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Table of Contents page
COURSEWORKHEADER SHEET.........................................................................................................................................1
1. INTRODUCTION ................................................................................................................................................4
2. LITERATURE REVIEW:.....................................................................................................................................5
2.1 INITIAL PUBLIC OFFERING AND POST IPO PERFORMANCE...........................................................................................5
2.2 IPO UNDERPRICING.....................................................................................................................................................6
2.3 POST IPO PERFORMANCE IN LONG RUN.......................................................................................................................7
2.3.1 Overoptimistic investors and timing of IPO.......................................................................................8
2.3.2 Buy and hold return............................................................................................................................8
2.3.3 Signaling hypothesis...........................................................................................................................9
2.3.4 Firm ownership and long-term performance......................................................................................9
2.4 SUMMARY:................................................................................................................................................................11
3. RESEARCH OBJECTIVE AND THE HYPOTHESIS ........................................................................................ 11
3.1 BACKGROUND OF UK IPO MARKET ..........................................................................................................................12
3.1.1 Pre flotation preparation and sales methods.....................................................................................12
3.1.2 Underpricing in UK market..............................................................................................................13
3.2 HYPOTHESIS..............................................................................................................................................................14
4. RESEARCH DESIGN ........................................................................................................................................ 14
4.1 DATA.........................................................................................................................................................................14
4.1.1 Data Type And The Matching Firms................................................................................................16
4.2 METHODOLOGY.........................................................................................................................................................18
4.3 RESULT ANALYSIS: AVERAGE RETURN .....................................................................................................................21
4.4 REGRESSION ANALYSIS.............................................................................................................................................24
4.4.1 Result Analysis:................................................................................................................................28
4.4.2 Cross-sectional regressions analysis.................................................................................................31
5. CONCLUSION .................................................................................................................................................. 32
6. REFERENCE LIST: ........................................................................................................................................... 33
7. APPENDICES.................................................................................................................................................... 37

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ABSTRACT
In this paper the research has been carried out over the 100 IPOs from UK stock market during 2000 to
2008 time period. To evaluate the IPO performance, 100 matching firm from the same industry have
been included in the sample size that have a close market capital with those IPOs. Daily average return
and the cross-sectional regression methods have been used to conclude the research result. In both cases
the research result reveals the underperforming characteristics of IPO return in compare to the matching
’ a y. In short run IPOs tend to generate more return than those of
matching firms. However, long run study suggests that the IPO starts performing badly after the next
few months of first trading day in the open market.
Key Words: IPOs, Matching Firm, Underpricing, Short-run performance, Long-run performance.

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1. Introduction
Perhaps the most basic answer why a company goes public is, to raise equity capital for the company
and create a public market from where the existing shareholders can convert part of their wealth into
cash. However, the real answer lies way beyond simply just concentrating on raising equity and
turning wealth into cash. In real world this notion is rather more complex and diversified.
Black and Gilson (1998) suggested that Initial Public Offering (IPO) is a way out of reestablishing
control by entrepreneurs over venture capital backed companies. Maksimovic and Pichler (2001)
believe that products achieve market competitiveness while company shows a higher public price. It
is also believed that going into public as pioneer from certain industry confer advantages of being
market leader. These are out of many potential reasons why a company might choose to float on the
stock market. Nevertheless, getting into flotation opens a door of more diverse and sophisticated
legislative world to the companies which requires them to produce, record, and present information
in specific ways. This process are significantly time consuming and expensive for companies. Above
all, no other issues are more sensitive than the agency relationship between the companies and the
directors who run the company on behalf of the shareholder. Thus, agency relationship demands
remunerations and other incentives which are very costly. On the other hand monitoring their works
require an effective auditing procedure along with strong internal control system and failing to do so
might trigger a potential going concern risk for the company.
There are many examples of well known corporate failure in recent years which permanently
changed both the business world and regulatory authorities in terms of the way they act, operate, and
think ever since. The recent development and redrafted (i.e. Sarbanes Oxley Act of 2002, ‘The UK
corporate Governance Code 2012) regulations imposed significant amount of new obligations over
the public limited companies across the world, Li (2010). For instance in UK every listed company
is expected to comply with corporate code of governance, a proper and acceptable explanation has to
be submitted otherwise (Financial Reporting Council, 2012). On the other hand Sarbanes Oxley Act
of 2002 in USA is one step forward.
Following the spectacular, highly-publicized frauds revealed at Enron, WorldCom, and Tyco
between 2000 to 2002, Sarbanes Oxley Act of 2002 has been published administrating by the
security and exchange commission to prevent such occurrence in future (Zhang, 2007). It requires
public companies to practice a good governance along with setting up effective internal control
system in addition to this, executive of the company obliged to report and certify that an effective
internal control system is in place and again failing to do so may result a penalty or even prosecution
for the executives of the company ( Ge and McVay, 2005).

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All these information suggest that, being a listed company in modern corporate world is not a
pleasant business at all. Therefore, the questions arise, after all these obligations and expensive
procedure of regulations, why a company might still choose to get listed offering IOPs. What are the
incentives behind it and how this IPO helps companies to achieve their corporate goals.
The objective of this research is to find out the answer of above questions by researching on the
possible relation between the company’s stock performance and the Initial Public Offering. There is
no denying that the most fundamental objective of a company is to maximizing the wealth of
shareholder by improving its operational performance as well as the profitability. Therefore the
initial focus of the research was on firm’s post-IPO operational and financial performance. This
research has been conducted precisely over a number of UK firms listed in London Stock Exchange
from 2000 to 2008. To carry out the process, specific data sets have been collected, processed and
analyzed using the most relevant methodology to obtain the optimal level of outcome.
2. LITERATURE REVIEW:
2.1 Initial Public Offering and post IPO performance
The post year IPOs share price performance captured more attention of researchers than perhaps any other
facets regarding IPO. And consequently the numbers of research on this relevant subject are extensive. The
essence of the majority researches are to find out the driving forces which influence the stock price movement
after the subsequent years of first public offering.
The substantial numbers of researches have come up with many different findings and various aspects of IPOs
to be discussed. Some results show that, IPOs price tend to go up shortly after the flotation on the stock
market (Ritter, 1984). Many researchers suggested that IPOs are usually issued at a lower price than the
actual value of the share price which leads to underpriced IPOs. According to a number of scholars,
Underwriter reputations and experiences are influential factors in terms of the IPOs price movement in short
run (Beatty and Ritter, 1986). There is also a claim by another group of researcher that in short run IPOs price
goes up at a certain tempo and it starts falling again to adjust the actual market price.

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Arguably, there are some points where handful of the research shows similar results. However, the overall
results are rather diversified and inconclusive in many aspects. The empirical review finds two basic areas
where the researchers discussed their findings more elaborately. These are as follows;
 IPO Underpricing
 Post IPOs performance in Long run.
The following literature review has been drawn based on the available research articles from financial and
accounting journals. A whole range of articles have been studied to identify the most critical points regarding
the IPO performance. Substantial period of time has been covered to find out the past dated research results;
this time horizon has started from as early as 1982 up to the recent time. The overall literature review has
been segregated in to two parts. Each of the parts contains the empirical discussion and findings over the (a)
IPO Underpricing and (b) Post IPOs performance in Long Run, respectively.
2.2 IPO Underpricing.
It is commonly believed that stock price takes an upward move after the first trading day in the open market
(Ritter, 1984). Some argue that the reason of such increasing price is ‘under pricing’ at the first place. Some
also believe that it the underwriters who under price the stocks to ensure the optimal level of open market
selling of the new stocks. Thus, there is an abnormal gain opportunity arise from such situation. However,
Carter and Manaster (1990) Beatty and Ritter (1986), Titman and Trueman (1986) all report that underpricing
is less likely to be occurred when a reputed underwriting firm advocates the IOP process. The idea behind the
argument is, well-known underwriting firms tend to underwrite relatively less risky IPOs to maintain their
reputations in the market which creates a negative relation between the under pricing and the reputation of
underwriter.
According to the adverse selection theory developed by Rock in 1986, there are two groups of investor in the
market, Informed and uninformed. As per theory, investors who are informed possess information about the
actual value of the IPO stock. On the other hand, the uninformed investors lack of knowledge regarding the
proper share price. Thus, they invest their money randomly. Furthermore, Rock (1986) suggest the investment
bank as an underwriter has the actual information of the value of IPOs therefore the issuing company has to
rely on the underwriter’s review for this information. As company’s share number is constant the demand
level of such share makes the price to fluctuate and this demand is divided into informed and uninformed of
investors thus an IPO price reflecting true value would leave only ‘uninformed investors’ in a position where
they either break even or lose money because the informed investors would only invest in the good IPOs and
making the profits. In that case, uninformed investors lose interests to participate in IPO market and
consequently this reduce the demand of IPO in the stock market for those firms’ who have a less impressive
performance and they are forced to issue an underpriced IPO.
Rock (1986) reports that some firms issue underpriced IPOs on purpose so that the uninformed investors take
part in the stock market which would ultimately maintain the current demand of the stock in the market.
However the company with a better value is less likely to issue an IPO with underpriced as there are already a
good demand of their share among the informed investors.

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The pricing mechanism above therefore indicates that IPO underpricing depends upon the uncertainty and the
actual value of the issuing firm. A further study on IPO underpricing suggests that there are numbers of
relevant theories which explain the underpricing of IPOs. However, in most of these theories largely focused
on some asymmetric information among investors, issuers and underwriters to evaluate the reason behind the
IPO underpricing.
A second theory over the underpricing evaluates the relationship between issuing firm and the investment
bank. A study by Baron (1982) discussed Hazard model of underpricing. This model of underpricing assume
that issuing firms rely on the auditing of the investment bank to address the actual information as they are
generally unaware about their own genuine market value. The IPO contract agreement between the
investment bank and the issuing firm undertakes based on the report provided by the investment firm over the
value of the firm. Contracts like this tend to satisfy various conditions demanded by each entity. Such as the
agreement price has to fulfill a minimal amount of return expected by the investment bank, also the IPO price
is expected to be relatively low to encourage investment bank to act in the best interest of issuing firm. This
theory also states that uncertainty level of the information that investment bank’s provide to the issuer firm is
positively correlated to the underpricing. Therefore, the cost of truthful efficient advice from the investment
banks can be reduced by underpricing IPO.
This hypothesis agrees the opinion given by Rock over the underpricing of small and less established
companies. Rock claimed that a small sized firm does not have similar opportunity as a large firm to perform
efficient internal audits however he criticized Baron’s model saying that this model is excessively simplistic
which does not consider the competitions among the investment banks within their business which could
create some level of agent loyalty. This model also does not consider the point that investment banks could be
concerned about its reputation which creates the incentive to generate the information for the issuing firm
which is credible and truthful. However, the relationship between the true value and the level of underpricing
can easily be identified from this model.
2.3 Post IPO performance in long run.
Ritter and Welch (2002) also stated that, long term performance of post-IPO is more of a standard asset
pricing issue than of an IPO or Corporate finance issue. In an earlier research Ritter, J. (1991) used a sample
of 1526 IPOs from the US market who were listed between 1975 and 1984. He found that over 3 years after
the companies’ gone public they notably underperformed market index as well as the similar size unlisted
companies within the industry and these conditions remain largely unchanged almost 6 years after the first
IPO Loughran and Ritter (1995) Study a sample of 4753 issues from 1970 to 1990 and reveal a result that
stock underperformance takes an over turn from the fifth year of the IPO. Another group of researchers
explain the over optimism as a driving force of underperformance (Heaton, 2001) and (Welch, 2001). They
believe that the underlying idea is in shorter period after the IPO, stock price takes a sharp increase from its
fundamental level of value but in long run this increased price starts to adjust the firms’ actual value and as a
result it takes a decline from its overvalued position which triggers an IPO to underperform in long run.
Several other studies have also discussed on post issue IPO share performance and in most of that studies
reveal that IPO firms show a decline in its operating performance based on cash flows deflected by asset
measures (Degeorge and Zeckhauser, 1993). As the reasons of such declining operating performance
researchers indicates few major factors which are directly related to the IPO underperformance. Underwriting
agency costs, Prior IPO window dressing in accounting information by the management, timing the offering

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to match with the abnormally high performance that reduce after the IPO, are among many factors mentioned
by those researchers which cause the post IPO underperformance (Jain and Kini, 1994). However, in contrast
they said that these firms also achieve a growth in sales and at the same time their capital expenditures are
high comparing to the other non listed firms in the industry as a result potential investors are attracted from
this.
The literature review over the long term IPO performance covers a larger area of discussions including many
different arguments over the issues and hypothesis regarding IPOs. The following part of literature review
shades a light on the major topics alongside some hypothesis related to IPO performance in long run.
2.3.1 Overoptimistic investors and timing of IPO
Loughran and Ritter (1995) explain, one of the major factors behind the stock underperformance is over
optimistic perception of the investors regarding the company’s post IPO performance. Loughran, at el. (1994)
propose that issuer companies time their IPOs to match with the time of over optimism. Therefore a company
goes in public when they consider the public reactions level stay at pick position.
In a study Jain and Kini (1994) assess investor expectations of post-IPO earnings growth using the price
earnings ratio and the market to book value of 682 IPOs in a time period of 1976 to 1988 and they found a
major decline in performance. Similar result can be drawn from Ritter (1991) and, Loughran and Ritter (1995)
where they stated, investors are usually over optimistic on the pre-IPO performance as well as the post
performance in long run. Therefore it is assume that IPO firms fail to maintain their pre issue performance
levels. With an expectation of increased profit margin post IPO share price raise. However, the empirical
evidence suggests this is not happen in most of the cases. As such, falling stock prices drag the overall firm
performance at a minimum level. Size of the IPO is another factor where investors are keen to look at before
proceeding with their investments. A larger size IPO generally comes from larger organization with high level
of capital and strong profitability which gives the shareholder confidence of better performing IPO in long
run.
2.3.2 Buy and hold return
Santos (2010) conducted a research over the IPO performance on both long and the short term of newly listed
companies. In his paper he worked on the buy and hold returns along with the first day returns. His study
reported that IPO underperformance begins from the first day closing stock price, this underperformance is
also related the underpricing of the stock during the first trading day of IPO in the open market. He blames
both the issuer firm and the investors for this underpriceding of initial stock. Santos (2010) also mentioned in
his paper that how unusually poor post IPO perform is still inclusive, and even if the long term return is
exceptionally low it is very difficult to conclude a statistical decision on that. He mentioned that, an access of
-40 percentages is required to refuse a hypothesis on underperformance. However, he claimed that IPOs and
the firms which have similar characteristics perform badly while the overall market has experienced a very
promising result.

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2.3.3 Signaling hypothesis
The signaling hypothesis has been coexisted with many other widely discussed theories regarding IPOs. This
hypothesis refers to the information associated with the reputation of Underwriter, size of the IPOs and
companies’ historical operating and financial performance. Some believe that these signals eliminate the
information asymmetry risks among the IPOs issuer and the Investors, which have obvious influence over the
long run IPO performance. Investors tend to assess IPOs quality referring the underwriters reputation as well
as highly regarded associate audit firm who works in IPOs issue process. Before IPO issue companies usually
publicize their historical financial performance along with the projected operational targets, these include the
equity quality, annual profits, asset turnover and target dividend for the shareholder. Reputed auditors make
sure the credibility of this information while same category underwaters ensures the quality of IPOs they are
undertaking. Thus, investors infer that companies employing high standard agencies on IPO issue process
should be performing better in long run.
2.3.4 Firm ownership and long-term performance
The correlation between firm ownership and the long-run IPO performance has been a debate since the early
age of the IPO research. Like other area of IPO, researchers have different opinion regarding this relationship.
Referring to Jain and Kini (1994) and Meeta (1997) a research over the US IPO market where they find
different results on ownership structure and IPO performance. As per Meeta (1997) long-run IPOs returns
over the first year of offering and following ten years of public trading have been negatively correlated with
the ownership structure of the company. Whereas Jain and Kini (1994) research suggest that there is fairly a
strong relationship between IPO performance and the ownership structure in long run of the IPO operation.
This research has been conducted using 682 IPOs from US market listed between 1976 and 1988. They
suggest that companies’ operating performance declines after IPOs issue comparing to the operational
performance before listing in the stock market. As soon as the organization got listed, previous management
(mainly the previous owner) lose the partial control over the company’s operation along with the incentive to
do best for their organization. New agency relationship between shareholder and the management causes
additional costs and monitoring time for the company which contribute to the deterioration of its long term
performance.

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Table1: Empirical evidence on the long-run performance of IPOs across countries
COUNTRY REFERENCE NUMBER OF IPOs YEAR OF ISSUE
AFTERMARKET
PERFORMANCE (%)
Australia Lee, Taylor and Welter (1996) 266 1976-1989 -46.5
Austria Aussenegg (1997) 57 1965-1993 -27.3
Jog (1997) 130 1971-1992 -35.13
Kooli and Suret (2002) 445 1991-1998 -16.86
Clile Aggarwal et al. (1993) 28 1982-1990 -23.7
Finland Keloharju (1993) 79 1984-1989 -21.1
Germany Liungqvist (1997) 172 1971-1990 -27
Japan Cai and Wei (1997) 172 1971-1990 -12.1
Korea Kim et al. (1995) 99 1985-1988 1.2
Mexico Aggarwal et al. (1993) 38 1987-1990 -19.6
Newzealand Firth (1997) 143 1979-1987 -10
Sweden Loughran et al. (1994) 162 1980-1990 1.2
United Kingdom Levis (1993) 712 1980-1988 -8.1
Loughran and Ritter (1995) 4753 1970-1990 -20
Brav et al. (2000) 4622 1975-1992 -44.2
United States
Canada

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2.4 Summary:
In summary the overall literature review extracts several factors which come across in various research
results. Two major areas came under the light of discussion while researchers study the IPO performance. (a)
IPO Underpricing and (b) Post IPO performance in long run.
Firm’s unawareness of the actual value of its own stock is one of the primary reasons why IPO experience an
underpriced stock value. To sustain the demand of stock in the market, firms artificially underprice their
IPOs. So that both informed and uninformed investors keep showing their interest over the newly arrived
IPOs in the stock market. Pre IPO poor performance by the firm is another factor been considered as a direct
reasons of IPO underpricing.
On the other hand a negative correlation between reputed underwriting firms and the IPO underpricing has
been identified by many research results. Also pre IPO healthy firm performance can prevent the IPO
underpricing.
IPO performance in long run has considered being the most controversial area of this review. Some research
claimed that most of the IPO firms experienced a three-year underperformance after the first entry into the
stock market. Few research believe this underperformance continue for a longer period of time while some
proved an overturning performance from the fifth year of the IPO.
Majority of the research claimed the over optimistic investor as the key reason behind the firm
underperformance after it goes public. However others found a direct link between the initial underpricing
and the long term IPO under performance. Also the change of ownership contributes a negative effect on
companies’ operating performance in long run. Nevertheless, some research report a complete different
opinion stating that how unusually poor post IPO perform is still inconclusive.
3. Research Objective and the Hypothesis
Literature review above suggests a diversified results and opinion over the post IPO firm performance.
Particularly the long run performance evaluation was largely inconclusive. Moreover the methodologies used
in those researches do not accommodate all the variables of IPO performance measures. For instance, many
researches concentrate over the average IPOs performance. However, addressing full determinates of cross
sectional variation in IPO returns were missing from their study. Due to different legislative obligations, IPO
might perform in different ways in different stock market. Therefore, a single set of evaluation process would
not be relevant for all the firms across the world.
Ideally the objective of this paper is to report the result from analysis of IPO performance in long run from
UK market. This research includes studying price trend of the fresh IPOs over short term and long term to
identify the price variances and the possible reason behind that. Outcomes of this research are expected to
contribute financial literature investigating the UK stock market. The study of British IPO market gives inside
of some interesting aspects of practical as well as the theoretical importance. Practically investors are keen to
understand if the IPOs are overpriced in long term. In terms of theoretical aspect this study also helps to
obtain functional inferences given the specific regulatory rule and practices characterizing the UK stock
market. The presence of large number institutional investors including mutual funds, pension funds, and
insurance companies gave it a distinctive feature over other stock markets around the globe. This institutional

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investors brings up with a significant amount of investments therefore the active investment strategy has a
strong practice among those investors. It also has more than 200 years of trading history which makes the
LSE a very mature and established trading place for the IPOs. Arguably majority of investors seem to behave
rationally however still there are many factors about how some of the investors behave in certain ways are
broadly unexplained. Taken into consideration of above points, this paper has conducted the research aiming
to find out the answers of some of those long standing unexplained factors as well as to provide supportive
evidence to the existing literate on UK IPO market.
3.1 Background of UK IPO market
3.1.1 Pre flotation preparation and sales methods
Before going public UK companies tend to restructure their senior management role along with the capital
structure. This includes appointing new and more experienced management personnel and writing off the long
term loans from the company’s balance sheet so that it looks attractive to the potential investors. (Curwen,
1986; cited in Menyah et al. 1995)
For the monopolistic organizations these restructuring encounters regulatory provisions which are designed to
encourage the productive and efficient competition within the market. Regulatory bodies have been
established for specific sectors such as gas, electricity, water, as well as the telecommunication companies.
Price control and reassuring competitions are among the other primary functions of these regulatory
authorities. Thus, unlike companies from other sectors, privatized monopolies are expected to encounter some
obligations from changes in rule. However, review of such regulations is usually carryout in every five years
which provides a bit more flexibility for those companies. Many believe that the regulatory obligations of a
company are a price determinant in the UK IPO market. Before floating on the stock market, companies
usually conduct a rigorous publicity of their operations using mainstream media to create a better impression
of their organization. Private sectors IPOs however restrain themselves from such heavy public exposure.
Consequently private companies sell an average of 30% of their share to the IPO in the UK market (Rouse
1990; cited in Menyah et al. 1995) on the other hand (Menyah et al. 1995) claimed that in their research
sample 33 out of 40 companies sold 100% of their share by government. The objective of selling all shares
was to bring autonomy in their operation so that all those companies can run commercially successful
operation. Some also argue that this proceeding was a part of government policy to meet the target income
from privatization sales.

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Information gathering process prior to the offer price fixing is rather informal in UK IPOs market than the
model proposed in Benveniste and Spindt (1989). It is also common for the government to control the final
share allocation process among the investors. Thus, underwriters are unable to manipulate share allocation
mechanism to generate incentives for forthright indication of interest. To create the IPO demand to a wide
range of subscribers, certain percentages of shares are allocated initially by the authority to be sold among
retail investors, institutional investors as well as international investors. If the application for those IPOs
outnumber the total issue number then the retail investors get the provisionally allocation of share followed by
the institutional and the overseas investors.
In the case of oversubscription who applied for the less number of shares are given priority from the retail
investors. Those who apply for a larger quantity of share get a fraction of allocated share in the event of
oversubscription. There was also an installment payment facility been introduced to encourage the smaller
investors to subscribe the new issue in the UK IPOs market. Share allocation and payment procedures
however are the same for all categories of IPOs applicants. Those who are issued a partial allocation of share
get the refund normally after the first trading day of the share in the open market. Thus, there might be an
opportunity cost involve in the whole process for the investors.
3.1.2 Underpricing in UK market
It has empirically suggested that the UK IPOs are generally issued at underprice. However, there are lacks of
investigation behind the common cause of these results (Menyah et al. 1990; and Levis 1993). UK
government’s target to increase the share ownership among the investors drives the IPOs to offer at a lower
price which is associated with the IPOs under pricing in this market (Vickers and Yarrow 1988). According
to Jenkinson and Mayer (1988) on the other hand public sector IPOs causes more underpricing than their
private sector counterpart regardless the selling methods are remain same. They also argued that if the shares
are sold a smaller volume initially at market price to gain the investors’ confidence and after selling the rest of
the called up shares can help to reduce the amount lost from underpricing.

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3.2 Hypothesis
The overall research would be designed to perform a conclusive result on the UK IPO performance. The
whole process is divided into two time segments. Firstly it will be focusing on the short-term performance of
IPO return by perusing the answer of Hypothesis 1 which is been drawn as bellow
 Hypothesis 1: Due to underpricing UK IPOs perform better in short term.
And secondly the long term IPO performance will also be assessed with the answer of following hypothesis
question.
 Hypothesis 2: In long-run UK IPOs suffer a decline compare with the matching firms in
same industry.
The above hypothesis will be answering the most common debating points over the UK IPO market. As well
as these will implement the research ground in the paper. The research design and methodologies are
explained in the following part as the process continues.
4. Research Design
4.1 Data
The data sets have been selected form UK IPO market dated from 2000 to 2008. Followed by the 2008
financial crisis, share markets all over the developed economies experienced a very unusual period in open
market trading, as a result IPOs and the existing share market behavied irationally for a substancial period of
time. This is a reason why this research has been condected over the pre financial crisis IPOs to get the more
representative results. The random walk theory suggests a weak form of market efficiency in UK stock
market which gave an unpredictable degignation to the UK share price movement. All IPOs price movement
therefore follow the similar pattern as other well known stock market across the reason. This price behiviour
provieds an ideal opportunity to evaluate the IPO performance in the UK market using conventional data
analysis tools and methods. There were 892 companies listed in London Stock Exchange as at 30th
april 2013,
among those 230 companies got listed between 2000 and 2008. Out of 230 companies 18 have terminated
their operations in the mean time, therefore those companies have been eleminated from the sample size.
Those companies who had less than 6 months of data available have also been taken off as sample IPO in line
with those do not have similar size matching IPOs in the stock market. Thus, 100 IPOs have been chosen
finally out of 230 IPOs from that time period. These IPO are consist of 30 different industries totaling £
140072.94 million worth in value. The majority issued IPO are from Equity Investment Instruments (22
firms) worth £ 1349.6395 million alone followed by the Support service, from which 11 new firms have issed
new IPO in the stock market with a total value of £ 8517.1466 million pound. Table 2 showes the list of the
sectors and the total market capital of those 100 IPOs.

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The following criterias have been considered to chose the sample IPOs form the UK stock market. (1) Face
value of the share is £1.00 or more, (2) The offer involved sommon stock only, (3) All the stock are from the
main market. (4) At liest 6 month of data availability before the end of 2008. (5) Available matching firm in
the same industry with a similar size market capital.
Table 2 : List of IPOs and Their Total Market Capital
SECTOR NO. IPO M.CAPITAL MILLION
Aerospace & Defence 1 1,250.64
£
Alternative Energy 1 43.24
£
Beverages 1 1,065.04
£
Construction & Materials 1 92.84
£
Electricity 1 2,462.15
£
Electronic & Electrical Equipment 1 252.82
£
Equity Investment Instruments 22 1,349.64
£
Food Producers 1 425.46
£
General Financial 9 15,901.18
£
General Retailers 6 9,658.50
£
Health Care Equipment & Services 3 771.72
£
Household Goods 1 33,563.54
£
Life Insurance 2 9,097.38
£
Industrial Transportation 1 64.31
£
Media 5 3,236.44
£
Mining 3 6,243.39
£
Mobile Telecommunications 1 3,234.95
£
Nonlife Insurance 1 3,475.59
£
Nonequity Investment Instruments 4 174.86
£
Oil & Gas Producers 1 465.85
£
Oil Equipment, Services & Distribution 1 2,876.86
£
Personal Goods 1 5,869.67
£
Pharmaceuticals & Biotechnology 3 2,740.88
£
Real Estate Investment Trusts 2 590.75
£
Real Estate Investment & Services 3 621.90
£
Support Services 11 8,517.15
£
Software & Computer Services 3 2,199.57
£
Travel & Leisure 7 22,416.66
£
Technology Hardware & Equipment 3 1,409.96
£
TOTAL 100 140,072.94
£

15. 16 | P a g e
4.1.1 Data Type And The Matching Firms
Daily closing adjusted share price of those 100 firms have been downloaded using the DataStream. At the
same time a cross check has been made with the data from yahoo finance to ensure data validity. Following
the data collection a shorting have been performed according to the criterias mensioned above. For each IPOs
, a matching firm was chosen and the share price was collected using the same technique. To achieve the best
possible comperison among IPOs and the existing firms’ performance, all matching firms are chosen from the
same industry as those IPO. And also the total market capital of each firm had to be close as those IPOs to be
selected as a matching firm. Tabel 3 bellow shows the sample list of IPOs and the Matching firms as
described
Table: 3 list of IPOs and the matching firms
Number LIST DATE COMPANY NAME SECTOR Mkt Cap £m LIST DATE COMPANY NAME SECTOR Mkt Cap £m
1 28-Sep-04 ADMIRALGROUP PLC Nonlife Insurance 3475.5943 03-Jul-89 RSA INSURANCEGROUP PLC Nonlife Insurance 3952.717307
2 05-Apr-07 ALBION ENTERPRISEVCTPLC Equity InvestmentInstruments 27.6398 04-Apr-96 ALBION VENTURECAPITALTSTPLC Equity InvestmentInstruments 26.31685004
3 07-Oct-04 ALBION INCOME&GROWTHVCTPLC Equity InvestmentInstruments 27.2589 12-Apr-01 BRITISHSMALLERCOMPANIESVCT2PLC Equity InvestmentInstruments 26.70442769
4 17-Jan-01 ALBION TECHNOLOGY&GENERALVCTPLC Equity InvestmentInstruments 32.6364 24-Apr-53 UK SELECTTRUST Equity InvestmentInstruments 33.155967
5 25-Mar-04 ALTERNATIVEASSETOPPORTUNITIES Nonequity InvestmentInstruments 18.4000 28-Jul-66 RIGHTS&ISSUES INVESTMENTTRUST Nonequity InvestmentInstruments 78.4097272
6 03-Aug-04 AMATI VCT2PLC Equity InvestmentInstruments 30.9506 24-Apr-53 UK SELECTTRUST Equity InvestmentInstruments 33.155967
7 29-Mar-05 AMATI VCTPLC Equity InvestmentInstruments 35.3334 04-Apr-96 KINGSARMSYARDVCTPLC Equity InvestmentInstruments 34.86690883
8 08-Mar-04 ARK THERAPEUTICSGROUP Pharmaceuticals &Biotechnology 0.8685 25-Apr-96 PHYTOPHARMPLC Pharmaceuticals &Biotechnology 4.853484062
9 14-Dec-04 ARTEMISVCTPLC Equity InvestmentInstruments 30.8065 24-Apr-53 UK SELECTTRUST Equity InvestmentInstruments 33.155967
10 17-Oct-06 ASHMOREGROUP PLC General Financial 2823.8309 16-Mar-62 PROVIDENTFINANCIAL General Financial 2250.453531
11 18-Dec-02 BARINGEMERGINGEUROPEPLC Equity InvestmentInstruments 168.0706 09-Mar-95 SCHRODERINCOMEGROWTHFUND Equity InvestmentInstruments 168.123244
12 30-Jan-01 BARONSMEADVCT3 Equity InvestmentInstruments 74.0292 20-Dec-94 MITON INCOMEOPPSTRUSTPLC Equity InvestmentInstruments 73.4631156
13 20-Dec-01 BARONSMEADVCT4 Equity InvestmentInstruments 67.0305 21-Oct-81 MIDWYNDINTLINVESTMENTTRUSTPLC Equity InvestmentInstruments 67.6968516
14 13-Mar-06 BARONSMEADVCT5PLC Equity InvestmentInstruments 34.7553 04-Apr-96 FORESIGHT3VCT Equity InvestmentInstruments 34.113184
15 07-Jun-02 BIGYELLOWGROUP Real Estate InvestmentTrusts 565.9964 15-Dec-93 WORKSPACEGROUP PLC Real Estate InvestmentTrusts 541.4072138
16 13-Dec-05 BLACKROCK COMMODITIESINCINV TST Equity InvestmentInstruments 107.8049 13-Feb-73 CAPITALGEARINGTRUST Equity InvestmentInstruments 105.7005972
17 20-Sep-04 BLACKROCK GREATEREUROPEINV TST Equity InvestmentInstruments 269.2948 21-Oct-52 NORTHAMERICAN INCOMETST(THE) PLC Equity InvestmentInstruments 262.85299
18 12-Dec-01 BLACKROCK INCOME&GROWTHINV TRUST Equity InvestmentInstruments 43.4665 21-Feb-94 MITHRASINVESTMENTTRUST Equity InvestmentInstruments 43.38231325
19 12-Apr-01 BRITISHSMALLERCOMPANIESVCT2PLC Equity InvestmentInstruments 26.7044 04-Apr-96 ALBION VENTURECAPITALTSTPLC Equity InvestmentInstruments 26.31685004
20 14-Dec-05 BRITVIC Beverages 1065.0376 02-Apr-70 BARR(A.G.) Beverages 639.8929034
21 18-Jul-02 BURBERRYGROUP Personal Goods 5869.6664 26-Nov-53 PZCUSSONS Personal Goods 1712.543309
22 23-Jun-08 CADOGAN PETROLEUM Oil &Gas Producers 32.0640 06-Jul-95 AMINEX Oil &Gas Producers 33.97432447
23 17-Dec-04 CENTAURMEDIA Media 65.1577 25-Jun-99 FUTURE Media 62.90874388
24 09-Aug-01 CHELVERTON GROWTHTRUST Equity InvestmentInstruments 4.1540 23-Jul-64 INVESTMENTCO Equity InvestmentInstruments 4.38836885
25 25-May-04 CHESNARA Life Insurance 274.7756 27-Aug-96 STJAMES'SPLACE Life Insurance 2770.712239
26 04-Apr-01 CHRYSALISVCT Equity InvestmentInstruments 18.0900 19-May-97 DOWNINGABSOLUTEINCOMEVCT1PLC Equity InvestmentInstruments 18.9193184
27 02-May-07 CINEWORLDGROUP Travel &Leisure 452.9661 06-Nov-95 ENTERPRISEINNS Travel &Leisure 495.6048976
28 02-Feb-01 COMPASSGROUP Travel &Leisure 15332.9243 16-Jul-98 RYANAIRHLDGS Travel &Leisure 7193.50389
29 12-Mar-07 COREVCTIV PLC Equity InvestmentInstruments 2.1579 04-Apr-97 OXFORDTECHNOLOGYVCTPLC Equity InvestmentInstruments 2.87877715
30 10-Mar-06 COREVCTPLC Equity InvestmentInstruments 11.5154 30-Nov-99 JUPITERDIVIDEND&GROWTHTRUST Equity InvestmentInstruments 11.37403049
COMPANIES ISSED IPO FROM 2000 TO 2008 MATCHING FIRMS

16. 17 | P a g e
Table 4 gives a quick overlook on few sample listed companies in the
main capital market on London stock exchange listed firms
Number of Companies Market Value (m) Count of techMARK
892 £1,988,477 67
List Date Company Group Sector Sub Sector Mkt Cap £m Countr
18-Jul-94 3I GROUP 8775 General Financial Specialty Finance 3191.18 GB
05-Nov-53 4IMPRINT GROUP PLC 5555 Media Media Agencies 133.33 GB
06-Apr-88 ABBEYCREST 3763 Personal Goods Clothing & Accessories 0.00 GB
01-Oct-98 ABERDEEN ALL ASIA INVESTMENT TRUST 8985 Equity Investment Instruments Equity Investment Instruments 55.65 GB
19-Oct-95 ABERDEEN ASIAN SMALLER CO INV TST 8985 Equity Investment Instruments Equity Investment Instruments 381.34 GB
28-Mar-91 ABERDEEN ASSET MANAGEMENT PLC 8771 General Financial Asset Managers 5260.79 GB
08-Sep-86 ABERDEEN DEVELOPMENT CAPITAL 8985 Equity Investment Instruments Equity Investment Instruments 0.00 GB
12-May-89 ABERDEEN NEW DAWN INVESTMENT TST 8985 Equity Investment Instruments Equity Investment Instruments 247.94 GB
22-Dec-89 ABERDEEN NEW THAI INVESTMENT TRUST 8985 Equity Investment Instruments Equity Investment Instruments 111.19 GB
28-Aug-92 ABERDEEN SMALLER COS HIGH INC TRUST 8985 Equity Investment Instruments Equity Investment Instruments 41.50 GB
06-Aug-90 ABERDEEN UK TRACKER TRUST PLC 8985 Equity Investment Instruments Equity Investment Instruments 296.97 GB
30-Apr-10 ABERFORTH GEARED INCOME TRUST PLC 8985 Equity Investment Instruments Equity Investment Instruments 133.32 GB
10-Dec-90 ABERFORTH SMALLER COMPANIES TRUST 8985 Equity Investment Instruments Equity Investment Instruments 766.83 GB
28-Mar-94 ACAL 2797 Support Services Industrial Suppliers 71.85 GB
29-Oct-12 ACORN MINERALS PLC 1775 Mining General Mining 6.66 GB
11-May-01 ACTIVE CAPITAL TRUST 8985 Equity Investment Instruments Equity Investment Instruments 0.00 GB
28-Sep-04 ADMIRAL GROUP PLC 8534 Nonlife Insurance Insurance Brokers 3475.59 GB
03-Dec-09 AFREN 533 Oil & Gas Producers Exploration & Production 1456.84 GB
24-Mar-10 AFRICAN BARRICK GOLD PLC 1777 Mining Gold Mining 717.65 GB
17-Sep-41 AGA RANGEMASTER GROUP PLC 3722 Household Goods Durable Household Products 54.33 GB
29-Sep-97 AGGREKO 2791 Support Services Business Support Services 4779.52 GB
All Companies on the London Stock Exchange at 30th April 2013

17. 18 | P a g e
Table 5 illustrates all the Companies decommissioned their operation after the IPO since 2000
4.2 Methodology
There are two relevant methodologies available and widely used by the previous empirical researches to
evaluate the IPO performance in long and short term. These are as follows;
 Matching Firms contrast
 Comparisons with industry index
Matching Firms method includes selecting similar sized sample firm from relevant industries and comparing
the performance within a specific period of time based on the historical data. The main advantage of using
this method is, results show more accurate comparison among the firms. This is because selected companies
are similar size in terms of resource and capital. Loughran and Ritter (1995) and Ritter (1991) used Matching
Firm method in their researches and demonstrate a better use of the method to evaluate firm’s performance
after the IPO offering. The major setback however, selected firms may be similar size in share capital but the
internal culture and policies make all the firms very different from one to another. On top of that, the actual
market capital would never be accurately matched with each other. Therefore the comparison may not always
represent a true picture of the company’s performance.
No. List Date Company Sector Mkt Cap £m
1 11-May-01 ACTIVE CAPITAL TRUST Equity Investment Instruments 0
2 09-Mar-05 ARDANA Pharmaceuticals & Biotechnology 0
3 03-Aug-07 BARCLAYS BANK PLC Preference 0
4 06-Nov-00 BEDE Technology Hardware & Equipment 0
5 16-Aug-06 BLUE PLANET FIN GRWTH&INC INV TST Equity Investment Instruments 0
6 06-Oct-06 CAPITAL SHOPPING CNTR DEBENTURE PLC Debentures & Loans 0
7 29-Apr-02 CHARTER EUROPEAN TRUST PLC Equity Investment Instruments 0
8 22-Oct-04 ERINACEOUS GROUP Support Services 0
9 15-Feb-01 GDT SECURITIES Preference 0
10 12-Apr-01 GLOBAL SPECIAL OPPORTUNITIES TRUST Nonequity Investment Instruments 0
11 22-Jan-01 LINDSELL TRAIN INVESTMENT TST(THE) Equity Investment Instruments 0
12 08-Feb-00 LLOYDS TSB CAPITAL 2 L.P. Preference 0
13 03-Apr-08 MWB GROUP HLDGS PLC Real Estate Investment & Services 0
14 14-Jun-01 NOTTINGHAM BUILDING SOCIETY Preference 0
15 12-Jul-06 SOUTHERN CROSS HEALTHCARE GROUP PLC Health Care Equipment & Services 0
16 29-Jul-05 WEST BROMWICH B.S. Preference 0
17 25-Mar-02 XSTRATA PLC Mining 0
18 28-Mar-06 YORKSHIRE BUILDING SOCIETY Preference 0
Companies Tarnminated Operations After IPOs (2000-2008) 30th April 2013

18. 19 | P a g e
On the other hand Industry Index comparisons represent, evaluating companies performance comparing to the
overall industry. A company might perform well or badly due to the contemporary economical conditions. As
such, focusing blindly on bad performance of a company might not always be rational without studying the
overall industry where it operates. In that case Using Industry Index would prove better option as a
benchmark. However, overall industry consists of many larger and smaller companies with a very different
share capital and resources which make this method of performance evaluation less effective in some sense.
After the analysis of these two methods the Matching Firms method seems more appropriate selection of
method for the performance comparison purpose over the Industry Index Method. However this is a demand
of the types and size of the sample data not an individual choice.
The next section would describe what technical methodology is well fit into the research motive and
determine the particular methods to apply as required.
There are many different methods available to calculate the IPOs abnormal return and the returns derive from
such study can be sensitive to the test static and also the model of abnormal returns Fama (1998) and
Loughran and Ritter (2000). The force of abnormal returns and the magnitude of the size are significantly
correlated. While talking about the excess return Loughran and Ritter (2000) and Loughran and
Ritter (1995) suggested that it is following equity offerings are much lower when it measured in event period
than those in calendar time. A study over the German IPOs between 1870 and 1914 by Schlag and Wodrich
(2000), claimed a significant underperformance in event time comparing to the calendar time.
Similar results have been identified by Gompers and Lerner (2000) when they analyzed the buy and hold
abnormal returns on IPO market. They claim these are negative in event time right after the IPOs however
when calculated in calendar time this result changed significantly. IPO return determined on calendar time
bases are found mostly identical to the return from the market.
In this paper the time period is set as 9 years horizon the current research on IPO long run returns are
generally covered 3 to 5 years time horizon after the first issue. The trading time periods are defined in line
with the calendar time approach which considers real event data from the post issue IPO market.
the first sample IPO in this paper has been issued in January 2000 and the last was in December 2008
according to the precondition of this research a 6-month window were to maintain which is why any IPO
issued after the June 2008 have been eliminated from the sample size. The initial return period is considered
from the first offering day and the adjusted closing balance of following days throughout the selected time
frame.

19. 20 | P a g e
4.2.1 Average Market adjusted returns model
The first model has been used in this paper is market adjusted return model which helps to determine the level
of return in long run. This method of calculating market return has also been used in many contemporary
research papers. There are mainly two components to consider determining the returns which are (1) Initial
returns (2) Market adjusted return
฀ Initial returns:
Daily share prices are downloaded using the DataStream for each of the IPO and the matching firms. This
share price is excluded dividends and other bonuses so that the price represents the actual market return in
stock market. Therefore, the initial returns are the difference between the unadjusted closing share price in
opening trading day and the offering share price. The following equation represents the method how the initial
return is been determined.
Where: = The IPOs initial market return
= Unadjusted closing share price
= The offering price share price
฀ Market-adjusted returns
Before calculating the average return it has been make sure that all share prices are the daily closing adjusted
figure. As share price moves up and down many times during the trading period thus the closing adjusted
price provides the more consistent share price for that particular trading day.
Using excel spread sheet 100 IPOs and their matching firms have been set next to each other in line with 180
trading days share prices. The next procedure was to calculate the daily return of those share prices using the
following formula.

20. 21 | P a g e
The whole 180 days period has been split into three different time set to compare the price movement from
one point to another. The first 30 trading days been considered the first month of the IPO trading followed by
the 90 days for three months and 180 days for 6 months respectively. This time split has also been performed
accordingly for the matching firms. To get the market return; previous closing price has been subtracted from
the current day closing price and the subtracted figure then been divided by the current day closing price. The
result shows the proportion of increase or decrease in price at the present time period from the previous day.
After calculating the 180 days market following the above process, an average market return has been
calculated for each time period (Month 1, Month 3 and Month 6). The maximum and the minimum market
return can also be found from the calculations. Taking all the average returns into a new spread sheet, three
tables have been drawn for each of the trading month segments (Appendix 1). The IPOs return and the
matching firms returns have seen set side by side in each of those table. The summations of individual firm’s
average have been calculated at the very end for both IPOs and matching firm to conclude the final result.
The first of research analysis discussion would be based on this result. Although this is inevitable to have
some errors during the process however the results give a general outlook of how the IPOs performed in
compare with the existing companies in terms of the average daily return.
4.3 Result Analysis: Average return
The overall result suggests that IPOs performed better in one and three month time duration compare to
matching firms in the same time spread. However in 6 months time, this scenario has changed other way.
Table: 6 Summary of Average Returns
Table 6 shows that the total average IPO return was 0.1264 or 12.63% where as the return from the matching
firm at the same time was -0.0112 or -1.12%. From the first trading month 30 IPOs out of those 100 samples
had generated a negative average return. On the other hand 39 matching firms out of 100 samples had earned
negative average return. It is also worth mentioning that 12 IPOs had not been able to generate any return at
all with 0% of average return compare to only 5 matching firms with a similar return (Appendix 1)..
This scenario supports many previous research results such as Ritter (1984) and many others; where it is
widely believed that immediately after the IPO issue, share price start climbing up due to the underpricing.
This result also supports research Hypothesis 1 that ‘Due to underpricing UK IPOs perform better in short
term’ which is believed to be a controversial area in the summary literature review. Menyah et al. (1990) and
Levis (1993) mentioned that underpricing is seemingly a common feature of UK IPOs. However, they also
raised points that the obvious impacts of such underpricing are yet to be discovered. The result analysis from
first 30 days average IPO return in this paper sheds a light over that inconclusive area. Apparently it can be
argued that the underpricing causes a sharp price increase which lead to a better average return in UK IPO
market over the short run.
No.
IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS
TOTAL 0.126366034 -0.011208304 0.02078862 -0.02251711 -0.025958627 -0.042203407
1-MONTH AVERAGE RETURN 3-MONTH AVERAGE RETURN 6-MONTH AVERAGE RETURN

21. 22 | P a g e
Continue with the second segment, IPOs still performed better than those matching firms from the sample in
terms of the average return. In three months time interval all 100 IPOs produce 2.02% daily average return
while at the same time existing firms still struggled with a negative -2.6% return (Table 6). However, IPOs
average return experienced a sharp fall from 12.63% down to only 2.02%. 43 out of 100 IPOs generated a
negative return this time which was 30 for the successive time segment. Matching firms have also suffered
from a higher volume firms producing negative returns. 46 firms have made a negative return and 2 made 0%
percent of return among those 100 matching firms. Although a slide improvement can be observed from the
IPOs in regard to the number of firms making 0% return. Only 3 IPOs were at 0% return mark which is steady
improvement in compare with the first month average return when this number was 12(Appendix 1). In this
stage all those IPOs which were previously underpriced start to adjust the market price with the actual price.
Immediately after the new issue, market reacts to the underpriced share. Investors are much eager to buy the
new IPOs which drive the share price up and this process continue for a certain period of time. There are
many uninformed investors in the market who rely upon the underwriters’ review over the IPOs pre listing
performance. Loughran and Ritter (1995) explain, these over optimistic investors are partially responsible for
underpriced IPOs at the first place. Loughran, at el. (1994) added that many companies utilized such market
expectations and timed their IPO issue when these expectation levels remain at the pick position. Jain and
Kini (1994) evaluate investor expectations of post-IPO earnings growth using the price earnings ratio and the
market to book value of 682 IPOs in a time period between 1976 and 1988; they found a major decline in
operational performance. Identical outcome can be observed from Ritter (1991) and, Loughran and Ritter
(1995) where they stated, investors are usually over optimistic on the pre-IPO performance as well as the post
performance in long run. Therefore it is assume that IPO firms fail to maintain their pre issue performance
levels and on the other hand IPO prices cross way above its actual market price and in few months time this
up word price takes a declining move. It is assumed that the result outcome from the 3 month average return
in this paper has a direct link with the above factors which better reflects the existing hypothesis.
While looking at the six months result it reveals a different outcome from the previous two segments. Instead
of generating positive return most of the IPOs started to decline their market value which brought the
segmental average return down to -2.6% from 2.02% percent (Table 6). This is a -4.8% percent fall from the
previous time slot. Although the dropping rate was much slower in 3 to 6 months time gap than from 1 to 3
month time duration. From 1
st
month to 3
rd
month of trading, the average returns droop by 10.61% percent
which has been slowing down at a rate of 4.8% percent after the 6
th
month. There are 54 IPO firms who made
a negative return during 3
rd
and 6
th
month time which had a direct impact on the overall performance of the
IPOs average return. 51 matching firms have also earned a negative return at the same time duration which
drags down the average return to -4.2% percent in 6 month time (Appendix 1).

22. 23 | P a g e
The bar chart above shows the downward return movement of IPO over the six months time. There is a sharp fall from
30 days to 90 days time interval which is still positive. However, after the 90 days and onward the average returns seem
to have a negative return for the IPO firms.
To sum up the overall result based on the average return analysis, it is clear that the IPO performed better than
those of matching firms over 1month, 3month and 6 month time interval. However, sharp decline in average
return has also been noticed at the same time. From the 1
st
month to 6
th
month, where matching firms suffered
a 5.3% drop in average return, the IPO firms on the other hand experienced a massive 15% drop in average
earnings. Therefore, this result suggests that in the UK market generally IPOs performed better in short term
however after 6 months and onward it starts to perform similar way or even worse than the existing firms in
the same industry.
The measure of average return is been used in many research papers. This is easy to calculate and a quick
simplistic measure of performance evaluation. However the validity of the result is like to be less reliable in
the long term performance evaluation. Moreover the data size and the possible errors within the measurement
process always count as a drawback in this methodology. Thus the reliability of the result outcome can easily
raise a question among the critics. As such to assess the long term IPO performance a different methodology
has been used which fits better into the long term performance evaluation. As stated above the cross-sectional
regression evaluation has been chosen as the more appropriate method to identify the performance movement
over the long term period. In the following part of the process cross-sectional regression methodology has
been explained along with the results from the method to conclude a supportive result to justify the validity of
the second research hypothesis. ‘Hypothesis 2: In long-run UK IPOs suffer a decline compare with the
matching firms in same industry’
In the regression process capital asset pricing model is used to find the market beta for both IPOs and the
matching firms. The beta values then used at the later part of the cross-sectional regression analysis to draw a
comparative result.

23. 24 | P a g e
4.4 Regression Analysis
 Validity of CAPM:
Van Horne and Wachowicz (2001) described the Capital Asset Pricing model and suggested that according to
this model, in a balanced market condition, excess return of a share is proportionate to the excess return of the
market portfolio. They illustrate as the stock return, where risk free rate is and the market portfolio
return is . Thus, the excess return from particular stock signify as ( ) and the market portfolio
excess return as ( - . The relationship between these variables can be denoted as follows
This can be rearranged as :
Where β represents the systematic risks exposure to a particular stock which is assume to be proportionately
constant to all stock in the same market.
To evaluate the IPO performance with the matching firms a set of regression have been done using X and Y
variables as and respectively. In total there are 200 separate regressions have been done
using IPO and matching firm return. The whole process has been described step by step as follows:
 Average Risk Free rate of Return:
One of the key elements of CAMP model is risk free rate of return on current market therefore the whole
process starts with collecting the risk free rate of return from the reliable data source. As this research is based
on the UK IPO market; Bank of England’s historical data has therefore been used as an authentic source of
data. From their website, monthly average rate of discount for 3 month Treasury bills have been downloaded
from January 2000 to December 2008. From this data range, the average yearly interest rate has considered as
the yearly risk free rate (The calculation is shown in Appendix 2). Which are 4.605 in the spread sheet. This
figure has been used later on to calculate the Daily risk free return.
Table: 7 Average Risk Free Rate of Return.
Day of IPO AVERAGE RISK FREE RETURN
RF
1 4.604596296
2 4.604596296
3 4.604596296

24. 25 | P a g e
 Daily share price:
The daily share price is simply the everyday closing adjusted share price for those 100 sample IPOs which
were used in previous methodology in this paper. As described before these daily data have downloaded from
the DataStream and all 100 IPOs have been set side by side from column C to CX in the spread sheet. The
daily returns are calculated from these daily share prices at the further part of the process.
Table: 8 Daily Share Price
 Market return and the daily risk free return:
CAPM also requires the market return to calculate the return of a particular stock. To continue this process the
next step was to calculate the daily market return. To keep the calculation process simple and understandable
the market return has been chosen as the FTSE 100 closing adjusted index price from 19th
January 2000 to
next 180 days daily index price. The reason being such randomly picked date was; same index price would be
used to calculate both the IPO and the matching firms return using the CAPM model therefore both IPOs and
matching firms would be affected same portion in that process and the result would still be comparable. From
the FTSE 100 index the daily returns have been defined using LN (Returns the natural logarithm of a number)
function in excel spread sheet. The daily risk free return is the average yearly risk free return divided by 365.
Table: 9 FTSE 100 Closing Adjusted Daily Return
ADMIRAL GROUP ALBION TECH.& GEN.VCT ALT.ASST.OPPS AMATI VCT 2 ARK THERAPEUTICS GP.
ADM(P) AATG(P) TLI(P) AT2(P) AKT(P)
22-09-04 28-11-00 18-03-04 29-01-01 02-03-04
275.0000 100.0000 87.1600 236.9200 132.3500
287.0000 100.0000 87.1600 236.9200 134.3400
287.5000 100.0000 87.1600 236.9200 140.3100
DAILY SHARE PRICE
6445.4000 0.0151 0.01262
6348.7000 0.0004 0.01262
6346.3000 -0.0053 0.01262
FTSE 100 Adj
Close
FTSE 100
return
DAILY RISK FREE
RETURN

25. 26 | P a g e
 Daily return:
The daily return represents the everyday price change of those IPO stock. Daily returns have been calculated
using the LN function (Returns the natural logarithm of a number) and divided the previous day’s closing
adjusted share price by the current day closing adjusted share price. This gives the every days returns of all
100 sample IPOs and according to the alphabetic order, they been arranged on the spread sheet from column
DF to HA.
Table 10: Daily Return
 Market premium:
The next step was to calculate the daily market premium which was calculated simply by subtracting the daily
IPO return from the risk free rate of return (=DF6-$DC$6). This process has been continued for all IPO return
to get the market premium for each individual IPO. These figures have been used as the Y variables in the
regression process.
Table 11: Stock Return-Risk Free Rate of Return
ADM IRAL GROUPALBION TECH.& GEN.VCT ALT.ASST.OPPS AM ATI VCT 2 ARK THERAPEUTICS GP.
ADM (P) AATG(P) TLI(P) AT2(P) AKT(P)
22-09-04 28-11-00 18-03-04 29-01-01 02-03-04
-0.0427 0.0000 0.0000 0.0000 -0.0149
-0.0017 0.0000 0.0000 0.0000 -0.0435
0.0017 0.0000 0.0000 0.0000 0.0036
DAILY RETURN
CHESNARA CHRYSALIS VCT CINEW ORLD GROUP COMPASS GROUPCSR
CYS(P) CINE(P) CPG(P) CSR(P)
-0.0015 -0.0126 -0.1498 -0.1328 -0.2206
0.0215 -0.0126 0.0200 -0.0218 0.0131
-0.0490 -0.0126 -0.0139 0.0123 -0.0332
STOCK (IPO) RETURN - RISK FREE RETURN

26. 27 | P a g e
This is the final piece of required elements to perform the regression analysis. The daily return from those
FTSE 100 index have been subtracted from the risk free rate of return. These values are the X variable for the
regression process at the next stage of analysis process.
Table: 12 FTSE 100 Daily Market Return
 Regressions:
The same process has also been performed for all the matching firms described as above. Taking as
X-variable and as Y-variable, 100 regressions have been done for each of the IPO and the matching
firm. Followed by the regression process five important values are picked and made table with R-square,
Alpha Beta t-stat and P-value (Appendix 3 & 4). The significance of all values above are analysed
and discussed at the result analysis part of this paper.
Table 13: T-Stat for IPO
 Cross sectional regression:
The final part of the whole calculation was to perform the cress sectional regression for both the IPOs and the
matching firms. These regressions have been performed with the Beta value from all the previous
regressions and the daily stock return. The daily stock returns of a randomly picked date have been transposed
from previous spread sheet for all the firms. On the cross sectional regression the dependent variable (Y) is
the daily stock return and the independent variable (X) is the beta values.
-0.00250
0.01224
0.01788
-0.00409
0.02866
0.02282
DAILY RM -RF FTSE 100
NUMBER NAME OF THE COMPANY R- square T- stat P-value
1 ADMIRAL GROUP 4.83384E-05 -0.0144 0.00651638 -11.94000522 1.62E-24
2 ALBION TECH.& GEN.VCT 0.002362151 -0.0126 0.041726053 -11.38660215 6.45994E-23
3 ALT.ASST.OPPS 0.010224547 -0.0125 -0.034193055 -28.86496783 4.7321E-69
T-STAT FOR IPO

27. 28 | P a g e
4.4.1 Result Analysis:
In the regression, the Beta β value represents the coefficient of X variable which shows the mixed negative
and positive values. The intercept Alpha however represents all negative values. This specify that
the is a function of and both are correlated to each other. According to CAPM theory the
will be zero at the same time when the value is zero. Which is the excess return of a share
is comparative to the excess return of the market portfolio.
In the process every company has come across with a slope of beta value β when is plotted as X-
axis and the is plotted as Y-axis. When the slope of beta is equivalent to 1, then the excess return of
a stock changes same proportion to the return of market portfolio. However, if the beta value is greater than 1,
then the excess return of stock changes disproportionately to the market return. Likewise, when the beta
values fall bellow or equal to the zero then the relationship between the stock excess return and the market
portfolio is less obvious to affect each other.
From the 100 regressions over the IPOs, 47 beta values out of those 100 outcomes were negative. On the
other hand Positive beta represents 52 and only one IPO generates zero beta value. If we compare these
results with same number of regressions over the matching firms, 43 beta values were negative whereas 57
were positive beta value in 100 regression results (Appendix 3 & 4).
These results suggest that 52 IPOs generated excess returns which were equal or more than the market
portfolio return. And the 47 IPOs however created the returns which were less sensitive to the level of market
return in the same time horizon. In terms of excess market return matching firms from the same industry as
the IPOs perform better form those IPOs. 57 matching firms regression had a positive beta value which is an
indication of better excess market return in compare to the market portfolio return.
The validity of above result can be further analyzed through some other components of the regression result.
 Coefficient of the variations (R-square)
The value of R-square represents the coefficient between the independent and the dependent
variables in the regression. This is a significant value to look at regarding the assessment of
regression results. This value indicates the strength of the correlation between the X and the Y
variables. The higher the R-square value the stronger the regression relationship (Silver, 1997).
The average R-square value of all IPO regression is close to 10% where as the R-square value of
matching firms regression is nearly 13% percent meaning that the variability of above excess returns
over the market portfolio return have been explained by 13% percent for matching firms which is
just 10% percent for IPO firms. A higher percentage of this number would have given more
reliability on the above results. Although the R square value in this research represents a lower value
but for the comparison purpose it still significant for both IPOs and those of matching firms. It has
been noticed that many IPOs and the matching firms’ regression result shows a very low level of R-
square value. This implies that excess returns from those sample firms are not well explained by the

28. 29 | P a g e
market portfolio return. For those stocks greater portion of unsystematic risk exposure can be
assumed to be the reason behind such lower reading of R-square value. Therefore it is likely that all
IPO in UK stock market have been suffered a great deal of firm specific risks exposure during the
initial terms of their trading operation. Lack of market experience and inefficient management might
be the reason behind that greater portion of unsystematic risks tolerance by those IPOs as these can
be diversified away with an efficient fund management and operational excellence. In contrast
matching firms however managed the firm specific risks better than those of IPOs. Which lead to an
ideal rate of excess return for them over the return from market portfolio.
 T-stat for
Alpha value represents the intercept point between the X-axis and the Y-axis of a linear regression. And
the T-stat determines the probability of that Alpha being close to Zero. Triola (2007) described as the lower
the T-stat value, higher the chance of alpha being zero in linear regression.
The general equation of this type of line is
r - Rf = Beta x ( Km - Rf ) + Alpha
Here, r is the fund's return rate, Rf is the risk-free return rate, and Km is the return of the index.

29. 30 | P a g e
Table 14: average Alpha and T-stat value of IPOs and Matching firms the regression
In this paper the T-state value for both IPO and the matching firms are negative for example the average T-
stat for IPO is -9.142 which is -9.706 for the matching firms. This means the probability of Alpha being zero
is higher for both categories of stocks.
The individual Alpha values of companies are negative. The average IPO Alpha value is -0.016
which is on the table above along with this the matching firms Alpha value is also represent a negative
value -0.0123 therefore both Alpha and T-state values suggest a higher probability of having no intercept
within the regression lines obtained in this paper.
 P-Value:
P-value of probability value represents the statistical significance of a hypothesis test. It is used as alternative
rejection mark to provide the smallest level of significance where the null hypothesis would be rejected.
Ideally the confidence level is considered based on certain standard level of P-value such as 0.01, 0.05, or
0.10. For instance statistically significance at the level of 99% confidence will be determined if the P-value
goes 0.01 or bellow. Likewise 0.10 p-value level would provide a 90% confidence that the null hypotheses
would be rejected. Therefore, smaller the p-value the stronger the confidence level rise in favor of the
alternative hypothesis.
Table 15: Average P-value
The result suggests that the P-values for both IPO and the Matching firms are less than the 0.01 standard
levels. This is a better indication that any result conclude from this regression would be supporting the
alternative hypothesis with a 99% percent confident level. The table shows that the IPO and the matching
firms P-value is -9.142 and -9.705 respectively which certainly a better indication of a legitimate regression
result.
Category T- stat
IPO -0.0126412 -9.142364498
Matching Firms -0.0123442 -9.705633918
CATEGORY P-VALUE
IPO -9.142364498
MATCHING FIRM -9.705633918

30. 31 | P a g e
4.4.2 Cross-sectional regressions analysis
The final peace of whole analysis process is the cross sectional regression which would determine the
conclusive result over the performance between the IPO and the matching firms. The cross sectional
regressions establish the correlation between the dependent and the independent variables of a specific period
of time (Andrews, 2005). The IPOs and the matching firms are chosen from the same industry thus, it is
expected that both IPOs and the matching firms would have similar level of market risk exposure. Therefore,
with the same level of beta ( value both matching firms and the IPOs would also expected to be generating
the equal market return. And if the market returns from any of those categories are less than one from another
than it suggests that those firms generated less return, performed badly. Having this idea in mind the cross
sectional regressions have been performed with two sets of data. The first data set were the matching firms
daily return which were used as the dependent variable ‘X’ and the beta ( from the CAPM model which
were calculated from the previous regression over the matching firms; been used as the independent variable
‘Y’ . Similar regression has also been carried out over the IPO daily return however the beta value were taken
from the matching firms CAPM model. As described above with the same level of beta ( value both
matching firms and the IPO firms are likely to produce the same level of return and any difference would lead
us to conclude the performance of those stock return.
Table 16: Summary of Cross-sectional Regression
Table 16 shows the summary of cross sectional regression over the IPOs and the matching firms. The R-
square value illustrates that dependent variable X or the IPO market return have been explain 15% percent by
the independent variable ‘Y’ which is the beta ( value of the matching firms extracted from the CAPM
model. This is 18% for the matching firms regressions, meaning that 18% of matching firms return has been
explain by the beta ( value of the ‘Y’ variable of the regression. The R-square value therefore gives us the
level of validity of any result concluded from this regression model. The intercept or Alpha value is
negative for both IPO and the matching firms. The P-value has a very important role to play upon determining
the final result this value would be representing the statistical significance of the regression result. The
summary table shows that P-value for the matching firms is 0.21 which means the confidence level is around
80% that the alternative hypothesis should be accepted which is less significant in this scenario. However to
evaluate the final result, P-value of IPO is more relevant in this case which is less than 0.10 meaning, the
confidence level is 90% that alternative hypothesis would be accepted and with no doubt this is a statistically
significant value.
CATEGORIES R- square T- stat P-value
IPO 0.147913052 -0.001607775 0.031009038 -1.672629931 0.09758984
MATCHING FIRMS 0.176562059 -0.001760534 0.050218486 -1.23580876 0.219483752
SUMMARY OF CROSS-SECTIONAL REGRESSION

31. 32 | P a g e
On the other hand matching firms’ beta ( ) value is 0.050 which also made a positive return. But when we
compare this two beta values, it shows that matching firms generated greater return than the IPO firms with a
same level of market risk exposure. Based on this research result it can be argued that any investment on UK
IPOs generated less return than the investment on the already exist companies in the stock market during the
2000 to 2008 time period which also explains the validity of the second hypothesis in this paper (In long-
run UK IPOs suffer a decline compare with the matching firms in same industry).
5. Conclusion
This study distinguished the performance between the Initial Public Offering (IPO) and their matching firms
in the same industry from the UK stock market. As a sample size this paper includes 100 IPOs and same
number of matching firms who fulfill some predetermined research criteria’s. The research has gone through
some rigorous technical process to find out a possible outcome over the IPOs’ short-term as well as the long-
term performance pattern. Initially the result reveals that IPOs were performing better immediately after the
first day of trading. On an average, IPO generated upto13% return for the investors in the first month of the
open market trading. However, from third to sixth month time this return started to fall significantly and at the
end of six month trading it produced a negative average(-0.2%) return for the investors. IPO underpricing,
over expectations from the uninformed investors and the pre issue window dressing have been identified as
some possible reason behind the IPO underperformance. To evaluate this research result, a cross-sectional
regression has been further carried out. Risk free rate of return from the Bank of England and the FTSE100
daily stock return were some of the key variables in the regression alongside the IPOs and matching firms’
daily stock return. After the regression it reveals that having a same level of market capital and risk exposure,
matching firms generated more return than those of IPOs in the same time frame. Again the result supports
the existing literature of underperforming IPOs in long-run. The overall research has been performed carefully
with the reliable data from legitimate sources. However, a number of limitations were there. First of all the
100 sample size may not be a sufficient sample population to conclude a strong result. And the matching
firms may not be representative to the IPOs due to the unique internal business culture and resources.
Secondly, the validity of the methods used in this paper may raise questions about the quality of result.
Precisely, the average return method is a very simplistic way to calculate the daily return which may lose its
superior status in compare to the other available research methods. Furthermore, the low R-square value in
cross-sectional regression generates another question about the validity of the final result.
In summary, it can be argued that regard less those research limitations the result out comes from this paper
provide a supportive statement to the existing literature on IPOs underperformance in both short and long run.
Therefore, based on this research it is obvious to say that during 2000 to 2008 time period majority of the
IPOs in UK failed to generate sufficient return in compare to the existing matching firms to satisfy the market
expectations.

32. 37 | P a g e
7. Appendices
No.
IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS
1 0.002016941 0.000603009 0.002574151 0.001501479 0.001637153 6.67757E-05
2 0 -0.000609596 -0.000591366 -0.001485376 -0.000640911 -0.000746279
3 0.001815884 0.000348916 0.000480717 -0.000342443 -0.000640911 -0.000746279
4 0 -0.001240432 0.000273912 -0.001064053 0.000136191 -0.001777712
5 -0.001654013 0.002167491 -0.003503009 -0.000608932 -0.002650442 -0.001558936
6 0 0.000294718 0.00064757 0.000891685 -0.000319292 0.001061357
7 0.006212987 -0.000457265 0.005486764 0.001649305 0.002621786 0.000704396
8 0 -0.000807741 -0.00117122 -0.000909433 0.000382155 0.000347311
9 0 0.000936478 0 -0.000262329 0.000266028 -0.000104655
10 0 0.001387502 0 0.000228977 -0.00050923 -0.001008766
11 -0.000884173 0 -0.000360127 0.000149928 -0.000449376 0.000225794
12 0.000370746 0.001029964 -0.000315181 0.001245101 -0.000438572 0.000141096
13 0.00147826 -0.000332059 0.001443552 -0.000264978 0.000337313 -0.000197016
14 0 -0.002820433 -0.000848801 -0.000279799 0.000544094 4.11722E-05
15 -0.000115327 -0.000656814 -0.000482364 -0.002130501 -0.002144718 -0.002218837
16 0 0 -0.000591366 -0.001810528 -0.002555632 -0.001036417
17 0.003286002 0.000568632 -0.001389198 0.000901834 -0.000853178 0.000735052
18 -0.007383689 -0.001346753 -0.000548373 0.001443145 3.99379E-05 -0.000220059
19 -0.002377891 -0.000249369 -0.002345878 -0.00086983 -0.000687919 -0.000857517
20 -0.010210238 -0.001814882 -0.005356309 -0.006367571 -0.00437165 -0.002863484
21 -0.002793567 0.003763709 -0.001132106 0.000412396 -0.000219605 0.001613916
22 0 -0.002378121 -0.000591366 -0.000832293 -0.002555632 -0.001839733
23 0.00675682 0.003324745 0.001905661 -0.000588701 -0.00223406 -0.001844497
24 0.002111384 0 0.000774487 0 -1.13043E-05 -0.006185156
25 0.006604006 -0.002926673 0.00716352 2.79368E-05 0.002488417 -0.000771965
26 0.004557833 0.004248002 0.002246754 -0.00191463 0.001902032 -0.00081479
27 -0.00164577 -0.004678104 -0.00052451 -0.001811125 -0.000324058 -0.000143695
28 0.003169103 -0.001739506 0.001708131 0.00046318 0.001841344 0.00160756
29 -0.007461097 0 -0.000921095 0 0.001285472 0
30 0.008105113 -0.001363891 0.005139715 0.001619339 0.003166933 0.001325037
31 0.006084964 0.002159896 0.00306013 0.0010766 0.00048613 -0.000796066
32 0.003689739 -0.000269347 0.00235389 0.000981205 0.00183962 0.000788641
33 0.000169652 0.001177787 -0.000116842 0.001319767 -0.000291343 0.001691543
34 -0.00087794 0.000368372 -0.002052296 0.000148433 -0.00250966 0.001044298
35 0.00625665 0.003429742 0.002912827 0.000140443 -0.001342675 3.85201E-05
36 0.003829073 0.000148227 0.002142363 0.001128924 0.003940207 0.00141742
37 -0.001829496 0.003819129 -0.004789634 0.004290333 -0.004436855 -0.000422639
38 0.002279171 -0.001776909 0.001026743 -0.002549465 0.001268859 0.001313749
39 -0.002795899 0.003177352 -0.000911023 0.001321042 -0.000452967 0.000128235
40 0 -0.000740611 -0.000710897 -0.000241323 -0.000353463 -0.000170602
41 0.008917943 -0.00312839 0.002919285 -0.00322402 -0.001040995 -0.002960137
42 0.002042307 0.00212352 -0.000250126 0.002405898 0.000771656 0.001285407
43 0.002780636 0.001839008 0.003388499 -0.000226605 0.001123791 -0.002641462
44 0.002425235 0.002524239 0.000408006 0.000664959 0.000166644 0.001528602
45 0.004014475 0.0009619 -0.000182142 -9.35761E-05 4.40445E-05 0.001641432
46 0.001296923 -0.005306256 0.001211105 -0.001925466 0.000112708 -0.000588632
47 0 -2.00248E-05 -0.002652934 -6.52494E-06 -0.000404293 -0.001896478
48 0.002840948 0.001184085 0.002514427 -0.000718711 0.001880417 -0.00116407
49 0.009424058 0.002691517 0.001144497 0.000517902 0.002475359 -0.000873806
50 -0.009957528 -0.003229395 -0.001263346 -0.00109284 -0.001526481 -0.001740108
Appendix 1: Average Market Return for IPOs and Matching Firms
1-MONTH AVERAGE RETURN 3-MONTH AVERAGE RETURN 6-MONTH AVERAGE RETURN

33. 38 | P a g e
No.
IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS IPO FIRMS MATCHING FIRMS
51 0.00210054 -0.02485473 7.63525E-05 -0.010776261 -0.000959691 -0.00524154
52 -0.000615016 0.001530792 0.000343095 0.000808222 0.000841584 0.001018438
53 -0.005552831 -0.000316245 -0.000426609 -0.001047645 -0.001779991 -0.002184455
54 0.007440931 0.000946615 0.005741465 0.002217869 0.002672172 -0.000711832
55 0.000904505 0.002292616 -0.000554647 0.001718336 -0.001224038 0.001250931
56 -0.001070877 0 0.000186649 -0.000671358 0.000626167 -0.000184044
57 0.003890407 0.00372512 0.004463595 0.005268364 0.002644974 0.002767334
58 0.001014482 0.000965644 -0.003143148 0.000314056 -0.00297751 -0.000260067
59 -0.001610175 0.004075424 -0.002709233 -0.001051214 -0.000265161 -0.002123282
60 0.002566389 0.001682759 0.00163069 0.001245898 0.001350938 0.000688659
61 -0.002644101 -0.005562425 -0.00108628 0.000123443 -0.000542386 0.001345317
62 0.008079489 0.000626729 -0.002157042 -0.00344436 -0.00073312 -0.002099997
63 -0.001994709 0.002871977 0.000513992 0.002520263 -0.000203098 0.001321546
64 -0.003478757 -0.002994127 -0.001580982 -0.004379443 -0.002134228 -0.004169699
65 0.002549806 0.002109599 0.001458957 0.001087858 0.002526823 0.000598299
66 -9.54021E-05 0.004098705 -0.001854954 0.000642614 -0.004349553 0.001040897
67 0.001662486 -0.000883628 0.002425874 -0.000368879 0.001664152 0.00042728
68 6.26573E-05 -0.00355327 -0.002634859 -0.000472756 -0.00176852 -0.000205155
69 0.004887776 0.001966976 0.00303116 0.001384889 0.000641949 0.000728636
70 0.005317304 -0.001301915 0.001673625 0.00336327 0.001353678 0.001744934
71 -0.005054621 0.000284292 -0.002078322 0.000670636 -0.001086397 0.000853833
72 0.000507669 0.00441774 0.001097907 -0.000249519 0.001640452 4.53847E-05
73 0 0.000963091 0 -0.000553694 0 -0.00161217
74 0.001045337 -0.005194488 0.000167833 -0.001093164 -0.00182068 -0.002700239
75 0.006067276 0.001364947 0.000397083 0.001366058 -0.0018703 0.000867941
76 0.007416578 0.000498777 -0.001612828 -0.000875356 -0.000360264 -0.001203513
77 -0.002591831 0.000346003 -0.002153282 -0.001086184 -0.000493361 0.000213372
78 5.85246E-05 0.002494042 8.53812E-05 -0.000532752 -0.000143928 -0.000238149
79 -0.003192498 0.000360921 -0.00770429 -0.002143194 -0.003010034 -0.002341707
80 0.001866744 -0.000785693 0.000767067 -0.000766385 -0.000175153 -0.000381404
81 -0.000103626 -0.001357798 -0.003245696 0.000521004 -0.002639867 -0.001661359
82 0.003188974 -0.002273709 0.001881295 0.000525366 -0.001111563 0.000399684
83 0.000545149 0.002660614 0.000756991 0.002523034 0.000921461 0.002432078
84 0.003683166 0.00072265 0.000454362 0.000457035 -0.003826938 0.000167944
85 -0.001327403 0.000612634 0.000520345 0.002164154 0.000881433 0.002168561
86 -0.003967041 0.001749619 -0.00598309 -0.001068203 -0.004606853 -0.001197559
87 0.002800094 0.000372604 0.002552115 0.000869009 0.001371718 6.23475E-05
88 0.002595968 0.001945238 0.005012823 0.000346018 0.00225903 -0.000222207
89 0.006164981 0.003786838 0.004051782 0.00240829 0.001879724 0.001112895
90 0.004233731 -0.002329974 -0.000403997 -0.000616367 -0.002560897 -0.002207938
91 0.006400645 -0.00592648 0.000166723 -0.000264306 0.000320879 0.001454162
92 -0.005544334 0.001934583 -0.002959454 0.000473223 6.87768E-05 7.59519E-05
93 0.004643801 0.0008571 -0.000142254 0.000280988 -0.00109072 2.13909E-05
94 0.001054633 0.00193658 3.76803E-05 0.000466513 -0.001627685 -0.000159615
95 -0.003982469 -0.001842074 -0.002163462 -0.003099649 -0.001913231 -0.003393567
96 0.001561299 -0.010858885 8.39705E-05 -0.005654334 -0.000855199 -0.003017628
97 0.004471043 0.004808411 0.002035386 0.000572017 0.00031675 -0.001330716
98 0.006946336 -0.001601859 0.004257799 0.000870121 0.001347854 0.000186168
99 0.002296296 -0.005700269 -0.000960491 -0.008612992 -0.002579669 -0.005805237
100 0.008616483 0.000734257 0.001146347 -0.001806404 0.000627826 -0.001101831
TOTAL 0.126366034 -0.011208304 0.02078862 -0.02251711 -0.025958627 -0.042203407
1-MONTH AVERAGE RETURN 3-MONTH AVERAGE RETURN 6-MONTH AVERAGE RETURN

34. 39 | P a g e
31-Jan-00 5.7218
29-Feb-00 5.8346
31-Mar-00 5.8582
30-Apr-00 5.9178
31-May-00 5.9501
30-Jun-00 5.8535
31-Jul-00 5.8333
31-Aug-00 5.8103
30-Sep-00 5.7798
31-Oct-00 5.7482
30-Nov-00 5.6833
31-Dec-00 5.6229
31-Jan-01 5.4852
28-Feb-01 5.4582
31-Mar-01 5.2286
30-Apr-01 5.1158
31-May-01 4.9765
30-Jun-01 4.991
31-Jul-01 5.0052
31-Aug-01 4.7198
30-Sep-01 4.4297
31-Oct-01 4.1567
30-Nov-01 3.7799
31-Dec-01 3.8296
31-Jan-02 3.8321
28-Feb-02 3.868
31-Mar-02 3.9672
30-Apr-02 3.9693
31-May-02 3.9525
30-Jun-02 3.9767
31-Jul-02 3.8408
31-Aug-02 3.7663
30-Sep-02 3.7861
31-Oct-02 3.7509
30-Nov-02 3.8033
31-Dec-02 3.8418
31-Jan-03 3.7993
28-Feb-03 3.4993
31-Mar-03 3.4721
30-Apr-03 3.4537
31-May-03 3.4366
30-Jun-03 3.4724
31-Jul-03 3.3119
31-Aug-03 3.3998
30-Sep-03 3.5239
31-Oct-03 3.6514
30-Nov-03 3.808
31-Dec-03 3.8298
31-Jan-04 3.8983
29-Feb-04 3.9788
31-Mar-04 4.1025
30-Apr-04 4.1862
3 month tresury bill rate
Appendix 2

35. 40 | P a g e
31-May-04 4.34
30-Jun-04 4.5793
31-Jul-04 4.6424
31-Aug-04 4.7218
30-Sep-04 4.6937
31-Oct-04 4.679
30-Nov-04 4.6578
31-Dec-04 4.677
31-Jan-05 4.6568
28-Feb-05 4.6858
31-Mar-05 4.7691
30-Apr-05 4.7047
31-May-05 4.6618
30-Jun-05 4.6175
31-Jul-05 4.4609
31-Aug-05 4.4057
30-Sep-05 4.4037
31-Oct-05 4.402
30-Nov-05 4.4169
31-Dec-05 4.4287
31-Jan-06 4.3906
28-Feb-06 4.3839
31-Mar-06 4.3956
30-Apr-06 4.4196
31-May-06 4.5012
30-Jun-06 4.5414
31-Jul-06 4.534
31-Aug-06 4.7544
30-Sep-06 4.8359
31-Oct-06 4.9357
30-Nov-06 5.0095
31-Dec-06 5.0759
31-Jan-07 5.304
28-Feb-07 5.3393
31-Mar-07 5.3274
30-Apr-07 5.4329
31-May-07 5.5516
30-Jun-07 5.6702
31-Jul-07 5.7742
31-Aug-07 5.7943
30-Sep-07 5.6896
31-Oct-07 5.6058
30-Nov-07 5.4986
31-Dec-07 5.3034
31-Jan-08 5.1215
29-Feb-08 5.0178
31-Mar-08 4.8835
30-Apr-08 4.8258
31-May-08 4.9496
30-Jun-08 5.1138
31-Jul-08 5.0843
31-Aug-08 4.9539
30-Sep-08 4.7425
31-Oct-08 3.6788
30-Nov-08 1.9948
31-Dec-08 1.2875
Average 4.604596296

36. 41 | P a g e
NUMBER NAME OF THE COMPANY R- square T- stat P-value
1 ADMIRAL GROUP 4.83384E-05 -0.0144 0.00651638 -11.94000522 1.62E-24
2 ALBION TECH.& GEN.VCT 0.002362151 -0.0126 0.041726053 -11.38660215 6.45994E-23
3 ALT.ASST.OPPS 0.010224547 -0.0125 -0.034193055 -28.86496783 4.7321E-69
4 AMATI VCT 2 0.01434063 -0.0125 -0.018752178 -62.63000981 3.3914E-123
5 ARK THERAPEUTICS GP. 0.006420231 -0.0118 0.128512531 -5.726930564 4.27764E-08
6 ARTEMIS VCT 0.000612232 -0.0125 0.016788335 -14.38137007 1.28223E-31
7 ASHMORE GROUP 0.009548676 -0.0183 0.215379134 -6.47396424 8.98574E-10
8 BARING EMERGING EUROPE 0.010237023 -0.014 0.073282804 -15.05879518 1.40009E-33
9 BARONSMEAD VCT 3 0.006008256 -0.0126 -0.0239952 -31.72004167 3.67187E-75
10 BARONSMEAD VCT 4 0.000333122 -0.0122 0.007799781 -22.24549765 2.77929E-53
11 BARONSMEAD VCT 5 0.011041189 -0.0133 0.083657904 -13.02742234 1.1169E-27
12 BIG YELLOW GROUP 0.0015848 -0.0119 -0.023921285 -15.42237585 1.25226E-34
13 BLACKROCK COMD.INC.IT. 1.33299E-06 -0.013 -0.001131778 -10.31786399 7.33357E-20
14 BLACKROCK GTR.EU.IT. 0.001206347 -0.0129 -0.021305897 -16.38741359 2.1584E-37
15 BLACKROCK I&G.IT. 0.015674476 -0.0087 -0.146935677 -5.838448715 2.44804E-08
16 BRITISH SMCOS.VCT 2 3.67115E-05 -0.0101 -0.008630018 -5.523501244 1.16314E-07
17 BRITVIC 0.003930388 -0.0103 -0.144556107 -3.494520767 0.000599328
18 BURBERRY GROUP 0.026335996 -0.0077 -0.430795988 -2.29912682 0.022659244
19 CENTAUR MEDIA 0.000801428 -0.0122 0.020642581 -13.04791354 9.7347E-28
20 CHELVERTON GROWTH TRUST 0.006054898 -0.0062 -0.202102489 -1.872241395 0.062813335
21 CHESNARA 0.011053041 -0.014 0.123394377 -9.354690087 3.60166E-17
22 CHRYSALIS VCT 0.008115485 -0.0086 -0.128312224 -4.723765335 4.68035E-06
23 CINEWORLD GROUP 0.000454667 -0.0114 0.051039231 -3.716594919 0.000270228
24 COMPASS GROUP 0.200759304 -0.0125 -0.031743676 -4.357233246 2.22127E-05
25 CSR 0.021149886 -0.0205 0.39469245 -5.948038273 1.40533E-08
26 DARTY 0.008657869 -0.0127 -0.158824589 -5.821019915 2.67236E-08
27 DEBENHAMS 0.001091783 -0.0119 -0.042218145 -7.233961589 1.34343E-11
28 DIGNITY 0.029548545 -0.0131 -0.109550652 -16.2347721 5.87716E-37
29 DOMINO'S PIZZA GROUP 0.013175067 -0.0099 -0.375421539 -2.374753462 0.018624551
30 DRAX GROUP 5.98449E-06 -0.0159 0.003280943 -9.241483457 7.3729E-17
31 DUNELM GROUP 0.0016818 -0.0142 0.07382644 -6.160322926 4.71027E-09
32 E2V TECHNOLOGIES 0.180321961 -0.0148 0.018699951 -8.275484688 2.92683E-14
33 THE ESTABLISHMENT IT. 0.001468553 -0.0122 -0.010043862 -36.24766122 4.24728E-84
34 F&C MANAGED PRTF.INC. 0.000277009 -0.01 -0.023865732 -5.406722718 2.04356E-07
35 FIBERWEB 0.00123602 -0.0107 -0.068370725 -4.278040791 3.07289E-05
36 GEIGER COUNTER 0.000884009 -0.0162 -0.040851483 -9.151324973 1.30177E-16
37 GENUS 0.001303895 -0.0075 -0.125514459 -1.677756345 0.095149651
38 HALFORDS GROUP 0.813286754 -0.014 0.006959493 -14.11788596 7.47002E-31
39 HARGREAVE HALE AIM VCT 1 0.007455369 -0.0116 -0.042710324 -18.3840449 5.37406E-43
40 HARGREAVE HALE AIM VCT 2 0.008433573 -0.0119 -0.030482783 -27.98054191 4.45295E-67
41 HARGREAVES LANSDOWN 0.000192002 -0.0119 -0.030482783 -3.835557653 0.000173739
42 HIBU SUSP - 25/07/13 0.015278643 -0.012 -0.11499062 -10.11262995 2.78387E-19
43 HIKMA PHARMACEUTICALS 0.430920073 -0.0135 -0.037561759 -5.799021948 2.98435E-08
44 HILTON FOOD GROUP 0.003356527 -0.0118 -0.096321485 -5.512710701 1.22572E-07
45 HOCHSCHILD MINING 7.14657E-06 -0.0129 -0.005480064 -4.886571319 2.2781E-06
46 HOGG ROBINSON GROUP 5.51363E-05 -0.013 0.009588674 -7.808145232 4.80001E-13
47 HYGEA VCT 0.003922342 -0.0113 -0.08142457 -6.780146902 1.70412E-10
48 IG GROUP HOLDINGS 5.68261E-05 -0.0148 0.011541004 -7.515695119 2.66034E-12
49 INMARSAT 0.01313806 -0.018 0.211996033 -7.606325419 1.57003E-12
50 INTERNATIONAL PSNL.FIN. 0.000949183 -0.0106 -0.083235768 -3.040421898 0.002719142
T-STAT FOR IPO
Appendix 3

37. 42 | P a g e
51 INTERTEK GROUP 5.19375E-05 -0.0119 0.010603512 -6.313814876 2.10653E-09
52 INVESCO PERP.SLT.UK EQ. 0.008869712 -0.0125 -0.08372213 -10.94946818 1.16556E-21
53 INVESTEC 0.002020248 -0.01 -0.085036275 -4.126747882 5.64372E-05
54 IP GROUP 0.011195671 -0.0179 0.194913702 -7.620347355 1.44663E-12
55 JPMORGAN INC.& GW.CAP. 0.003139769 -0.0124 0.073866281 -7.354146885 6.7584E-12
56 JUPITER GREEN INV.TST. 0.002430586 -0.0134 0.01543457 -33.42944572 1.22307E-78
57 KAZAKHMYS 0.006569824 -0.0183 0.205964334 -5.611809919 7.55597E-08
58 LOCAL SHOP.REIT (THE) 0.001463038 -0.009 -0.073942084 -3.619085809 0.000385116
59 LONDON STOCK EX.GROUP 0.007407129 -0.0097 -0.261526726 -2.497937572 0.0133989
60 LSL PROPERTY SERVICES 0.010779318 -0.0155 0.11746492 -10.72690166 5.04514E-21
61 MECOM GROUP 0.000919046 -0.0119 -0.01136127 -24.80091486 1.19818E-59
62 MICHAEL PAGE INTL. 0.003071514 -0.0143 0.153126911 -4.04328536 7.83836E-05
63 MITCHELLS & BUTLERS 0.000512806 -0.013 0.033229738 -6.880837824 9.77269E-11
64 MONEYSUPERMARKET COM GP. 0.013001918 -0.007 -0.320954567 -1.952107699 0.052494183
65 NCC GROUP 0.000167442 -0.0154 0.016162399 -9.616383448 6.80353E-18
66 NORCROS 0.000121384 -0.0089 0.023554064 -3.24375482 0.001408863
67 OFFICE2OFFICE 0.00260102 -0.0149 0.048623078 -12.2070207 2.72423E-25
68 OPTOS 0.009583102 -0.0129 0.152258258 -6.498671021 7.87033E-10
69 PAYPOINT 0.002799986 -0.0125 -0.065617846 -7.875004662 3.23124E-13
70 PHOENIX IT GROUP 0.009181182 -0.0159 0.14050201 -8.457172524 9.68407E-15
71 PREMIER EN.&WT.TRUST 0.011031503 -0.0126 0.083269038 -12.45412749 5.21189E-26
72 PREMIER FOODS 0.000353136 -0.0146 0.021171789 -10.08193891 3.39653E-19
73 PROVEN GROWTH & INC.VCT 1 -0.0126 0 0 0
74 PUNCH TAVERNS 0.007871651 -0.0132 0.17225935 -5.318694735 3.10887E-07
75 PURICORE 0.000501368 -0.0114 0.036080539 -5.497497262 1.31956E-07
76 PV CRYSTALOX SOLAR 0.013062849 -0.009 -0.293924639 -2.748790335 0.006598272
77 QINETIQ GROUP 0.004027401 -0.0111 -0.092805917 -5.920786274 1.61428E-08
78 RECKITT BENCKISER GROUP 0.003162266 -0.0115 -0.089049812 -5.671935391 5.61879E-08
79 RECORD 0.003942098 -0.0129 0.202404268 -3.110009314 0.002179082
80 RIGHTMOVE 0.005488065 -0.0148 0.163360915 -5.24535102 4.39437E-07
81 SAFESTORE HOLDINGS 0.001050584 -0.0111 0.064560995 -4.327357788 2.51185E-05
82 SALAMANDER ENERGY 0.030010984 -0.0171 0.413741586 -5.651023431 6.22998E-08
83 SECURITIES TST.OF SCTL. 4.9203E-05 -0.0135 -0.005416317 -13.60489723 2.32225E-29
84 SEPURA 0.000571291 -0.0101 0.062829678 -2.989109729 0.00319362
85 SMITHS NEWS 0.001352354 -0.0146 0.06791783 -6.142931498 5.15606E-09
86 SPORTS DIRECT INTL. 7.94245E-05 -0.0083 -0.024696518 -2.323232352 0.021297077
87 STANDARD LIFE 0.013890676 -0.0124 -0.136944559 -8.33051289 2.09589E-14
88 STHREE 0.003612406 -0.0163 0.09880953 -7.720542668 8.04294E-13
89 STYLES & WOOD GROUP 0.014533773 -0.0172 0.200783068 -8.086806673 9.13221E-14
90 SYNERGY HEALTH 0.00132515 -0.0111 0.062366544 -5.022656777 1.23189E-06
91 TELECITY GROUP 0.001435026 -0.0121 -0.128288989 -2.782252326 0.005980546
92 THOMAS COOK GROUP 0.001560069 -0.0143 0.097955237 -4.502415504 1.21166E-05
93 TRIBAL GROUP 0.001235711 -0.0127 0.072083807 -4.829340516 2.93995E-06
94 TULLETT PREBON 0.005042481 -0.0098 -0.103878968 -5.247492055 4.3504E-07
95 VEDANTA RESOURCES 0.000194577 -0.0106 -0.021169942 -5.437258629 1.7649E-07
96 WILLIAM HILL 0.002391916 -0.0133 0.101048778 -5.021918411 1.23604E-06
97 WINCANTON 0.005160306 -0.0138 0.065174943 -11.8647666 2.68018E-24
98 WOLFSON MICROELECTRONICS 5.29249E-05 -0.0144 0.014703128 -5.549059051 1.0271E-07
99 WOOD GROUP (JOHN) 0.005016816 -0.0129 0.18685861 -3.804869857 0.0001949
100 XCHANGING 0.000378102 -0.0139 0.035803749 -5.881678751 1.9682E-08
AVERAGE 0.015149153 -0.0126 0.004161478 -9.142364498 0.003103796
MAXIMUM 1 -0.0062 0.413741586 0 0.095149651
MINIMUM 1.33299E-06 -0.0205 -0.430795988 -62.63000981 0