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Fuzzy Time Series Theory Application for the China Containerized Freight Index

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  • Ming-Tao Chou

Abstract

China has evolved into one of the world¡¯s largest trading nations. China has adequate supply for imports and exports, and therefore, major shipping companies from various countries around the world all joined this market to perform freight transport. Currently, the main method of transporting goods is via shipping. China¡¯s containerized freight index (CCFI) is mainly used as a reference to evaluate the current freight tariffs standard. This study uses fuzzy time series to predict the CCFI. The results of our analysis found the following: 1. CCFI yield series has a volatility-clustering characteristic (the mean of the current yield is negative); 2. the R.M.S.P.E. (root mean square percentage error) value is 0.078%, indicating that the goodness-of-fit of the model is quite good; 3. future CCFI will be maintained at a low point of around 893.557, which is an optimistic long-term indication for freight; 4. currently, the supply of ships outweighs the demand, causing a long-term low CCFI. These four conclusions are hoped to serve as references for relevant policymakers in the future.

Suggested Citation

  • Ming-Tao Chou, 2016. "Fuzzy Time Series Theory Application for the China Containerized Freight Index," Applied Economics and Finance, Redfame publishing, vol. 3(3), pages 127-135, August.
    • Handle: RePEc:rfa:aefjnl:v:3:y:2016:i:3:p:127-135
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    References listed on IDEAS

    as
    1. Shi Xin, 2000. "The study on the compilation of the China container freight index," Maritime Policy & Management, Taylor & Francis Journals, vol. 27(3), pages 303-308.
    2. Bondia, Ripsy & Ghosh, Sajal & Kanjilal, Kakali, 2016. "International crude oil prices and the stock prices of clean energy and technology companies: Evidence from non-linear cointegration tests with unknown structural breaks," Energy, Elsevier, vol. 101(C), pages 558-565.
    3. Ming-Tao Chou, 2019. "Fuzzy Forecast Based on Fuzzy Time Series," Chapters, in: Chun-Kit Ngan (ed.), Time Series Analysis - Data, Methods, and Applications, IntechOpen.
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    Cited by:

    1. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).

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    More about this item

    Keywords

    Fuzzy; China¡¯s containerized freight index; Fuzzy time series;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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