Carbon, Energy, and Industrial Metals Market Spillover Analysis

Shuifeng Hong's research dataset investigates spillover effects and co-movements among carbon, energy, and industrial metals markets. The analysis employs a multidimensional framework using cointegration, a discrete wavelet-based Diebold-Yilmaz model, and wavelet coherence analysis. The dataset is a 690.5 KB DOCX file published on figshare under a CC-BY-4.0 license.

Use Cases

• Modeling long-term cointegration relationships among commodity markets based on the time-domain analysis described.
• Identifying net spillover transmitters and recipients in commodity markets based on the discrete wavelet-based DY model results.
• Analyzing time-varying, fragmented co-movements in the time-frequency domain using wavelet coherence.
• Assessing the impact of crisis events on market correlations based on the findings of intensified relationships.
• Investigating the positive correlation between carbon market price increases and energy/metals returns.

Strengths

• Applies a multidimensional research framework encompassing time, frequency, and time-frequency domains.
• Uses multiple established methodologies: cointegration, a discrete wavelet-based Diebold-Yilmaz model, and wavelet coherence analysis.
• Findings include specific market roles, identifying carbon and oil as net spillover transmitters.

Limitations

• The dataset is a 690.5 KB DOCX file, suggesting limited scope and likely containing textual analysis rather than raw time-series data.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

Shuifeng Hong via figshare.

Collection Method

Likely contains processed results and analysis from applying econometric models to market data.

Freshness

Last updated 2026-05-13 11:32:24; freshness should be verified.