business finance report final

7/29/2019 Business Finance Report Final

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1 IntroductionThis report intends to explain the aims and objectives of the portfolio project

undertaken. In order to determine whether any aims and objectives have been

achieved, relevant theory and analysis of findings will be used. The aims of thisportfolio project was to invest a notional principal amount of 200,000 was made

available to invest in securities on the London Stock Exchange during the period from

4th October 2010 till the 1st April 2011, on which date the portfolio will be liquidated

and any gains realised. Furthermore the project will be split between the two terms, in

which to different investment strategies will be applied, in the first term an active

trading strategy shall be adopted whereas in the second term a buy and hold strategy

shall be put into place. The objective of this project was to develop an understanding

of the stock market and to create a portfolio that is well diversified and minimises

total risk. Moreover, this report shall explain any relevant theory in order to and

demonstrate how this affected the strategy that was adopted for investment and how it

was used in practice. It will also outline any limitations that were found through the

project. Furthermore, the findings will be explained, showing how using different

strategies affected the profit from investment, for example if active trading gave

higher profit than buying and holding the shares. Finally, the report will come to a

conclusion which will show in general how the market has performed and if the

project would be approached differently if done again.

2 Theory:2.1Stock Market.

The stock market acts as an efficient allocator of funds within the financial economy.

The stock market is split into the primary and secondary markets. The primary market

is there so newly issued shares can be sold to raise capital for the company. The

secondary market is for existing shares and involves in the buying and selling these

shares.

2.2Relationship between risk and returnThe risk of a security is the uncertainty that the actual return will vary from the actual

return. In an efficient capital market investors are risk averse and will want greater

levels of return for being exposed to higher levels of risk. However with greater levels

of risk the investor has a higher chance of earning greater returns. The risks that the

investors are likely to face are systematic and unsystematic risk. Systematic risk is the


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inherent market risk that every business and investor faces and cannot be reduced

with diversification, the amount of systematic risk the investor is out of their control it

controlled by factors in the environment surrounding the market and therefore is

unavoidable. Unsystematic risk is the company or industry specific risk and can be

reduced with the appropriate diversification; it is caused by a number of factors e.g.

managerial inefficiency. Unsystematic risk is broken down into 2 categories; Business

Risk and Financial Risk. Business risk is the risk associated with circumstances of

the particular company which may affect the ability of the company to produce stable

earnings. Financial risk of the company is affected by the level debt to equity

financing it has, with higher levels of debt the investor has a higher risk of losing their

investment if the company goes into administration.

2.3Portfolio Theory:Portfolio theory was developed by Harry Markowitz, 1952, in order to quantify the

risk of an investment portfolio, and to help investors develop an optimal portfolio.

This a theory where the investor creates a portfolio in order to maximise their return

from their investment at a given level of portfolio risk by diversification and using

proportions of various securities. Modern Portfolio Theory is based on a number of

assumptions in order for the model to hold. The assumptions of the theory include;

there are no transaction costs or taxes, all investors will have access to information at

the same time, all investors are price taker and therefore do not have an effect on the

share price, all investors will try to maximise economic benefit and all investors will

be able to accurately predict possible returns. However some of the assumptions that

are needed for the model for hold are unrealistic. In reality investors are subject to

taxes and transaction cost and therefore their optimal portfolio will be different from

the one calculated with the model. Moreover, the model also assumes that investors

are price takers; however in reality if investors were to buy and/or sell shares in large

quantities then they would have an effect on the share price. Furthermore, the model

assumes that shares can be split into fractions in order to have correct proportion that

should be invested, however in reality this may not be possible and the investor may

be required to purchase a minimum order of shares and therefore this would also

affect the optimal portfolio that was derived from the model. Therefore portfolio

theory is a useful tool for quantifying risk and creating a portfolio using

diversification in order to reduce risk, however the optimal portfolio produced by themodel may have to be adjusted because of the unrealistic assumptions.


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2.4Efficient Market HypothesisThe Efficient Market Hypothesis implies that, if new information is revealed

about a firm, it will be incorporated into the share price rapidly and rationally,

with respect to the directions of the share price movement and the size of that

movement (Arnold, 2008, p. 563)For a stock market to be efficient, it has to be

Operationally, Allocationally and Pricing Efficient. The market is operationally

efficient when transactions take place at the lowest possible cost, speedily and reliably.

A market is allocationally efficient when resources are allocated to the firms which

will use them to be the most productive. The major implication for investment is

that investors cannot expect to beat the risk-adjusted average, except by chance.

Investors should instead seek to maximise the effectiveness of diversification in

their portfolio. (Firth et al, 1986, p. 12) Furthermore, a market is pricing efficient

when the investor can only earn a risk adjusted return from their investments as prices

move immediately and unrelated to announcement. Within an efficient market,

investors will not be able to make any abnormal profits because all historical and

present information about the company will be reflected in the share price, and only

new information will bring a change in the share price, and as news is unforecastbale

as a result future prices are as well. Within the efficient market there is three levels of

efficiency; weak-form, semi-strong form and strong-form efficient. In a Weak-form

efficient market the current share price will reflect all information that caused past

price movements. In a Semi-strong form efficient market current share prices will

reflect all information available to the public, such as earnings reports and dividend

announcement, and therefore assuming that there will be no point in analysis publicly

available information after release as it will be incorporated in the share price. In a

Strong-form efficient market all relevant information about the company has been

reflected within the share price and no one, not even people with inside information,

is able to make an abnormal profit. In reality, stock markets are seen to be closer to

semi-strong form efficiency because most investors are only able to view publicly

available information, but are not able to use that information to make a gain as it will

be reflected in the share price instantaneously. This is backed up by Firth (1967a,

1979, 1980) who found that after the announcement of a takeover bid share prices

were instantaneously and fully adjusted to their correct levels.

2.5Random Walk Theory:


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The random walk model is assumed to imply that successive price changes (or

more usually, successive one-period returns) are independent. In addition, it was

usually assumed that successive changes (or returns) are identically distributed.

Together the two hypotheses constitute the random walk model." (Fama (1970), p.

386.) The random walk theory suggests that future changes in stock prices cannot be

predicted by looking at trends in past price movements. Moreover evidence from

empirical testing shows that a technical trader using past prices for investment

decisions will not be able to realise greater profits than those investors that choose to

buy and hold.

2.6Beta:The Beta of a security is the measure of how volatile the security is compared to the

market portfolio, therefore is a measure of the systematic risk of the company. In this

case the FTSE 100 has been used as a proxy for the market portfolio and therefore has

a Beta of 1. If a security is more volatile than the market in general then it is likely to

be more risky, therefore it will have a Beta of greater than 1. If a security is less

volatile than the market it is seen it is seen as being less risky as well and will have a

Beta of less than 1. The Beta is a useful to the investor because helps them determine

whether they are likely have a higher or lower return, for example if a security has a

Beta of more than 1 then it is more risky and the investor can expect that it will

provide higher levels of return and vice versa. However, because the Beta of a

security is calculated using historical price information will give little indication to the

investor of how the security will perform in the future and is no guarantee of future

returns. Furthermore because the Beta is calculated on historical prices it is not

possible to calculate an accurate Beta on newly issued securities.

2.7Filter Rule.The filter rule involves the investor looking at historical trends in share prices to

identify a pattern which will make it possible for the investor to determine when it is

the best time to buy or sell a security and will create a point, when the share price is

percentage above or percentage below the current share price. The advantage of

using this will be that the investors loss will be limited during a bear market, and the

investor will be able to spot opportunities to buy during a bull market. However when

taking into account transaction costs and commission, a buy and hold strategy may

provide better earnings.


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3 Strategy Explained:3.1Diversification of portfolio

The purpose of diversification of my portfolio was to reduce the total risk that I faced,

this is done to try and minimise the variability in the average earnings. Diversificationto minimise total risk involves buying shares across many different industries this is

backed by Markowitz in his journal of portfolio selection where he states that The

adequacy of diversification is not thought by investors to depend solely on the

number of different securities held. A portfolio with sixty different railway

securities, for example, would not be as well diversified as the same size portfolio

with some railroad, some public utility, mining, various sorts of manufacturing,

etc. The reason is that it is generally more likely for firms within the same

industry to do poorly at the same time than for firms in dissimilar industries.

(Markowitz, 1952, pp.77-91) In order for diversification to be successful in reducing

risk the portfolio will have to spread across different sectors, this is because across the

different sectors a negative in one industry will generally be outweighed by a positive

performance in another industry therefore reduce the chance of loss. Furthermore

diversification reduces the unsystematic risk that the investor faces, and making the

systematic risk the main risk that they face. However diversification across industries

will only be affective if the securities are not perfectly correlated.

3.2Reason why I selected sharesBefore buying any shares I decided to, at first, use simple techniques to determine

which securities to purchase, this was because I did not have sufficient knowledge of

the stock market. At first I used the random walk approach to select shares, this

involved drawing a line across the financial times shares and picking any shares that

were any points across the line. Furthermore, I also picked the first few shares

according to companies I know, because I thought it would have been easier to keep

track of companies that I am interested in. However these techniques did not take into

account any level of risk involved. My strategy was to try and pick shares that had a

low or medium level of risk attached to them, this was because I wanted the portfolio

to have less volatility in the returns, to do this I tried to find the Beta of various share

to see how they performed in comparison to the market. Beta, as explained above is

the measure of systematic risk of the company compared to the market. Furthermore,

once I have selected the shares I want to buy and hold, I will pick a selection of 5


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shares and the market proxy, and will monitor their returns for a 6 month period. This

will allow me to work out their returns over that period and use them to work out the

Beta of each security, to show if they are aggressive or defensive in comparison to the

market. The higher the beta will show that the shares have a higher systematic risk.

Moreover I will also calculate the standard deviation of the 5 shares and the market

proxy to measure of how far apart the data is from the average of the data. If all the

observations are close to their average then the standard deviation will be small,

whereas if the observations are spread then their standard deviation will be higher.

The standard deviation will also show how risky each security is, and can be used to

calculate expected returns.

4 Relate theory to practiceWhile the project was ongoing I decided to see the effect that any public

announcements would have on the share price of a company, this was to see if the

efficient market hypothesis held and the UK stock market was semi-strong efficient. I

monitored the share price the day before and after the announcement in order to

determine whether the theory held or not. This was based on the assumption that

favourable news should see a rise in the share price and negative news will see a

decrease in the share price. Moreover I calculated Beta for a select number of shares

to determine how they would react in comparison to the market.

5 LimitationsThroughout the duration of the portfolio project I found limitations with the strategy I

used. When I was using the random walk approach for selection of my shares I found

that my shares were being diversified because the line did not cross the same industry

more than once. However these initial techniques were simple ways of picking

securities to purchase, however these methods of picking shares did not take into

account what level of risk the security has attached to and therefore it will not be clear

if the greatest level of returns were being achieved for the given level of risk.

Moreover I was not able to determine an accurate Beta of a security because there was

not enough finance available to create the market portfolio. The market portfolio is

defined as A theoretical bundle of investments that includes every type of asset

available in the world financial market, with each asset weighted in proportion


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to its total presence in the market. (Investopedia, 2011) With the market portfolio

all unsystematic risk will be diversified away, leaving only systematic risk. This was

desirable because, in reality a proxy to the market is being used, which would contain

an element of unsystematic risk within the calculation of Beta, whereas when using

the market portfolio all unsystematic risk will be diversified away leaving only the

systematic risk showing the true performance of the security in relation to the market.

Furthermore I found that there was a lack of information within the stock market and

was not able to determine how much of the risk associated with each company, was

business risk or financial risk this was not possible as there was insufficient data about

the stability of earnings compared with other companies in the industry.

6 FindingsAt the end of the portfolio project once the shares had been liquidated, I found that

efficient market hypothesis hold, in respect

to it being semi-strong efficient and

incorporating public announcements in share

prices instantaneously. I found this

monitoring the share price of three

companies after public announcements. In

regards to HMV Group and Renovo PLC, the

negative public announcement (Appendix 17

& 18) had an instantaneous negative effect

on the share price of the company as the market reacted to the news, the share prices

dropped 16.6% and 75.2% respectively. However in the case of Ocado PLC

(Appendix 16) there was not instantaneous reaction to the news, yet the share price

rose slowly to its peak then levelled out, this is demonstrated by (Appendix 10).

Moreover, I general I found that the shares that I was monitoring showed an upward

move (Appendix 10-14), except for GlaxoSmithKline (Appendix 12) which in general

went down this was due to several negative public announcements over the period

monitored, in addition over the time period monitored, the market index (Appendix 15)

showed an upward move in its share value. Additionally while calculating the Beta

for the securities (Appendix 5 to 9), I found that each of the securities were between 0

and 1. Therefore they were all less aggressive than the market proxy therefore were

HMV Share Price

Before News 43.75p 8th Dec 2010

After News 36.50p 9th Dec 2010

Renovo

Before News 68.5p 10th Feb 2011

After News 17.00p 11th Feb 2011

Ocado

Before News 181.00p 10th Jan 2011

After News 285.00p 8th Feb 2011


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less risky. However, within my Beta calculations I found that GlaxoSmithKline had a

Beta between 0 and 1 (Appendix 7), so in theory it should have moved up with the

market but a slower rate, however when compared with the graph for share prices of

the company (Appendix 12) and the market (Appendix 14), this shows that using Beta

to select share may not always be applicable. Furthermore, when adopting the

different strategies during the two terms, either to be an active trader or to buy and

hold, I found that the profit that the profit figures (Appendix 3) with the two strategies

were close to each with active trading jus coming out better. I believe this is due to

being able to sell share when you see that they peaked, because I found that buying

and holding the shares made me miss out on the selling shares when they on the rise,

in addition to this with the buying and holding strategy I was subject to bad news

(Appendix 18) causing the share price to drop rapidly and make a loss on that security.

7 ConclusionThe objective of this project was to create a well diversified portfolio, using different

strategies within the two terms, to buy and hold and to actively trade. Over the project

relevant theory was used to influence decisions to buy and sell securities.

I have found through this project that active trading may have been the best strategy

because it allowed me to benefit from positive performance and limit my loss when

performance was negative.

If I were to do this project again, I would have applied the filter rule to a section of

my portfolio as it may have given me a guide when to sell share, i.e. following a 5%

fall in price.


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8 References.Fama, E F. "Efficient Capital Markets: A Review of Theory and Efficient Work,"Journal

of Finance, 26, No. 1 (May, 1970), pp. 383-417.

Markowitz, H. Portfolio Selection, the Journal of Finance, Vol. 7, No. 1 (Mar, 1952),pp. 77-91

Fama, E. Efficient capital Markets: II, Journal of Finance 46, (1991), pp.1575-1617.

Goldfarb, D. Iyengar, G. Mathematics of Operations Research, Vol. 28, No. 1 (Feb,

2003), pp. 1-38.

Arnold, G. (2008), Corporate Financial Management, 4th ed, Harlow, Pearson Education

Limited.

Brealey, R. Myers, S. Allen, F. (2008), Principles of Corporate Finance, 9th Ed,

McGraw-Hill.

Investopedia,Market Portfolio, [Online], Available at:

[Accessed 1 April 2011].

Firth, M. Kean, S. (1986),Issues In Finance, Philip Allan Publishers Limited.

9 Appendix


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Appendix 3: Profit from Sales

Total Profit 9,314.90

Profit From Active Trading 4,557.30

Profit From Buy And Hold 4,446.38

Appendix 4: Standard Deviations

Appendix 5: Ocado Beta

SUMMARY OUTPUT

Regression Statistics

Multiple R 0.152296456

R Square 0.023194211

Adjusted R Square 0.013801847Standard Error 0.035369821

Observations 106

ANOVA

df SS MS F Significance F

Regression 1 0.003089374 0.003089374 2.469475432 0.119114163

Residual 104 0.130106521 0.001251024

Total 105 0.133195895

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 0.004693269 0.003448128 1.36110647 0.176422015 -0.002144497 0.011531035 -0.002144497 0.011531035

X Variable 1 0.621187976 0.395294422 1.571456468 0.119114163 -0.162695674 1.405071626 -0.162695674 1.405071626

Beta 0.621187976

Market 0.8768305%

Ocado 3.5616462%

BSkyB 0.7027800%

GlaxoSmithKline 1.1678031%

Inmarsat 1.3745059%

Admiral 1.3425711%

Market Beta 1


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Appendix 6: BskyB Beta

Appendix 7: GlaxoSmithKline Beta

SUMMARY OUTPUT


Multiple R 0.335718288

R Square 0.112706769Adjusted R Square 0.104175103

Standard Error 0.006651674

Observations 106

ANOVA


Regression 1 0.000584491 0.000584491 13.21040619 0.000434598

Residual 104 0.004601455 4.42448E-05

Total 105 0.005185947


Intercept 0.001292606 0.000648457 1.993355662 0.04884136 6.69091E-06 0.002578521 6.69091E-06 0.002578521

X Variable 1 0.270194713 0.07433935 3.634612248 0.000434598 0.122776996 0.41761243 0.122776996 0.41761243

Beta 0.270194713

SUMMARY OUTPUT


Multi ple R 0.505151476

R Square 0.255178014

Adjusted R Square 0.248016264

Standard Error 0.010126838Observations 106

ANOVA


Regression 1 0.003654028 0.003654028 35.63067952 3.34537E-08

Residual 104 0.010665496 0.000102553

Total 105 0.014319524

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0%

Intercept -0.001042083 0.000987244 -1.055547749 0.293620812 -0.002999824 0.000915658 -0.002999824

X Variable 1 0.675575262 0.113177914 5.969143952 3.34537E-08 0.451139217 0.900011307 0.451139217

Beta 0.675575262


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Appendix 8: Inmarsat Beta

Appendix 9: Admiral Beta

SUMMARY OUTPUT


Mul ti pl e R 0.222112205

R Square 0.049333832

Adjusted R Square 0.040192811

Standard Error 0.013466

Observations 106

ANOVA


Regressi on 1 0.00097865 0.00097865 5.396971807 0.022118085

Residual 104 0.018858647 0.000181333

Total 105 0.019837297


Intercept 0.000247896 0.001312771 0.188834159 0.850590808 -0.002355379 0.002851171 -0.002355379 0.002851171

X Variable 1 0.349624207 0.150496507 2.323138353 0.022118085 0.051183995 0.648064419 0.051183995 0.648064419

Beta 0.349624207

MMARY OUTPUT


ltiple R 0.45414852

quare 0.206250878justed R Square 0.198618675

ndard Error 0.012018684

servations 106

OVA


gression 1 0.00390355 0.00390355 27.02376698 1.0096E-06

sidual 104 0.015022672 0.000144449

al 105 0.018926221


ercept -0.000382433 0.001171676 -0.326398668 0.744778668 -0.00270591 0.001941043 -0.00270591 0.001941043

ariable 1 0.698260836 0.134321255 5.198438898 1.0096E-06 0.431896754 0.964624917 0.431896754 0.964624917

ta 0.698260836


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Appendix 10: Ocado Graph

Appendix 11: BskyB Graph

Appendix 12: GlaxoSmithKline Graph

0

50

100

150

200

250

300

19/9/10 9/10/10 29/10/10 18/11/10 8/12/10 28/12/10 17/1/11 6/2/11 26/2/11 18/3/11

Ocado

680

700

720

740

760

780

800

820

840

19/9/10 9/10/10 29/10/10 18/11/10 8/12/10 28/12/10 17/1/11 6/2/11 26/2/11 18/3/11

BSkyB

1100

1150

1200

1250

1300

1350

19/9/10 9/10/10 29/10/10 18/11/10 8/12/10 28/12/10 17/1/11 6/2/11 26/2/11 18/3/11

GlaxoSmithKline


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Appendix 13: Inmarsat Graph

Appendix 14: Admiral Graph

Appendix 15: FTSE 100 Graph

600

620

640

660

680

700

720

740

19/09/10 09/10/10 29/10/10 18/11/10 08/12/10 28/12/10 17/01/11 06/02/11 26/02/11 18/03/11

Inmarsat

1,450.00

1,500.00

1,550.00

1,600.00

1,650.00

1,700.00

1,750.00

1,800.00

19/9/10 9/10/10 29/10/10 18/11/10 8/12/10 28/12/10 17/1/11 6/2/11 26/2/11 18/3/11

Admiral

5,500.00

5,600.00

5,700.00

5,800.00

5,900.00

6,000.00

6,100.00

6,200.00

19/9/10 9/10/10 29/10/10 18/11/10 8/12/10 28/12/10 17/1/11 6/2/11 26/2/11 18/3/11

FTSE 100


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Appendix 16: Financial Times: January 10 2011: Ocado reports 27% rise in Christmas sales

Ocado, the online grocer, on Monday reported a 27 per cent rise in sales in the four weeks

to Christmas as shoppers took to the internet to avoid the severe weather and busy

supermarkets. Fourth-quarter sales increased 27.4 per cent to 178.9m, compared with

140.5m last year. Average orders per week for the period were 28 per cent higher

against last year, while average order size was broadly flat at 112.12 compared with

112.67 last year. Gross sales rose 29 per cent to 551.1m for the 52 weeks to November

28, compared with 427.3m last year, in line with analysts consensus estimates. Ocado

said it was able to deliver 98 per cent of orders during the Christmas period in spite of the

snowy conditions, although it did have to reduce the number of delivery slots available to

customers in light of the weather. Andrew Bracey, chief financial officer, said Ocado has

done exactly what it said it would do at the time of the flotation and added that the group

was in line with market expectations for full-year earnings. Ocado is due to report

preliminary results on February 1. However, shares in the group slid 3 per cent to 180p

in afternoon London trading. The stock, which floated last July at 180p, had rallied in

recent sessions on expectations of a strong Christmas performance, having spent much of

the past five months below the offer price. In our view, the December trading indicates

that Ocado had a solid start to the new financial year despite the challenging weather

conditions, said Karen Hooi and Temilade Olatunde, analysts at Goldman Sachs, one of

the banks that advised Ocado on its IPO. They estimate sales growth for the current

financial year of 29 per cent on earnings before interest, tax, depreciation and

amortisation of 39.4m. Ocado said the timeline and budget for a second processing site,

or customer fulfilment centre, were on track and it had appointed a main building

contractor. The centre, based on the Staffordshire/Warwickshire border, will give Ocado

four times the order-processing capacity it had going into the listing. It will create around2,000 new jobs.

http://www.ft.com/cms/s/0/92e19864-1c8b-11e0-a106-00144feab49a.html#axzz1Igbc0i6l
http://markets.ft.com/tearsheets/performance.asp?s=uk:OCDOhttp://markets.ft.com/tearsheets/performance.asp?s=uk:OCDOhttp://www.ft.com/cms/s/0/92e19864-1c8b-11e0-a106-00144feab49a.html#axzz1Igbc0i6lhttp://www.ft.com/cms/s/0/92e19864-1c8b-11e0-a106-00144feab49a.html#axzz1Igbc0i6lhttp://www.ft.com/cms/s/0/92e19864-1c8b-11e0-a106-00144feab49a.html#axzz1Igbc0i6lhttp://markets.ft.com/tearsheets/performance.asp?s=uk:OCDO


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Appendix 17: HMVshares slump as big freeze adds to its woes

(Reuters) - Music, DVD, games and books retailer HMV (HMV.L) said severe weather was

hitting Christmas trade, compounding problems caused by competition from grocers and the

internet which have driven some peers out of business.

The British group posted a wider-than-expected first-half loss, a big increase in its debt and

cut its dividend, sending its shares down as much as 29 percent to a record low of 31 pence

on Thursday.

With forecasters predicting more snow and sub-zero temperatures in the run-up to Christmas,

chief executive Simon Fox said he was concerned about the short term trading outlook.

"Our stores are ready (for Christmas). We have done everything we possibly can but if

customers cannot get on to the high street it will be very serious for all retailers, including

ourselves," he told reporters.

He said the outcome for HMV's year to end-April would be largely determined by the next

four weeks of the Christmas trading period which together with the final four months of the

year account for 60 percent of total sales.

Prior to Thursday's update HMV shares had lost 62 percent of their value over the past year,massively underperforming a 3 percent fall in the general retailers index .FTASX5370.

"These results do little to ease fears that HMV is slowly being consigned to the history

books," said Keith Bowman, analyst at Hargreaves Lansdown Stockbrokers.

The 89-year-old group, which trades from over 730 HMV, Fopp and Waterstone's stores, has

benefited in recent years from the demise of rivals like Woolworths, Zavvi and Borders. But

it faces the same competition from supermarkets, online retailers and digital downloading

that landed those businesses in trouble.

In March, it set out a strategy to boost profits focused on evolving its product mix, growing

business in live music and ticketing, and improving Waterstone's margins.

"The attempts by the group to diversify into live music have had little effect, today leaving

shares of the group worth roughly 30 percent of their market valuation in 2009," said Richard

Curr, head of dealing at Prime Markets.
http://uk.reuters.com/business/quotes/overview?symbol=HMV.Lhttp://uk.reuters.com/business/quotes/overview?symbol=HMV.Lhttp://uk.reuters.com/business/quotes/overview?symbol=HMV.Lhttp://uk.reuters.com/business/quotes/overview?symbol=HMV.L


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"The statement today paints a stark picture of a company in an increasingly rapid decline,

with increased losses, falling like-for-like sales and soaring debt levels."

Citi analysts said they expected HMV to move into a "sharp cost reduction phase" in 2011,

that could include closing shops.

PROFIT FORECASTS FALL, DEBTS RISE

HMV, which makes all its profits in its second half, made an underlying pretax loss of 41.3

million pounds for the six months to October 23, compared with analyst forecasts for a loss

of 38-39 million pounds, according to a company poll.

Sales fell 6 percent to 749.5 million pounds, with sales at stores open over a year down 11.5

percent. Underlying net debt surged 72 percent to 151.6 million pounds and the company

halved its interim dividend to 0.9 pence a share.

"The concern is that, if double digit like-for-like sales declines perpetuate, then even our

forecasts could be too high and this could cause significant cashflow weakness," said Altium

analyst Philip Dorgan, who is forecasting a full-year profit of 46 million pounds, down from

74.2 million last year.

Aside from the severe weather Britain's retailers are worried higher taxes and public spendingcuts aimed at reducing government debt will hit consumer demand in the months ahead.

An industry survey on Tuesday showed British retail sales growth slowed in November,

while on Wednesday electricals retailer Kesa (KESA.L) said the market environment was

"increasingly uncertain" and computer games group Game (GMG.L) said its profit margins

would fall by more than it previously expected.

At 1204 GMT, HMV shares were down 26 percent at 32-1/2 pence, valuing the company at

about 135 million pounds and helping to drag down the UK general retail index .FTASX5370.

http://uk.reuters.com/article/2010/12/09/us-hmv-

idUKTRE6B828U20101209?pasgeNumber=1
http://uk.reuters.com/business/quotes/overview?symbol=KESA.Lhttp://uk.reuters.com/business/quotes/overview?symbol=KESA.Lhttp://uk.reuters.com/business/quotes/overview?symbol=KESA.Lhttp://uk.reuters.com/business/quotes/overview?symbol=GMG.Lhttp://uk.reuters.com/business/quotes/overview?symbol=GMG.Lhttp://uk.reuters.com/business/quotes/overview?symbol=GMG.Lhttp://uk.reuters.com/article/2010/12/09/us-hmv-idUKTRE6B828U20101209?pasgeNumber=1http://uk.reuters.com/article/2010/12/09/us-hmv-idUKTRE6B828U20101209?pasgeNumber=1http://uk.reuters.com/article/2010/12/09/us-hmv-idUKTRE6B828U20101209?pasgeNumber=1http://uk.reuters.com/article/2010/12/09/us-hmv-idUKTRE6B828U20101209?pasgeNumber=1http://uk.reuters.com/article/2010/12/09/us-hmv-idUKTRE6B828U20101209?pasgeNumber=1http://uk.reuters.com/business/quotes/overview?symbol=GMG.Lhttp://uk.reuters.com/business/quotes/overview?symbol=KESA.L


18/18

Appendix 18: February 11th

2011: Renovo's anti-scarring product fails; shares plunge

Key anti-scarring product Juvista fails in Phase III trial

Renovo's shares down 75 pct

LONDON, Feb 11 (Reuters) - Renovo (RNVO.L) said its key anti-scarring product Juvista

had failed in a final stage clinical trial, sending shares in the British biotechnology group

plunging. "We are extremely surprised and disappointed by the failure of Juvista to meet the

Phase III trial primary and secondary endpoints," chief executive Mark Ferguson said in a

statement on Friday.

"The board of Renovo will now consider all options open to it to maximise shareholder

value."

Pharmaceutical group Shire (SHP.L) has a licence to sell Juvista in the United States, Mexico

and Canada.

Shares in Renovo fell 75 percent following the failure, wiping nearly 100 million pounds

($161 million) from the company's valuation.

Shire's shares were 1.5 percent higher. (Reporting byPaul Sandle, Editing by Mark Potter)

http://uk.reuters.com/article/2011/02/11/renovo-idUKLDE71A1D520110211
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