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  • 标题:A Comparative Study of Numeric and Symbolic Representation of Stock Data
  • 本地全文:下载
  • 作者:Mukesh Kumar ; Dr. Arvind Kalia
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2011
  • 卷号:2
  • 期号:4Ver 3
  • 出版社:Ayushmaan Technologies
  • 摘要:Recently there has been a lot of interest in mining the time series data. Stock data mining plays an important role to visualize the behavior of financial market. In financial data mining the data is normally represented in the numeric format, however, the symbolic representation is also used to evaluate the overall impact. Time series data are difficult to manipulate, but when they are treated as symbols instead of data points, interesting patterns can be discovered and it becomes an easier task to mine them. In this paper, a preliminary comparative study of numeric and symbolic representation of NSE stock data of thirteen years period i.e. from Jan. 1996 to Dec.2008 is presented.. First of all the data was normalized, and the study has been conducted on the normalized data. Euclidean distance measure has been used to establish relationships among various stocks. Three symbols [up, down, neutral] have been used for symbolic representation of the data and distance is evaluated as per the matching pattern of these symbols. It has been found that in most of the cases the numeric representation of stock data gives better results than symbolic representation, but symbolic representation provides an easier interpretation and helped to determine an overall pattern. Symbolic pattern is having resemblance with price change pattern in numeric representation.
  • 关键词:Financial data mining; numeric data set; symbolic data set;similarity pattern
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