| Summary: | 碩士 === 國立臺灣師範大學 === 管理研究所 === 105 === The Big data analysis has been used more extensively in various industries. This paper explored whether the big data analysis can help fund managers to improve fund performances. This study used the Case-Based Reasoning system of the collective intelligence to develop new investment strategies. The thesis examined if there was a significant difference between the fund performance with original investment strategies and the one with improved strategies in which share holdings are changed by the Case-Based Reasoning system.
The Case-Based Reasoning system is a recommendation system that tries to solve new problems by looking for solutions in similar cases. Therefore, this study used two methods to find similar cases, namely mathematical and artificial methods. According to the five steps of Case-Based Reasoning system: the retrieve, reuse, revise, review and retain steps, this study firstly singled out the neighborhoods through the first two steps- retrieval and reuse; then picked out the relatively diversified neighborhoods with better performances in the revise step; finally, hence built a new portfolio by averaging out the portfolios of selected neighborhoods in the last two steps- review and retain. This paper tested whether there were different fund performances between these two methods. The thesis provided evidence that the usage of the two fund-based collective intelligence methods can develop more diversified portfolio and significantly improve fund performances.
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