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BDI Forecasting Based on Fuzzy Set Theory, Grey System and ARIMA

  • Hsien-Lun Wong
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8482)

Abstract

Baltic Dry Index (BDI) is an important response of maritime information for the trading and settlement of physical and derivative contracts. In the paper, we propose fuzzy set theory and grey system for modeling the prediction of BDI, and employ ARIMA for the calibration of data structure to depict the trend. The empirical results indict that for both short-term and long-term BDI data, fuzzy heuristic model has lowest prediction error; Structural change ARIMA fits better for the prediction in the long term, while the GM (1,1) has the greatest prediction error. Moreover, the relationship that the change between in current BDI and in previous is highly positive significance; the external interference for the current BDI index is negatively related. The conclusion of the paper would provide the bulky shipping with a beneficial reference for the market and risk assessment.

Keywords

Baltic dry index Bulky shipping Fuzzy set theory Grey system ARIMA 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Hsien-Lun Wong
    • 1
  1. 1.Minghsin University of Science and TechnologyHsinfongTaiwan

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