Group 1:- Tiago Pena Pereira- Roman Prokofjev- Adam Konkolski

MultinationalFinancial

Management

Case study 1

TABLE OF CONTENTS

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1. The annualized returns and standard deviations for the equity markets of Australia, Canada, France, Germany, Hong Kong, Japan, UK, and the US from 1981-2003using both native currency based returns and US dollar based returns

Our target is to compare the market among each other´s. First our group has transformed the data to percentage monthly return of each market. We have transferred as well data of each market to US based percentage monthly return. Based on this modified data we have continued with our comparison.

1.1 Strategic Orientation Compare the performance of the stock markets in different coun-tries over various time periods

For comparing the performance group number 1 has calculated following aspects: Mean by year, Variance and Annual Standard Deviation. We have done it for both, Local currency markets, and US based currency markets.

Exhibit 1 – Mean of Annual returns versus Standard Deviation of each Country, in local currency

The upper graph shows the comparison between Mean and Standard Deviation of all markets in local currency. The highest Standard deviations in comparison to the mean we can notice in few markets, Honk Kong, Japan, Germany we can assume as well as reaching out of the mean.

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Exhibit 2 – Mean of Annual returns versus Standard Deviation of each Country, in USD base

This graph shows comparison between Mean and S.D. of each market US Based. The difference between Mean and S.D. has increased for countries Honk Kong, Japan¸ Germany rather stood stable but Australian “gap” has increased.

1.2 Use the Sharpe ratio to compare the performance of each stock marketOur next goal was to compare the market among each other based on Sharpe Ratio.

We were dealing with a problem how to estimate the Risk Free Rate; finally we have solved such an issue by estimating average during past 23 year based on the interest rate on a three-month U.S. Treasury bill is often used as the risk-free rate. After such a calculation we have come out with the Risk Free Rate for each market fixed on 5, 96%. We as well assume that the Risk free Rate fixed for all markets is for comparison purposes sufficient.

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The most stable is Us market the SHP shows that this market brings highest return in terms of risk. In terms of local currency the best is United Kingdom with the highest SHP. If we talk about the local markets than third market is France, but if we take I consideration the US based fluctuation, then immediately all SHP ratios drop, and after US market the most interesting in returns in term of risk is United Kingdom and France.

Summary data - Annual baseAustralia Canada France Germany Hong Kong Japan U.K. U.S.

Annual Return - Local currency 13,64% 12,23% 16,46% 12,19% 19,07% 6,99% 15,85% 14,99%

Annual Return - USD based 12,61% 12,21% 16,03% 13,60% 17,32% 11,05% 14,69% 14,99%

Annual Return - Local/USD 2,55% 0,53% 1,23% -0,40% 1,91% -2,03% 1,88% 0,00%

S.D. - Local currency 18,56% 15,52% 20,74% 19,57% 30,69% 19,25% 16,65% 15,53%

S.D. - USD based 23,44% 17,82% 21,75% 20,73% 31,64% 23,96% 18,39% 15,53%

S.D. - Local/USD 10,65% 4,97% 11,29% 11,35% 3,95% 11,99% 10,94% 0,00%

SHP - Local currency 0,41 0,40 0,51 0,32 0,43 0,05 0,59 0,58

SHP - USD based 0,28 0,35 0,46 0,37 0,36 0,21 0,47 0,58

SHP - Local/USD -0,32 -1,09 -0,42 -0,56 -1,02 -0,67 -0,37 0,00

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Exchange Rate Analysis(Annual base - 1981-2003 period)

Mean (%) SD(%) SHP Mean (%) SD(%) SHP Δ SHP Δ% ΔR (p.a.)Australia 13,6% 18,6% 0,41 12,6% 23,4% 0,28 0,13 31,4% 2,4%Canada 12,2% 15,5% 0,40 12,2% 17,8% 0,35 0,05 13,2% 0,8%France 16,5% 20,7% 0,51 16,0% 21,8% 0,46 0,04 8,5% 0,9%

Germany 12,2% 19,6% 0,32 13,6% 20,7% 0,37 -0,05 -15,7% -1,0%Hong Kong 19,1% 30,7% 0,43 17,3% 31,6% 0,36 0,07 15,9% 2,1%

Japan 7,0% 19,3% 0,05 11,0% 24,0% 0,21 -0,16 -298,6% -3,1%U.K. 15,8% 16,6% 0,59 14,7% 18,4% 0,47 0,12 20,0% 2,0%U.S. 15,0% 15,5% 0,58 15,0% 15,5% 0,58 0,00 0,0% 0,0%

Domestic Results US based Results Effects of exchange rates

Effects of changes in the exchange rate(Annual base - 1981-2003 period)

Var (Ri$) Var (Ri) Var (ei) 2 Cov (Ri,ei) Δ Var

Australia 5,5% 3,4% 1,1% -0,09% 1,0%Canada 3,2% 2,4% 0,2% -0,04% 0,6%France 4,7% 4,3% 1,3% 0,07% -0,9%

Germany 4,3% 3,8% 1,3% 0,07% -0,9%Hong Kong 10,0% 9,4% 0,2% -0,05% 0,5%

Japan 5,7% 3,7% 1,4% -0,03% 0,6%U.K. 3,4% 2,8% 1,2% 0,06% -0,6%U.S. 2,4% 2,4% - - -

* Formula:

1.3 Evaluate the effect of exchange rate fluctuations

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Correlations among international stock returns(in Local Currency, 1981-2003 period) Annual baseAustralia Canada France Germany Hong Kong Japan U.K. Mean (%) SD (%) SHP Rank

Australia 13,6% 18,6% 0,41 5

Canada 0,59 12,2% 15,5% 0,40 6

France 0,41 0,53 16,5% 20,7% 0,51 3

Germany 0,43 0,51 0,71 12,2% 19,6% 0,32 7

Hong Kong 0,47 0,48 0,37 0,45 19,1% 30,7% 0,43 4

Japan 0,33 0,38 0,40 0,35 0,28 7,0% 19,3% 0,05 8

U.K. 0,53 0,63 0,61 0,60 0,54 0,40 15,8% 16,6% 0,59 1

U.S. 0,51 0,78 0,59 0,58 0,45 0,38 0,71 15,0% 15,5% 0,58 2

Correlations among international stock returns(in US dollars, 1981-2003 period) Annual baseAustralia Canada France Germany Hong Kong Japan U.K. Mean (%) SD (%) SHP Rank

Australia 12,6% 23,4% 0,28 7

Canada 0,60 12,2% 17,8% 0,35 6

France 0,39 0,47 16,0% 21,8% 0,46 3

Germany 0,38 0,44 0,73 13,6% 20,7% 0,37 4

Hong Kong 0,47 0,48 0,33 0,39 17,3% 31,6% 0,36 5

Japan 0,33 0,35 0,41 0,34 0,27 11,0% 24,0% 0,21 8

U.K. 0,55 0,59 0,60 0,57 0,48 0,45 14,7% 18,4% 0,47 2

U.S. 0,47 0,76 0,52 0,51 0,43 0,33 0,61 15,0% 15,5% 0,58 1

2. The correlations between the different markets over the entire period using first the re - turns data based on local currencies and then the US dollar based data

The correlation is +1 in the case of a perfect positive (increasing) linear relationship (correlation), −1 in the case of a perfect decreasing (negative) linear relationship (anticorrelation), and some value between −1 and 1 in all other cases, indicating the degree of linear dependence between the variables. As it approaches zero there is less of a relationship (closer to uncorrelated). The closer the coefficient is to either −1 or 1, the stronger the correlation between the variables.

If we look on the local currency, we can see that the highest correlation is between US/Canada than France/Germany, and UK/US. On the other hand we can say that the worst correlation is between Asia and other countries. If we look on correlation US between the others countries, than we can see that UK, CANADA are highest. The other countries in correlation with US are rather stable except Honk Kong and especially Japan.

The correlation among the countries done in US dollars shows that the highest correlation is between US/Canada again afterwards France/Germany where the correlation has increased, and afterwards the UK/US correlation. The worst is again Asia markets where correlation has dropped.

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3. Development of each market

3.1 Australia

3.2 Canada

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3.3 France

3.4 Germany

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3.5 Honk Kong

3.6 Japan

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3.7

3.8 U.K.

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