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Constructing a Composite Leading Indicator for the Global Crude Oil Price

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Listed:
  • Mei-Teing Chong
  • Chin-Hong Puah
  • Shazali Abu Mansor

Abstract

Crude oil, as the most traded commodity in the world, exhibits prices with a clear influence on other commodities in the worldwide market. It also poses implications regarding the economic growth of oil-exporting and oil-importing nations. This study provides an unprecedented method of employing the indicator approach as proposed by the Conference Board, National Bureau of Economic Research, to construct a leading indicator for the global crude oil price. The results reveal that the constructed oil price indicator can predict the cyclical movement of the oil price by moving in advance of 3.5 months on average. This finding could provide better signaling to oil-related nations as well as other commodities that consider crude oil to be a leader in the market.

Suggested Citation

  • Mei-Teing Chong & Chin-Hong Puah & Shazali Abu Mansor, 2018. "Constructing a Composite Leading Indicator for the Global Crude Oil Price," International Business Research, Canadian Center of Science and Education, vol. 11(5), pages 129-134, May.
  • Handle: RePEc:ibn:ibrjnl:v:11:y:2018:i:5:p:129-134
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    References listed on IDEAS

    as
    1. Cheong, Chin Wen, 2009. "Modeling and forecasting crude oil markets using ARCH-type models," Energy Policy, Elsevier, vol. 37(6), pages 2346-2355, June.
    2. Cong, Rong-Gang & Wei, Yi-Ming & Jiao, Jian-Lin & Fan, Ying, 2008. "Relationships between oil price shocks and stock market: An empirical analysis from China," Energy Policy, Elsevier, vol. 36(9), pages 3544-3553, September.
    3. Soytas, Ugur & Sari, Ramazan & Hammoudeh, Shawkat & Hacihasanoglu, Erk, 2009. "World oil prices, precious metal prices and macroeconomy in Turkey," Energy Policy, Elsevier, vol. 37(12), pages 5557-5566, December.
    4. Abramson, Bruce & Finizza, Anthony, 1991. "Using belief networks to forecast oil prices," International Journal of Forecasting, Elsevier, vol. 7(3), pages 299-315, November.
    5. Aloui, Chaker & Jammazi, Rania, 2009. "The effects of crude oil shocks on stock market shifts behaviour: A regime switching approach," Energy Economics, Elsevier, vol. 31(5), pages 789-799, September.
    6. Agnolucci, Paolo, 2009. "Volatility in crude oil futures: A comparison of the predictive ability of GARCH and implied volatility models," Energy Economics, Elsevier, vol. 31(2), pages 316-321, March.
    7. Lawrence J. Christiano & Terry J. Fitzgerald, 2003. "The Band Pass Filter," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 44(2), pages 435-465, May.
    8. Park, Jungwook & Ratti, Ronald A., 2008. "Oil price shocks and stock markets in the U.S. and 13 European countries," Energy Economics, Elsevier, vol. 30(5), pages 2587-2608, September.
    9. Wong, Shirly Siew-Ling & Puah, Chin-Hong & Abu Mansor, Shazali & Liew, Venus Khim-Sen, 2012. "Early warning indicator of economic vulnerability," MPRA Paper 39944, University Library of Munich, Germany.
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    JEL classification:

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

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