1. Research and contributionEconomist HarryMarkowitz won the Nobel Prize in 1952 for developing the Markowitz AssetAllocation Model in his paper “Portfolio Selection”. The model is also known asModern Portfolio Theory, or can be simply abbreviated as MPT which I will usefor simplification throughout this thesis. Before MPT, there does not exist asystematic way for fund managers to allocate weights to their assets or assetclasses. Furthermore, MPT greatly emphasizes on the benefits ofdiversification, which means the investors can reap the benefits of investingin multiple assets or asset classes in specific weights.
There are quite afew researches available about the application of MPT. These researches,however, only focus on finding the optimal portfolio consisted of individualstocks, using the Markowitz Model. Therefore, my research topic about whetheror 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 depthinto the subject by comparing the results with the market benchmark and morespecifically using the Scandinavian market. And lastly, as there is an ongoingdebate on whether or not fund managers can actually beat the market in the longrun, the result from this thesis will provide economic significance for bothfund managers and investors. More and more active fund managers are turning topassive index fund managers as the historical data over the last 15 years showthat most fund managers fail to outperform the market in the long run and evenwhen they do, it is due to luck.
This thesis is therefore to challenge thisstatement by exploring whether a fund manager can outperform the market, usingspecific data from the Scandinavian market. The results of the thesis will notonly give an answer to this statement but also provides values for fundmanagers and investors. From the perspective of fund managers, if the resultshows that it is a fruitless attempt to try to outperform the market, the fundmanagers might want to change from active fund management to passive fundmanagement. On the other hand, from the perspective of investors, the resultswill give them a better idea on which type of fund managers they should reallybe looking for. 2. Research methodI will use the existing theoriesand the underlying assumptions of MPT as the foundation for my approach to myresearch question. It is assumed that the future will be like the past (Sharpe,2000). Therefore, the future values of average return, risks and correlationcan be calculated based on the historical values.
However, it should also benoted that for the above assumption to hold, the requirement that theunderlying distribution of return has to be stable over the time periodchosen(Sharpe,2000). Therefore, I have chosen a 10-year time frame from1990-2000, where the distribution of return appears to be quite stable. The10-year period has to be divided into two parts. The first part is the firstfive years (1990-1995), which will be used as the estimation period on which wewill base our future prediction, and the second part is the second five years(1995-2000), which will be used as the investigation period to recalculateoptimizing weights to each sub-index quarterly. The benchmark index we chose isthe VINX Nordic Benchmark Equity Indexes, producedin conjunction with Oslo Börs (Oslo Exchange), track constituents from each ofthe Nasdaq Nordic exchanges (Copenhagen, Helsinki, Oslo, Reykjavik andStockholm) and Oslo Börs(The benchmark index is consisted of 10 sectors whichwe will later use as our sub-indexes to construct optimal portfolios to becompared with the benchmark. A portfolio, consisting of 10 sub-indexes that arecompounded in a specific way according to MPT, is used to compare with the marketbenchmark VINX.
The 10 indexes chosen are the following: basic materials,consumer services, consumer goods, financials, health care, industrials, oilgas, technology, telecommunication services, utilities. Each of these indexesrepresents a sector or industry in the Scandinavian region. Theten-sector breakdown is based on the VINX industrial classification of 36industries. Each sector may be regrouped if a change in industrial structuremakes adjustment necessary.
The 450 most liquid issues will be categorized intothe 10 sectors mentioned above(Nasdaq,2018). The fact that these indexes aremajor components of the VINX index makes the relevance and the analysis fromthe research accurate. The historical data for each of the sector and thebenchmark index is provided by NASDAQ Nordic and can be found on its website. Ihave chosen to obtain all the data denominated in Euro, and all the data inthis thesis is daily data unless mentioned otherwise.In order to construct the capitalmarket line, we will also need a risk free asset.
The risk free asset I choseis a 3-month treasury note from Riksbanken. A weighting process needs to beadded in the evaluation process. Because of the fact that macro-economicfactors affect the market and a specific sector fluctuates over time (De Bondt,1985), distribute returns are not fixed over time and therefore the weights ofthe portfolio have to be recalculated based on the average returns andcorrelations among the 10 sub-indexes. New estimates for the average returnsand standard deviation of the risky portfolio are recalculated every quarter inthe investigation period using the preceding five years of historical data(Konno,1991).
A new optimal risky portfolio is constructed based on the new weights assignedto each sub-index each quarter. The optimal weights for the portfolios arepresented in the appendix.The returns from the portfoliowill be compared to the returns of the benchmark VINX. One thing that needs tobe noted when evaluating performances is the fact that two portfolio havedifferent risks and therefore the risk-adjusted returns have to be taken into account(Konno, 1991).
No valid results can be obtained without such riskadjustments. Sharpe ratio is a usefulmeasure in this case since it indicates the reward-to-variability ratio, or inother words, it examines the performance adjusted for risks. A Sharpe ratiograph that covers 20 quarters in the investigation period (1995-2000) will beconstructed for both the VINX benchmark and the optimal portfolios. To furtherinvestigate whether the portfolio outperforms the market benchmark VINX, I willcalculate the risk adjusted returns for both VINX and the portfolios.
In orderto compare the returns in a solid way, I will match the risks of the portfolioweights with the risks of the benchmark, and then present them in arisk-adjusted returns graph and compare the returns. The risk adjusted matrixesare presented in the appendix.