1. it is a fruitless attempt to try

1.  Research and contribution

Economist Harry
Markowitz won the Nobel Prize in 1952 for developing the Markowitz Asset
Allocation Model in his paper “Portfolio Selection”. The model is also known as
Modern Portfolio Theory, or can be simply abbreviated as MPT which I will use
for simplification throughout this thesis. Before MPT, there does not exist a
systematic way for fund managers to allocate weights to their assets or asset
classes. Furthermore, MPT greatly emphasizes on the benefits of
diversification, which means the investors can reap the benefits of investing
in multiple assets or asset classes in specific weights.

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There are quite a
few researches available about the application of MPT. These researches,
however, only focus on finding the optimal portfolio consisted of individual
stocks, using the Markowitz Model. Therefore, my research topic about whether
or not a fund manager can beat the market benchmark with the Markowitz Model,
using the empirical data from the Scandinavian stock market, digs more in depth
into the subject by comparing the results with the market benchmark and more
specifically using the Scandinavian market. And lastly, as there is an ongoing
debate on whether or not fund managers can actually beat the market in the long
run, the result from this thesis will provide economic significance for both
fund managers and investors. More and more active fund managers are turning to
passive index fund managers as the historical data over the last 15 years show
that most fund managers fail to outperform the market in the long run and even
when they do, it is due to luck. This thesis is therefore to challenge this
statement by exploring whether a fund manager can outperform the market, using
specific data from the Scandinavian market. The results of the thesis will not
only give an answer to this statement but also provides values for fund
managers and investors. From the perspective of fund managers, if the result
shows that it is a fruitless attempt to try to outperform the market, the fund
managers might want to change from active fund management to passive fund
management. On the other hand, from the perspective of investors, the results
will give them a better idea on which type of fund managers they should really
be looking for.



2.  Research method

I will use the existing theories
and the underlying assumptions of MPT as the foundation for my approach to my
research question. It is assumed that the future will be like the past (Sharpe,
2000). Therefore, the future values of average return, risks and correlation
can be calculated based on the historical values. However, it should also be
noted that for the above assumption to hold, the requirement that the
underlying distribution of return has to be stable over the time period
chosen(Sharpe,2000). Therefore, I have chosen a 10-year time frame from
1990-2000, where the distribution of return appears to be quite stable. The
10-year period has to be divided into two parts. The first part is the first
five years (1990-1995), which will be used as the estimation period on which we
will base our future prediction, and the second part is the second five years
(1995-2000), which will be used as the investigation period to recalculate
optimizing weights to each sub-index quarterly.

The benchmark index we chose is
the VINX Nordic Benchmark Equity Indexes, produced
in conjunction with Oslo Börs (Oslo Exchange), track constituents from each of
the Nasdaq Nordic exchanges (Copenhagen, Helsinki, Oslo, Reykjavik and
Stockholm) and Oslo Börs(The benchmark index is consisted of 10 sectors which
we will later use as our sub-indexes to construct optimal portfolios to be
compared with the benchmark.

A portfolio, consisting of 10 sub-indexes that are
compounded in a specific way according to MPT, is used to compare with the market
benchmark VINX. The 10 indexes chosen are the following: basic materials,
consumer services, consumer goods, financials, health care, industrials, oil
gas, technology, telecommunication services, utilities. Each of these indexes
represents a sector or industry in the Scandinavian region. The
ten-sector breakdown is based on the VINX industrial classification of 36
industries. Each sector may be regrouped if a change in industrial structure
makes adjustment necessary. The 450 most liquid issues will be categorized into
the 10 sectors mentioned above(Nasdaq,2018). The fact that these indexes are
major components of the VINX index makes the relevance and the analysis from
the research accurate. The historical data for each of the sector and the
benchmark index is provided by NASDAQ Nordic and can be found on its website. I
have chosen to obtain all the data denominated in Euro, and all the data in
this thesis is daily data unless mentioned otherwise.

In order to construct the capital
market line, we will also need a risk free asset. The risk free asset I chose
is a 3-month treasury note from Riksbanken.

A weighting process needs to be
added in the evaluation process. Because of the fact that macro-economic
factors affect the market and a specific sector fluctuates over time (De Bondt,
1985), distribute returns are not fixed over time and therefore the weights of
the portfolio have to be recalculated based on the average returns and
correlations among the 10 sub-indexes. New estimates for the average returns
and standard deviation of the risky portfolio are recalculated every quarter in
the investigation period using the preceding five years of historical data(Konno,1991).

A new optimal risky portfolio is constructed based on the new weights assigned
to each sub-index each quarter. The optimal weights for the portfolios are
presented in the appendix.

The returns from the portfolio
will be compared to the returns of the benchmark VINX. One thing that needs to
be noted when evaluating performances is the fact that two portfolio have
different risks and therefore the risk-adjusted returns have to be taken into account
(Konno, 1991). No valid results can be obtained without such risk
adjustments.  Sharpe ratio is a useful
measure in this case since it indicates the reward-to-variability ratio, or in
other words, it examines the performance adjusted for risks. A Sharpe ratio
graph that covers 20 quarters in the investigation period (1995-2000) will be
constructed for both the VINX benchmark and the optimal portfolios. To further
investigate whether the portfolio outperforms the market benchmark VINX, I will
calculate the risk adjusted returns for both VINX and the portfolios. In order
to compare the returns in a solid way, I will match the risks of the portfolio
weights with the risks of the benchmark, and then present them in a
risk-adjusted returns graph and compare the returns. The risk adjusted matrixes
are presented in the appendix. 


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