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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/110089


    Title: Data Mining for the Global Natural Resources Funds Development
    Authors: Shu-Hsien Liao;Chien-Wen Li;Yi-Fang Tsai
    Keywords: data mining;association rules mining;natural resources funds;co-movement;investment portfolios;risk management;fund development;investment value;big data analytics;product design;investment decision making;commodity prices
    Date: 2016-06-01
    Issue Date: 2017-03-23 02:11:07 (UTC+8)
    Publisher: Inderscience Publishers
    Abstract: After the financial crisis in 2008, easy money policy and fiscal policy implemented by countries have managed to aid the recovery of the global economic. Recovering economic activities and infrastructure projects have also increased the demand for raw material, pushing up commodity prices. Under these related demand drives, the exceptional performance of natural resources funds has proven its investment value. However, it is difficult to select proper funds or make investment choice with limited funds. Therefore, this study implements the big data analysis, the association rules, using SPSS Modeler as a tool to discover the co-movement knowledge of global natural resources fund market. This provides investors with feasible suggestions while creating their investment portfolios as well as different ways of investing their funds. On the other hand, from investment corporations' point of view, this study provides three sets of natural resources funds combinations for possible product design and investment decision making.
    Relation: International Journal of Intelligent Information and Database Systems 9(3-4), p.289-314
    DOI: 10.1504/IJIIDS.2016.081603
    Appears in Collections:[管理科學學系暨研究所] 期刊論文

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