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Exploring the Elliott Wave Principle to interpret metal commodity price cycles

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  • Marañon, Matias
  • Kumral, Mustafa

Abstract

The Wave Principle, known as Elliott Wave Principle (EWP), is a theory widely used in technical analysis and is based on the idea that the fluctuations in markets follow recognizable and repetitive cycles, which are the reflection of market participants’ mass psychology. Considering that metal commodity prices have empirically demonstrated cyclical behavior and investors and speculators’ mass physiology could be becoming an influential factor in commodities price formation given their increasing participation in last decades, this article explores whether EWP can be used to analyze commodity cycles. To see the applicability of EWP to commodity markets, a Monte-Carlo simulation was conducted over detected Elliott waves in the prices of gold, silver and copper, as well as on a metal price index. The results of the investigation suggest that EWP would not be a strong approach to analyze commodity markets in a cycle basis, which is confirmed by the results of the simulation. Nevertheless, there is evidence that mass psychology affects commodity markets as posited by Elliott, and therefore this factor could be considered as an explanatory variable of commodity price formation and cycles, for what is proposed to test its causality.

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  • Marañon, Matias & Kumral, Mustafa, 2018. "Exploring the Elliott Wave Principle to interpret metal commodity price cycles," Resources Policy, Elsevier, vol. 59(C), pages 125-138.
    • Handle: RePEc:eee:jrpoli:v:59:y:2018:i:c:p:125-138
    DOI: 10.1016/j.resourpol.2018.06.010
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    1. Marañon, Matias & Kumral, Mustafa, 2019. "Kondratiev long cycles in metal commodity prices," Resources Policy, Elsevier, vol. 61(C), pages 21-28.
    2. Aldin Ardian & Mustafa Kumral, 2021. "Enhancing mine risk assessment through more accurate reproduction of correlations and interactions between uncertain variables," Mineral Economics, Springer;Raw Materials Group (RMG);Luleå University of Technology, vol. 34(3), pages 411-425, October.

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