An Application of Fuzzy Time Series: A Long Range Forecasting Method in the Global Steel Price Index Forecast

نویسنده

  • Ming-Tao Chou
چکیده

The global steel price index is a leading indicator in the bulk shipping industry. A study of the global steel price index combined with the establishment of fuzzy time series models can be used to predict future trends in the trading range of the global steel price index. Analysis of applied fuzzy time series data shows the following results: (1) Price volatility of the global steel price index remains positive following the global financial crisis; (2) Mode analysis shows that the 2012 global steel price index has a predictive value of 211.864 and its trading range will fluctuate between 74.577 and 211.864; (3) The group average prediction error rate is 4.40%. This paper describes the results of a study that can provide reference data to investors for hedging purposes and to operators in the shipping industry.

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تاریخ انتشار 2013