On the linkages between energy and agricultural commodity prices: A dynamic time warping analysis

Dragan Miljkovic and Puneet Vatsa

International Review of Financial Analysis, 2023, vol. 90, issue C

Abstract: We use dynamic time warping, a non-parametric pattern recognition method, to study interlinkages between major energy and agricultural commodity prices. Cluster analysis is conducted to group commodity prices based on their behavioral likeness by maximizing the differences between groups while minimizing the differences within groups. Two clusters emerge: one comprises the prices of crude oil and six major agricultural commodities, whereas the other contains coal and natural gas prices. Regarding lead-lag associations, oil prices generally lag crop prices; however, there are periods during which the former lead the latter. Furthermore, the duration with which oil prices lead or lag crop prices changes frequently.

Keywords: Commodity prices; Dynamic time warping; Lead-lag analysis; Pattern recognition; Time-series clustering (search for similar items in EconPapers)
JEL-codes: C14 C63 Q11 Q41 (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:90:y:2023:i:c:s1057521923003502

DOI: 10.1016/j.irfa.2023.102834

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