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  • 标题:Predicting Closed Price Time Series Data Using ARIMA Model
  • 本地全文:下载
  • 作者:S. AL Wadi ; Mohammad Almasarweh ; Ahmed Atallah Alsaraireh
  • 期刊名称:Modern Applied Science
  • 印刷版ISSN:1913-1844
  • 电子版ISSN:1913-1852
  • 出版年度:2018
  • 卷号:12
  • 期号:11
  • 页码:181-185
  • DOI:10.5539/mas.v12n11p181
  • 语种:English
  • 出版社:Canadian Center of Science and Education
  • 摘要:Closed price forecasting plays a main rule in finance and economics which has encouraged the researchers to introduce a fit model in forecasting accuracy. The autoregressive integrated moving average (ARIMA) model has developed and implemented in many applications. Therefore, in this article the researchers utilize ARIMA model in predicting the closed time series data which have been collected from Amman Stock Exchange (ASE) from Jan. 2010 to Jan. 2018. As a result this article shows that the ARIMA model has significant results for short-term prediction. Therefore, these results will be helpful for the investments.
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