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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/75064

    Title: Self-organizing maps as a foundation for charting or geometric pattern recognition in financial time series
    Authors: Chen, Shu-heng;Tsao, Chueh-Yung
    Contributors: 經濟系
    Date: 2003
    Issue Date: 2015-05-11 11:48:06 (UTC+8)
    Abstract: For a long time technical analysts have detected trading signals with charts. Nonetheless, from a scientific viewpoint, charts are somewhat subjective objects. Using Kohonen's self-organizing maps (SOMs), the research presented proposes a systematic and automatic approach to charting, or more generally stated, geometric pattern recognition. It is found that the charts discovered using SOM in empirical time series do transmit useful information, and that it is hard for such information to be captured by ordinary econometric methods.
    Relation: Computational Intelligence for Financial Engineering, 2003. Proceedings. 2003 IEEE International Conference on 20-23 March 2003, Page(s): 387 - 394
    Data Type: conference
    DOI 連結: http://dx.doi.org/10.1109/CIFER.2003.1196286
    DOI: 10.1109/CIFER.2003.1196286
    Appears in Collections:[經濟學系] 會議論文

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