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  • 标题:Short Term Predicting Volatility Service Jordanian Sector
  • 本地全文:下载
  • 作者:S. Al Wadi ; Ola Basbous
  • 期刊名称:European Journal of Business and Management
  • 印刷版ISSN:2222-2839
  • 电子版ISSN:2222-2839
  • 出版年度:2019
  • 卷号:11
  • 期号:36
  • 页码:124-127
  • DOI:10.7176/EJBM/11-36-14
  • 出版社:The International Institute for Science, Technology and Education (IISTE)
  • 摘要:Stock market volatility have added an important section in risk scholarship and it is actual problem particularly in emerging markets. Earlier, it is measured by standard deviation of the return. Consequently, in this research the volatility data will be predicted based on ARIMA model (Autoregressive Integrated Moving Average model) of the service sector in Amman Stock Exchange (ASE) from January 2019 to December 2019. Consequently this article shows that the ARIMA model has important results in prediction. Therefore, These outcomes will be helpful for the investments..
  • 关键词:ARIMA model; forecasting; Service sector.
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