| Summary: | 碩士 === 國立臺北大學 === 企業管理學系 === 97 === In 1952, Markowitz innovates the mean-variance model for the portfolio selection problems. Henceforward this model has been the cornerstone of portfolio research and has served as a basis for the development of financial investment methodology. However, the problems of modern investment have become more complex, so the conventional methodology seems incapable of solving those problems effectively. Therefore, it is a very important issue that how to acquire the problem-solving methods between the computational technology and the traditional model.
During the last decade, using artificial intelligence to solve portfolio problems has become a creative trend in investment research and one of those popular artificial intelligence is the genetic algorithm (GA). In many portfolio researches using GA, the index tracking problem is the most common subject. However, the fundamental and technical analysis, which have been emphasized criteria in stock investment, have been ignored. Meanwhile, because the Sharpe Index can not reflect the investment loss literally, so we revise the Sharpe Index through the Semi-Deviation.
Therefore, this paper presents a modified Sharpe Index model and applies genetic algorithm on the optimal portfolio selection problems, in which the investments’ fundamental and technical analysis are considered and performed. Meanwhile, we propose five investment procedures, and those proposed investment procedures have been tested with TSEC Taiwan 50 Index’s data from 2005 to 2008. The empirical results show the one of proposed investment procedures (Procedure 3) is able to obtain approximately 17.11% average rate of return. Furthermore, the results also dominate the performance of TSEC Taiwan 50 Index during the same empirical period. Besides, the synergy of combining the rule of experience and scientific models has been observed in this paper.
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