PRESTIGIOUS AFFILIATES

1. Studied by :
Namra Mubarak

2.  prestige enhancement a firm engages in
during the year before its initial public
offering.
 As the final year counts down, prestige-
poor firms aggressively hire prestigious
executives and directors and pay higher
prices to do so.

3.  Scholars have long been interested in the
idea that organizations can signal their
worthiness by having affiliations with
prestigious parties .
These prestigious affiliates include
 toptier underwriters
 well-established auditors
 Leading venture capitalists
 prominent alliance Partners
 upper echelons members

4. The first mechanism, the “prestige
snowball model,” represents consolidated
portrayal
of some well-known processes—notably,
“homophily,” social validation, and signaling—
that cause those organizations that already
have the most prestige to steadily
accumulate even more

5. Our second model, the “dressing-up model,” is
built upon a phenomenon that, to our
knowledge, has not been studied in the
context of macro-organizational behavior:
deadline-induced remediation.
(i.e., as the final year counts down) those
firms that are most lacking in prestigious
affiliates will aggressively enlist new
affiliates.

6.  Hypothesis 1. The greater the quantity of
preexisting prestige, the greater the number
of prestigious executives and directors hired
during the year leading up to an IPO.
 Hypothesis 2. As the final year prior to IPO
progresses (as urgency increases), the
greater the number of prestigious executives
and directors hired.

7. Hypothesis 3. The combination (or
interaction)
of increased urgency and scarcity of
preexisting prestige is positively associated
with the number of prestigious executives
and directors hired during the year leading
up to an IPO.
Hypothesis 4. Increased urgency further
enhances the effects of scarcity of
preexisting prestige on the premium that
prestigious executives are paid.

8. sample included all U.S. IPOs issued from
1994 to 1996 in three sectors of the computer
software industry: computer programming
services (SIC 7371), computer software (SIC
7372), and computer integrated
systems design (SIC 7373).
Our final sample
consisted of 242 IPO firms. Pre-IPO financial
data.

9.  size, measured as the market capitalization
at the end of each year
 Financial viability, measured as the
percentage of quarters during the three-
year period in which the firm was
profitable;
 Liquidity, the ratio of annual dollar
value traded to market capitalization; and
 Free float, the percentage of each
company’s shares that are available for
trading in the market.

10. DEPENDENT VARIABLE:
 Number of prestigious executives and
prestigious directors hired each month.
INDEPENDENT VARIABLE:
 Urgency. This was measured as the inverse of
the number of months remaining until the IPO
registration date.
 Scarcity of preexisting prestige
 Personal prestige. This measure was a dummy
variable (coded 1 if a hired executive was
prestigious,and 0 otherwise). This measure was
used to test our compensation hypotheses.

11.  Firm characteristics.
 Number of prestigious underwriters.
 Segment and year dummies.
 Individual characteristics.
 Peers’ compensation.
 Number of preexisting executives, outside
directors,

12. were in support of
Hypothesis 4, indicates that a firm must pay
particularly high compensation if the
executive is prestigious, and the firm lacks
preexisting prestige, and the IPO
registration date is drawing near.
compensation results clearly support the
dressing-up model by indicating that deadline-
induced remediation is possible—but
relatively costly.

13. o we did not have data on any individuals who
were previously with a firm but left prior to
IPO. Relatedly, we lacked data on the
complete employment histories of executives
and directors
o data on when an underwriter
is enlisted is not publicly disclosed.

14.  Section 4 discusses what I term the CLAS
controversies. C is the payment of excessive
commissions by investors. L is laddering, the practice
of allocating shares in return for promises of
additional purchases once the stock starts Trading . A
is biased analyst recommendations, with
underwriters competing for business from issuers by
either implicitly or explicitly promising favorable
coverage from their research analysts. S is spinning,
the practice of allocating shares from other IPOs to
the personal brokerage accounts of issuing
 Section 5 analyzes why average underpricing is so high
 Section 6 discusses why IPO volume has been low in the U.S.
ever since the tech stock bubble burst in 2000.
 Section 7 summarizes the evidence on the long-run
performance of IPOs.

15.  The U.S. has 4 historically been the world’s
largest IPO market
 China has had the most extreme
underpricing

18.  With the exception of 1999-2000, the under
pricing of IPOs in the U.S. has been modest
in comparison to China.

19.  The empirical IPO literature focuses mainly
on returns, both first-day and long-term. Yet,
many questions are about price levels.

20.  Rock’s (1986) adverse selection model
assumes that the issuing firm and its
underwriters do not know the value of the
firm with certainty, but that some investors
do know. There are no agency problems
between issuers and underwriters, so
underwriters play no role.

21.  As long as issuing firms desire favorable
coverage from influential security analysts
 employed by investment banking firms that
also underwrite equity securities, one way to
attract
 business (“winning the mandate”) is to
bundle analyst coverage with underwriting.

22.  Underwriters receive revenue both from the
gross spread paid by issuers on IPOs and
from soft dollars paid by rent-seeking
investors

23.  The author is not aware of any affiliations,
memberships, funding, or financial holdings
that
might be perceived as affecting the
objectivity of this review. The author would
be happy to
receive large amounts of external funding
that would create a conflict of interest

25.  Taylor & Francis makes every effort to ensure the
accuracy of all the information (the "Content”)
contained in the publications on our platform.
 Samuel Sejjaaka
A Makerere University Business School , P.O. Box
1337, Kampala, Uganda.
 Published online: 04 Oct 2011
 To link to this article:
http://dx.doi.org/10.1080/17520843.2011.59

26.  To identify determinants of initial public offers
readiness in large firms that have not yet sought to
raise capital through a stock market.
 A conceptual framework is developed to determine
micro determinants of initial public offers readiness

29. •IPO can facilitate future acquisitions,
higher valuations, debt reductions and
public profile enhancement.
•Making the transition from public to
private can take anywhere from nine to
eighteen months, requiring a huge
commitment in terms of time, effort and
resources on behalf on the organization

30. Once senior executives make the
decision to go forward with an IPO,
there is no guarantee the firm will
succeed. ((Latham and Bran, 2010).
IPO market serves as an economic
indicator :
Due to its proven pro-cyclical nature
Economic Expansion : HOT markets
Regression : COLD markets.

31. Findings or Gap filled by Article :
Investigating a 20-year time series, including
three periods declared recessions by the
National Bureau of Economic Research, of U.S.
IPOs.

32. Collective Gap.
•IPOs occurring during hot markets are
fundamentally different from those occurring
during cold markets.
•By reviewing the theory “Second,
Chemmanur
and He (2011)”
•Firms go public during the hot market will
have
lower productivity and post-IPO profitability.

33. •Do firms that go public in hot markets
have a different survival probability than
firms that go public in cold markets?
•We investigate whether survival
features such as survival probability
and survival duration are the same in
both hot-market and cold-market IPOs.
•We will study whether the
characteristics of firms that went public
in the first half of a hot market
(pioneers) differ from those of firms that
went public in the second half of the
same hot market (followers) .[ALTI

34. Variables
Independent Variable :
COLD MARKET AND HOT MARKET.
Dependent Variables :
Survival of Firm ,Long run performance of Firm.

35. http://www.apjfs.org/conference/2
012/cafmFile/11-2.pdf
http://www.fma.org/NY/Papers/mark
et_volatility_IPO_timing.pdf
REFERENCES
Baker, Malcolm and Jeffrey Wurgler,
2002, Market timing and capital
structure, Journal of
Finance 57, 1-32