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Dynamic of consumer groups and response of commodity markets by principal component analysis

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  • Nobi, Ashadun
  • Alam, Shafiqul
  • Lee, Jae Woo

Abstract

This study investigates financial states and group dynamics by applying principal component analysis to the cross-correlation coefficients of the daily returns of commodity futures. The eigenvalues of the cross-correlation matrix in the 6-month timeframe displays similar values during 2010–2011, but decline following 2012. A sharp drop in eigenvalue implies the significant change of the market state. Three commodity sectors, energy, metals and agriculture, are projected into two dimensional spaces consisting of two principal components (PC). We observe that they form three distinct clusters in relation to various sectors. However, commodities with distinct features have intermingled with one another and scattered during severe crises, such as the European sovereign debt crises. We observe the notable change of the position of two dimensional spaces of groups during financial crises. By considering the first principal component (PC1) within the 6-month moving timeframe, we observe that commodities of the same group change states in a similar pattern, and the change of states of one group can be used as a warning for other group.

Suggested Citation

  • Nobi, Ashadun & Alam, Shafiqul & Lee, Jae Woo, 2017. "Dynamic of consumer groups and response of commodity markets by principal component analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 337-344.
    • Handle: RePEc:eee:phsmap:v:482:y:2017:i:c:p:337-344
    DOI: 10.1016/j.physa.2017.04.105
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    References listed on IDEAS

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    1. Teng, Sin Yong & How, Bing Shen & Leong, Wei Dong & Teoh, Jun Hao & Cheah, Adrian Chee Siang & Motavasel, Zahra & Lam, Hon Loong, 2019. "Principal component analysis-aided statistical process optimisation (PASPO) for process improvement in industrial refineries," MPRA Paper 94058, University Library of Munich, Germany, revised 01 Jan 2019.

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