Setiawan, Marissa
(2010)
Perbandingan metode peringkat excess return to beta dengan metode diversifikasi Solnik = Comparison between excess return to beta ranking method and solnik diversification method.
Bachelor thesis, Universitas Pelita Harapan.
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Abstract
Stock is one of the most famous assets in society. Because of this reason, most people choose to make their investment in stock. Single-Index Model is chosen because this model reduces the number on calculation compared to the ordinary model which was made by Markowitz. After reduce the calculation, the next thing to do is choosing the appropriate stocks to make optimal portfolio. To choose appropriate stocks, excess return to beta ranking method and Solnik Diversification Method are used. The first method is used because this method interprets connection between return and risk for each stock, and the second method is used because it is believed that this method can reduce the risk that investor will face. This research will use stocks from Kompas 100 Index There are ten portfolios, which build by ten stocks each, based on the ranking of market capitalization from each stock. Each stock that matches the criteria from this index is analyzed with excess return to beta ranking method and Solnik Diversification Method. The results from these two models will be used to make the efficient frontier and capital market line to get the percentage from each stock. The results will be used to build each portfolio and the performance will be measured to decide which method is a better method.
If the comparison is seen only from the average return, it can be said that Solnik Diversification Method is a better method. This method produced higher average return for three different periods, which are one month, three months, and five months. Although the average return shows that Solnik Diversification Method is a better method, the ANOVA test shows different result. The ANOVA test shows that methods do not have significance contribution to the return. Finally, for the researchers who interest to continue this research can use Multiple-Index Method for the next research.
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