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Multiscale Price Lead-Lag Relationship between Steel Materials and Industry Chain Products Based on Network Analysis
Sui Guo1, Ze Wang2,3, Xing Zhou1
1School of Business, Jiangsu Normal University, Xuzhou 221116, China.
Entropy (Basel, Switzerland)
|July 27, 2022
Summary
Iron ore prices often lead steel product prices by one day, while scrap steel prices fluctuate concurrently. Downstream products can also lead iron ore prices, with lead relationships strengthening over longer time scales.
Area of Science:
- Materials Science
- Economics
- Data Science
Background:
- Iron ore and scrap steel are primary steelmaking inputs with distinct price dynamics.
- Understanding their price lead-lag relationships (PLRs) with steel products is crucial for market analysis.
Purpose of the Study:
- To compare the price influences of iron ore and scrap steel on midstream and downstream steel products.
- To analyze these relationships across different time scales.
Main Methods:
- Maximal Overlap Discrete Wavelet Transform (MODWT) for price series decomposition.
- Cross-correlation and Podobnik test for PLR calculation.
- Network construction and indicator analysis.
Main Results:
- Iron ore prices typically lead steel product prices by one day; scrap steel prices often move concurrently.
- Downstream steel products can exhibit price leadership over iron ore.
- Lead relationships intensify from steel materials to products as the time scale lengthens.
Conclusions:
- Price leadership dynamics between steelmaking materials and products vary significantly with time scale.
- Network analysis provides valuable insights into complex interdependencies in steel markets.
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