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A Study of the Dynamic Relationship between Crude Oil Price and the Steel Price Index


  • Ming-Tao Chou

    () (Chang Jung Christian University, Republic of China (Taiwan))

  • Ya - Ling Yang

    () (Chang Jung Christian University, Republic of China (Taiwan))

  • Su-Chiung Chang

    (Chang Jung Christian University, Republic of China (Taiwan))


Bulk shipping providers predominantly supply transportation services for bulk cargo, such as iron ore, grain and coal. As steel price index is a leading indicator of Baltic Dry Index, the cost of marine fuel becomes one of the key costs for shipping providers. By collecting data and building a VARMA model, this study will attempt to discover the dynamic relationship between crude oil price and the global steel price index. The results of this study are as follows: (1) The outcomes of examining the unit root using the Phillips-Perron-test indicates that the two variables, the crude oil price and global steel price index, have a co-integration effect. This also proves that a long term balancing phenomenon exists between the crude oil price and global steel price index. (2) VARMA (3, 2) is the most suitable stage of the model for both the crude oil price and global steel price index. (3) There is a unidirectional relationship between crude oil price and the global steel price index, which means that the price of crude oil is only impacted from its own volatility. However, the global steel price index is impacted from both the movements of its own price and the volatility of crude oil price. (4) The crude oil price moves prior to movements in the global steel price index. When crude oil price increases, the global steel price index follows this upward movement. This study aims to provide a reference for investors¡¯ investment activities and shipping operators¡¯ risk aversion decisions.

Suggested Citation

  • Ming-Tao Chou & Ya - Ling Yang & Su-Chiung Chang, 2012. "A Study of the Dynamic Relationship between Crude Oil Price and the Steel Price Index," Review of Economics & Finance, Better Advances Press, Canada, vol. 2, pages 30-42, May.
  • Handle: RePEc:bap:journl:120203

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    References listed on IDEAS

    1. Hansen, Bruce E & West, Kenneth D, 2002. "Generalized Method of Moments and Macroeconomics," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 460-469, October.
    2. Cullinane, Kevin, 1995. "A portfolio analysis of market investments in dry bulk shipping," Transportation Research Part B: Methodological, Elsevier, vol. 29(3), pages 181-200, June.
    3. Nelson, Charles R. & Plosser, Charles I., 1982. "Trends and random walks in macroeconmic time series : Some evidence and implications," Journal of Monetary Economics, Elsevier, vol. 10(2), pages 139-162.
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    More about this item


    Bulk shipping; Crude oil price; Steel price index; VARMA;

    JEL classification:

    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General


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