Introduction

The report analyzes the performance of 30 non-financial IPO’s, floated in the Alternative investment market (AIM) during the period of Jan 2002- Dec 2004, the main tasks undertaken were First, to define a portfolio of 30 IPO’s that were floated in the given time period. Second, calculating the initial returns of the selected IPO’s and testing them. Third, deriving a 24 month return of the same securities and thereafter testing those returns, in both the circumstances (second & third) the return is tested by deriving the basic descriptive statistics (mean, standard deviation etc.) on the data collected and hence discussing and commenting on the same

The sample of IPO’s that our group has selected is basically refined from Jan 2002 - Dec 2003. The criteria taken into consideration while selecting the IPO’s was to make a portfolio that would cover different sectors of the market, basically diversifying and defining the movements of these securities in the AIM market more precisely; the sample is divided into 4 major industrial sectors

• Pharmaceuticals & biotechnology.

• Mining.

• General finance.

• Software & computer services

The IPO’s that we have selected were floated in the market either by placing or by an open offer. The table given below shows the name of the companies that our group has selected with a detailed synopsis of the companies selected, illustrating the data on the Initial Public Offerings. (Date of issue, market capitalization, issue price etc.)

Computing the initial return of the IPO’s

For computing the initial return of the IPO’s we have taken into account the issue price of the securities and the price after 12 months from the issue also bearing in mind if any dividend is paid out during this period. The initial return formula that we have used has 3 variables which can be solved for;

Initial Return = (P1 – P0) +div

P0

Where,

P0 = Issue Price.

P1 = Price after 12 months.

Div = Dividend paid during this period.

We can see that for the 12 month period considered, the pharmaceutical & the biotechnology sector is showing a bearish trend giving negative returns with DDD Group with the lowest at -86.69%, the gold mining and the other minerals extracting sector is giving a positive return during this period of 12 months, with African Eagle Resources showing the maximum positive return of 283% in one year, the performance of the general finance sector is bullish with almost all the companies giving a positive return. Also observed is that most of the companies in the portfolio have not declared any dividends after there first financial year, therefore in most of the cases dividend paid out is taken

The issue price for Caledon Resources Plc & Healthcare Enterprise Group could not be found out therefore it was not possible to calculate there initial returns. For all the other stocks refer to Table .01 and the histogram (fig. 01) displaying the returns. For an extensive reference and guidance to how the returns were calculated refer to Appendix 02 (returns).

Table .01

Testing the initial return

For testing the return, we have used some basic descriptive statistical tools such as;

Mean: The mean is the "standard" average and is defined as, mean is the sum of the observations divided by the number of observations.

Where,

Xi= observations (i=1, 2, 3……., n)

n=number of observations

The mean is the arithmetic average of a set of values, or distribution; however, for skewed distributions, the mean is not necessarily the same as the middle value (median).

For example, mean income is skewed upwards by a small number of people with very large incomes, so that the majority has an income lower than the mean. By contrast, the median income is the level at which half the population is below and half is above.

For example, the arithmetic mean of 34, 27, 45, 55, 22, 34 (six values) is; (34+27+45+55+22+34)/6 = 217/6 ≈ 36.167.

Standard Deviation: is a measure of the spread of its values. The standard deviation is usually denoted with the letter σ (lower case sigma). It is defined as the square root of the variance.

To understand standard deviation, keep in mind that variance is the average of the squared differences between data points and the mean. Variance is tabulated in units squared. Standard deviation, being the square root of that quantity, therefore measures the spread of data about the mean, measured in the same units as the data.

Stated more formally, the standard deviation is the root mean square (RMS) deviation of values from their arithmetic mean. Below given is the formula for standard deviation.

Where,

Xi=random variable (i=1, 2, 3…n)

X = mean of the observations

n= number of observations

Median: A median is described as the number separating the higher half of a sample, a population, or a probability distribution, from the lower half. The median of a finite list of numbers can be found by arranging all the observations from lowest value to highest value and picking the middle one. If there is an even number of observations, the median is not unique, so one often takes the mean of the two middle values.

The table given below shows the mean standard deviation and other descriptive statistical measures of the IPO’s, the analysis is divided into three options, option A, B & C. these option are considered generally to define the data more accurately and to test the data more efficiently.

Table 01(A)

Option A: Takes into account the initial return of all the thirty companies and thereby calculating the mean that comes to 14.29% and a standard deviation of 65.46%, this tells us that there is high degree of dispersion between the returns of the securities, also we can see that the analysis given a median of 4.89% which is relatively small. This is due to an outlier (i.e. African Eagle Resources) generating a return of 283.33%. (Shown in fig 01(a))

Option B: Therefore, undertaking the analysis once more after removing the outlier (refer fig A) we get a more exact result; it can be now observed that the mean has relatively diminished and the result is less dispersed and shows less variance. Also we can see that the data is now more into the range with the maximum return of 76.67% and the minimum return of -86.69%. The count of the data i.e. the number of the observations has lessened by 1. Also the median is fairly close to the mean

Option C: The analysis of data in option c is done, to make sure the calculated statistical information was correct and accurate, what we did in this step was we made the data more defined by deleting 2 extreme negative returns and the positive outlier, therefore keeping the range of the return less than -35% and a max of 76.67%.what we concluded was that the result was more accurate with mean and the median close to each other and a less varied dispersion was obtained of 32%

Conclusion

Hence we can conclude that the initial return on the AIM had a dispersion of 32% with a portfolio of companies from the selected 4 sectors and a rational investment in the market could reap a return of at least 11%. Also we can observe that mean and median are relatively close to each other giving us a normal distribution.

24 month long-term return

For calculating the long-term return of 24 months for the IPO’s selected, the data taken into account is the annualized share price of 2006 and price of the stock as on 25^th march 2008 [Refer to appendix 02 (returns)], also keeping in mind the dividend paid during this period. The method used to calculate the long term return is similar to the formula used for calculating the initial return that is.

Initial Return = (P1 – P0) +div

P0

Where,

P0 = Annualized price for 2006

P1 = Price as on 25^th march 2008

Div = Dividend paid during the 24 month period

The figure shows the histogram of the returns produced by the IPO’s in the given 24 month period ,it is observed from the results, that the 24 month returns scarcely correlate with the initial returns of the IPO’s selected. African eagle resources the highest gainer initially has now produced negative returns of 19%, the biotechnology sector is still showing a bearish trend, the top gainer for the 24 month period selected is the ‘First Derivative’ generating a return of 146% , the biggest loser is the ‘Healthcare Enterprise Group’ generating -94.29% returns.

We can also say that during this period most of the securities in the AIM have generated negative returns with a some exceptional outliers showing a positive returns and a few with an outstanding return. In our selected portfolio around 19 securities out of 30 are generating negative returns.

Table 02

Testing the Long-term Return

Once again we have used the statistical tools to test the long term return of the IPO’s, same measures have been taken for deriving the mean and standard deviation of the calculated return in the Option A accounts for all the 30 companies, as could be observed the mean return of the portfolio was negative i.e. -13.5% with high spread of 63%. The range of the data in this option was big with the highest return of 146.41% and the lowest return of – 94.39%, the analysis seemed to be vague.

Therefore we run the analysis again (Option B) removing the high positive return of 146%, we found out that the mean return experience a greater fall reducing to -19% the dispersion lessens but is still significant, the median in both the cases is around -20% which do not link with the mean, thus we go for Option C that is, further removing a high positive outlier and hence obtaining a more precise outcome with a mean and median of -25% and a less dispersed data set, the count of the observations in this option is 28 that is 2 less than the given data set.

Conclusion

The tests of the returns show that the AIM during the 24 month period is demonstrating a bearish trend with certain stocks trying to go against the trend, the overall return that a balanced portfolio could generate out the market for the given period would be negative.

Further Analysis

In our study we have also collected the data on the return of equity (ROE) for the individual IPO’s (refer to appendix 02) these returns are the annualized returns for the securities (as on 25^th march 2008) the data collected is from official website of Reuters (link given in the references) we have used these returns to correlate the 24 month long-term returns that we have calculated correlating the ROE with the 24 month return calculated we get a correlation of 0.63 this shows that the 24 month returns and the return on equity link with each other (the correlation analysis is an additional analysis that our group has undertaken, this examination has further helped to verify the accuracy of the results).

Conclusion

The 30 IPO’s selected are some of the high risk equities , an investment in these securities can yield unpredicted returns both positive and negative, to argue this point refer to the beta’s exhibited in the appendix 0, the beta shows how volatile is the share price to the movement of the overall market, a non volatile stock should have a beta near to 1, but the computed beta’s show that there are certain securities that even show a beta of more than 3 which proves that the movement of these stocks are extremely volatile and hence the returns are uncertain.

References

• http://www.londonstockexchange.com/en-gb/pricesnews/investorcentre/companyprofile/companyprofileselection.htm

• www.reuters.com

• www.investopedia.com

• http://www.londonstockexchange.com/en-gb/pricesnews

• http://www.growthcompany.co.uk/aim/

• Introductory Econometrics, a modern approach, by; Wooldridge, Third edition.

• Business finance: A value- based approach, by; Neale & McElroy.
• IPO市场公司
  介绍
  该报告分析了30非金融IPO的，漂浮的另类投资市场（ AIM ） ， 2002年1月期间 - 2004年12月的表现，承担的主要任务是首先，定义30首次公开发行的，在浮动组合给出的时间段。其次，计算初始选定的首次公开募股和测试他们的回报。第三，获得24个月的同一证券的回报，其后测试这些回报，在这两个情况下（第二和第三）返回测试通过派生基本的描述性统计（平均，标准偏差等）对数据的收集，因此讨论和评论在同一
  首次公开招股，本集团已选定的样品基本上是从2002年1月 - 2003年12月精炼。考虑，而选择IPO的标准是做一个组合，将涵盖不同行业的市场，基本上多样化和界定这些证券在AIM市场的变动，更精确的样品被分为4个主要工业行业
  制药和生物技术。
  矿业。
  一般性金融。
  软件及电脑服务
  IPO的，我们已经选择浮动在市场配售或公开发售。如下表所示，本集团已选定的公司选择了一个详细的大纲上的数据，说明首次公开募股的公司的名称。 （签发日期，市值，发行价等）
  计算初始的IPO的回报
  用于计算初始的IPO的回报，我们已考虑该证券的发行价和12个月后的价格问题，同时铭记，如果在此期间支付任何股息。初始收益公式使用，我们已经有3个变量可以解决;
  初始收益率= （ P1 - P0 ） + DIV
  P0
  其中，
  P0 =发行价。
  P1 = 12个月后的价格。
  DIV =在此期间支付的股息。
  我们可以看到，对于12个月内考虑，制药与生物技术行业正在展现出一个看跌的趋势与DDD集团最低，为-86.69 ％ ，采金及其他矿物提取部门给予负回报是给人一种积极的回报非洲鹰资源在一年内最大的正回报283％ ， 12个月，在此期间，一般金融业的表现是看涨的，几乎所有的公司给予了积极的回报。还观察到的是组合中的大部分公司还没有宣布任何股息后的首个财政年度，因此在大多数的情况下，支付股息
  卡利登资源公司和医疗保健企业集团的发行价可能不被发现，因此，它是不可能计算有初步的回报。对于所有其他的库存，请参阅表0.01和显示返回的直方图（图01 ） 。对于广泛的借鉴和指导意义的回报如何计算参阅附录02 （回报） 。
  表.01
  安全
  回报（％）
  安全
  回报（％）
  COBRA生物制造
  -10.75
  CUSTOMVIS
  -24.17
  YM生物科学公司
  -21.78
  MICAP
  9.09
  了Cyprotex
  -70.68
  保健品企业集团
  辛克莱药业
  11.08
  DIPFORD集团
  10.71
  王泽HAMBRO矿业
  1.53
  灯塔集团
  -33.75
  高地黄金矿业
  55.26
  VANTIS
  -3.89
  蒙特瑞科金属
  35.18
  最终金融集团
  -37.5
  银禧PLATINUM
  25
  VOLVERE
  75
  CALEDON资源PLC
  评委资本
  36.842
  GMA资源
  76.67
  CANISP
  54.54
  非洲雄鹰资源
  283.33
  DDD组
  -86.69
  横贯西伯利亚的黄金
  -16
  PILAT MEDIA GLOBAL
  -7.5
  先进的医疗解决方案
  8.23
  统筹软件
  -25
  第一牙科实验室
  -12.03
  一阶导数
  46.5
  DAWMED系统
  22
  试金石集团
  -1.25
  测试的初始回报
  对于测试的回报，我们已经使用了一些基本的描述性统计工具如;
  平均数：平均值是“标准”的平均，并且被定义为平均的观测值的总和除以观测值的数量。
  其中，
  XI =观察（ I = 1 ，2，3 ......， N）
  N =若干意见
  均值是一组值，或分布的算术平均值，但是，对于倾斜分布，平均不一定是相同的中间值（中值） 。
  例如，平均收入是向上偏斜由少数人具有非常大的收入，使广大收入低于平均。与此相反，平均收入一半的人口是在哪一级的下面的一半是上面。
  例如，算术平均值为34 ， 27 ，45 ， 55 ， 22 ， 34 （ 6个值）是（ 34 +27 +45 +55 +22 +34 ） / 6 = 217 / 6 ≈ 36.167 。
  标准差是衡量其价值观的传播。的标准偏差通常是表示用字母σ （小写西格玛） 。它被定义为方差的平方根。
  要了解标准偏差，记住，方差是平均数据点之间的平均平方差。方差表（单位）的平方。标准偏差，即该数量的平方根，因此，测量的平均值，测量数据的单位相同的数据的传播。
  更正式地说，标准偏差是根均方（ RMS ）的偏差值的算术平均。在下面给出的标准差的公式。
  其中，
  西安=随机变量（I = 1 ，2 ，3 ，...，N ）
  X =意思的意见
  N =若干意见
  中位数：中位数被描述为分离的较高的样品的一半，人口，或一个概率分布，从下半部数量。有限的中位数的号码清单，可以发现从最低值到最高值，并安排所有的意见，挑选中间的一个。如果有偶数个观测值，中位数是不是唯一的，所以人们常常需要两个中间值的平均值。
  如下表显示的平均标准偏差和其他措施，首次公开招股的描述性统计，分析分为三个选项，选项A，B和C 。这些选项通常被认为是更准确地定义数据和测试数据更效率。
  表01 （ A ）
  选项A
  选项B
  选项C
  意味着
  14.29％
  4.32％
  10.96 ％
  圣开发
  0.6546
  0.3952
  0.3266
  最高
  283.33 ％
  76.67 ％
  76.67 ％
  最低
  -86.69 ％
  -86.69 ％
  -33.75 ％
  中位数
  4.89％
  1.54％
  8.24％
  算
  28
  27
  25
  选项A：考虑到初始收益的所有30家公司，并由此计算出的平均值为14.29％和65.46％ ，标准差为，这告诉我们证券的回报之间有高度分散，也我们可以看到，给定的分析中位数为4.89 ％，这是比较小的。这是由于一个离群值（即非洲雄鹰资源）产生回报283.33 ％ 。 （图中所示为：图01 （ a ）条）
  选项B：因此，进行一次分析后去除离群值（参考图一） ，我们得到了更准确的结果，现在可以观察到的平均相对减少，其结果是少分散，显示较少的方差。此外，我们可以看到，现在数据是范围最大的回报为76.67 ％和-86.69 ％的最低回报。的计数的观测数据的数量的数据，即已经减弱1 。此外，中位数相当接近均值的
  选项C：选项c中的数据分析，以确保计算的统计信息是正确的，准确的，我们所做的事情在这一步，我们做了更明确的数据，因此通过删除2的极端负回报和积极的离群保持回报率低于-35 ％ ， 76.67％和最大的范围内，我们的结论是，得到的结果是更准确的均值和中位数彼此接近和减多样化的分散体为32％ ，得到
  结论
  因此，我们可以得出结论，初始回报的AIM从选定的4个部门和在市场理性的投资组合公司中有32％的分散可以收获至少11％的回报。此外，我们可以观察到，平均数和中位数相对接近对方给我们一个正态分布。
  24个月之久的长期回报
  对于计算的24个月为首次公开招股的选择长期回报，考虑的数据是2006年的年度股价和价格的股票截至二零零八年三月二十五日[请参阅附录02 （回报率） ] ，也保持在介意在此期间支付的股息。用来计算长期回报的方法是类似的公式用于计算初始回报。
  初始收益率= （ P1 - P0 ） + DIV
  P0
  其中，
  P0 = 2006年年均价格
  P1 =价格为2008年3月25日
  DIV =在24个月期间支付股息
  图中显示的直方图在给定的24个月内的首次公开招股产生的回报，这是观察的结果， 24个月的回报率几乎与最初选择的IPO的回报。非洲雄鹰资源的最高涨幅现在已初步产生了19％的负回报，生物技术领域仍呈现下跌趋势，选定的24个月期间的涨幅最大的个股是“一阶导数产生146 ％的回报，最大的输家是“医疗保健企业集团产生-94.29 ％的回报率。
  我们也可以说，在此期间，大部分证券在AIM一些特殊离群呈现出积极的回报和一些杰出的回报产生负回报。在我们选定的投资组合中，约有19家证券出30产生负回报。
  表02
  安全
  回报（％）
  安全
  回报（％）
  COBRA生物制造
  -58.74 ％
  CUSTOMVIS
  77.45％
  YM生物科学公司
  -77.59 ％
  MICAP
  -77.32 ％
  了Cyprotex
  -3827 ％
  保健品企业集团
  -94.29 ％
  辛克莱药业
  -70.46 ％
  DIPFORD集团
  -87.80 ％
  王泽HAMBRO矿业
  6.26％
  灯塔集团
  21.33％
  高地黄金矿业
  20.94％
  VANTIS
  -22.01 ％
  蒙特瑞科金属
  -53.22 ％
  最终金融集团
  -73.68 ％
  银禧PLATINUM
  7.86％
  VOLVERE
  -8.93％
  CALEDON资源PLC
  32.39％
  评委资本
  19.49％
  GMA资源
  2.99％
  CANISP
  -88.89 ％
  非洲雄鹰资源
  -19.51 ％
  DDD组
  -38.30 ％
  横贯西伯利亚的黄金
  -22.67 ％
  PILAT MEDIA GLOBAL
  -54.60 ％
  先进的医疗解决方案
  105.45 ％
  统筹软件
  127.78 ％
  第一牙科实验室
  -21.83 ％
  一阶导数
  146.41 ％
  DAWMED系统
  -38.89 ％
  试金石集团
  -27.67 ％
  测试长期回报
  再次，我们已经使用的统计工具来测试的长短期回报的IPO ，采取同样的措施已经被采取推导计算期权回报的平均值和标准偏差为所有30公司à帐户，作为可以被观察到的投资组合的平均回报为负即-13.5 ％与63％的高利差。在此选项中的数据范围大回报率最高为146.41 ％ - 94.39％ ，回报率最低的分析似乎是模糊的。
  因此，我们再次运行分析（选项B ） ，去除146％的正回报高，我们发现，平均回报体验更大的下降减少-19％的分散减轻，但仍然显着，在这两种情况下的中位数是不链接，平均-20％左右，因此，我们去选项C ，进一步消除较高的阳性离群，用均值和中位数为-25 ％和设置一个不太分散的数据，从而获得更精确的结果在这个选项中观测的计数28 2小于给定的数据集。
  结论
  回报的测试表明，在24个月期间的AIM展示一个看跌的趋势，某些股票，试图去对抗的趋势，一个平衡的投资组合的整体回报，可能会产生一定时期内的市场将为负数。
  进一步的分析
  在我们的研究中，我们也收集数据的回报权益（ ROE ）的个别首次公开招股的（请参阅附录02 ）这些回报是的年率化回报率的证券（如在二零零八年三月二十五日）收集到的数据是从官方网站路透社（参考文献中给出的链接） ，我们使用这些回报相关的24个月的长期回报，我们所计算的净资产收益率相关联的24个月回报计算，我们得到的相关性为0.63这表明24个月的回报，返回链接与对方的股权（相关分析是一个额外的分析，本集团已承诺，进一步帮助这个考试来验证结果的准确性） 。
  结论
  30首次公开招股的选择是一些高风险的股票，这些证券的投资可以产生难以预料的回报正面和负面的，认为这一点的测试是展出的附录0 ，公测显示如何波动是股价到市场整体的运动，非挥发性的股票应该有一个测试接近1 ，但计算测试的节目，有若干证券，甚至表明这证明，这些股票的运动是极为动荡和一个测试超过3因此，回报是不确定的。
  参考文献
   
  www.reuters.com
  www.investopedia.com
   
  http://www.londonstockexchange.com/en-gb/pricesnews
  http://www.growthcompany.co.uk/aim/
  计量经济学导论，现代的做法，由伍尔德里奇，第三版。
  企业融资：基于价值的方法;尼尔＆麦克尔罗伊。