤erences between European and American IPO markets, European
Financial Management 4, 421-434.
[30] Rogers, W. H.,1993, Regression standard errors in clustered samples, Stata Technical
Bulletin 13, 19-23. Reprinted in Stata Technical Bulletin Reprints 3, 88–94.
[31] White, Halbert, 1980, A heteroscedasticity-consistent covariance matrix estimator
and a direct test of heteroscedasticity, Econometrica 48, 817-838.
27
Table 1
The number of Initial Public O¤erings on the Oslo Stock Exchange
The column labeled "IPOs" lists the number of Initial Public O¤erings on the Oslo Stock Exchange in
the sample period. The column labeled "Data" indicates the IPOs with allocation data. The column labeled
"Prospectus" lists the IPOs where we have been able to locate the listing prospectus. The column labeled
"Sample" lists the 23 sample IPOs. The columns labeled "Value of shares" list the annually aggregate million
USD values of shares sold in the 153 IPOs with listing prospectus. "All", "New" and "Secondary" indicates
the value of all shares, only newly issued shares and shares sold by existing shareholders respectively. The
columns labeled "P" and "S" is the annual aggregated USD million value of shares sold in the IPOs with
prospectuses and in the 23 IPO sample respectively. Value of shares sold is reported in USD using a
USD/NOK exchange rate of 0.1792. The sample period is January 1993 through September 2007.
Number of IPOs
Value of shares (Million USD)
All
Year
IPOs
Data
Prospectus
1993
11
9
7
1994
15
9
1995
14
1996
15
1997
S
New
Sample
P
8
3
275
12
9
2
452
49
403
11
7
2
137
80
56
81
80
29
25
19
9
976
230
504
21
471
209
1998
12
9
8
1
189
87
145
87
1999
3
3
3
2000
10
10
10
2001
4
4
4
2002
2
2
2
541
817
70
P
218
142
57
101
753
64
43
89
64
65
51
2
2
2
83
78
5
2004
14
14
14
1,605
1,319
287
2005
31
30
30
2006
18
17
16
2,730
2,237
493
2007
15
14
14
912
517
395
Total
195
171
153
2,041
23
11,061
28
34
749
566
7,232
12
17
2003
2
5
29
166
70
S
2
21
183
2
S
539
147
50
2
P
Secondary
23
427
1,475
3,873
5
11
322
Table 2
Summary Statistics of Firms Going Public on the Oslo Stock Exchange
Panel A reports the company characteristics for the 23 sample IPOs and all 171 IPOs with ownership
data. "After-listing/ issued" is the additional shares purchased after the listing divided by the shares issued
in the IPOs. "-Sell within 6 months " is the "(After-listing shares/shares issued) %" for only investors
that sell all shares within six months of the listing date. "Market V. (M.USD)" is the number of shares
outstanding on the listing day times the …rst day closing price. "Book/Market" is the book value of equity
after the IPO divided by the market value on the listing day. "O¤er price" is the USD IPO price in the
listing prospectuses. "VC backed d." is a dummy variable that takes the value of one if the company has
venture capital backing. "High-tech d." takes the values of one for IT -companies. "First day return" is the
percentage price change from the o¤er price to the …rst day closing price. USD values are calculated from a
USD/NOK exchange rate of 0.1792. In Panel B the 23 Sample IPOs are split into IPOs with high and low
after-listing purchases by investors that sell all shares within six months of the listing date. T –statistics
are calculated as: Di¤erence / (square root [(variance sample 1/ numbers in sample 1) + (variance sample
2/ numbers in sample 2)].
Panel A
After-listing/ issued
Sample 23 IPOs
All 171 IPOs
Mean di¤erence
N
Mean
Std.Dev
Median
N
Mean
Std.Dev
Median
Di¤.
t-stat.
23
8.7%
7.6%
6.2%
171
5.8%
6.2%
3.8%
2.9%
(1.8)
-Sell within 6 months
23
3.3%
3.7%
2.3%
171
3.6%
5.0%
1.7%
-0.3%
(-0.3)
Market V. (M.USD)
23
$149.3
$145.2
$117.3
171
$311.4
$871.9
$108.3
-$162.1
(-2.2)
O¤er price USD
23
$8.7
$6.9
$7.2
171
$8.2
$6.4
$6.8
$0.5
(0.3)
Book/Market
23
0.3
0.29
0.23
171
0.46
0.33
0.4
-0.16
(-2.4)
VC backed d.
23
0.17
0.39
0.0
171
0.18
0.38
0.0
-0.01
(-0.1)
High-tech d.
23
0.09
0.29
0.0
171
0.12
0.32
0.0
-0.03
(-0.5)
First day return
23
0.13
0.19
0.09
171
0.08
0.19
0.03
0.05
(1.2)
N
Mean
Std.Dev
Median
N
Mean
After-listing/ issued
11
12.6%
8.5%
8.4%
12
-Sell within 6 months
11
6.2%
3.5%
5.2%
12
Market V. (M.USD)
11
$117.3
$67.1
$95.8
Book / Market ratio
11
0.34
0.3
O¤er price (USD)
11
$9.0
$5.4
VC backed d.
11
0.09
High-tech d.
11
0.0
First day return
11
0.16
Panel B
11 high laddering IPOs
12 low laddering IPOs
Mean di¤erence
Std.Dev
Median
Di¤.
t-stat.
5.2%
4.7%
4.4%
7.4%
(2.6)
0.7%
0.8%
0.4%
5.5%
(5.1)
12
$178.8
$190
$144.9
-$61.5
(-1.1)
0.26
12
0.26
0.29
0.22
0.08
(0.6)
$8.1
12
$8.5
$8.3
$5.7
$0.5
(0.2)
0.3
0.0
12
0.25
0.45
0.0
-0.16
(-0.1)
0.0
0.0
12
0.17
0.39
0.0
-0.17
(-1.5)
0.16
0.18
12
0.1
0.21
0.06
0.06
(0.8)
29
Table 3
Summary Statistics on IPO Allocations and on Investors Trading
Panel A reports the summary statistics for the individual trading prior to the 23 sample and all 171
IPOs on the Oslo Stock Exchange in the period 1993 to 2007. "(Allocated/issued) " is the number of
allocated shares to each investor divided by the shares issued in the IPO. "(After-listing/issued) " is the
additional shares purchased after the listing divided by the shares issued in the IPOs. "Commission" is
the accumulated commission generated in USD by the investors in the two years before the IPO allocation
date. "Portfolio value" is the portfolio value in million USD for each allocated investor at 31.12.xx in
the year before the IPO allocation date. "Previous IPOs" is the accumulated previous IPO participations
by the investors divided by the accumulated IPO number in the sample." Previous Buy-and-hold " is the
accumulated previous number of times the allocated investor has been a buy-and-hold investor as a percent
of all previous IPO participations. This is the number of times the investor has held some IPO allocated
shares for more than six months in previous IPOs. "Previous Flipping" is the accumulated number of times
the investor have ‡ipped previous IPOs as a percent of all previous IPO participations before the IPO
allocation. Flipping is when all shares are sold within one month of the listing. USD values are calculated
from a USD/NOK exchange rate of 0.1792. Panel B reports that investors that buy (and sell) more shares
after the listing are allocated signi…cantly more IPO shares than investors that do not. T –statistics are
calculated as: Di¤erence / (square root [(variance sample 1/ numbers in sample 1) + (variance sample 2/
numbers in sample 2)].
Panel A
Sample 23 IPOs
All 171 IPOs
N
Mean
Std.Dev
Median
N
Mean
Std.Dev
Median
(Allocated/issued)
16,593
0.053%
0.173%
0.009%
175,382
0.036%
0.14%
0.003%
(After-listing/issued)
16,593
0.011%
0.19%
0.0%
175,382
0.006%
0.12%
0.0%
Commission USD
16,593
$3,544
$46,711
$37.9
175,382
$6,274
$93,395
$30.8
Portfolio value M.USD
16,593
$2.6
$44.5
$0.003
175,382
$3.6
$72.6
$0.004
Previous IPOs
16,593
0.05
0.05
0.04
175,382
0.03
0.05
0.017
Previous Buy-and-hold
16,593
0.21
0.37
0.0
175,382
0.21
0.37
0.0
Previous Flipping
16,593
0.15
0.31
0.0
175,382
0.1
0.25
0.0
Panel B: Comparing IPO allocations to after-listing investors and non after-listing investors
Laddering investors
All investors
Mean Di¤erence
N
Mean
Std.Dev
Median
N
Mean
Std.Dev
Median
Di¤.
t-stat.
*D1
427
0.116%
0.264%
0.018%
16,593
0.053%
0.173%
0.009%
0.06%
(4.9)
*D1*D2
195
0.097%
0.263%
0.009%
16,593
0.053%
0.173%
0.009%
0.04%
(2.3)
*D1*D3
357
0.097%
0.239%
0.017%
16,593
0.053%
0.173%
0.009%
0.04%
(3.5)
*D1*D2*D3
195
0.097%
0.263%
0.009%
16,593
0.053%
0.173%
0.009%
0.04%
(2.3)
30
Table 4
Relationship between After-listing Purchases and IPO Allocations
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with (allocated shares/issued shares) %
as the dependent variable. This is a standard OLS model. Only the 23 IPOs with exact allocations are
included. All variables are as described in Table 2 and Table 3. In regression 6 and 7 D1 indicates if more
than 50% of shares are sold within three and six months.
(Allocated shares/shares issued) %
Reg 1
Reg 2
Intercept
0.6366
0.7096
(2.3)
(2.8)
(After-listing shares/shares issued) %
0.0738
0.054
(1.6)
(1.4)
(After-listing shares/shares issued) %* D1
0.1306
(1.7)
D1 -Investors sell shares within months a listing
-0.0283
(-1.3)
Log (commission)
0.0111
(2.5)
(2.2)
Log (portfolio value)
0.0014
0.0018
(0.6)
(0.9)
Previous IPOs
0.2242
0.2085
(0.7)
(0.7)
-0.0076
-0.0046
(-0.3)
(-0.2)
-0.019
-0.0207
(-0.6)
(-0.6)
0.0657
0.0743
Previous buy-and-hold
Previous ‡ipping
Financial institution dummy
Log (market value)
BV / MV equity
0.0096
(0.9)
(1.1)
-0.0573
-0.0602
(-4.2)
(-4.8)
0437
0.4309
(7.3)
(6.7)
-0.0024
-0.0023
(-4.0)
(-3.9)
VC backed dummy
1.0986
1.1027
(15.5)
(14.5)
High-tech dummy
-0.9268
-0.9488
O¤er price
First day return
Company and year dummy
Observations (IPO allocations)
(-12.0)
(-14.5)
dropped
dropped
yes
yes
1,016
1,016
-of which are laddering investors
427
Adjusted R -squared
33.6%
Investors sell within months of listing
35.2%
all 6m.
31
Continued...
(Allocated shares/shares issued) %
Intercept
(After-listing shares/shares issued) %
Reg 3
Reg 4
Reg 5
Reg 6
Reg 7
6.0717
1.9466
1.268
1.3036
1.1851
(16.8)
(9.4)
(10.6)
(10.6)
(13.7)
0.0486
0.0587
0.0587
0.062
0.0487
(1.2)
(1.4)
(1.4)
(1.5)
(1.4)
0.286
0.3013
0.2398
(After-listing shares/shares issued) %* D1*D2
0.286
(4.2)
(After-listing shares/shares issued) %* D1*D3
0.2698
(4.9)
(After-listing shares/shares issued) %* D1*D2*D3
D1 -Investors sell shares within months a listing
(4.2)
(2.9)
(7.7)
-0.0384
-0.0249
-0.0249
-0.0434
-0.0093
(-1.6)
(-1.2)
(-1.2)
(-1.7)
(-0.5)
-0.2606
-0.2075
-0.2138
-0.2053
(-5.3)
(-4.5)
(-4.5)
(-4.5)
0.1551
0.1713
0.1267
D2 - Positive drift in share price after the listing
D3 - Underpriced IPO
0.5297
Log (commission)
0.0083
(1.8)
(1.8)
(1.8)
(2.4)
(2.3)
Log (portfolio value)
0.0024
0.0023
0.0023
0.0015
0.0019
(1.2)
(1.2)
(1.2)
(0.8)
(1.0)
0.1996
0.2351
0.2351
0.2691
0.2274
(0.6)
(0.8)
(0.8)
(0.9)
(0.8)
-0.002
-0.0072
-0.0072
-0.007
-0.0061
(-0.1)
(-0.3)
(-0.3)
(-0.3)
(-0.2)
Previous ‡ipping of possible
-0.0172
-0.0167
-0.0167
-0.011
-0.0194
(-0.5)
(-0.5)
(-0.5)
(-0.4)
(-0.6)
Financial institution dummy
0.0703
0.0641
0.0641
0.0644
0.0611
(20.1)
Previous IPOs of possible
Previous buy-and-hold of possible
Log (market value)
BV / MV equity
0.0085
(2.6)
(2.7)
(2.0)
0.0085
0.0103
0.0094
(1.1)
(0.9)
(0.9)
(0.9)
(0.9)
-0.3003
-0.0983
-0.0636
-0.0656
-0.0599
(-16.8)
(-9.6)
(-11.5)
(-11.4)
(-15.9)
dropped
dropped
dropped
dropped
dropped
-0.009
-0.0016
-0.0023
-0.0025
-0.002
O¤er price
(-12.4)
(-1.8)
(-2.9)
(-3.1)
(-2.5)
VC backed dummy
-0.4496
0.6022
0.5567
0.5428
0.6072
(-17.2)
(-16.6)
(7.0)
(6.5)
(7.4)
High-tech dummy
-1.0434
-1.0831
-0.8529
-0.8437
-0.8859
(-12.7)
(-16.8)
(-8.8)
(-8.5)
(-9.6)
dropped
dropped
dropped
dropped
dropped
yes
yes
yes
yes
yes
1,016
1,016
1,016
1,016
1,016
First day return
Company and year dummy
Observations (IPO allocations)
-of which are laddering investors
357
195
195
145
217
38.3%
37.0%
34.5%
36.2%
37.9%
all 6m.
all 6m.
all 6m.
50% 3m.
50% 6m.
Adjusted R -squared
Investors sell within months of listing
32
Table 5
After-listing Purchases in Past IPOs Give More Future IPO Ownership
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with (allocated shares/issued shares) %
as the dependent variable. This is a standard OLS model. All variables are as described in Table 2 and
Table 3. Regression 1 includes all IPOs. Regression 2 and 3 includes hot and cold IPOs respectively. There
are 171, 105 and 45 IPOs in regression 1, 2 and 3. Regression 4 to 6 drop all company speci…c control
variables. Past laddering includes only investors who have purchased more shares right after the listing and
then sold some of the shares within six months of the listing date in past IPOs.
(Allocated shares/shares issued) %
Reg 1
Reg 2
Reg 3
Reg 4
Reg 5
Reg 6
-0.12984
0.1096
0.7882
-0.0278
2.0078
0.0587
(-25.9)
(6.9)
(100.0)
(-7.0)
(90.8)
(10.6)
0.1114
0.1137
0.0877
0.1114
0.1137
0.0877
(9.3)
(8.2)
(3.4)
(9.3)
(8.2)
(3.4)
0.006
0.0051
0.012
0.006
0.0051
0.012
(4.1)
(3.6)
(8.9)
(4.1)
(3.6)
(8.8)
Log (portfolio value)
0.0085
0.0007
0.0013
0.0009
0.0007
0.0013
(2.6)
(2.3)
(2.2)
(2.6)
(2.3)
(2.2)
Previous IPOs
0.1535
0.1619
0.1865
0.1535
0.1619
0.1865
Intercept
Previous laddering
Log (commission)
Previous buy-and-hold
Previous ‡ipping
Financial institution dummy
Log (market value)
(3.8)
(3.6)
(3.0)
(3.8)
(3.6)
(3.0)
-0.0156
-0.0153
-0.0177
-0.01558
-0.0153
-0.0177
(-7.8)
(-7.0)
(-3.0)
(-7.8)
(-7.0)
(-3.0)
-0.0022
-0.0051
0.0061
-0.0022
-0.0051
0.0061
(-0.9)
(-1.9)
(0.9)
(-0.9)
(-1.9)
(0.9)
0.1779
0.1653
0.1807
0.1779
0.1653
0.1807
(9.5)
(6.9)
(5.3)
(9.5)
(6.9)
(5.3)
0.0121
-0.008
-0.0357
(21.4)
(-9.8)
(-109.1)
BV / MV equity
-0.0108
0.0474
-0.2327
(-2.1)
(10.3)
(-90.3)
O¤er price
-0.0011
-0.001
0.0008
(-63.6)
(-32.3)
(64.4)
0.1196
0.0493
-0.2708
(29.7)
(5.0)
(-85.9)
-0.1668
-0.44
0.0599
(-33.4)
(-42.8)
(27.3)
0.4163
0.3627
dropped
(16.3)
(12.5)
yes
yes
yes
yes
yes
yes
175,382
145,392
22,114
175,382
145,392
25,891
22.0%
21.7%
20.1%
22.0%
21.7%
20.1%
all
hot
cold
all
hot
cold
VC backed dummy
High-tech dummy
First day return
Company and year dummy
Observations
Adjusted R -squared
IPOs
33
Table 6
Actual Return from After-listing Purchases
This table reports the average USD return for the investors that buy more shares after the listing. Only
IPOs with exact IPO allocations are included in the analysis (23 IPOs). First day return $ is calculated as:
the number of shares allocated in the IPO * (…rst day closing price - o¤er price) * 0.1792 (The NOK/USD
exchange rate). First month return $ is calculated as: (The number of shares allocated in the IPO + The
shares purchased after the listing) * ( Price one month after the listing - …rst day closing price) * 0.1792
(The NOK/USD exchange rate). Panel A investigate only IPO allocated investors with after-listing buying
that sell early in hot IPOs. Panel B investigate only IPO allocated investors with after-listing buying that
sell early in IPOs with a positive drift after the listing. Panel C investigate only IPO allocated investors
with after-listing buying that sell early in cold IPOs. Panel C includes all IPO trading for the 70 investors
that buy more shares after the listing in the cold IPOs. These 70 investors lose money on their cold IPO
after-listing purchases, but they earn money in total. Together these investors receive 447 allocations in the
sample. Panel D and E investigates non-allocated IPO investors who buy shares after the listing. Panel D
investigates the 11 IPOs with high laddering. Panel E investigates the 12 IPOs with low laddering.
Panel A: (IPOs=14)
First day return $
First month return $
Total return $
Std.Dev.
Investors
All investors
$6,526
$9,197
$15,723
$59,730
357
Institutions
$16,400
$21,866
$38,265
$106,181
92
First day return $
First month return $
Total return $
Std.Dev.
Investors
All investors
$6,712
$15,592
$22,303
$61,822
195
Institutions only
$17,217
$50,733
$67,949
$117,353
40
Panel B: (IPOs=6)
Panel C:
First day return $
First month return $
Total return $
Std.Dev.
Allocations
All investors
$17,705
$3,744
$21,449
$167,687
447
Institutions only
$46,297
$13,428
$59,725
$266,893
169
Panel D: The 11 IPOs with high laddering
Six month return $
Std.Dev.
Investors
All investors
-$5,611
-$139,736
10,748
Institutions only
-$22,189
-$339,564
1,806
Panel E: The 12 low laddering IPOs
Six month return $
Std.Dev.
Investors
All investors
-$324
-$327,450
6,554
Institutions only
$1,276
$711,068
1,388
34
Table 7
After-listing Purchases and Generated stock-trading Commissions
This table reports the coe¢ cients and White (1980) heteroscedasticity consistent t-statistics in parentheses for the regressions with the aggregate (after-listing shares/shares issued) % as the dependent variable.
All variables are as described in Table 2 and Table 3. All regressions are standard OLS models, and the
sample period is from January 1993 to September 2007. Only investors that sell some shares within six
months of the listing are included in Aggregate (After-listing shares/shares issued) %. Only investors that
do not buy shares after the listing are included in Log (average commission per share). Regression 2 and 4
drop the variables that Hao (2007) and Aggarwal et al. (2006) predict increase laddering. Regression 3 and
4 use average commission by shares instead of the sum of commission scaled by commission in all IPOs.
Log (aggregate after-listing shares/shares issued) %
Intercept
(Combined commission) %
Reg 1
Reg 2
Reg 3
Reg 4
1.5289
1.5296
0.6737
0.3876
(1.5)
(1.6)
(0.7)
(0.4)
51.5725
44.7781
(3.9)
(4.4)
0.2172
0.2116
Log (average commission per share)
Log (market value)
-0.0289
-0.03153
(1.8)
(1.7)
0.01
0.0306
(-0.5)
(-0.5)
(0.2)
(0.5)
-0.147
-0.1551
-0.2652
-0.2938
(-0.5)
(-0.5)
(-0.9)
(-0.9)
-0.4901
-0.6445
-0.505
-0.5339
(-1.5)
(-2.3)
(-1.5)
(-1.7)
High-tech dummy
-0.2395
-0.2797
-0.1333
-0.1139
(-0.7)
(-0.9)
(-0.4)
(-0.3)
Absolute price revision
-0.0305
BV / MV equity
VC backed dummy
Sentiment investors (million)
Observations
Adjusted R -squared
35
-0.0044
(-0.2)
(-0.2)
0.0000
0.0001
(-0.3)
(2.2)
171
171
171
171
7.8%
7.4%
4.7%
4.1%
Table 8
Relationship between After-listing Purchases and IPO Allocations
-Robustness
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with (allocated shares/issued shares) %
as the dependent variable. This is a standard OLS model. Only the 23 IPOs with exact allocations are
included. All variables are as described in Table 2 and Table 3. In regression 1 all PCC (savings banks) are
included. In regression 2 IPO allocations are trimmed at 0.1%.
Intercept
(After-listing shares/shares issued) %
(After-listing shares/shares issued) %* D1 *D2 *D3
D1 -Investors sell shares within six months a listing
D2 - Positive drift in share price after the listing
1.5432
1.0574
(14.3)
(2.8)
0.0772
0.249
(1.9)
(4.6)
0.2674
0.5255
(3.7)
(1.7)
-0.0201
-0.0326
(-1.1)
(-0.6)
0.1242
-0.1165
(7.6)
(-1.6)
-0.1832
-0.4437
(-15.0)
(-5.5)
0.0093
0.029
(2.5)
(2.1)
0.0035
0.0005
(2.0)
(0.1)
Previous IPOs of possible
0.0171
0.0135
(0.1)
(0.0)
Previous buy-and-hold of possible
-0.004
0.0311
(-0.2)
(0.6)
-0.0346
-0.0602
(-1.1)
(-1.3)
0.1086
0.4664
(1.5)
(1.7)
-0.0779
-0.0727
D3 - Underpriced IPO
Log (commission)
Log (portfolio value)
Previous ‡ipping of possible
Financial institution dummy
Log (market value)
(-19.2)
(-4,2)
BV / MV equity
0.0331
dropped
O¤er price
0.0002
0.0152
(1.4)
(11.4)
0.7644
-0.4935
(23.7)
(-4.8)
0.3245
0.4879
(12.8)
(7.2)
dropped
dropped
(6.3)
VC backed dummy
High-tech dummy
First day return
Company and year dummy
Observations (IPO allocations)
-of which are laddering investors
Adjusted R -squared
Investors sell within months of listing
36
yes
yes
1,251
1,064
209
200
34.2%
31.6%
all 6m.
all 6m.
Table 9
IPO Allocations and After-listing Purchases -Robustness 2
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with (allocated shares/issued shares) %
as the dependent variable. This is a standard OLS model. Only the 23 IPOs with exact allocations in the
sample period are included. All variables are as described in Table 2 and Table 3. All IPO speci…c control
variables are removed.
(Allocated shares/shares issued) %
Intercept
(After-listing shares/shares issued) %
(After-listing shares/shares issued) %* D1
Reg 1
Reg 2
Reg 3
Reg 4
-0.3023
0.3133
0.2943
-0.2871
(-2.2)
(1.5)
(4.2)
(-1.4)
0.054
0.0486
0.0587
0.0587
(1.4)
(1.2)
(1.4)
(1.4)
0.1306
(1.7)
(After-listing shares/shares issued) %* D1 *D2
0.286
(4.2)
(After-listing shares/shares issued) %* D1 *D3
0.2698
(4.9)
(After-listing shares/shares issued) %* D1*D2 *D3
0.286
(4.2)
D1 -Investors sell shares within 6m. a. listing
-0.0283
-0.0384
(-1.3
(-1.4)
D2 - Positive drift in share price after the listing
-0.0249
(-1.2)
(-1.2)
-0.6103
0.5593
(-6.4)
D3 - Underpriced IPO
Log (commission)
Log (portfolio value)
Previous IPOs of possible
Previous buy-and-hold of possible
Previous ‡ipping of possible
Financial institution dummy
Observations (IPO allocations)
-of which are laddering investors
Adjusted R -squared
37
-0.0249
(24.9)
-0.6049
-0.5883
(-9.0)
(-8.9)
0.0096
0.0083
0.0085
0.0085
(2.2)
(1.8)
(1.8)
(1.8)
0.0018
0.0024
0.0023
0.0023
(0.9)
(1.2)
(1.2)
(1.2)
0.2085
0.1996
0.2351
0.2351
(0.7)
(0.6)
(0.8)
(0.8)
-0.0046
-0.002
-0.0072
-0.0072
(-0.2)
(-0.1)
(-0.3)
(-0.3)
-0.0207
-0.0172
-0.0167
-0.0167
(-0.6)
(-0.5)
(-0.5)
(-0.5)
0.0743
0.0703
0.0641
0.0641
(1.1)
(1.1)
(0.9)
(0.9)
1,016
1,016
1,016
1,016
427
357
195
195
35.2%
38.3%
37.0%
37.0%
Table 10
Aggregate IPO Laddering and Allocations
This table reports the aggregate allocation and laddering at the IPO level. Panel A includes the 11
high laddering IPOs. Panel B includes also the 12 low laddering IPOs.
Panel A
Group
Investors
Allocation
Laddering
Total
IPOs
D1
363
3.6%
6.2%
9.8%
11
D1, D3
317
3.5%
6.3%
9.8%
9
D1, D2
174
4.5%
8.7%
13.2%
4
D1
427
2.5%
3.5%
6.0%
20
D1, D3
357
2.5%
4.5%
7.0%
14
D1, D2
195
5.9%
3.2%
9.1%
6
Panel B
.
38
Figure 1
The Factors that Create the Incentives to Engage in IPO Laddering
Laddering investors are allocated some shares in the IPO and then they buy more shares after the
listing before they sell all shares. Commission investors are investors that generate high levels of stocktrading commission to the investment bank through trading in other shares. Investment bank is the lead
manager in the IPO. Hot and cold IPOs are high and low oversubscribed IPOs. Hot and cold IPOs are
proxied for by positive and non-positive …rst day return.
Hot IPOs
Laddering
Agree to buy more shares after the listing to increase
Pulliam and Smith (2000)
investors
current hot IPO allocations
and the SEC litigation
releases
Commission
Pay increased stock-trading commissions to the investment
Reuter (2006) and
investors
bank, through trades in other shares, to increase
Nimalendran, Ritter
current and future hot IPO allocations
and Zhang (2006)
1) Increase received commissions by allocating IPO
Hao (2007)
Investment banks
shares to laddering investors and commission investors
2) Ensure a successful IPO by allocating shares to
Hao (2007)
laddering investors that increase prices after the listing
Cold IPOs
Laddering
Agree to buy more shares after the listing to increase
investors
future hot IPO allocations
Investment banks
Gri¢ n et al. (2007)
1) Ensure a more successful IPO by allocating shares to
Gri¢ n et al. (2007)
laddering investors that increase prices after the listing
and Hao (2007)
2) Reduces after-listing price uncertainty by allocating
Gri¢ n et al. (2007)
shares to laddering investors
3) Reduces the risk of damaged reputation from IPOs
that fall in price by allocating shares to laddering
investors
39
Gri¢ n et al. (2007)
Figure 2
Theoretical Predictions By Hao (2007) and Aggarwal et al. (2006)
Predictions made by Hao (2007)
Laddering will increase the following variables:
1) Laddering results in a higher o¤er price if investors are not expected to sell shares in the six m. after-listing
2) Laddering is positively related to money left on the table.
3) Laddering in itself does not necessarily increase underpricing.
4) Laddering contributes to long-run underperformance.
The following variables will increase laddering:
5) More expected underpricing (without laddering) leads to more laddering
6) When there are information momentum e¤ects, there is more laddering.
7) When underwriters shares in on the pro…ts from underpriced IPOs, there is more laddering
Predictions made by Aggarwal et al (2006)
Laddering will increase the following variables:
1) Returns should be higher for IPOs with laddering over the six months after the listing
2) The long-run return should be lower for IPOs with laddering than for IPOs with no laddering
3) The number of sentiment investors increases IPO underpricing for IPOs with laddering.
4) Turnover and volume (shares traded) are greater for IPOs with laddering than for IPOs with no laddering
The following variables will increase laddering:
5) Underpricing is higher for IPOs with laddering than for IPOs with no laddering
6) When there are more sentiment investors there is a bigger likelihood of laddering
Major Di¤erences
1) Hao (2007) predict intentional underpricing, and Aggarwal et al. (2006) predict price run ups that are corrected
2) Hao (2007) and Aggarwal et al. (2006) predicts that laddering increases o¤er/closing and underpricing respectively
40
Figure 3
Timeline of the IPO Allocations for the Di¤erent Groups
Listing in database is when the company list ownership records in the ownership database. This is
when the ownership records are observed in the data the …rst time. IPO allocation is when the companies
distribute the allocated shares in the ownership database. Listing is when the company is listed publicly.
After-listing purchases is when the laddering trades are calculated. Group 1 to 3 is the ordering of the group
of detail in the allocations. Group 1 is 100% accurate IPO allocations. Group 2 IPO allocations includes
one to 30 days of after-listing trading. Group 3 IPO allocations includes existing owners who have not sold
all of their shares in the IPO. There are 23, 143 and 5 companies in group 1, 2 and 3 respectively.
Timeline
Six months before
One month before
the listing
the listing
Group 1
Listing in database
IPO allocation
Group 2
Listing in database
Listing month
One month after
the listing
Listing
IPO allocation
After-listing purchases
After-listing purchases
Listing
Group 3
Listing in database
Listing
IPO allocation
41
After-listing purchases
.
42
3
Using Stock-trading Commissions to Secure IPO Allocations
Sturla Lyngnes Fjesme34
BI Norwegian Business School
Roni Michaely
Cornell University and the Interdisciplinary Center
Øyvind Norli
BI Norwegian Business School
.
.
.
.
.
.
.
.
.
JEL classi…cation: G24; G28
Keywords: IPO allocations; Equity issue; Commission; Rent seeking
34
We are grateful to Jay Ritter, Øyvind Bøhren, François Derrien, seminar participants at BI Norwegian
Business School for valuable suggestions, “The Center for Corporate Governance Research (CCGR)” at
BI Norwegian Business School for …nancial support, the Oslo Stock Exchange VPS for providing the data
and the investment banks and companies that helped us locate the listing prospectuses. All errors are
our own.
Contact: BI Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway. E-mail address:
[email protected] Telephone: +47-957-722-43.
43
Abstract
Using data, at the investor level, on the allocations of shares in initial
public o¤erings (IPOs), we document a strong positive relationship between
the amount of stock-trading commission and the number of shares an investor
receives in a subsequent IPO. We …nd no evidence to support the idea that investment banks allocate shares to investors that are perceived to be long-term
investors. Our …ndings are consistent with the view that investment banks
are able to capture some of the pro…ts earned by investors when participating
in underpriced IPOs.
44
3.1
Introduction
The Securities and Exchange Commission (SEC) has since the early 2000s investigated the
initial public o¤ering (IPO) allocation practices of several major investment banks. One
concern is that IPO allocations are tied to excessively large stock-trading commissions
and that such a practice would constitute illegal kickbacks from investors to investment
banks. Reuter (2006) points out that such kickbacks would allow the underwriter to share
more of the bene…ts of underpriced IPOs— and, therefore, exacerbate the agency con‡ict
that exists between the issuing …rm and the lead underwriter of the IPO. This paper
investigates whether or not investors that has generated large stock-trading commissions
in the past receives a preferential treatment in future IPO allocations.
Using data on the stock-holdings for every single investor that owned common shares
that was listed or became listed on the Oslo Stock Exchange during the period 1993
through 2007, we are able to link stock-trading commission and IPO allocation at the
investor level. The main …nding of the paper is a strong and robust positive relationship
between the level of stock-trading commission generated by an investor prior to the IPO
and the number of shares the same investor receives through the IPO allocation. It can
be argued that large investors that generate more commissions are likely to apply for
more IPO shares. However, the economic and statistical signi…cance of the relationship
between commission and allocation is robust to controlling for the market value of the
investors portfolio, as well as to other investor characteristics. We conclude that investors
generating large stock-trading commission receives the most IPO shares because of the
commission they generate. Other investor characteristics are of less or no importance for
IPO allocations.
The empirical research on the allocation practices of investment banks have been hampered by the lack of data on IPO allocations.35 Since information about stock-trading
commissions are equally hard to come by, there is little empirical research on the relationship between commissions and allocations. One exception, and the paper closest to ours,
is Reuter (2006) who …nds a positive correlation between stock-trading commission paid
by mutual funds to lead investment banks and the holdings in IPOs underwritten by the
same banks. This suggests, in general, that having a business relationship with the lead
underwriter increases the chance of getting shares in underpriced IPOs. In particular,
it suggests that investors can “buy” allocations by channeling their trades through the
brokerage arm of the lead underwriter. In another related paper, Nimalendran, Ritter and
Zhang (2006) show that there is a positive relationship between money left on the table
in IPOs and trading volume in liquid shares around IPO allocation dates. This is indirect
evidence of a positive relationship between trading commission and IPO allocations.
The strength of our paper, compared to the existing literature, is that we are able to
analyze exact allocations at the investor level. In the main part of the paper, we study
24,308 IPO allocations.36 The existing literature has suggested at least three potential
explanations for what determines investment banks’decision of which investors are getting shares in oversubscribed IPOs. First, Benveniste and Spindt (1989) suggest that
investment banks allocate IPO shares to informed investors in return for a truthful revelation of their valuation of the issuer. Second, investment banks themselves tend to argue
35
See Ritter (2003) and Jenkinson and Jones (2004) for papers that study IPO allocations and summarizes IPO allocation studies.
36
These exact allocations are from 30 di¤erent IPOs. In other words, there are 24,308 unique investorIPO combinations in our data. In robustness tests, we also study 162,384 investor-IPO pairs where the
IPO allocation data might be contaminated with some post-IPO trading.
45
that they are looking for long-term investors. Third, investment banks allocate shares to
investors that can provide some form of kickback.
The empirical literature provides mixed results in terms of understanding IPO allocations in the light of the above three potential explanations.37 An important contribution
of our paper is that we examine and contrast all three potential explanations simultaneously. As already mentioned, our data strongly support the view that investors can secure
themselves IPO allocations through large stock-trading commissions. We …nd no evidence
of a preferential treatment of buy-and-hold investors. Neither do we …nd any support for
the idea that investors get allocation in return for revealing private information about
issuing …rm value.
The rest of paper is organized as follows: Section 3.2 describes the related literature.
Section 3.3 describes theoretical predictions and the testable implications. Section 3.4
describes the data set. Section 3.5 gives the empirical results, and section 3.6 concludes.
3.2
Related literature
Ritter (2003) and Jenkinson and Jones (2004) argue that there are three views on how
IPOs are allocated. First, is the academic view based on Benveniste and Spindt (1989).
In this view, investment banks allocate IPO shares to informed investors in return for
true valuation and demand information. Second, is the pitchbook view where investment banks allocate shares to institutional investors that are likely to be buy-and-hold.
Finally, is the rent seeking view where investment banks allocate shares to investors in
return for kickbacks. Existing research have found support for each of these views and
against the academic view and the pitchbook view. The existing research have investigated these views one by one. The exception is Jenkinson and Jones (2004) that compares
the academic view to the pitchbook view.
There are many papers that investigates the academic view alone, as described by
Benveniste and Spindt (1989). Cornelli and Goldreich (2001) investigate the order book
of 23 and 16 international IPOs and SEOs. They …nd that regularly participating, large
bid and domestic participants are favored in allocations. They also …nd that bidders that
participate in both hot and cold issues are given larger allocations in hot issues. Cornelli
and Goldreich (2003) investigate the order book of 37 and 26 international IPOs and
SEOs. They …nd that bids from large, frequent bidders that include a limit price a¤ect
the issue price. It is concluded that book-building is designed to extract information from
investors. Ljungqvist and Wilhelm (2002) look at allocations between institutional and
retail investors for 1,032 international IPOs. They …nd that institutional investors are
favored over retail investors. They …nd that an increased institutional allocation is linked
to a higher deviation from the midpoint of the book-building pricing range to the …nal
o¤er price. It is concluded that underwriters use institutional bids to set the o¤er prices
in IPOs. Binay, Gatchev and Pirinsky (2007) investigate 4,668 U.S. IPOs and …nd that
underwriters favor institutions they have previously worked with. A relationship with the
underwriter is more important in IPOs with strong demand, IPOs of less liquid …rms and
IPOs by less famous underwriters. It is argued that favoring regular investors is done to
price IPOs more correctly. Regular investors have incentives to report their true value in
the book-building so that they will be favored in future IPOs. Bubna and Prabhala (2007)
investigate 137 Indian IPO allocations. They …nd that book-building and discretion in
37
Table 1 summarizes related papers.
46
allocation enhances pre-market price discovery. All these papers are consistent with the
academic view of IPO allocations
The two main papers that investigate the pitchbook view of IPO allocations are Jenkinson and Jones (2004) and Aggarwal (2002). Jenkinson and Jones (2004) study 27
European IPO order books to compare the pitchbook view to the academic view. They
…nd that there is limited information gathering in the book-building procedure. This
is inconsistent with the academic view. Jenkinson and Jones (2004) do, however, …nd
evidence in favor of the pitchbook view and concludes that IPO allocations are made to
buy-and-hold investors. Aggarwal (2002) investigate the pitchbook view by looking at
‡ipping activity of institutional and retail investors in 193 U.S. IPOs. It is found that
institutional investors ‡ip a larger part of their IPO allocations than retail investors. This
is taken as evidence against the pitchbook view. This view argues that institutions are
allocated more IPO shares because institutions are more likely to be buy-and-hold than
retail investors.
There are four types of IPO rent seeking that have led to investigations (and settlements) between the SEC or NASD and di¤erent investment banks, see Liu and Ritter (2010).38 IPO allocations can be tied to future corporate business (IPO spinning),
after-listing purchases of the IPO shares (IPO laddering) and stock-trading commissions.
Issuing companies can also agree to heavy underpricing in return for after-listing coverage
from star analysts provided by the investment bank (analyst con‡ict of interest). The
underpriced shares are then allocated to clients that generate high commissions so that
the investment bank is able to recapture some of the underpricing. All of these allocation
practices have been looked at in di¤erent studies. Liu and Ritter (2010) investigate IPO
spinning, Fjesme (2011) investigate IPO laddering, Cli¤ and Denis (2004) investigate analyst con‡ict of interest and Reuter (2006) and Nimalendran, Ritter and Zhang (2006)
investigate IPO allocations for commission trading.
Reuter (2006) investigate if IPO allocations are tied to stock-trading commissions by
studying 1,868 IPOs on NYSE, AMEX and Nasdaq in the period 1996 to 1999. Reuter
(2006) …nd a positive relationship between stock-trading commissions paid by mutual
funds to IPO lead underwriters and mutual fund holdings of IPO shares after the listing.
It is concluded that commission generation is a likely reason behind IPO allocations for
mutual funds. Reuter (2006) establish a link between IPO allocations and stock-trading
commission for mutual funds, but it is not investigated if commission is important for
IPO allocations for other investor groups. Nimalendran, Ritter and Zhang (2006) study
investor trades in the 50 most liquid stocks in the U.S. during the days surrounding IPO
allocations. They …nd that trading volume is positively related to money left on the table
in IPOs. It is suggested that this increased trading is done purely to increase stock-trading
commission as payment for IPO share allocations. Both of these papers support the rent
seeking view.
3.3
Theoretical predictions and testable implications
Investors are placed on A, B and C lists by investment banks before any IPO.39 Investors
from the A list, that applies for shares, are more likely to receive more IPO allocations
38
Figure 1 describes the four types of IPO rent seeking.
The information about IPO allocation practices is obtained from meetings with former Norwegian
investment bankers.
39
47
than investors on the B lists etc.40 We do not know how investors are placed on the A,
B and C lists, but we expect that this is related to the pitchbook, the academic and the
rent seeking view of IPO allocations. The investment bank prepares a list with proposed
allocations after the book building/pricing of the IPOs that is given to the board of the
issuing company. The board then decides IPO allocations based on this list. Anecdotal
evidence suggests that most boards approve the proposed list without adjustments. Being
on the A list of the lead investment bank is therefore very important when applying for
IPO shares.
In this paper we test if information gathering, allocation to long term buy-and-hold
investors or rent seeking are likely reasons behind IPO allocations. We measure if providing pricing information, price stability or stock-trading commission will place investors on
the A, B and C lists of the investment banks. The three allocation views are not mutually
exclusive within or between IPOs. It is therefore possible that di¤erent IPOs are allocated
based on di¤erent views. It is also possible that di¤erent investors are allocated shares
based on di¤erent views within one IPO.
3.3.1
The rent seeking view of IPO allocations
Rent seeking is an area that have received allot of attention in the media, but there is
limited empirical research on the rent seeking view of IPO allocations. A likely reason
for this is that it is very hard to obtain data to test for rent seeking. Testing for money
transfers from one bank account to another obviously requires very detailed data. The
cover-up activities needed to hide transfers as legitimate activities can be very creative.
In this paper we focus on the rent seeking suggested in Reuter (2006) and Nimalendran,
Ritter and Zhang (2006). We study if IPO allocations are related to generated stocktrading commission. In the Robert Stevenson settlement, an investment bank settled to
pay a …ne for alledgedly tying IPO allocations to stock-trading commission, it was argued
that clients both increased trading and increased commission rates per trade to receive
IPO shares.41 In the Norwegian data it is only possible to test if there is a relationship
between trading and allocations. It is not possible to detect changes in payments per
trade in the data. The data also only let us test for commission generation on monthly
trading.42 This means that it is possible that commission trading takes place even if it
does not show up in the data.
The rent seeking view is tested by regressing IPO allocations on stock-trading commission generated by the allocated investors and a set of control variables. Generated stocktrading commission is accumulated, per investors ID, over monthly portfolio changes in
the past 24 months prior to any IPO. Only buy generated commission is included to avoid
any issues related to portfolio rebalancing (to make room for the new shares). If investors
that generate more commission are also allocated more IPO shares, we conclude that
the rent seeking view is an accurate view of IPO allocations. If there is no relationship
between commission and IPO allocations, we are not able to reject the rent seeking view
because it is possible to hide this type of trading. It is also tested if there is a link between
40
Figure 2 describes all the steps in the IPO allocation process.
See January 9, 2003 NASD settlement http://www.…nra.org/Newsroom/NewsReleases/2003/P002957
42
Commissions are generated from monthly data and not daily data. Because of this it is possible that
commission trading takes place even if we are not able to …nd it in our data set. If commissions are
generated from daily buy and sell orders in the same shares we are not able to detect this. It is also
possible that some investors pay higher commission rates to get allocations. This should, however, be
discovered in auditing.
41
48
the number of IPO participations and commission. If rent seeking is an active strategy,
there will be a strong relation between stock-trading commission and the number of IPO
participations by each investor. It is possible that investors that get repeated allocations
do so because they generate high commissions. IPO investors with single time IPO allocation may be kept out of future IPOs because they do not generate su¢ cient levels of
stock-trading commission.
3.3.2
The pitchbook view of IPO allocations
The pitchbook view of IPO allocations comes from the sales pitch slides of the investment
banks (Ritter, 2003). In these slides it is usually argued that investments banks will use
their power to allocate shares to long term buy-and-hold investors. It is argued, by the
investment banks, that buy-and-hold investors will create price stability that is good for
the issuing company. If buy-and-hold is an accurate view of IPO allocations, investors
that buy-and-hold IPO shares must also receive future IPO allocations. There must also
be a punishment in terms of no (or at least less) future IPO allocations for investors
that sell shares early (‡ipping investors).43 An investment bank that underwrite many
IPOs will have a more reliable reward/threat system than less active investment banks.
Therefore, it should also be more buy-and-hold investors in IPOs by active investment
banks. It should also not be possible for investors to repeat a ‡ipping strategy in IPOs
by the same bank over time.44 If buy-and-hold investors do not have the potential threat
of not receiving future allocations, there is no point of being buy-and-hold. If investors
that continue to ‡ip their shares still get IPO allocations, this is also support against the
pitchbook view.
The pitchbook view of IPO allocations is tested by splitting allocated IPO investors
into three groups. Group one investors ‡ip their shares (sell all shares within the …rst
month after the listing), group two investors hold their shares in the long term (hold some
shares longer than six months after the listing) and group three investors are all remaining
investors.
To control for past buy-and-hold and ‡ipping we add the number of times each investor
has been, out of all past IPO participations, placed in group one or two. This will control
for past buy-and-hold and past ‡ipping activity in all previous IPO participations. The
past buy-and-hold and the past ‡ipping variables are calculated both on the total sample
and on a bank by bank basis. The pitchbook view is then tested by regressing IPO
allocations on the past level of buy-and-hold and ‡ipping. If investors are allocated shares
because they are buy-and-hold, the buy-and-hold variable will be positively related to IPO
allocations and the ‡ipping variable will be negatively related to IPO allocations. Since the
views are not mutually exclusive, it is possible that both buy-and-hold and stock-trading
commission are important for IPO allocations. Because of this, past buy-and-hold and
past ‡ipping are included as control variables when testing the other views as well.
43
The rent seeking view and the academic view can be tested in one speci…c or several unrelated IPOs.
The buy-and-hold view should, however, be tested in several related IPOs. The key of the buy-and-hold
view is that investors that provide this service over time are allocated shares over time. Investors that
hold shares in the long run are rewarded with more shares in the future. Investors that sell shares early
are punished by no future allocations.
44
Flipping investors are normally meant to be investors that sell their allocated shares during the …rst
day of trading (Krigman, Shaw and Womack, 1999). We really want to test how selling shares early
a¤ects future allocations. It is therefore more accurate for our analysis to include all shareholders that
sell their shares within the …rst month as ‡ipping investors.
49
3.3.3
The academic view of IPO allocations
The idea of Benveniste and Spindt (1989) is that investment banks meet with informed
investors to price the IPO shares. Investment banks use investor bids to build a demand
curve of the company shares. Investors are rewarded for their pricing service with IPO
allocations that are underpriced on average. The academic view is controlled for by
including a dummy variable that takes the value of one for all professional investors
(…nancial institutions). It is possible that other investors, like non-…nancial institutions
or retail investors, are participating in pricing of the shares, but it is not expected that
this is very common. Investment banks are more likely to meet with …nancial institutions
when they price IPO shares. To test the academic view more directly we proceed in
the direction of Ljungqvist and Wilhelm (2002). The absolute percentage change from
the midpoint in the initial pricing range to the actual o¤er price is used as the measure
of pricing information. This measure should change when more pricing information is
collected. The percentage change from the midpoint in the pricing range to the o¤er
price is regressed on the combined allocation percentage to …nancial institutions and a
set of control variables. If there is pricing information, the …nancial institution allocation
percentage will be related to the percentage change in the pricing range. When …nancial
institutions are allocated IPO shares, there should be a signi…cant e¤ect on the price.
This analysis can, however, only be performed at the company level on the 71 IPOs that
are priced through book-building.
3.4
Data
There are 403 new listings on the OSE in the period January 1993 to September 2007. In
total, 193 of the 403 companies listed through private placements, cross listings, spin-o¤s
to existing shareholders or directly without any o¤erings. There are 89 companies with no
o¤erings to new shareholders. The remaining 210 companies listed through IPOs. Table
2 gives the annual distribution of IPOs on the OSE in the period 1993 to 2007.
In 30 of the 210 IPOs we have obtained 24,308 IPO allocations. (In 155 additional
IPOs we have obtained 162,384 IPO allocations that might be contaminated with afterlisting trading. The 162,384 IPO allocations are used in robustness testing). One listing
requirement on the OSE is that all shareholders must be registered in the Norwegian
Central Depository (the VPS) before the listing. The number of shares owned by each
investor must be given to the VPS before any company can list publicly. This database is
100% accurate, as it is not possible to list otherwise. The VPS database includes all shareholders in all companies that are publicly listed or intend to list publicly. This database is
used to obtain the IPO allocations by taking the di¤erence in company ownership before
and after allocation dates.45 Only IPO allocations to new shareholders are investigated.
45
In 16 of the 210 IPOs it has not been possible to calculate IPO allocations from the ownership
data. These companies are listed in the database (VPS) in the same month as the listing month. These
companies are therefore removed from the sample. In three companies there is missing allocation data,
and in four companies it has not been possible to locate the pricing information (no o¤er price). These
IPOs are therefore not included in the analysis. There are three privatizations in the period that are
removed. The …nal sample is 185 IPOs with allocation and pricing data. 210 IPO companies - 16
companies that list in both VPS, OSE and IPO in the same month - 3 privatizations - 2 missing VPS
data - 4 missing prospectus and newspaper articles on pricing = 185 companies.
50
More allocations to existing shareholders are removed. Allocation dates are collected from
the IPO listing prospectuses.
Some companies list in the VPS database in years before the listing. Other companies
list in the VPS as part of the listing process. The number of shares by each investor ID is
observed at the end of each month. All companies list in the VPS, sell shares in the IPO
and list on the OSE. Allocations, by investor ID, are calculated as the di¤erence in company share holdings before and after allocation dates. In terms of IPO allocations there
are three dates that are important in the listing process. When companies list in the VPS
ownership database, when companies distribute shares in the IPO and when companies
list on the OSE in‡uence IPO allocations. Companies do this process in di¤erent orders.
This leads to three di¤erent levels of detail in the obtained IPO allocations. All ownership
is observed on a monthly level, so if more than one listing event is performed within the
same calendar month we are not able to distinguish between the events. Figure 3 gives
a detailed description of how the IPO allocations are obtained for the di¤erent company
groups.
There are 15 savings banks (PCC list) out of the 210 IPOs on the OSE in the sample
period. In total, 14 and seven of these savings banks are in the 155 IPOs with allocation
data and in the 30 exact sample respectively. These banks are owned by the bank guarantee fund before they are publicly listed. All results remain unchanged if the banks are
included or not.
3.4.1
IPO allocations
Group one companies list their ownership records in the VPS database in good time
before the IPO. These companies also list on the OSE in the calendar month after the
IPO. For these companies the IPO allocations are completely accurate. There are 24,308
IPO allocations in these 30 IPOs. Some of these allocations are the same investors that
are allocated shares in more than one IPO. IPO allocations for group one companies are
obtained as the end of IPO month company ownership minus the ownership prior to the
IPO month ownership. The owners that are left are the IPO allocated investors.46
3.4.2
After-listing ownership
Group two companies list in the VPS database in good time before the IPO, but these
companies list on the OSE in the same calendar month as the IPO allocation month.
These companies have IPO allocations that include the actual IPO allocations and some
after-listing trading (150 companies out of 185). The IPO allocations for these companies
include the actual IPO allocations and between one and 30 days of after-listing trading.
IPO allocations for group two companies are calculated as the listing month (and IPO
allocation month) end of month company ownership minus the company ownership prior
to the listing month. The investor holdings that are left are the allocated investors and
the investors that have purchased shares in the period between the listing day and the
end of the listing month.47
46
Over the counter (OTC) trading in the IPO allocation month will be treated as IPO allocations. It
is, however, not expected that OTC trading will be a big issue because few investors are likely to trade
shares in this period. Few IPO allocated investors are likely to sell their allocation and potentially lose
out on the …rst day return. The average time between the IPO allocation and listing is less than two
weeks in the 30 IPOs.
47
Group two company IPO allocations includes some after-listing trading, but it is expected that most
of these allocations are actual IPO allocations. If past trading activity is important for current allocations,
51
Group three companies list in the VPS database in the same month as the IPO allocation month. These IPO allocations does not include any after-listing trading, but they
include existing owners who have not sold their shares (5 companies). IPO allocations for
these companies are calculated as the end of listing in the VPS month ownership (and
IPO allocation month ownership). Previous owners for these companies are not removed.
Group two and three companies are used in robustness testing.
3.4.3
Variable description
Company characteristics and the aggregate distribution of allocations between the di¤erent investor groups are given in Table 3. Market value is the total market value in USD
at the listing date of the IPO company. This is calculated as the number of outstanding
shares times the …rst day closing price. Book/Market is the book to market ratio of the
IPO company at the listing date. This is calculated as the book value of equity, after the
IPO, divided by the market value. O¤er price is the actual o¤er prices in USD reported
in the listing prospectuses or in the newspapers after the listing. VC dummy is a dummy
variable that takes the value of one for companies with venture capital baking. High-tech
dummy is a dummy variable that takes the value of one for IT -companies. Year dummy
are dummy variables for each of the 15 years in the sample period. Company dummy
are dummy variables for each of the 185 companies in the sample. Lead manager IPOs
is the number of times the lead manager has been lead in the sample period. There are
32 di¤erent mangers in the 185 IPOs. There is one big manager that underwrites 23 out
of the 185 IPOs. The ten biggest managers underwrite 144 of the 185 IPOs. There are
14 di¤erent managers that underwrite the 30 sample IPOs. Lead manager market share
is the market share of the lead manager. This is calculated by the percentage market
capitalization of the companies taken public out of total in the sample.
Investor characteristics, for the individual investors on the OSE in the period 1993 to
2007, are described in Table 4. The dependent variable (Allocated shares/shares issued) is
allocated shares to each investor divided by the total number of shares issued in the IPO.
This is the same dependent variable as in Reuter (2006). The all IPO sample of 190,504
IPO allocations (in 185 IPOs) is trimmed at 1% to 186,694 allocations. This has no e¤ect
on results. This is done to remove the most extreme IPO allocations. Commission is
the accumulated stock-trading commission generated by the investors in the two years
before the IPO allocation dates.48 Commission is calculated as the monthly portfolio
turnover times the share prices and a …xed percentage commission rate.49 Commission
this will be re‡ected in the data even if the data includes some after-listing trading. This is especially
true for the past buy-and-hold trading variables. Buy-and-hold investors will not sell their allocated
shares, so if past buy-and-hold behavior is important for future IPO allocations this will be observed in
the group two IPO allocations also. Group two IPO allocations can, however, not be used to reject that
‡ipping investors are not punished for selling shares early. This is because some of the ‡ipping investors
are lost in the way the group two IPO allocations are obtained.
48
Commissions are generated from monthly data and not daily data. Because of this it is possible that
commission trading takes place even if we are not able to …nd it in our data set. If commissions are
generated from daily buy and sell orders in the same shares, then we are not able to detect this. It is
also possible that some investors pay higher commission rates to get allocations. This should, however,
be discovered in auditing.
49
We construct two separate data sets. In the …rst data set we obtain the allocated shares in the IPOs.
The second data set is constructed by using the allocated shares in the …rst data set. For all allocated
investors we collect the portfolio of publicly traded shares on OSE. We collect the change in the monthly
portfolio ownership for each investor and this is multiplied with the correct market stock prices and the
standard commission rates. The average commission rate o¤ered by the 11 biggest internet share trading
52
is calculated as buy generated commissions only.50 Only commission by investors that
do at least one trade in each of the four six months periods before the IPO is included.
This has no e¤ect on results as most investors trade in all four periods. This is done
to remove investors that buy a large block of a company in one period without trading
in the other periods. Generated commission below the minimum rate is replaced by the
…xed minimum fee for one transaction ($15). The non-negative underpricing dummy is a
dummy variable that takes the value of one for all IPOs with zero or positive underpricing.
The variable commission*D is commission times the non-negative underpricing dummy.
This variable is used to test if generated commission is more important for allocations in
IPOs with a non-negative underpricing. Portfolio value is the portfolio value, in million
USD, for each allocated investor at 31.12.xx in the year before the IPO allocation date.
Previous IPOs is the accumulated number of past IPO participations by investors
divided by the accumulated IPO number in the sample. This is used to measure how
many IPOs, out of all possible, each investor has participated in. Previous buy-and-hold
is the accumulated previous number of times the allocated investor has been a buy-andhold investor divided by all previous IPO participations. This is the number of times,
out of all previous IPO participations, an investor has held some IPO allocated shares for
more than six months. Previous ‡ipping is the accumulated number of times an investor
has ‡ipped previous IPOs divided by all previous IPO participations. Flipping is when
all shares are sold within one month after a listing. This is the number of times, out
of all previous IPO participations, the investor has held all IPO allocated shares for less
than one month. Held cold IPO dummy is a dummy variable that takes the value of one
if the IPO has a positive underpricing and the investor is allocated shares in a previous
IPO with a negative underpricing. This variable is used to test if investors receive shares
in hot IPOs because they accepted allocations in past cold IPOs. The Previous IPOs,
Previous buy-and-hold, Previous ‡ipping and Held cold IPO dummy are calculated on all
185 IPOs when allocations of the 30 exact IPOs are studied separately. The variables are
also recalculated on a bank by bank basis when the most active bank is studied separately.
Financial institution dummy is a dummy variable that takes the value of one for investors
that are either Norwegian or foreign …nancial institutions.
3.5
Empirical results
The main empirical result is that there is a strong and robust relationship between stocktrading commission generated in the period before IPO allocations and the number of
shares allocated in IPOs. This is true for all investor types (retail and institutions). There
is no consistent relationship between previous IPO share holding periods and current
IPO allocations. There is also not more change in the pricing range of book-built IPOs
when more shares are allocated to …nancial institutions (or institutions in general). It is
concluded that IPO shares are allocated to the investors that generate the most stocktrading commission before the IPO allocations.
companies in Norway is 0.075%. Some investors are likely to buy shares directly from their broker at a
higher commission rate. We use the commission rate of 0.075% for all investors. The …nal number is the
monthly commissions paid by each investor. The commission generated in each speci…c IPO is removed.
50
Sell generated commission variables are also related to IPO allocations. Only buy generated commission in the 24 month period before the IPOs is used as commission This is to avoid any issues related
to sell generated commissions from rebalancing portfolios before IPOs. The results are the same when
di¤erent measures of commission are used.
53
3.5.1
The rent seeking view of IPO allocations
From Table 5 it can be seen that there is a positive relationship between generated stocktrading commission and IPO allocations in the 30 IPO sample (group one companies).
IPO allocated shares, scaled by total shares issued in the IPOs, is regressed on the accumulated stock-trading commission in the 24 month period before the IPO allocation and a
set of control variables. The level of generated commission is highly related to the number
of allocated shares. This result control for investor size (measured by investor portfolio
value), investor past trading behavior (past buy-and-hold, past ‡ipping, past IPO participations and past accepted cold IPO allocations), investor type (…nancial institution or
not), company …xed e¤ects, year …xed e¤ects and company speci…c variables.
The results are statistically signi…cant even if the sample size in all regressions is
very large. All signi…cance levels are correspondingly large to the sample sizes.51 The
results are also economically signi…cant. The point estimate for stock-trading commission
is about 0.1 for retail investors (and 0.05 for institutional investors). If stock-trading
commission is increased by 10% for retail investors, the allocation percentage is increased
with one percent, see Wooldridge (2003).
Stock-trading commission is also calculated for only IPOs with a non-negative underpricing. E.g. Stock-trading commission is multiplied with an interaction dummy variable
that takes the value of one for IPOs with a non-negative underpricing. This new variable,
Commission*D, is used to test if IPO shares are mainly allocated to investors with a high
level of commission when IPOs are underpriced. The Commission*D is not always signi…cant. This means that high commission investors are allocated more shares in general and
not only in underpriced IPOs.52 Investors that generate high commission rates are likely
to be preferred when they apply for IPO shares regardless of the expected underpricing.
It is likely that high stock-trading commission will place investors on the A, B and C
lists of the banks. When investors from these lists apply for shares, they are likely to be
allocated shares. It seems unlikely that investment banks will discourage investors from
accepting IPO allocations even if the issues may fall in price after the listing (even if the
investors are from the A, B or C list). IPO allocations are also studied on the sub groups
only retail investors and only institutional investors. The results remain unchanged.
In Table 6 IPO allocations in group two and three are also included in the analysis.
From Table 6 it can be seen that there is a positive relationship between generated stocktrading commission and IPO allocations for all IPOs. The results remain unchanged
when the IPOs that might be contaminated by after-listing trading are included in the
analysis. The number of IPO participations by each investor is also regressed on the
stock-trading commission. The results are highly signi…cant and explanatory. There is
a strong relationship between generated stock-trading commission and the number of
investor IPO participations. This means that investors that generate more commission
are also participating in more IPOs than investors that generate less commission (not
reported).
51
Even if the sample sizes are reduced by a large factor and the corresponding t –statistics are reduced
by the square root of this factor, the …ndings are still signi…cant; see Kecskes, Michaely and Womack,
2010.
52
Investors are, however, not likely to always know if IPOs will be under or overpriced. Investors are
likely to apply for the shares they want. It is not certain that it is always the expected underpricing that
drives the IPO application. If this was the case, there would be no IPO applicants in overpriced issues.
Investors are likely to apply for shares in some issues that will fall in price after the listing. It is also
likely that investment banks will allocate to investors that generate high commission rates when they
apply for IPO shares.
54
3.5.2
The pitchbook view of IPO allocations
The pitchbook view of IPO allocations is controlled for by including the past number of
times investors have been buy-and-hold or ‡ipping, out of past IPO participations, in all
regressions. The pitchbook view argue that IPO shares are allocated to investors that are
expected to be long term buy-and-hold investors. Buy-and-hold investors will create long
term price stabilization of the IPO shares. Long term buy-and-hold investors can develop
a relationship with investment banks and then be rewarded with future IPO allocations in
return for previous buy-and-hold services. The long term investors will hold their shares
to avoid being blacklisted in future IPOs. From Table 5 (the exact IPO allocations) it
can be seen that the number of times an investor has been buy-and-hold in the past is
negatively related or unrelated to current IPO allocations. For retail investors there is
actually a positive relationship between past ‡ipping activity and current IPO allocations.
In Table 6 (all IPO allocations) the exact same results appear. This indicates that there
is no or limited IPO allocations to buy-and-hold investors.
The 30 exact IPOs are underwritten by several di¤erent investment banks. The same is
true when all 185 IPOs are studied together. It is possible that this is causing the results.
In many listing prospectuses there are two to three participating investment banks. It
is then assumed that the bank that is mentioned …rst on the left side on the cover page
of the listing prospectus is the lead investment bank. The single most active bank is the
lead underwriter in 23 (out of 185) IPOs in the sample period. To study the pitchbook
view it is necessary to also study this sample separately.53
From Table 7 it can be seen that there is not allocations to buy-and-hold investors
for the most active bank either. There is no signi…cant relationship between previous
holding periods and future IPO allocations when only the single most active bank is
studied separately. This is the exact same result as in Table 5 and Table 6. In Table
7 (regression 2 and 4) investors are also classi…ed as only buy-and-hold investors if they
have never been ‡ipping investors in the past. (E.g. An investors that has a positive
value for ‡ipping in the past will take a zero value for the buy-and-hold by de…nition).
The results remain unchanged. We are not able to detect a positive relationship between
long holding periods and IPO allocations. It is concluded that the pitchbook view is not
a likely reason behind IPO allocations.
3.5.3
The academic view of IPO allocations
The academic view of IPO allocations is controlled for by including a dummy variable
that takes the value of one for the expected pricing investors (…nancial institutions) in
all regressions. In Table 8 the academic view is tested more directly. In Table 8 the
percentage price revision in book-built IPOs is regressed on the allocation percentage
to …nancial institutions and a set of control variables. This is similar to Ljungqvist and
53
Most of the IPOs of the very active banks are of the group two IPO allocations. This means that
these IPO allocations includes from one to 30 days of aftermarket trading. We argue that this is of smaller
importance when we study the pitchbook view, as this view argues that the investors hold their shares
in the long run. The IPO allocations from group two will include the long term buy-and-hold investors
if they are really buy-and-hold investors. In the sample it is observed if investors that hold shares in the
long run are allocated more shares in future IPOs. The only problem is that some investors may buy
shares after the listing and then hold these shares in the long run. These investors will be treated as
buy-and-hold investors in the data, but they will not be awarded with future shares. It is expected that
there will be less of this type of investors than actual buy-and-hold if buy-and-hold is an accurate view.
Group two IPOs allocations should therefore detect any IPO allocations in return for past buy-and-hold.
55
Wilhelm (2002) that regress the percentage price revision on the percentage IPO allocation
between institutional and retail investors. Ljungqvist and Wilhelm (2002) show that IPO
allocations to institutional investors have a signi…cant impact on price revisions. From
Table 8 it can be seen that IPO allocations to …nancial institutions have no impact on
the percentage price revision in our sample. IPO allocations to …nancial institutions is
actually negatively related to changes in the o¤er price in the book-building period. This
indicates that there is no price information collected from …nancial institutions. The same
result is found when total allocations to institutional investors is investigated separately.
The sample size is, however, very low with only 71 book-built IPOs in the sample.
3.5.4
Robustness
As robustness we also test if there is a relationship between share ownership right after
new listings and generated stock-trading commission for companies with no IPO. There
are 89 companies with a su¢ cient share spread and equity value to list directly at the
OSE without conducting an IPO …rst. These 89 straight listings are used as a comparable
sample. From Table 9 it can be seen that there is a relationship between stock-trading
commission and share holdings after the listing in non-IPO companies also, but that this
relationship is weaker than for IPOs. Investor stock-trading commission is multiplied
with a dummy variable that takes the value of one for the IPO companies. After-listing
ownership for both IPO companies and non-IPO companies is regressed on stock-trading
commission. The coe¢ cient for the relation between stock-trading commission and IPO
allocations is many times greater in IPOs than in non-IPOs. It is concluded that the
relationship between after-listing share ownership and stock-trading commission is driven
by IPO allocations. In Table 9 the IPO allocations are also trimmed at 1%.
In Table 10 the allocated investors are matched one for one with a non allocated
investor in a Tobit regression. These IPO allocations are also trimmed at the 1% level. In
total 9,498 (out of 24,308 investors) are …rst observed in the data with their IPO allocation.
These investors have no previous stock-trading commission, past trading or portfolio size.
The remaining investors are matched one for one with a non-allocated investor with no
IPO participations in the last 12 months on investor type, investor country and number of
shares in the portfolio. Among these investors the investor with the closest portfolio size
is selected as the matching investor. The allocation percentage is then regressed on stocktrading commission and the control variables in a Tobit regression. The matching investors
take the value of zero for (Allocated shares/shares issued) because they are not allocated
IPO shares. We do not know if the matching investors applied for shares or not, but
the regressions in Table 10 show that the matching investors generated less stock-trading
commission than the allocated investors before the allocations. This further indicates
that the stock-trading commission was generated to receive IPO allocations. The level of
stock-trading commission is highly related to IPO allocations. This show that investors
that are allocated IPO shares generate more stock-trading commission than investors that
are not allocated IPO shares (matching on investor type, investor country and portfolio
value).
3.6
Conclusion
The main …nding of the paper is that there is a strong and robust relationship between
stock-trading commission generated by investors before IPO allocations and the number
56
of shares allocated in IPOs. The investors that generate the most stock-trading commission are also allocated the most IPO shares. This result is consistent for all investor
types, in all IPOs and in all sample years. This result control for the portfolio value of the
allocated investors, past trading behavior (the pitchbook view) and investor types (information gathering view). The result is also robust to companies that do not conduct IPOs
and investors who are not allocated IPO shares. The meaning of this result is that there
is a strong indication that investors are able to buy IPO allocations with stock-trading
commission. The investors that are the most pro…table clients, for the investment banks,
are rewarded with the most IPO allocations. It can be argued that investors that trade
more are also likely to apply for more IPO shares. The IPOs are, however, on average
highly oversubscribed, so some investors are given more IPO allocations than other investors. We show that the investors that generate the most stock-trading commission are
allocated the IPO shares.
There is no evidence that support the information gathering view. There is not a
bigger change in the percentage price revision from the midpoint in the pricing range to
the o¤er price when …nancial institutions, or institutions in general, are allocated more
shares. The sample size for the information gathering view is, however, too small to
make any meaningful inferences. There is also no support for the pitchbook view. There
is no detectable relationship between past IPO share holding periods and current IPO
allocations. Investors that hold shares in the long run are not allocated more future IPO
shares. This is also true when IPOs are studied on a bank by bank basis. Some investors
are also able to obtain IPO allocations even if they repeatedly ‡ip their shares.
The conclusion is that more IPO shares are allocated to investors that generate more
stock-trading commission. IPO shares are allocated based on the rent seeking view of IPO
allocations. This …nding is consistent with Reuter (2006) and Nimalendran, Ritter and
Zhang (2007) in that IPO shares are allocated in return for stock-trading commission. A
main contribution to the previous literature is that we are able to combine all existing
views on IPO allocations in the same data set. We rank the views as the most to the least
important view. This has not been possible to do before. There is strong evidence supporting the rent seeking view. There is no evidence supporting the academic view or the
pitchbook view when controlling for the rent seeking view. There are also some practical
implications of the study. Investors should be able to increase IPO allocations by increasing their stock-trading commission before IPOs. Investors can also be able to increase IPO
allocations by directing trades to investment banks that underwrite many IPOs. There
should also be more regulatory investigations into IPO allocation practices. It seems like
the exchange of IPO allocations with stock-trading commission is a widespread practice.
There are some limitations to the study. It is not observed that stock-trading commission is paid from the allocated investor to the investment bank. It is only observed
that the commission is generated. Commission is also calculated based on monthly data.
This is likely to underestimates commission. For future research it would be interesting
to study stock-trading commission that is paid directly to the investment bank for all the
allocated investors on a daily basis.
57
References
[1] Aggarwal, Reena, 2002, Allocation of initial public o¤erings and ‡ipping activity,
Journal of Financial Economics 68, 111-135
[2] Benveniste, Lawrence M. and Paul A. Spindt, 1989, How investment bankers determine
the o¤er price and allocation of new issues, Journal of Financial Economics 24, 343-361.
[3] Binay, Murat M., Vladimir A. Gatchev and Christo A. Pirinsky, 2006, The role of
Underwriter-Investor Relationships in the IPO Process, The Journal of Financial and
Quantitative analysis 42, 785-809.
[4] Bubna, Amit and Nagpurnanand R. Prabhala, 2007, When Bookbuilding
Meets IPOs, AFA 2008 New Orleans Meetings Paper Available at SSRN:
http://ssrn.com/abstract=972757
[5] Cli¤, Michael T. and David J. Denis, 2004, Do Initial Public O¤ering Firms Purchase
Analyst Coverage with Underpricing?, Journal of Finance 6, 2871-2901.
[6] Cornelli, Francesca and David Goldreich, 2001, Bookbuilding and strategic allocation,
Journal of Finance 56, 2337-2369.
[7] Cornelli, Francesca and David Goldreich, 2003, Bookbuilding: How informative is the
order book?, Journal of Finance 58, 1415-1443.
[8] Derrien, François and Kent L. Womack, 2003, Auctions vs. Bookbuilding and the
Control of Underpricing in Hot IPO Markets, The Review of Financial Studies 1, 3161.
[9] Eckbo, Espen B. and Øyvind Norli, 2005, Liquidity risk, leverage and long-run IPO
returns, Journal of Corporate Finance 11, 1-35.
[10] Fjesme, Sturla Lyngnes, 2011, Laddering in Initial Public O¤ering Allocations, Working paper, Norwegian Business School (BI).
[11] Hao, Qing (Grace), 2007, Laddering in Initial Public O¤erings, Journal of Financial
Economics, 85, 102-122
[12] Jenkinson, Tim and Howard Jones, 2004, Bids and Allocations in European IPO
Bookbuilding, Journal of Finance 59, 2309-2338.
[13] Kecskes, Ambrus, Roni Michaely and Kent Womack, 2010, What drives the Value of
Analysts Recommendations: Earnings Estimates or Discount Rate Estimates?, Working paper Cornell University.
[14] Krigman, Laurie, Wayne H. Shaw and Kent L. Womack, 1999, The persistence of
IPO mispricing and the predictive power of ‡ipping, Journal of Finance 54, 1015-1044.
[15] Liu, Xiaoding and Jay R. Ritter, 2009, The economic consequences of IPO spinning,
Forthcoming in Review of Financial Studies.
[16] Ljungqvist, Alexander P. and William J. Wilhelm, 2002, IPO allocations: discriminatory or discretionary?, Journal of Financial Economics 65,167-201.
58
[17] Loughran, Tim and, Jay Ritter, 2004, Why has IPO underpricing changed over time?,
Financial Management 33, 5-37.
[18] Nimalendran, M., Jay R. Ritter, and Donghang Zhang, 2007, Do today’s trades a¤ect
tomorrows IPO allocations?, Journal of Financial Economics 84, 87-109.
[19] Pulliam, Susan and Randall Smith, Linux Deal is focus of IPO-Commission Probe,
The Wall Street Journal, December 12, 2000.
[20] Reuter, Jonathan, 2006, Are IPO allocations for sale? Evidence from Mutual Funds,
Journal of Finance 61, 2289-2324.
[21] Ritter, Jay, 1991, The long run performance of Initial Public O¤erings, Journal of
Finance 46, 3-27.
[22] — — , Jay R. and Ivo Welch, 2002, A review of IPO activity, pricing and allocations,
Journal of Finance 57, 1795-1828.
[23] — — , Jay R., 2003, Di¤erences between European and American IPO markets, European Financial Management 9, 421-434.
[24] Rogers, W. H.,1993, Regression standard errors in clustered samples, Stata Technical
Bulletin 13, 19-23. Reprinted in Stata Technical Bulletin Reprints 3, 88–94.
[25] White, Halbert, 1980, A heteroskedastic-consistent covariance matrix estimator and
a direct test of heteroscedasticity, Econometrica 48, 817-838
[26] Wooldridge, Je¤rey M., 2003, Introductory Econometrics A Modern Approach
(Tsinghua, Tsinghua University Press, South-Western College Publishing Thompson
Learning).
59
Table 1
Related Empirical Papers
Rent seeking view
Reuter (2006)
Positive relationship between commission and
holdings of IPO shares after new listings
Nimalendran, Ritter and Zhang (2006)
Positive relationship between money on table
and trading volume in liquid shares
Liu and Ritter (2010)
Find evidence of IPO spinning
Cli¤ and Denis (2004)
Find evidence of analyst con‡ict of interest
Academic view
Cornelli and Goldreich (2001)
Regularly participating, large bid and domestic
participants are favored in allocations
Cornelli and Goldreich (2003)
Bids from large, frequent bidders that
include a limit price a¤ect the issue price
Ljungqvist and Wilhelm (2002)
Increased institutional allocations results in
higher o¤er price deviations from the midpoints
of the book-building pricing ranges
Binay, Gatchev and Pirinsky (2007)
Underwriters favor institutions they
have previously worked with
Bubna and Prabhala (2007)
Book-building and discretion in allocation
enhances pre-market price discovery
Jenkinson and Jones (2004)
Find evidence against the
academic view
Pitchbook view
Aggarwal (2002)
Institutions ‡ip more than retail investors
(Evidence against the pitchbook view)
Jenkinson and Jones (2004)
Find evidence in favor
of the pitchbook view
60
Table 2
The Number of Initial Public O¤erings on the Oslo Stock Exchange
The column labeled "IPOs" lists the number of Initial Public O¤erings on the Oslo Stock Exchange in
the sample period. The column labeled "Data" indicates the IPOs with allocation data. The column labeled
"Prospectus" lists the IPOs where we have been able to locate the listing prospectus. The column labeled
"Sample" lists the 30 sample IPOs. The columns labeled "Value of shares" list the annually aggregate million
USD values of shares sold in the IPOs with listing prospectus. "All", "New" and "Secondary" indicates
the value of all shares, only newly issued shares and shares sold by existing shareholders respectively. The
columns labeled "P" and "S" are the annual aggregated USD million value of shares sold in the IPOs
with prospectuses and in the 30 IPO sample respectively. Value of shares sold is reported in USD using a
USD/NOK exchange rate of 0.1792. The sample period is January 1993 through September 2007.
Number of IPOs
Value of shares USD
All
Year
IPOs
Data
Prospectus
Sample
P
S
541
New
P
Secondary
S
P
539
S
1993
11
9
7
1994
18
12
11
5
626
392
218
142
409
1995
18
14
11
3
516
47
113
47
403
1996
14
12
8
3
146
89
65
9
81
80
1997
30
26
20
9
988
229
516
20
472
208
1998
15
11
11
2
233
95
190
94
43
1
1999
4
4
4
2000
12
12
11
2001
4
4
4
2002
2
2
2
60
2
839
31
112
183
2
70
2
765
29
90
166
70
64
74
64
6
2
2
2
83
78
5
2004
14
14
14
1,605
1,319
287
2005
32
31
31
2006
18
17
17
2007
16
15
15
1
931
20
Total
210
185
168
30
11,621
1,130
2,069
61
2,730
61
594
22
17
2003
3
250
51
1,475
537
20
395
7,431
550
4,190
2,237
6
11
493
580
Table 3
Summary Statistics of Firms Going Public on the Oslo Stock Exchange
Panel A reports the average percentage distributions of the IPO allocations. The exact sample includes
the 30 IPOs with no after-listing trading. The total sample includes all 185 IPOs with IPO allocations.
Panel B reports the IPO company characteristics for the 185 and the 30 companies. "Market value (Mill
USD)" is the number of shares outstanding on the listing day times the …rst day closing price. "O¤er price"
is the USD IPO price in the listing prospectuses. "Book/Market" is the book value of equity after the IPO
divided by the market value on the listing day. "VC backed dummy" is a dummy variable that takes the
value of one if the company has venture capital backing. "High-tech dummy" is a dummy variable that
takes the value of one for IT companies. "% change in pricing range" is change from the midpoint in the
pricing range to the o¤er price in book-building IPOs. "Lead manager IPOs" is the average number of
times the lead manager has been lead in the total 185 sample period. "Lead manager market share" is
the market share of the lead manager. This is calculated by the percentage market capitalization of the
companies taken public out of total in the sample. USD values are calculated from a USD/NOK exchange
rate of 0.1792. IPO allocations are trimmed at 1%.
Exact allocations
Variable
N
Mean
Std.Dev
Full Sample
Median
N
Mean
Std.Dev
Median
A. Average Percent Allocation
Retail %
30
39.9%
19.5%
38.3%
185
41.9%
23.6%
40.4%
Norwegian non …nancial %
30
30.3%
16.6%
30.2%
185
24.5%
14.8%
23.2%
Norwegian …nancial %
30
16.4%
16.6%
10.9%
185
13.9%
12.2%
12.3%
Foreign %
30
7.9%
8.7%
3.7%
185
15.3%
17.5%
6.7%
Other %
30
5.5%
5.5%
3.2%
185
4.4%
5.2%
1.2%
Market value (Mill USD)
30
$128
$135
$98.2
185
$291.2
$841.2
$101.4
O¤er price USD
30
$11.4
$7.8
$8.2
185
$9.1
$6.9
$7.2
Book/Market
30
0.77
1.4
0.29
185
0.63
0.82
0.42
VC backed dummy
30
0.13
0.35
0
185
0.16
0.37
0
High-tech dummy
30
0.07
0.25
0
185
0.11
0.32
0
% change pricing range
30
0
0
0
71
8.3%
8.2%
7.3%
Lead manager IPOs
30
9.8
7.5
7
185
6.3
7.6
3
Lead manager market share
30
4.6%
11.9%
1.3%
185
3.1%
8.2%
0.5%
B. IPO Characteristics
62
Table 4
Summary Statistics on IPO Allocations and on Investors Trading
This table reports the summary statistics for the individual trading prior to the 30 sample IPOs and
all 185 IPOs on the Oslo Stock Exchange in the period 1993 to 2007. Panel A reports the percentage share
distribution between the investor groups. Panel B reports the investor characteristics. "Commission" is the
accumulated commission generated in USD by the investors in the two years before the IPO allocation date.
"Non negative underpricing dummy" takes the value of one for all IPOs with zero or positive underpricing.
"Commission *D" is commission times the Non-negative underpricing dummy. "Portfolio value" is the
portfolio value in million USD for each allocated investor at 31.12.xx in the year before the IPO allocation
date. "Previous IPOs" is the accumulated previous IPO participations by the investors divided by the
accumulated IPO number in the sample. "Previous buy-and-hold" is the accumulated previous number of
times the allocated investor has been a buy and hold investor as a percent of all previous IPO participations.
This is the number of times the investor has held some IPO allocated shares for more then six months in
previous IPOs. "Previous ‡ipping" is the accumulated number of times the investor have ‡ipped previous
IPOs as a percent of all previous IPO participations before the IPO allocation. Flipping is when all shares
are sold within one month of the listing. "Held cold IPO dummy" takes the value of one if the IPO has
a positive underpricing and the investor is allocated shares in a previous IPO with negative underpricing.
USD values are calculated from a USD/NOK exchange rate of 0.1792. IPO allocations are trimmed at 1%.
Exact Sample 30 IPOs
N
Mean
Std.Dev
Full Sample 185 IPOs
Median
N
Mean
Std.Dev
Median
A. Average Allocation
All %
24,308
0.06%
0.17%
0.01%
186,692
0.04%
0.14%
0.004%
Retail %
19,999
0.03%
0.098%
0.01%
157,942
0.02%
0.08%
0.003%
Norwegian non …nancial %
2,336
0.18%
0.33%
0.04%
14,310
0.12%
0.26%
0.02%
Norwegian …nancial %
524
0.39%
0.42%
0.21%
3,377
0.3%
0.41%
0.11%
Foreigners %
937
0.1%
0.25%
0.03%
7,073
0.15%
0.32%
0.02%
Others %
512
0.12%
0.25%
0.03%
3,990
0.07%
0.18%
0.01%
B. Investor Characteristics
Commission USD
24,308
$2,328
$38,680
0
186,692
$5,406
$87,915
0
Non-neg. underpricing d.
24,308
0.73
0.44
1
186,692
0.86
0.35
1
Commission *D
24,308
$2,030
$37,974
0
186,692
$4,133
$74,132
0
Portfolio value million USD
24,308
$2.01
$37.32
0
186,692
$3.43
$70.44
$0.003
Previous IPOs
24,308
0.05
0.05
0.04
186,692
0.04
0.05
0.02
Previous Buy-and-hold
24,308
0.19
0.36
0
186,692
0.21
0.37
0
Previous Flipping
24,308
0.12
0.28
0
186,692
0.09
0.25
0
Held cold IPO dummy
24,308
0.1
0.3
0
186,692
0.12
0.33
0
63
Table 5
IPO Allocations and Generated Commission for the 30 Sample IPOs
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with the number of allocated shares
divided by the total number of shares issued in the IPO as the dependent variable. This is a standard OLS
model. Only the 30 IPOs with exact allocations in the sample period September 1993 to January 2007
are included. All variables are as described in Table 3 and Table 4. Regression 1 includes all investors.
Regression 2 includes only retail investors. Regression 3 includes only institutional investors. In Regression
4 and 5 the investors with zero in commission in the 24 month period before the new listings are dropped.
In Regression 6 the savings banks (7) are removed. IPO allocations are trimmed at 1%.
Log (Allocated shares/shares issued) %
Intercept
Log (commission)
Log (commission) *D
Non-negative underpricing D.
Log (portfolio value)
Previous IPOs
Previous buy-and-hold
Previous ‡ipping
Held cold IPO dummy
Financial institution dummy
Reg 1
Reg 2
Reg 3
Reg 4
Reg 5
Reg 6
4.356
-16.1345
2.5336
-0.9762
-3.2502
5.0669
(19.3)
(-48.0)
(8.6)
(-2.5)
(-8.3)
(48.5)
0.0949
0.0961
0.0539
0.081
0.0487
0.0962
(5.7)
(5.8)
(3.2)
(7.9)
(3.4)
(7.4)
-0.0714
-0.077
-0.0277
-0.0561
-0.0237
-0.0522
(-3.6)
(-3.5)
(-1.5)
(-4.0)
(-1.4)
(-2.8)
0.6562
2.7586
-1.1431
0.3261
-0.1382
-3.3122
(18.5)
(3.5)
(-21.7)
(5.9)
(-1.6)
(-75.9)
0.0513
0.0327
0.0668
0.035
0.0768
0.0404
(4.3)
(3.5)
(5.8)
(4.1)
(5.9)
(3.5)
0.8032
-0.321
0.8488
-0.6907
0.4453
-0.1461
(1.0)
(-0.7)
(0.9)
(-1.8)
(0.4)
(-0.2)
-0.1286
-0.0798
-0.03
-0.0711
-0.0119
-0.1544
(-2.7)
(-2.3)
(-0.4)
(-1.6)
(-0.1)
(-3.1)
0.1446
0.2016
-0.2193
0.2568
-0.0388
0.1295
(2.4)
(3.5)
(-1.7)
(4.3)
(-0.4)
(2.1)
0.0788
0.0087
-0.0106
-0.0005
0.0418
0.0506
(1.2)
(0.2)
(-0.1)
(-0.0)
(0.5)
(0.6)
1.8786
dropped
0.5319
dropped
0.502
1.1784
(3.6)
(6.3)
-0.0861
-0.5397
(10.2)
Log (market value)
BV / MV equity
O¤er price
VC backed dummy
High-tech dummy
-0.4328
(3.9)
0.4991
-0.3657
-0.2573
(-29.8)
(30.2)
(-20.5)
(-12.0)
(-4.8)
(-59.1)
0.316
0.5386
0.3979
0.3877
0.4329
dropped
(28.1)
(62.6)
(51.7)
(83.1)
(32.3)
0.0069
-0.0103
0.0001
-0.0034
0.0063
0.0084
(14.0)
(-35.3)
(0.3)
(-33.8)
(13.5)
(24.1)
1.6586
0.69
0.7532
-0.4467
0.3223
5.5484
(16.9)
(9.6)
(12.7)
(-8.5)
(2.7)
(39.3)
dropped
4.433
-1.7555
0.1653
dropped
-7.8126
(201.3)
(-17.5)
(2.5)
yes
yes
yes
yes
yes
yes
Observations
24,308
19,999
4,309
10,207
2,876
16,593
Adjusted R -squared
42.4%
49.1%
34.6%
42.5%
31.5%
42%
All
Retail
Institution
Retail
Institution
All
Year and Company dummy
Investor group
64
(-77.9)
Table 6
IPO Allocations and Generated Commission for All 185 IPOs
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with the number of allocated shares
divided by the total number of shares issued in the IPO as the dependent variable. This is a standard OLS
model. All 185 IPOs in the sample period September 1993 to January 2007 are included. All variables are
as described in Table 3 and Table 4. Regression 1 includes all investors. Regression 2 includes only retail
investors. Regression 3 includes only institutional investors. In Regression 4 and 5 the investors with zero
in commission in the 24 month period before the new listings are dropped. In Regression 6 the savings
banks (14) are removed. IPO allocations are trimmed at 1%.
Log (Allocated shares/shares issued) %
Intercept
Log (commission)
Log (commission) *D
Non-negative underpricing D.
Log (portfolio value)
Previous IPOs
Reg 1
Reg 2
Reg 3
Reg 4
Reg 5
Reg 6
-4.185
-14.8485
-4.9007
-12.9069
-0.0259
-8.818
(-29.8)
(-85.7)
(-29.1)
(-141.4)
(-0.1)
(-40.7)
0.0679
0.0384
0.0608
0.0392
0.0612
0.0674
(6.1)
(4.3)
(5.3)
(6.3)
(5.7)
(5.9)
0.014
0.0079
0.02359
0.0031
0.0164
0.0187
(0.6)
(0.5)
(1.1)
(0.3)
(1.0)
(0.8)
-4.1829
-1.2985
-0.9574
-1.2387
-0.4123
-1.14076
(-70.8)
(-24.6)
(-8.0)
(-36.4)
(-4.2)
(-12.5)
0.042
0.0285
0.057
0.0296
0.0678
0.0403
(13.4)
(9.7)
(13.3)
(9.7)
(11.6)
(13.8)
-1.1269
-1.067
-0.6539
-1.1515
-0.6968
-1.3911
(-1.6)
(-2.5)
(-0.9)
(-3.7)
(-1.5)
(-2.0)
Previous buy-and-hold
0.0396
0.115
-0.1148
0.0445
-0.1463
0.0424
(0.3)
(1.0)
(-2.0)
(0.5)
(-3.9)
(0.3)
Previous ‡ipping
0.2679
0.3299
-0.1543
0.3323
-0.1023
0.272
(3.0)
(4.2)
(-1.7)
(5.4)
(-1.3)
(2.9)
0.0805
0.04
0.0486
0.0518
0.0673
0.0877
(2.4)
(1.3)
(1.0)
(2.0)
(1.4)
(2.4)
1.1915
dropped
0.6573
dropped
0.6003
1.8942
(8.3)
(16.2)
0.1266
Held cold IPO dummy
Financial institution dummy
(18.2)
Log (market value)
BV / MV equity
O¤er price
VC backed dummy
High-tech dummy
Year and Company dummy
Observations
Adjusted R -squared
Investor group
0.0987
(8.0)
0.4584
-0.0064
0.4066
-0.0336
(21.0)
(48.0)
(-2.6)
(126.7)
(-12.6)
(15.3)
-0.0094
0.0979
0.1429
0.0984
0.1518
2.1588
(-0.9)
(8.2)
(22.1)
(10.5)
(12.2)
(31.2)
0.0055
-0.0138
0.0085
-0.0125
-0.0025
-0.001
(51.6)
(-39.3)
(40.7)
(-76.0)
(-6.5)
(-5.8)
1.6097
-1.9087
-0.2361
-2.2017
-0.6031
-0.3591
(18.5)
(-322.9)
(-6.0)
(-258.2)
(-56.1)
(-23.4)
-0.2622
2.2149
-1.0701
2.4697
-0.0991
0.2558
(-3.5)
(69.0)
(-11.4)
(66.8)
(-2.9)
(8.1)
yes
yes
yes
yes
yes
yes
186,692
157,942
28,750
94,362
21,195
175,382
79.5%
84.2%
53.4%
83.3%
48.6%
79.5%
All
Retail
Institution
Retail
Institution
All
65
Table 7
IPO Allocations to Buy-And-Hold Investors
This table reports the coe¢ cients and Clustered (Rogers, 1993) heteroscedasticity consistent t-statistics
in parentheses for the regressions with the number of allocated shares divided by the total number of shares
issued in the IPO as the dependent variable. All variables are as described in Table 3 and Table 4. All
regressions are standard OLS models, and the sample period is from January 1993 to September 2007. Only
the 23 IPOs by the most active bank in the sample period is investigated. Previous trading variables are
only in past IPOs by the most active bank. Regression 1 and 2 includes all IPO allocations. Regression
3 and 4 includes only allocation in the 13 underpriced (hot) IPOs. Regression 2 and 4 includes only past
buy-and-hold for investors who have never been ‡ipping investors before. IPO allocations are trimmed at
1%.
(Allocated shares/shares issued) %
Reg 1
Reg 2
Reg 3
Reg 4
Intercept
0.0668
0.0668
0.0317
0.0315
(58.3)
(57.7)
(26.9)
(26.1)
Log (commission)
0.0038
0.0038
0.0007
0.0007
(8.5)
(8.9)
(3.5)
(3.4)
-0.0031
-0.0031
(-6.1)
(-6.3)
-0.0036
-0.0004
(-0.2)
(-0.2)
0.0002
0.0002
0.0002
0.0002
Log (commission) *D
Non-negative underpricing D.
Log (portfolio value)
Previous IPOs
Previous buy-and-hold
Previous ‡ipping
Held cold IPO dummy
Financial institution dummy
Log (market value)
BV / MV equity
O¤er price
VC backed dummy
High-tech dummy
Year dummy and Company dummy
Observations
Adjusted R -squared
Included IPOs
66
(3.3)
(3.4)
(3.1)
(3.2)
-0.0016
0.0013
-0.0004
0.001
(-0.6)
(0.4)
(-0.2)
(0.3)
0.0003
-0.0004
00005
-0.0002
(0.4)
(-0.4)
(0.7)
(-0.2)
0.0034
0.001
(1.3)
(0.7)
0.001
0.0012
0,002
0.0022
(0.5)
(0.7)
(1.1)
(1.2)
0.0315
0.0314
0.0285
0.0285
(4.2)
(4.3)
(4.0)
(4.0)
-0.0025
-0.0025
-0.0005
-0.0005
(-15.0)
(-14.6)
(-8.3)
(-8.4)
0.0002
0.0001
0.0002
0.0001
(0.6)
(0.3)
(0.3)
(0.2)
-0.002
-0.0002
-0.0003
-0.0003
(-16.8)
(-16.3)
(-65.2)
(-63.6)
-0.0283
-0.0284
dropped
dropped
(-40.8)
(-43.9)
0.0101
0.0101
0.0068
0.007
(20.7)
(20.1)
(10.6)
(10.6)
yes
yes
yes
yes
67,795
67,795
63,539
63,539
33%
33%
20.4%
20.4%
22
22
13
13
Table 8
IPO Allocations in Return for Pricing Information
This table reports the coe¢ cients and White (1980) heteroscedasticity consistent t -statistics in parentheses for the regressions with the absolute percentage change in the price revision as the dependent variable.
This is a standard OLS model, and all book-built IPOs in the sample period from January 1993 to September 2007 are included. All variables are described in Table 3 and Table 4. Regression 1 includes "Financial
institution allocation %" in all book-built IPOs. Regression 2 includes "Institutional allocation %" in all
book-built IPOs.
Absolute % price revision
Reg 1
Reg 2
Intercept
17.7888
11.9459
(2.3)
(1.1)
Financial institution allocation %
-0.1046
(-2.0)
Institutional allocation %
-0.0022
(-0.0)
Log (market value)
BV / MV equity
O¤er price
-0.472
-0.2403
(-1.1)
(-0.5)
-1.3576
-1.4011
(-0.5)
(-0.5)
0.016
0.0008
(0.5)
(0.0)
VC backed dummy
3.6374
4.1113
(1.5)
(1.6)
High-tech dummy
1.2246
0.2923
(0.5)
(0.1)
Observations
Adjusted R -squared
67
71
71
5.8%
0.4%
Table 9
Commission and Share holdings of Newly Listed Companies with No IPO
This table report the coe¢ cients and Rogers (1993) clustered (on company) heteroscedasticity consistent t-statistics in parentheses for the regressions with the shares owned per investor at the end of the
listing month divided by outstanding shares in the listed company as the dependent variable. There are 89
companies that list with no o¤ering to new shareholders. The regression is a standard OLS model, and the
sample period is from January 1993 to September 2007. Regression 1 includes allocations and after-listing
ownership in all 185 IPO companies and all 89 companies with no IPO. The dummy IPO takes that value
of one for all investors in the 185 IPOs and zero for all the investors in the 89 non-IPO companies. "Log
(commission) * Dummy IPO" is investor commission in all IPOs and zero commission in all 89 non-IPOs.
IPO allocations and after-listing ownership are trimmed at 1%.
Variables
(Shares holdings/shares outstanding) %
Reg 1
Intercept
0.1697
(7.0)
Commission
0.00000
(7.3)
Commission * Dummy IPO
0.0048
(4.7)
Dummy IPO
0.1679
(370.1)
Portfolio value
0.0000
Previous IPOs
0.1208
(3.5)
(4.3)
Previous buy-and-hold
-0.00062
(-5.5)
Previous ‡ipping
0.005
(2.6)
Financial institution dummy
0.127
(11.4)
Year and Company dummy
yes
Observations
374,584
Adjusted R -squared
22.6%
68
Table 10
Matching Allocated Investors with Non-Allocated Investors
This table reports the coe¢ cients and Rogers (1993) heteroscedasticity consistent t -statistics in parentheses for the regressions with the number of allocated shares divided by the total number of shares issued
in the IPO as the dependent variable. This is a standard Tobit regression. Allocated investors with previous
trading are matched one for one with a non-allocated investor. The non-allocated investors takes a value of
zero for "(Allocated shares/shares issued) %". IPO allocations are trimmed at 1%. Regression 1 includes
all exact IPO allocations and matched investors that did not receive IPO allocations. Regression 2 includes
only investors with a positive level of commission.
(Allocated shares/shares issued) %
Intercept
Log (commission)
Reg 1
Reg 2
-0.1971
-0.2331
(-12.9)
(-20.1)
0.0079
0.0106
(6.7)
(7.8)
-0.0038
-0.0037
(-2.1)
(-1.6)
0.0465
0.0174
(7.1)
(1.2)
-0,0001
0.0003
(-0.4)
(0.9)
Previous IPOs
0.5768
0.5341
(5.5)
(4.7)
Previous buy-and-hold
-0.006
-0.0055
(5.5)
(-1.2)
0.0076
0.0124
(1.3)
(1.8)
-0.0152
-0.0138
(-3.4)
(-3.2)
Financial institution dummy
0.0914
0.0747
(8.4)
(6.6)
Log (market value)
0.0077
0.0079
(10.4)
(14.2)
BV / MV equity
0.0136
0.0134
(14.8)
(20.1)
-0.0001
0.0004
(-3.8)
(15.9)
0.0461
0.0334
(7.6)
(24.1)
0.2516
0.0268
(79.8)
(12.4)
yes
yes
Observations
38,973
27,774
Pseudo R -squared
16.9%
10.5%
Log (commission) *D
Non-negative underpricing D.
Log (portfolio value)
Previous ‡ipping
Held cold IPO dummy
O¤er price
VC backed dummy
High-tech dummy
Year dummy, Company dummy
69
Figure 1
The di¤erent IPO Allocation Views
Ritter (2003) and Jenkinson and Jones (2004) argue that there are three views on how IPOs are
allocated. First, is the academic view based on Benveniste and Spindt (1989). In this view investment
banks allocate IPO shares to informed investors in return for true valuation and demand information.
Second, is the pitchbook view where investment banks allocate shares to institutional investors that are
likely to be buy-and-hold. Finally, is the rent seeking view where investment banks allocate shares to
investors in return for some form of kickback.
The Rent seeking view of IPO allocations
Commission
Shares are allocated to investors that generate
high levels of stock-trading commissions.
IPO spinning
Shares are allocated to company executives to attract
corporate business.
IPO laddering
Shares are allocated to investors that will provide
after-listing share price support. Underpriced shares are
allocated to investors that generate high
stock-trading commissions.
Analyst overage
Companies accept underpricing in exchange for future.
research coverage. Underpriced shares are allocated
to investors that generate high stock-trading commissions.
The pitchbook view of IPO allocations
Shares are allocated to investors that are expected to be
buy-and-hold. This will create long run price stability.
The academic view (information gathering) of IPO allocations
Shares are allocated to investors that report true share values.
Shares are exchanged with price information.
70
Figure 2
Timeline of the Listings on the Oslo Stock Exchange
Listing in the VPS is when the company list ownership records in the ownership database. This is
when the ownership records are observed in the data the …rst time. Public O¤ering is when the companies
distribute the allocated shares in the ownership database. The public o¤ering is in most cases in the month
before (30 exact IPOs) or the month of the listing (150 IPOs).
Timeline of the listing
Company list shares in the VPS database
Six months before the listing
The company selects an investment bank
The initial meeting between company, investment bank and the OSE
Compliance report is …nalized by the investment bank
The legal and accounting due diligence is performed
The formal application is submitted to the OSE
Prospectus is …nalized and distributed
IPO shares are priced through meetings with investors
One month before the listing
Shares are transferred in the Public O¤ering
Listing month
Listing
71
Figure 3
Timeline of the IPO allocations for the di¤erent groups
Listing in database is when the company list ownership records in the ownership database. This is
when the ownership records are observed in the data the …rst time. IPO allocation is when the companies
distribute the allocated shares in the ownership database. Group 1 to 3 is the ordering of the group of
detail in the allocations. Group 1 is 100% accurate IPO allocations. Group 2 IPO allocations includes one
to 30 days of after-listing trading. Group 3 IPO allocations includes existing owners who have not sold all
of their shares in the IPO. There are 30, 150 and 5 companies in group 1, 2 and 3 respectively.
Timeline of the listing
Six months before
One month before
the listing
the listing
Group 1
Listing in database
IPO allocation
Group 2
Listing in database
Listing month
Listing
IPO allocation
Listing
Group 3
Listing in database
Listing
IPO allocation
72
.
4
Initial Public O¤ering or Initial Private Placement?
Sturla Lyngnes Fjesme54
BI Norwegian Business School
Øyvind Norli
BI Norwegian Business School
.
.
.
.
.
Abstract
This paper studies the choice between an auction and a negotiation when
selling a large fraction of a company. Using detailed data on ownership structure in 123 public o¤erings and 88 negotiated private placements, we show
that negotiated private placements are much more common when there are
signi…cant private bene…ts of control. This …nding supports the idea that a
negotiated transaction allow the seller to extract more of the gains from trade
when the gains from trade include private bene…ts.
JEL classi…cation: G24
Keywords: Private Placements; Public O¤erings; IPOs; Equity o¤erings
54
We are grateful to "The Center for Corporate Governance Research (CCGR)" at BI Norwegian
Business School for …nancial support, to Øyvind Bøhren, François Derrien, and seminar participants at
BI Norwegian Business School for valuable suggestions, and the Oslo Stock Exchange VPS for providing
the data. All errors are our own.
Corresponding author: BI Norwegian Business School, Nydalsveien 37, 0484 Oslo, Norway, E-mail
address: [email protected], Telephone: +47-957-722-43
73
4.1
Introduction
Stock exchanges have stringent rules on minimum equity levels and the minimum number
of shareholders that are required to list publicly. Most private companies must issue equity
to be able to meet these minimum requirements. Shares can either be sold in an IPO to
a large group of dispersed investors or in a negotiated private placement to a small group
of specialized investors. Most theoretical papers on equity o¤erings show that public
o¤erings will almost always be preferred by the seller, so why some companies use private
placements has been the focus of many empirical studies in …nance. The research question
addressed in this paper is whether private placements are used to transfer private bene…ts
of control from the seller to the buyer. The new and unique data in this paper includes
investor level ownership and audited …nancial statements in 88 private placements and
123 public o¤erings during their listing on the Oslo Stock Exchange (OSE) in the period
1993 to 2007.
The main contribution of the paper is that we show a strong and robust relationship
between private bene…ts of control before the initial equity o¤ering and the use of private
placements55 . This suggests that sellers of a company use private placements to transfer
private bene…ts of control to buyers. Private placements are used by family …rms and …rms
with controlling owners before the o¤erings. Public o¤erings are used by companies with
more dispersed ownership before the o¤erings. Companies that use private placements
also have more block ownership after the listings. Public o¤erings reduce block ownership.
The main implication of this …nding is that companies with low private bene…ts of control
should be sold in public o¤erings and companies with higher private bene…ts of control
should be sold in private placements. The …nding also have implications for research on
auctions and negotiations. When auctions are structured like IPOs and there are large
private bene…ts of control, the seller is likely to prefer a negotiation over an auction.
Several papers have proposed explanations to the private placement choice made by
some companies. Some papers argue that private placements are used to attract value
creating investors such as monitoring or certi…cation investors (Wruck, 1989; Hertzel and
Smith, 1993). These investors ensure that companies are run optimal or put their stamp of
approval on company valuations. Other papers suggests that private placements are used
when buyers value private bene…ts of control (Zingales, 1995; Zingales, 1994; Zwiebel,
1995 and Damodaran, 2005).
Most existing research on private equity o¤erings are on SEOs by publicly listed companies. The reason for this is likely to be that there are more available data on publicly
listed companies. Only investigating public companies is problematic for this research
question because this leaves out the major equity o¤erings taken place before the actual listing. Many of the companies that list on the OSE through private placements
have follow-on public and employee o¤erings before the listing. This shows that private
placements must often be used in connection with a follow-on o¤ering to meet listing
requirements. This also show that the private or public choice is not dictated by the
minimum size listing requirements.
55
The agency problem investigated is between large owners and small owners. Large owners have a
controlling bene…t at small owners expense. Throughout the article, we mean the private bene…t of
controlling the …rm enjoyed by the controlling/big shareholders at the expense of smaller owners when
the term private bene…t of control is used. Other agency problems, that we do not study, can for instance
be between owners and managers in the …rm.
74
Derrien and Kecskés (2007) show that many U.K. companies lists publicly without
issuing equity and that these companies issue equity in a SEO after the listing. This
two-stage listing is cheaper than the normal IPO. On the OSE there are only a limited
number of companies that are allowed to use this two-stage process. In most listings on
the OSE the o¤ering is a requirement to list. The choice faced by most companies is not if
there should be an o¤ering before or after the listing. The choice is if the required o¤ering
should be public, private or to existing shareholders. Few companies have an existing
shareholder base that can cover the o¤ering in full. Listing rules require that there must
be at least 500 owners to list on the main list of the OSE (100 at the Small and Medium
Sized SMB/Axess list). Only 21 out of 403 companies have listings with only an o¤er
to existing shareholders. Therefore, the main choice at the OSE is between a negotiated
private placement and an IPO. This makes the OSE an ideal market to study the choice
between IPOs and private placements.
The remaining paper is organized as follows. Section 4.2 describes related literature.
Section 4.3 describes the road to the listing. Section 4.4 describes predictions and testable
implications. Section 4.5 and 4.6 describes the data set and the empirical results. Section
4.7 concludes.
4.2
Literature review
There are many theoretical papers that study the equity sales process.56 Bulow and Klemperer (1996, 2009) compare auctions to negotiations and sequential sales mechanisms.57
Bulow and Klemperer (1996) show that for a seller it is better to sell in an auction with
(N+1) bidders than in a negotiation with N bidders. The seller should therefore focus
on maximizing the number of bidders and not focus on …nding a single bidder to negotiate with. The exception to this rule is when more information must be disclosed in
the auction. When more information, that can possible reduce the future asset value for
the …nal owner, is disclosed in the auction, it is possible that the negotiation is more
pro…table for the seller than the auction. Bulow and Klemperer (2009) show that buyers
(usually) prefer to buy in a sequential sale (negotiation), and sellers (usually) prefer to
sell in an auction. The exception to this …nding is when the marginal revenue curve of
the winner is very ‡at, there are many potential bidders and the bidder cost of obtaining
value information is neither too high nor to low. French and McCormick (1984) …nd that
negotiations should be used instead of auctions when there is an ongoing relationship
between bidder and seller, there is a low asset value di¤erence between bidder and seller,
there is a low asset value di¤erence between di¤erent bidders and the actual negotiation
cost is low compared to auctions.
Zingales (1995) propose that the buyer of a company can have a higher company
value than the current owner from either an increase in the private bene…ts of control
or an increase in the cash ‡ow. By selling to dispersed shareholders the proceeds from
the sale of cash ‡ow rights are maximized. Through bargaining with a buyer the seller
maximizes proceeds from the sale of control rights. Zingales (1994) argue that one of
56
Table 1 summarizes all related papers.
IPOs are not really open auctions, and private placements are not really negotiations in the exact
same sense as used in all of the literature. There are, however, large similarities between IPOs and
auctions and private placements and negotiations, and we therefore include a literature review on the
auctions and negotiations literature. We also expect that our …ndings may have implications for research
on auctions.
57
75
the most common areas of private bene…ts of control is dilution of minority property
rights. This shows that there should be some smaller investors in the companies that use
private placements. It is also argued that control is more valuable during proxy contests.
Damodaran (2005) argues that the value of a block of shares comes from the ability to
in‡uence control by changing the way the business is currently run. Damodaran (2005)
argues that block shares are sold at a premium compared to dispersed shares. Value
of control can be calculated as the value of the …rm assuming that it is optimally run
minus the status quo value of the …rm. Control of a …rm does not necessarily require
51% of shares if the remaining shares are sold to a dispersed group of shareholders.
Zwiebel (1995) investigates smaller block shares. It is argued that there are bene…ts of
having blocks that are smaller than controlling stakes from partial bene…ts of control.
Smaller block holders can join together and get control if desired. Private bene…ts of
control can be the ability of owners, management or directors to dilute corporate funds
for private bene…ts.58 Private bene…ts can also be synergies obtainable through mergers
(during takeover contests opposing sides actively recruit block shareholders), favors by
…rms, access to inside information, perquisites of control and utility derived directly from
power of control. Some …rms, such as sports and communication …rms, are likely to yield
private bene…ts from the nature of their business. Stoughton and Zechner (1998) argue
that IPOs are allocated to institutions to increase monitoring.
Several empirical papers propose explanations to the private placement choice. Wruck
(1989), later referred to as the monitoring hypothesis, show that active investors buy
shares privately and monitor management. It is argued that monitoring will increase value
by ensuring e¢ ciency and openness to value creating takeovers. The article investigates
128 private placements made by companies listed on NYSE and AMEX in the period
1979 to 1985. Hertzel and Smith (1993), later referred to as the certi…cation hypotheses,
argues that an informed investor buy large blocks of shares in private placements to
put their stamp of approval on company valuations. The paper investigates 106 private
placements made by smaller companies listed on NASDAQ in the period 1980 to 1987.
It is concluded that certi…cation is a likely reason behind private placements. Barclay et
al. (2007) investigate if monitoring (Wruck, 1989) and certi…cation (Hertzel and Smith,
1993) explains private placements by investigating 594 U.S. publicly traded …rms in the
period 1979 to 1997. The main …nding is that private placements are often allocated to
passive investors that help management keep control of the companies. This is proposed
as the entrenchment hypothesis, and it is concluded that entrenchment is a more likely
reason for private placements than monitoring or certi…cation.
Anshuman et al. (2010) propose the undervaluation hypothesis as appose to the monitoring, certi…cation and entrenchment hypotheses. The undervaluation hypothesis is an
extension of Myers and Majluf (1984), and the hypothesis propose that company management and insiders buy shares in their own company, through private placements, when
they believe that the company is undervalued. The hypothesis is tested on a sample of
164 private placements in the Indian capital market in the period 2001 to 2009. It is concluded that private placements (to company insiders) can eliminate underinvestment, and
the underinvestment hypothesis can explain the private placement choice after controlling
for monitoring, certi…cation and entrenchment. Wu (2003) investigates how information
asymmetry and monitoring a¤ects the company choice between public o¤erings and private placements. The data investigated is 728 public o¤erings and 360 private placements
58
In this paper we study private bene…ts of control enjoyed by big owners through dilution of corporate
funds.
76
made by high technology companies that have recently been publicly listed on NYSE,
Nasdaq or AMEX. The main …nding is that private placement companies have a higher
information asymmetry than public o¤ering companies. Private placement investors also
do not monitor more than public o¤erings investors. Wu (2003) concludes that monitoring
is not a likely reason behind private placements. Brennan and Franks (1997) investigate
67 U.K. IPOs and …nd that underpricing is used to ensure su¢ cient oversubscription and
rationing of shares. This is done by IPO company insiders to discriminate between shareholders and reduce block sizes. Brennan and Franks (1997) argue that underpricing is
used to avoid block holder formations. Aru¼
gaslan, Cook and Kieschnick (2004) investigate
3,441 U.S. IPOs. They …nd that determinants of initial returns, institutional share holdings and post- IPO likelihood of acquisition are not consistent with either Brennan and
Franks (1997) or Stoughton and Zechner (1998). Aru¼
gaslan et al. (2004) conclude that
monitoring considerations are not important determinants of IPO underpricing. Cronqvist and Nilsson (2005) investigate how Swedish publicly traded companies in the period
1986 to 1999 choose between rights o¤erings and private placements in SEOs. It is found
that companies with much asymmetric information will choose private placements over
rights o¤erings. Companies will choose private placements to current shareholders when
asymmetric information is extreme. Companies also do private placements to new business partners. It is concluded that private placements can be used to reduce moral hazard,
adverse selection costs and o¤set high issue cost.
Boone and Mulherin (2007) investigate why not all …rms are sold in competitive auctions. The investigated data includes 202 auctioned and 198 negotiated takeovers of U.S.
public …rms in the period 1989 to 1999. The main …nding is that there is no di¤erence
in wealth e¤ects of the target …rms after negotiations and an auctions. Auctions does
not increase revenue for the sellers. Boone and Mulherin (2008) investigate 145 auctioned
and 163 negotiated takeovers by U.S. publicly traded bidders in the period 1989 to 1999.
The paper test if the return to the winning bidder is related to the level of competition
in the takeover market. It is assumed that there is a negative relationship between the
number of bidders and the level of value uncertainty and the bidder return if the winners
curse is true. The main …nding is that there is no relationship between bidder return
and competition. It is concluded that there is no winners curse in the corporate takeover
market.
4.3
The road to the listing
The listing process includes many formal requirements. These are dictated changes the
private company must make to be allowed to list publicly. The private company must
also make many decisions that are not formal requirements. The most notable, for this
article, is if equity should be raised through an IPO or in a negotiated private placement.
4.3.1
The formal listing process
The listing process at the OSE takes between eight and 14 weeks to complete.59 The
private company must …rst select an investment bank to help with the listing process.
The company and the chosen investment bank then have a meeting with the board of the
OSE to initiate the listing process. After this initial meeting the investment bank hires
59
The information about the listing process is obtained from the seminar “The road to the listing”
November 3, 2009 by Deloitte Public Accountants and the Oslo Stock Exchange.
77
an accounting …rm and a law …rm to complete a …nancial and a legal due diligence of the
private company. The investment bank then, assuming everything is in order, makes a
compliance report that shows that the private company meet all formal requirements to list
on the OSE. Four weeks after the initial meeting with the OSE, there is a meeting between
the accounting …rm, the law …rm and the OSE. At this time, the formal application is
handed in to the OSE by the investment bank. During the next four weeks, the investment
bank completes the formal listing prospectus. The OSE use this time to go through the
application. The company is then accepted or rejected to list on the OSE. About 80 to
90% of all companies are accepted. Most companies are, however, accepted to list with
conditions. Most companies have to adjust before they are allowed to list publicly.
There are two very common conditions to list. The …rst common condition is that the
equity level must be increased. Companies must show that they have su¢ cient equity to
keep the company running for at least 12 months after the listing. It is not necessary
with a positive cash ‡ow as long as the company can run on equity for at least 12 months.
Many companies on the OSE are shipping companies with high cash out‡ows around the
listing date and high cash in‡ows at a later point in time. The second common condition
is that one or two members of the board must be replaced with more independent board
members. Many private companies have boards consisting of representatives that are
related to the company in some way. Public companies must have more independent
boards. When a company is accepted or accepted with conditions, the investment bank
starts the roadshow (the marketing and sale of new stock). This is the main reason why
a private company needs to use an investment bank. Distribution of shares is potentially
hard to accomplish without the sales force of the bank. The company has 45 days to list
after it has been accepted or accepted with conditions. If the company is not listed in
this period, the process must be repeated. Most of the companies that list on the OSE
are forced to issue equity as a part of the listing process. Out of the 403 listings at the
OSE in the period 1993 to 2007 only 90 companies are able to list without increasing their
equity level in some way.60
4.3.2
A public or a private o¤ ering?
Due to oversubscription and share rationing it is di¢ cult for investors to buy large blocks
of shares in IPOs. In the traditional IPO setting investors submit bids for a given number
of shares at a speci…ed o¤er price (book-building). (In a …xed price o¤ering the investment
bank determine the price …rst and then investors submit bids for shares at the given price).
It is common that IPOs are oversubscribed. This means that there are normally bids for
more shares than the company is planning to sell. Investment banks usually set the o¤er
price where demand is above supply. Sometimes demand is many times greater than the
supply of shares (this is the oversubscription fraction reported in the newspapers after the
o¤ering). When IPOs are oversubscribed, shares are often rationed to the applicants at
the price decided. An investor that bid for a high number of shares with a high bid price
is likely to only be awarded a fraction of the applied for shares. The price is likely to be
lower than the bid price because there is only one o¤er price to all investors. Rationing
means that investors are likely to not be allocated blocks of shares.
In negotiated private placements, on the other hand, shares are normally sold in
blocks. The investors that are willing to pay the most for blocks of shares are awarded
the blocks. This means that negotiated private placements are more suitable to transfer
60
Figure 1 list the timeline in the listing process.
78
blocks of shares. It is easier for an investors to obtain company blocks following private
placements. An investor that wants to sell company control rights should therefore issue
shares in a private placement. It is possible to stage the equity sales by …rst selling blocks
and then selling the remaining shares. This is also what is observed in the data. Many
companies that use private placements also sell shares publicly afterwards. Interestingly,
this is the opposite order of what is predicted by Zingales (1995).61
4.4
Theoretical predictions and testable implications
The value of owning company shares can come from two sources. The …rst source is the
residual claim to cash (cash ‡ow rights). When all debtholders and other claimants to
company cash ‡ow has been paid, the remaining cash is the property of shareholders.
The second source is the ability to enforce control (control rights). An owner with a high
ownership percentage can in‡uence more control and dilute more corporate resources
away from smaller owners. This is private bene…ts of control that comes from owning
a big stake in a company. The private bene…ts of control only goes to the controlling
owner(s). Private bene…ts of control is enjoyed by the single biggest owner, or a group
that together makes a controlling stake, at the expense of smaller shareholders (Zwiebel,
1995). Zwiebel (1995) explains that smaller block holders can join together and get
control if desired. Transfer of control is therefore not necessarily from one big shareholder
to another big shareholder. Transfer of control can also be from one big shareholder to
a small group of block shareholders. Value of control can come from in‡uencing how a
company is run, but value of control can also come from the ability to misuse corporate
resources. In some companies it is likely that it is easier to use control to move resources
than in other companies.
According to Zingales (1995) the seller of a company can maximize proceeds from cash
‡ow rights by selling in an IPO to dispersed shareholders. The seller can maximize proceeds from control rights by directly bargaining with the buyer. Zingales (1995) explains
that companies should optimally be sold in a two-stage process. Sellers should …rst sell a
part of the company to dispersed shareholders. Then, the control rights should be sold in
a private negotiation. In our data set there are no companies that follow this two-stage
strategy, so we can not test this model directly. We can, however, test if companies with
more value from control rights (higher private bene…ts of control) are more likely to be
sold in negotiations (private placements). A company with a high value of control should
be sold in a private placement because it is easier to transfer control this way.62 The
testable prediction from Zingales (1995) is that there should be a relation between private
bene…ts of control and the use of private placements. We label this the private bene…ts
of control hypothesis based on Zingales (1995).
61
Zingales (1995) predicts that companies with high private bene…ts of control will sell shares in a
public o¤ering …rst. Remaining shares will be sold in a private placement at a later stage. We observe
that the private placement takes place before the public o¤ering every time this two stage process is used.
This is opposite of what is predicted by Zingales (1995).
62
If there are high private bene…ts of controlling a …rm, the …rm could potentially stay private so that
the owner can continue to enjoy the private bene…ts of control. If owners still want to go public, it can
be argued that it will be better for the seller to sell control rights separately. There are many bene…ts
of being publicly listed. The most notable is access to capital. It is therefore safe to assume that also
companies with high private bene…ts of control bene…t of being publicly listed.
79
4.4.1
The private bene…ts of control hypothesis
To test the relationship between private bene…ts of control and the use of private placements it is necessary to measure private bene…ts of control. It is not possible to know the
exact level of private bene…ts of control because it is an unobservable variable. It is, however, possible to observe some sources of private bene…ts of control. We use these sources
as estimates of the private bene…ts of control for the controlling owners. It is mainly
expected that companies with block ownership before the initial o¤ering have higher private bene…ts of control. Zwiebel (1995) argue that the main reason why there are block
owners is because of private bene…ts of control from taking advantage of smaller owners.
Accordingly, there should be more private bene…ts of control in a company when there
are more and bigger block owners. Private bene…ts of control are therefore estimated on
the basis of bock ownership before the o¤erings.63 The ownership fraction of the largest
owner before the o¤ering is used as one measure of private bene…ts of control.64 The
combined ownership fraction of all block holders is used as another measure of private
bene…ts of control.
Other measures that also indicate the level of private bene…ts of control are the timing of the o¤ering, company industry, dividend payout, family ownership and positions,
minority power and CEO/board compositions. In 2006 there was introduced a new law
that increased tax on dividends in Norway. It is expected that this new tax will reduce
the level of dividend paid out after 2006. It is expected that private bene…ts of control
will increase after 2006 because more money is left in the companies. Total dividends
paid in the year before the listing is also included based on the same argument. It is also
expected that …rms in certain industries give higher private bene…ts of control. Especially,
it is expected that …rms in the sports and communications industry have more bene…ts of
control, see Zwiebel (1995). Unfortunately, there are no sports companies and very few
communications companies listed in Norway. This variable is therefore dropped.
It is also expected that family …rms have higher bene…ts of private control than nonfamily …rms. It can be argued that family …rms have already used their bene…ts of control
by placing family members in management positions. Family …rms are de…ned, in this
paper, as …rms where members of one family together hold the largest fraction of the
company and more than one member of the family is in the senior management. It is also
expected that minority power is decreasing in private bene…ts of control. It is expected
that the founder is the minority owner in the company. New owners can group together
and gain control. It is therefore expected that minority (founder) power should decrease
in private bene…ts of control. Minority power is measured by founder position in the
63
It is likely that tunneling is one of the major sources of private bene…ts of control. In tunneling, the
biggest owner owns a large stake (e.g. 51%) in one …rm and 100% of another …rm. The biggest owner
then tunnels resources from the …rm with 51% ownership to the …rm with 100% ownership. Tunneling
can for instance be in the form of selling assets below actual value. Tunneling lets the big owner steal
resources from the shareholders that own the remaining 49% of the shares in the …rst company. We are
not able to detect tunneling in the data.
64
All variables, unless otherwise speci…ed, are obtained in the VPS ownership database prior to the
o¤ering or in the listing prospectus made before the o¤ering. This means that all independent variables are
known and observed before the private placement/public o¤ering choice is made. The listing prospectus is
mainly based on annual accounting data, so it is reasonably assumed that all information in the prospectus
is available before the public o¤ering/private placement choice is made. Even the level of capital raised
should be known before the public o¤ering/private placement choice is made. Capital raised is in most
cases dictated by OSE as a requirement to list. We argue that there are no simultaneous decisions in our
data, and there is no endogeneity issues in the analysis.
80
companies (E.g. The founder is the CEO or on the board of directors). The ownership
concentration of the owners besides the single biggest owner is also a measure of minority
power. This is measured by the Her…ndahl index of the 50 biggest owners besides the
single biggest owner. Finally, it is expected that there are more private bene…ts of control
in companies where the largest owner use control in an observable manner. It is expected
that in companies where the largest owner is the CEO or on the board of directors there
are more bene…ts of private control. The dummy variable private placements (0) or public
o¤erings (1) is regressed on the private bene…ts of control measures in a standard probit
model to test if companies use private placements when there are more private bene…ts
of control.65
4.4.2
Alternative explanations
Private placements have, in addition to private bene…ts of control, also been explained
with the monitoring (Wruck, 1989), the certi…cation (Hertzel and Smith, 1993), the entrenchment (Barclay et al.,2007), the undervaluation (Anshuman et al., 2010) and the
asymmetric information (Cronqvist and Nilsson, 2005) hypotheses. The monitoring hypothesis is that investors buy shares in private placements to increase company valuation
through increased monitoring of management. It is likely that companies with high ownership concentration, before the initial o¤ering, already have more monitoring of management than companies with lower ownership concentration. Block owners are more likely to
monitor management because they have more at stake in the companies. The monitoring
hypothesis therefore predicts (indirectly) that companies with lower ownership concentration should be more likely to use private placements. This is the opposite prediction
of the private bene…ts of control hypothesis. The monitoring hypothesis is therefore controlled for by testing the relationship between ownership concentration, before the initial
o¤ering, and the use of private placements.
The certi…cation hypothesis is that informed investors buy shares in private placements to put their stamp of approval on company valuations. This does not give the
same implications as the private bene…ts of control hypothesis. There is no reason why
a company with more concentrated ownership would need more certi…cation than a company with less concentrated ownership. It is, however, likely that smaller and younger
companies would be more likely to want certi…cation, as there is less information publicly
available for these companies. The certi…cation hypothesis is therefore controlled for by
including the number of employees (size) and company age in all regressions.
The entrenchment hypothesis is that private placements are used by company management to keep their positions (even if they perform poorly). Entrenchment is a highly
unlikely explanation for the companies in our sample. All companies are eventually listed
publicly and this indicates that these companies are doing very well. It is very unlikely
that the companies in our sample have management that consistently need ownership
manipulation to keep their positions. It can also be seen in Table 3 that most of the
companies in the sample have the largest owner as the CEO or on the board of directors.
This indicates that these owners are active and not passive investors that help keep poor
management in their positions. The entrenchment hypothesis will also not explain why
companies with more concentrated ownership before the initial o¤ering are more likely to
65
It is argued that value of control does not require 51% of the shares (Damodaran, 2005). We do not
know how much ownership that is needed to enjoy private bene…ts of control, so the ownership percentage
of the largest owner or the combined block ownership is included in all regressions.
81
use private placements. If private placements are used by companies with poor management, it is, however, likely that company results before the o¤ering are negatively related
to the use of private placements. The entrenchment hypothesis is therefore controlled for
by including company results before the o¤ering in all regressions.
The undervaluation hypothesis is that insiders buy shares through private placements
when they perceive the company to be undervalued. In the capital history section in
the listing prospectus there are clear distinctions between employee o¤erings and private
placements. Company insiders buy shares in employee o¤erings and not through private
placements. The ownership level for all company insiders is also disclosed before and
after the equity o¤erings, so we know that the private placements are not made towards
company insiders. The undervaluation hypothesis is therefore not relevant for our data
set and question.
The asymmetric information hypothesis is that companies with high information discrepancies, between company insiders and outsiders, use private placements to reduce
the cost of conveying information to investors. It is likely that certain (harder to value)
industries are more likely to have more information asymmetry. Especially, it is expected
that companies in the information technology (IT) sector have more information asymmetry than other companies that list on the OSE. It is also expected that younger and
smaller companies have more information asymmetry because less information is publicly
available for these companies. IT, younger and smaller companies should use more private placements if this hypothesis is true. It is tested if asymmetric information drives
the private placement choice by including a dummy variable for all companies in the IT
sector, the company age and the number of employees in all regressions.
4.4.3
Other control measures
The reasons why companies issue equity is to have su¢ cient levels of equity and number
of owners before the listings. The OSE requires a minimum of 500 investors to list on the
main list of the OSE (and 100 to list in the small and medium sized list). Therefore, it
is necessary to control that the number of investors prior to the o¤ering and the capital
raised do not decide the method chosen. These variables are therefore included in all
regressions.
Carpentier and Suret (2009) show that Canadian …rms that use private placements
have lower book to market rations, are in special industries, are …nancially distressed or
constrained, are in the development stage and in general raise less capital. Barclay et al.
(2007) show that private placements are made at a discount to certain investors. Boone
and Mulherin (2007) show that market value is related to the use of private placements.
The problem with these variables is that they are observed only after the listing. Most of
these variables are observed the …rst time about six months after the initial private placement or public o¤ering choice has been made. The variables book to market ratio, …rst
day return and market value are observed the …rst time on the day of the listing. These
variables are not available for the companies in our sample because they are privately
held. All companies in the sample are also eventually listed on the stock exchange, so
there are no …nancially distressed or constrained …rms in the sample. (This is, however,
controlled for by including the last annual net result reported in the listing prospectus).
82
4.4.4
Private bene…ts of control also after the listing
It can be argued that companies with high private bene…ts of control should stay private.
The reason for this is that some of the private bene…ts of control is likely to disappear
when companies become public. We therefore test if there are private bene…ts of control
after the new listings. If control rights are sold in private placements, there should be
greater values of control also after the listings following private placements. To test for
bene…ts of control after the listing it is necessary to regress private bene…ts of control
after the listing on the public o¤ering or private placement choice.
Private bene…ts of control is an unobservable variable that is estimated by a portfolio
of measures. Most of these measures are very persistent. E.g. Few companies change the
CEO or board members right after the listing and company speci…c variables such as age,
number of employees, family …rm, result and dividend do not change. These variables are
not suitable as single measures of private bene…ts of control. A more suitable measure of
private bene…ts of control is the ownership fraction of the biggest owner(s) after the listing.
If there is a more concentrated ownership also after the listing, it can be argued that there
is persistence in the control. This is tested by regressing the ownership percentage of the
biggest owner(s) one month after the listing on the private placement or public o¤ering
choice (before the o¤ering) and a set of control variables.
4.5
Data and descriptive statistics
There are 403 companies the list publicly on the OSE in the period January 1993 to
September 2007. Table 2 gives the yearly distribution of IPOs and negotiated private
placements in this period. All companies must list their ownership records in the Norwegian central depository (VPS) database as a part of the listing procedure. From this
database the pre o¤ering ownership in all listed companies is observed. Accounting variables are collected from the listing prospectuses. It is assumed that private placements
in the six month period before the listing date are part of the listing procedure. Private
placements before this are assumed to not be part of the listing procedure.66
Company ownership at the end of month six prior to the listing date is the measure
of ownership concentration prior to the o¤ering. Most public o¤erings are in the calendar
month before or in the same calendar month as the listing date. Private placements are
spread out over the six months prior to the listing date. From Table 2 it can be seen
that there is a proportionate number of private placements and IPOs over the sample
period. There is a slight increase in the number of private placements compared to IPOs
in the end of the sample period. It is argued that the reason for this is an increase in the
Norwegian tax rates in 2006 that increased overall private bene…ts of control from more
retained cash.
There are 210 public o¤erings and 106 private placements by companies listing on
the OSE in the period 1993 to September 2007.67 For 19 public o¤erings and 6 private
66
Companies de…ne the equity o¤ering to be private or public in the capital history section in the listing
prospectuses. Data on all historical equity o¤erings are provided in these prospectuses.
67
In total, 44 companies used a private placement before a public o¤ering, and 131 companies did not
o¤er shares to new investors in the lead up period to the listing (21 of these companies were spino¤s to
existing shareholders). Private placements are made at di¤erent points in time in the six months period
before the listings. Private placements before this is not included in the sample. The public o¤erings are
83
placements it has not been possible to identify the ownership before the o¤ering from the
VPS ownership database. These companies are removed from the sample.68 A total of
44 companies made a private placement before the public o¤ering. These companies are
regarded as only private placement companies as they made this o¤ering …rst.69 The …nal
sample is 88 companies that used a private placement and 123 companies that used an
IPO.
4.5.1
Descriptive statistics
From Table 3 it can be seen that companies that use private placements and public
o¤erings are very similar. Private placement companies do, however, have on average
more large owners on the boards, higher ownership fractions of the largest owners after
the listings, more founders on the boards or as the CEOs, are more likely to be family
…rms before the o¤erings and have lower age. The average capital raised in the 88 private
placements is $57.3 million. This is just below the average size of the public o¤erings.
For private placements the combined sale of new and existing shares averages about 22%
of total outstanding shares at the listing date. For public o¤erings this number is 41%.
There are no signi…cant di¤erences between companies that use private placements and
public o¤erings on total assets, dividends, results, number of owners before the o¤ering,
capital raised and number of employees.
4.5.2
Variable description
The dependent variable in most regressions is a dummy variable for public o¤ering (1) and
private placements (0).70 Combined block ownership is the combined ownership fraction
of all investors that owns more than 5% of the company before any o¤ering is made.71
Holding of largest owner b. o¤er is the holding fraction of the single biggest owner before
the o¤ering. Holding of largest owner a. listing is the holding fraction of the single biggest
owner one month after the listing. Largest owner is the CEO and Largest owner is on the
board are dummy variables that takes the value of one for companies where the largest
usually performed in the month before the listing or in the listing month itself. Some private placements
have a follow on o¤ering to the public or to employees of the company. By using follow on o¤erings the
minimum number of investors regulation, set by stock exchanges, has no in‡uence on the equity o¤ering
method chosen. The remaining 110 listings are results of mergers with an already listed company, cross
listings or companies traded actively at the Norwegian over the counter list (OTC list) before the OSE
listing.
68
For 27 public o¤erings and 12 private placements it has not been possible to obtain all company
speci…c information (i.e. listing prospectuses). These companies are therefore removed from the sample.
69
When there is both a public and a private sale it is common that the investors in the private placement
sell a small …xed percentage of their allocated shares in the public o¤ering. It is likely that the private
placement is made to increase the capital for the company through the issue of new shares. It is also
likely that the public o¤ering is made to increase the number of shareholders. It is common that there
is one …xed resell percentage that applies to all investors in the private placement. This percentage is
usually very low (less than 10%). The issuing company have then sold shares with the condition that
the investors must sell some of their allocated shares before the listing. It is likely that this condition is
included to meet minimum spread requirements set by the OSE. The …nal sample is 123 public o¤erings
and 88 private placements.
70
All ownership variables are obtained from the VPS database. All other pre listing variables are
obtained from the listing prospectuses that are made in connection with the listings.
71
In Norway, all shareholders that own more than 5% of the outstanding shares must be reported in
the listing prospectus. In the remainder of the article we refer to shareholders that own more than 5%
of outstanding shares as block holders.
84
owner is the CEO or on the board of directors. The founder is the CEO and The founder
is on the board are dummy variables that take the value of one if the founder is the CEO or
on the board of directors. Her…ndahl index is the squared ownership fraction of the sum
of the 50 biggest owners besides the largest owner.72 The 2006 dummy takes the value
of one for all companies listed after 2005. (Dividend / Total Assets) is the total dividend
payment made in the year before the listing year scaled by total assets. The Family …rm
dummy takes the value of one for family …rms. Family …rms are identi…ed in the listing
prospectuses as …rms where members of one family together hold the largest fraction of the
company and more than one member of the family is in the senior management of the …rm.
Age is the di¤erence between listing year and the year of incorporation of the companies.
Number of employees is the number of annual accumulated full time employees in the
issuing company. Capital raised is the total number of shares sold in the o¤ering times
the o¤er price. N. owners before o¤ering is the number of investors that own shares in
the company before the o¤ering. Capital raised and N. owners before o¤ering are weakly
negatively correlated. (Net result / Total Assets) is the last annual end of year result,
scaled by total assets, listed in the listing prospectus. IT dummy takes the value of one
for companies in the information technology (IT) sector. Year …xed dummy is included
as dummy variables for the di¤erent years in the sample period (1993 to 2007).
4.6
Empirical Results
The main empirical …nding of the paper is that companies with more block ownership,
before the o¤erings, are more likely to use private placements instead of public o¤erings.
The companies that did use private placements also have more block ownership after the
listings. There is also a bigger reduction in block ownership following public o¤erings
than following private placements.
4.6.1
The private bene…ts of control hypothesis
The dummy dependent variable private placement (0) or public o¤ering (1) is regressed
on the estimated private values of control in a probit regression.73 From Table 4 it can be
seen that companies with one large owner prior to the initial o¤ering are more likely to use
private placements. The coe¢ cient for holding fraction of the largest owner on the issue
choice is positive and signi…cant at the 0.01 level. The positive coe¢ cient supports the
private bene…ts of control hypothesis that private placements are used to transfer private
bene…ts of control. Companies where there is one controlling owner prior to the o¤ering
72
In general, it is expected that private bene…ts of control should decrease in minority power. There
are, however, some sample characteristics that may alter this expectation. In many companies there are
a small group of investors that jointly owns a controlling stake in the company together (E.g. a family
or a group of friends). It is expected that all of these investors will enjoy the private bene…ts of control
even if one investor have a slightly larger stake than the others. Zwiebel (1995) also argues that there
are private bene…ts of control from block holders that are not the single biggest owner.
73
We do not expect there to be any problems with endogeneity in the analysis. All independent
variables are observed in the listing prospectus before the public o¤ering. We assume that these variables
are also publicly available before the private placements even if these may be up to …ve moths before the
listing prospectus is available. We argue that the used independent variables are determined before the
private placement/public o¤ering choice, and any endogeneity due to simultaneity will therefore not be
an issue. The variables in the listing prospectuses are also available in annual (and quarterly) reports. It
is reasonably assumed that investors are able to locate this information before the private o¤ering.
85
are more likely to use private placements instead of public o¤erings. Companies that issue
equity in periods where there is likely to be more private bene…ts of controlling …rms (after
2006) also issue more in private placements. Companies that use private placements are
also more likely to be family …rms. Most control variables are unrelated to the issue
choice. The level of capital raised is highly related to the use of public o¤erings.
From Table 5 it can be seen that the exact same results are obtained when the block
ownership fraction of the biggest owners is used instead of the ownership fraction of
the single biggest owner. Companies with more block ownership are more likely to use
private placements whereas companies with less block ownership are more likely to use
IPOs. These results control for the level of capital raised, the number of investors that
own shares in the companies before the o¤erings and the alternative explanations for
private placements. The results are also robust to the removal savings banks (13).
From Table 6 it can be seen that the relationship between private bene…ts of control
and private placements is robust to including year …xed e¤ects. It is not possible to reject
the hypothesis that private placements are used to transfer private bene…ts of control.
4.6.2
Alternative explanations
The private placement choice has in the previous literature, in addition to the private bene…ts of control hypothesis, been explained with monitoring, certi…cation, entrenchment,
undervaluation and asymmetric information. There is a positive relationship between
the use of private placements and the holding fraction of the largest owner(s) before the
o¤ering. This is the opposite …nding of what is predicted by the monitoring hypothesis
and this hypothesis is therefore rejected. There is not a consistent relationship between
the use of private placements and company age and number of employees. It is likely
that younger and smaller companies have more need for value certi…cation from informed
investors than other companies. The certi…cation hypothesis is therefore also rejected.
If company management use private placements to keep their control even if they perform poorly, it is expected that there will be a negative relationship between company
results and the use of private placements . There is, however, not a consistent relationship between company results before the o¤erings and the use of private placements. The
entrenchment hypothesis is therefore also rejected. There is also not more private placements by younger and smaller companies in the IT industry. If private placements are
used to reduce the problems associated with information asymmetry, it is expected that
there will be a relationship between companies with more expected information asymmetry (e.g. smaller, younger and IT companies) and the use of private placements. This
relationship does not exist and the asymmetric information hypothesis is therefore also
rejected.
4.6.3
Private bene…ts of control also after the listing
If control rights are sold in private placements, there should be greater values of control
also after the listing in companies that used private placements. This is tested by regressing private bene…ts of control after the listing on the IPO or private placement choice. In
Table 7 the combined ownership percentage of block owners one month after the listing is
regressed on the public o¤ering or private placement choice (and the control variables for
the alternative explanations). There is more block ownership one month after the listing
following private placements than following public o¤erings. Public o¤erings are related
to smaller block ownership one month after the listing. In Table 8 it can be seen that
86
the exact same results are found when only the ownership of the single largest owner is
studied separately. This show that there is more block ownership in companies that used
private placements also after the listings.
4.7
Conclusion
There is a strong and robust relationship between the ownership fraction of the largest
owner(s), before the initial equity o¤ering, and the use of private placements. The biggest
owner(s) also have a higher ownership fraction following private placements than following public o¤erings. If it is assumed that the main reason that investors are willing to
hold blocks of shares is to enjoy private bene…ts of control, it can be concluded that
private placements are used to transfer private bene…ts of control. Zwiebel (1995) argue that the only reason investors hold blocks of shares is to enjoy private bene…ts of
control. We reject that private placements are used because of monitoring, certi…cation,
entrenchment, undervaluation or asymmetric information considerations. We conclude
that private placements are used to transfer private bene…ts of control between the seller
and the buyer.
The main theoretical implication of this …nding is that Zingales (1995) is correct in
that company control rights are better sold separately. Companies are sold based on
the value of control rights when they are higher than the stand alone cash ‡ow rights.
The …nding also have implications for auction theory. When the auction makes it hard
to obtain blocks of shares, as in the case of the IPO, the negotiation may be preferred
by the seller if there are private bene…ts of control. The main practical implication of
this …nding is that companies should use private placements when the value of control
rights are higher than stand alone cash ‡ow rights. If there are larger private bene…ts of
controlling a …rm, the …rm should be sold in a private placement.
There are some limitations to the study. Private bene…t of control is an unobservable
variable that can come from an unlimited number of sources. Private bene…t of control is
estimated based on existing ownership and company speci…c variables. A more directly
observable measure of private bene…ts of control would have been preferable. It is also
not possible to detect tunnelling in the data. Tunnelling is likely to be a major source of
private bene…ts of control.
For future research it would be interesting to study a bigger sample that includes more
…rms with obvious private bene…ts of control such as sports companies. It would also be
very interesting to study cross company ownership and related business deals. Business
deals by companies with the same ownership would allow us to study tunneling.
87
References
[1] Anshuman, V. Ravi, Vijaya B. Marisetty and Marti G. Subrahmanyam, 2010, Private
Placements, Regulatory Restrictions and Firm Value: Theory and Evidence from the
Indian Market, NYU working paper.
[2] Aru¼
gaslan, Onur, Douglas O. Cook and Robert Kieschnick, 2004, Monitoring as a
Motivation for IPO Underpricing, Journal of Finance 59, 2403-2420.
[3] Barclay, Michael J., Cli¤ord G. Holderness and Dennis P. Sheehan, 2007, Private
Placements and Managerial Entrenchment, Journal of Corporate Finance 13, 461-484.
[4] Boone, Audra L. and J. Harold Mulherin, 2007, How are Firms Sold?, Journal of
Finance 2, 847-875.
[5] Boone, Audra L. and J. Harold Mulherin, 2008, Do Auctions Induce a Winner’s Curse?
New Evidence from the Corporate Takeover Market, Journal of Financial Economics
89, 1-19.
[6] Bulow, Jeremy and Paul Klemperer, 1996, Auctions Versus Negotiations, The American Economic Review 86, 180-194.
[7] Bulow, Jeremy and Paul Klemperer, 2009, Why Do Sellers (Usually) Prefer Auctions?,
The American Economic Review, forthcoming.
[8] Brennan, Michael and Julian Franks, 1997, Underpricing, Ownership and Control in
Initial Public O¤erings of Equity Securities in the U.K., Journal of Financial Economics
45, 391-413.
[9] Carpentier, Cecile and Jean-Marc Sure, 2009, Private Placements by Small Public Entities: Canadian Experience, Douglas J. Cumming, Ed., Companion to Private
Equity, Wiley, Chapter 8, forthcoming.
[10] Cronqvist, Henrik and Mattias Nilsson, 2005, The Choice Between Rights O¤erings
and Private Equity Placements, Journal of Financial Economics 78, 357-407.
[11] Damodaran, Aswath, 2005, The value of Control: Implications for Control Premia,
Minority Discounts and Voting Share Di¤erentials, NYU working paper.
[12] Derrien, François and Ambrus Kecskés, 2007, The Initial Public O¤erings of Listed
Firms, Journal of Finance 1, 447-479.
[13] French, Kenneth R. and Robert E. McCormick, 1984, Sealed Bids, Sunk Cost, and
the Process of Competition, The Journal of Business 4, 417-441.
[14] Hertzel, Michael and Richard L. Smith, 1993, Market Discounts and shareholder
Gains for placing Equity Privately, Journal of Finance 48, 459-485.
[15] Jenkinson, Tim and Howard Jones, 2004, Bids and Allocations in European IPO
Bookbuilding, Journal of Finance 59, 2309-2338.
[16] Megginson, William L., Robert C. Nash, Je¤ry M. Netter and Annette B. Poulsen,
2004, The Choice of Private Versus Public Capital Markets: Evidence from Privatizations, Journal of Finance 59, 2835-2870.
88
[17] Myers, S.C., Majluf, N., 1984, Corporate Financing and the Investment Decision
When Firms Have Information that Investors do not have, Journal of Financial Economics 13, 187-221.
[18] Ritter Jay R., 2003, Di¤erences between European and American IPO markets, European Financial Management 9, 421-434.
[19] Ritter Jay R., 1984, The Hot Issue Market of 1980, The Journal of Business 57,
215-240.
[20] Stoughton Neal and Josef Zechner, 1998, IPO –Mechanisms, Monitoring and Ownership Structure, Journal of Financial Economics 49, 45-77.
[21] White, Halbert, 1980, A heteroskedastic-consistent covariance matrix estimator and
a direct test of heteroscedasticity, Econometrica 48, 817-838
[22] Wu, YiLin, 2004, The Choice of Equity Selling Mechanisms, Journal of Financial
Economics 2004, 3-28.
[23] Wruck, Karen Hopper, 1989, Equity Ownership Concentration and Firm Value: Evidence from private equity …nancing, Journal of Financial Economics 23, 3-28.
[24] Zingales, Luigi,1995, Insider Ownership and the Decision to Go Public, The Review
of Economic Studies 62, 425-448.
[25] Zingales, Luigi, 1994, The value of Voting Right: A study of the Milan Stock Exchange Experience, The Review of Financial Studies 1, 125-148.
[26] Zwiebel, Je¤rey, 1995, Block Investment and Partial Bene…ts of Corporate Control,
The Review of Economic Studies 62, 161-185
89
Table 1 Related Studies
Auction (theory)
Bulow and Klemperer (1996)
Seller prefer to sell in an auction
Bulow and Klemperer (2009)
Buyers prefer to buy in negotiation
and sellers prefer to sell in an auction.
French and McCormick (1984)
Auctions are usually preferred
Equity o¤erings (theory)
Zingales (1995)
Control rights are optimally sold private
Zingales (1994)
Private bene…ts of control is dilution
of minority property rights
Zwiebel (1995)
There are bene…ts of blocks smaller than control
Stoughton and Zechner (1998)
Private placements increase monitoring
Attract certain types of investors (empirical)
Wruck (1989)
Monitoring hypothesis
Hertzel and Smith (1993)
Certi…cation hypotheses
Barclay et al. (2007)
Entrenchment hypothesis
Anshuman et al. (2010)
Undervaluation hypothesis
Brennan and Franks (1997)
Underpricing used to
avoid block holder formations
Aru¼
g aslan, Cook and Kieschnick (2004)
Monitoring not important
Wu (2003)
Monitoring not important
Cronqvist and Nilsson (2005)
Private placements reduce
moral hazard and adverse selection
Boone and Mulherin (2007)
Auctions does not increase revenue
for the seller
Boone and Mulherin (2008)
There is no relation between bidder
return and competition
90
Table 2
IPOs and Private Placements on the Oslo Stock Exchange
This table gives the annual distribution of initial o¤erings: Column 1 is the sample years. Column 2
is the number of public o¤erings per year. Column 3 is the average underpricing of the public o¤erings per
year. Column 4 is the total capital raised in all public o¤erings combined per year in USD. Column 5 is the
number of private placements per year. Column 6 is the average underpricing of the private placements per
year. Column 7 is the total capital raised in all private placements combined per year in USD. Underpricing
is calculated as: (o¤er price in the listing prospectus – …rst day closing price) / o¤er price in the listing
prospectus. Value of shares sold is reported in USD using a USD/NOK exchange rate of 0.1792. The sample
period is January 1993 through September 2007.
Public O¤erings
Distribution
Year
Private Placements
Capital raised
N
Underpricing %
M USD
1993
5
-1.8%
1994
10
4.2%
1995
6
6.7%
Distribution
Capital raised
N
Underpricing %
M USD
$474
4
27.4%
$81
$609
2
4.8%
$20
$467
5
8.1%
$49
1996
4
24%
$99
5
10.6%
$49
1997
15
16.6%
$972
11
34.6%
$139
1998
8
1.9%
$185
6
-6.1%
$108
1999
4
18.7%
$185
0
0
0
2000
9
-0.9%
$517
6
36%
$527
2001
4
-7.4%
$183
2
6.5%
$483
2002
2
-9.8%
$70
1
2.5%
$210
2003
2
-2.3%
$83
0
0
0
2004
13
5.6%
$1,602
1
5.5%
$3.6
2005
20
3.3%
$1,709
18
6.6%
$1,711
2006
12
3.2%
$1,417
9
9.2%
$584
2007
9
3.3%
$793
18
6.9%
$1,077
Total
123
5.3%
$9,365
88
12.7%
$5,074
91
Table 3
Summary Statistics on Firms Going Public
This table show the di¤erence between companies using initial private placements and initial public
o¤erings. "Combined block ownership" is the combined ownership of all investors that owns more than 5%
of the company before the o¤ering. "Holding of largest owner b. o¤er" is the holding fraction of the single
biggest owner before the o¤ering "Holding % of largest owner a. listing" is the holding fraction of the single
biggest owner one month after the listing. "Reduced % of largest owner" is the di¤erence in the ownership
fraction of the largest owner from before the o¤ering to one month after the listing. "Largest owner is
the CEO dummy", "Largest owner is on the board dummy", "The founder is the CEO dummy" and "The
founder is on the board dummy" are dummy variables that take the value of one if the biggest owner or
founder are the CEO or on the board. Her…ndahl index is the sum of the squared ownership fraction of the
50 biggest owners besides the largest owner. "Age of company" and "Number of employees" is the age and
the number of employees of the issuing company. "2006 dummy" and "Family …rm dummy" takes the value
of one for issues after 2006 and family …rms respectively. "IT dummy" takes the value of one for companies
in the information technology (IT) sector. "Capital raised " is the o¤er price times the number of shares
sold in the o¤ering. "N. owners before o¤ering" and "First day return %" are the number of owners in the
company before the o¤ering and the …rst day return from o¤er price to …rst day closing price respectively.
"Market value" is the number of outstanding shares at the listing day times the …rst day closing price.
"Fraction of company sold" is the fraction of sold shares to outstanding shares in the o¤ering. "Net result",
"Dividends" and "Total assets" are the last annual result, dividend paid and total assets reported in the
listing prospectus before the o¤ering. The t –statistic is calculated as: (Mean private placements - mean
public o¤erings) / (square root [ (variance private placements / numbers of private placements) + (variance
public o¤erings/ numbers of public o¤erings)].
Private placement
Variables
Public o¤ering
Di¤erence
Obs.
Mean
Std.Dev
Obs.
Mean
Std.Dev
Di¤.
t-stat.
88
0.78
0.23
123
0.76
0.26
0.02
(0.6)
-with no savings banks
88
0.78
0.23
110
0.74
0.26
0.04
(1.1)
Holding largest owner b. o¤er
88
0.5
0.31
123
0.5
0.34
-0.01
(-0.2)
88
0.5
0.31
110
0.47
0.32
0.02
(0.7)
Holding largest owner a. listing
85
0.3
0.16
123
0.26
0.18
0.04
(1.7)
Reduced % of largest owner
85
0.2
0.23
123
0.25
0.32
-0.05
(-1.3)
Largest owner is the CEO D
88
0.24
0.43
123
0.16
0.37
0.08
(1.4)
Combined block ownership
-with no savings banks
Largest owner is on the board D
88
0.52
0.5
123
0.31
0.46
0.21
(3.1)
Her…ndahl index
88
0.05
0.05
123
0.04
0.05
0.01
(1.4)
The founder is the CEO D
88
0.27
0.45
123
0.18
0.38
0.09
(1.5)
The founder is on the board D
88
0.36
0.48
123
0.23
0.42
0.13
(2.0)
Age of company in years
88
19.5
28.4
123
36.2
47
-16.7
(-3.2)
92
Table 3 continued.
Variables
Private placement
Obs.
Public o¤ering
Mean
Std.Dev
Obs.
Di¤erence
Mean
Std.Dev
Di¤.
t-stat.
Number of employees
88
507
1,343
123
735
2,220
-228
(-0.9)
2006 dummy
88
0.31
0.46
123
0.17
0.38
0.14
(2.3)
Family …rm dummy
88
0.27
0.45
123
0.12
0.32
0.15
(2.7)
IT dummy
88
0.15
0.36
123
0.2
0.4
-0.05
(-0.9)
Capital raised (Mill USD)
88
57.3
93.1
123
75.1
121
-17.8
(-1.2)
N. owners before o¤ering
88
233
654
123
135
265
98
(1.3)
First day return
88
0.13
0.334
123
0.05
0.14
0.08
(2.0)
Market value E. (Mill USD)
88
351.8
525.2
123
236.6
418.7
115.2
(1.7)
Fraction of company sold
88
0.22
0.24
123
0.41
0.26
-0.19
(-5.5)
Net result (Mill USD)
88
5.6
74.5
123
4.2
30.8
1.4
(0.2)
Dividends (Mill USD)
88
0.31
0.96
123
1.4
9.3
-1.1
(-1.3)
Total assets (Mill USD)
88
912
4,926
123
408
968
504
(0.9)
93
Table 4
Private Placements and Private Bene…ts of Control of the Single Biggest
Owner
This table reports the coe¢ cients and t -statistics in parentheses for the regressions with the dummy
variable that takes the value of one for IPOs and zero for private placements as the dependent variable.
All regressions are standard Probit models. The sample period is September 1993 to January 2007. All
variables are as described in Table 3. Age, employees, capital raised and number of owners are in log in all
regressions. In all Regressions the ownership fraction of the single biggest owner before the (…rst) o¤ering
is included. In Regression 1 and 2 savings banks (13) are dropped. Regression 2 includes White (1980)
robust standard errors. In regression 3 all savings banks (13) are included. No independent variables have
a correlation above 0.5.
Dummy IPO (1) or Private Placement (0)
Intercept
Holding fraction of largest owner before o¤ering
Reg 1
Reg 2
Reg 3
-4.6415
-4.6415
-4.0439
(-2.9)
(-2.8)
(-2.6)
-1.5283
-1.5283
-1.5313
(-2.5)
(-2.4)
(-2.6)
Largest owner is the CEO dummy
0.2489
0.2489
0.1852
(0.9)
(0.9)
(0.6)
Largest owner is on the board dummy
-0.257
-0.257
-0.303
(-1.0)
(-1.0)
(-1.2)
-3.9762
-3.9762
-5.0464
(-1.6)
(-1.5)
(-2.1)
-0.3744
-0.3744
-0.3821
(-1.3)
(-1.3)
(-1.3)
The founder is on the board dummy
0.2393
0.2393
0.1855
(0.9)
(0.9)
(0.7)
Age of company
0.1346
0.1346
0.203
Her…ndahl index
The founder is the CEO dummy
Number of employees
2006 dummy
Family …rm dummy
Capital raised
N. Owners before the o¤ering
Net result / Total Assets
Dividend / Total Assets
IT dummy
Observations
Pseudo R -squared
94
(1.6)
(1.4)
(2.6)
0.077
0.077
0.0556
(1.4)
(1.3)
(1.0)
-0.5095
-0.5095
-0.5206
(-2.1)
(-2.2)
(-2.2)
-0.4829
-0.4829
-0.5055
(-1.7)
(-1.8)
(-1.8)
0.2998
0.2998
0.2789
(3.6)
(3.4)
(3.4)
-0.1183
-0.1183
-0.145
(-1.6)
(-1.6)
(-2.0)
0.3284
0.3284
0.3076
(1.2)
(1.7)
(1.1)
3.9909
3.9909
3.0634
(0.8)
(0.8)
(0.6)
0.421
0.421
0.4179
(1.5)
(1.6)
(1.5)
198
198
211
15.8%
15.8%
16.9%
Table 5
Private Placements and Private Bene…ts of Control of Block Owners
This table reports the coe¢ cients and t -statistics in parentheses for the regressions with the dummy
variable that takes the value of one for IPOs and zero for private placements as the dependent variable.
All regressions are standard Probit models. The sample period is September 1993 to January 2007. All
variables are as described in Table 3. Age, employees, capital raised and number of owners are in log in
all regressions. In all Regressions the combined block ownership fraction of all investors with a holding
percentage above 5% before the (…rst) o¤ering are included. In Regression 1 and 2 savings banks (13) are
dropped. Regression 2 includes White (1980) robust standard errors. In regression 3 all savings banks (13)
are included. No independent variables have a correlation above 0.5.
Dummy IPO (1) or Private Placement (0)
Reg 1
Reg 2
Reg 3
-3.7758
-3.7758
-3.1326
(-2.3)
(-2.2)
(-1.9)
Combined block ownership fraction
-2.0244
-2.0244
-2.0456
(-2.8)
(-2.8)
(-2.8)
Largest owner is the CEO dummy
0.2298
0.2298
0.1654
Intercept
(0.8)
(0.8)
(0.6)
-0.2156
-0.2156
-0.2618
(-0.9)
(-0.9)
(-1.1)
1.515
1.515
0.4645
(0.8)
(0.8)
(0.2)
-0.3396
-0.3396
-0.348
(-1.1)
(-1.1)
(-1.2)
The founder is on the board dummy
0.2199
0.2199
0.1652
(0.8)
(0.8)
(0.6)
Age of company
0.1298
0.1298
0.2004
(1.6)
(1.4)
(2.6)
0.0945
0.0945
0.072
(1.7)
(1.6)
(1.4)
-0.4829
-0.4829
-0.4951
(-2.0)
(-2.0)
(-2.1)
-0.5202
-0.5202
-0.5425
(-1.8)
(-1.9)
(-1.9)
0.2786
0.2786
0.256
Largest owner is on the board dummy
Her…ndahl index
The founder is the CEO dummy
Number of employees
2006 dummy
Family …rm dummy
Capital raised
N. Owners before the o¤ering
Net result / Total Assets
Dividend / Total Assets
IT dummy
Observations
Pseudo R -squared
95
(3.4)
(3.3)
(3.2)
-0.1256
-0.1256
-0.1521
(-1.7)
(-1.7)
(-2.1)
0.3123
0.3124
0.2913
(1.2)
(1.6)
(1.1)
4.5216
4.5216
3.4597
(0.8)
(0.9)
(0.7)
0.4253
0.4253
0.4199
(1.5)
(1.6)
(1.4)
198
198
211
16.4%
16.4%
17.6%
Table 6
Private Placement and Private Bene…ts of Control - Year Fixed E¤ects
This table reports the coe¢ cients and standard t -statistics in parentheses for the regressions with the
dummy variable that takes the value of one for IPOs and zero for private placements as the dependent
variable. All regressions are standard Probit models. The sample period is September 1993 to January
2007. All variables are as described in Table 3. Regression 1 and 3 includes year …xed e¤ects and the
combined block ownership fraction before the o¤ering. Regression 2 and 4 includes year …xed e¤ects and
the holding fraction of the single largest owner before the o¤ering. In regression 3 and 4 all savings banks
(13) are included. No independent variables have a correlation above 0.5.
Dummy IPO (1) or Private Placement (0)
Reg 1
Reg 2
Reg 3
Reg 4
Intercept
-4.3351
-5.2256
-3.6263
-4.5002
(-2.2)
(-2.8)
(-1.9)
(-2.5)
Combined block ownership fraction
-1.9282
-1.8672
(-2.5)
(-2.4)
Holding fraction of largest owner before o¤ering
Largest owner is the CEO dummy
0.1811
Largest owner is on the board dummy
-1.5167
-1.4764
(-2.4)
(-2.3)
0.204
0.1156
0.1377
(0.6)
(0.6)
(0.4)
(0.4)
-0.3166
-0.3572
-0.3425
-0.3803
(-1.1)
(-1.3)
(-1.2)
(-1.4)
2.9923
-2.3186
1.305
-3.8551
(1.4)
(-0.9)
(0.6)
(-1.5)
-0.3931
-0.4329
-0.387
-0.425
(-1.2)
(-1.3)
(-1.2)
(-1.3)
0.2501
0.2547
0.1538
0.1625
(0.8)
(0.8)
(0.5)
(0.5)
Age of company
0.1224
0.1342
0.2132
0.2212
(1.4)
(1.5)
(2.6)
(2.6)
Number of employees
0.0924
0.0727
0.0597
0.0419
Her…ndahl index
The founder is the CEO dummy
The founder is on the board dummy
2006 dummy
Family …rm dummy
Capital raised
N. Owners before the o¤ering
Net result / Total Assets
Dividend / Total Assets
IT dummy
Year …xed dummy
Observations
Pseudo R -squared
96
(1.6)
(1.2)
(1.0)
(0.7)
-0.29
-0.1931
-0.3488
-0.2583
(-0.5)
(-0.4)
(-0.6)
(-0.5)
-0.4996
-0.463
-0.5252
-0.4857
(-1.6)
(-1.5)
(-1.7)
(-1.6)
0.3048
0.3271
0.2801
0.303
(3.3)
(3.4)
(3.2)
(3.3)
-0.1051
-0.1027
-0.1416
-0.1416
(-1.3)
(-1.3)
(-1.8)
(-1.8)
0.3574
0.3762
0.3003
0.3239
(1.2)
(1.3)
(1.1)
(1.2)
4.7078
3.4868
3.5196
2.4382
(0.8)
(0.6)
(0.6)
(0.4)
0.4174
0.3761
0.3965
0.3652
(1.3)
(1.1)
(1.2)
(1.1)
yes
yes
yes
yes
193
193
205
205
21.9%
21.6%
22.1%
21.9%
Table 7
Block Owners own more of the Company Following Private Placements
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with the combined ownership percentage
of the biggest owners one month after the listing as the dependent variable. All regressions are standard
OLS models. The sample period is September 1993 to January 2007. All variables are as described in
Table 3. Regression 1 drops savings banks (13). Regression 2 includes savings banks (13). No independent
variables have a correlation above 0.5.
Combined block ownership % after the listing
Intercept
Dummy IPO (1) or Private Placement (0)
Age of company
Number of employees
.
Reg 1
Reg 2
71.1734
67.771
(2.9)
(3.2)
-4.5329
-8.4463
(-2.0)
(-3.3)
2.3088
0.2019
(2.5)
(0.2)
0.435
1.4037
(0.7)
(1.7)
-0.4381
-0.365
(-0.4)
(-0.3)
-1.6963
-0.5708
(-2.7)
(-1.0)
Net result / Total Assets
-2.1682
-1.1675
(-1.3)
(-0.5)
IT dummy
-1.1653
-1.003
Capital raised
N. Owners before the o¤ering
(-0.3)
(-0.3)
Year …xed dummy
yes
yes
Observations
195
208
11.1%
8.1%
Adjusted R -squared
97
Table 8
The Biggest Owner have a Larger Ownership % Following Private
Placements
This table reports the coe¢ cients and heteroscedastic consistent t -statistics (errors adjusted for clustering across …rms Rogers, 1993) in parentheses for the regressions with the ownership percentage of the
biggest owner one month after the listing as the dependent variable. All regressions are standard OLS
models. The sample period is September 1993 to January 2007. All variables are as described in Table 3.
Regression 1 drops the savings banks (13). Regression 2 includes the savings banks (13). No independent
variables have a correlation above 0.5.
Ownership % of the biggest owner after the listing
Reg 1
Reg 2
10.7614
6.9755
(0.5)
(0.3)
-3.4035
-6.3423
(-1.8)
(-3.1)
2.9051
1.3201
(2.5)
(1.1)
Number of employees
0.0852
0.8391
(0.2)
(1.5)
Capital raised
0.9532
1.0741
(0.8)
(1.0)
-1.9657
-1.1421
(-2.6)
(-1.6)
0.7173
1.4292
(0.3)
(0.7)
-6.1962
-5.6924
Intercept
Dummy IPO (1) or Private Placement (0)
Age of company
.
N. Owners before the o¤ering
Net result / Total Assets
IT dummy
(-2.3)
(-2.2)
Year …xed dummy
yes
yes
Observations
195
208
15.7%
9.7%
Adjusted R -squared
98
Figure 1
Timeline of the Listings on the Oslo Stock Exchange
Listing in database is when the company list ownership records in the ownership database. This is
when the ownership records are observed in the data the …rst time. Public o¤ering or Private placement is
when the companies distribute the allocated shares in the ownership database. The private placement can
be at any point in time in the six month period leading up to the listing. The public o¤ering is in most
cases in the month before or the month of the listing.
Timeline of the listing
Private placements
Public o¤erings
Listing in database
Listing in database
Meeting with the OSE
Meeting with the OSE
Six months before the listing
Compliance report
Compliance report
Due diligence
Due diligence
Application submitted
Application submitted
Prospectus is made
Prospectus is made
Private Placement
One month before the listing
Listing month
(Public O¤ering)
Public O¤ering
(Employee o¤ering)
(Employee o¤ering)
Listing
Listing
99
5
Summary
This dissertation consists of the three papers; ’Laddering in Initial Public O¤ering Allocations’, ’Using Stock-trading Commissions to Secure IPO Allocations’and ’Initial Public
O¤ering or Initial Private Placement?’ In the paper ’Laddering in Initial Public O¤ering
Allocations’it is found that it is likely that IPO allocations are tied to after-listing purchases of the IPO shares (IPO laddering). In the paper ’Using Stock-trading Commissions
to Secure IPO Allocations’ it is found that it is likely that IPO allocations are tied to
stock-trading commissions before the allocations. In the paper ’Initial Public O¤ering or
Initial Private Placement?’ it is found that it is likely that private placements are used
to transfer private bene…ts of control from the seller to the buyer.
The overall contribution of these …ndings is an extension to our understanding of how
companies and investment banks allocate shares in initial/primary equity o¤erings. There
is strong evidence supporting the rent seeking view of IPO allocations. Both in terms of
allocating IPO shares based on after-listing purchases (IPO laddering) and allocating IPO
shares based on stock-trading commissions. There is no evidence supporting the academic
view or the pitchbook view of IPO allocations. The thesis also shows that investors with
private bene…ts of controlling companies are likely to sell their control rights in private
placements. The overall conclusion is that both investors and investment banks are likely
to optimize their own return in the equity issuance process.
100
101