Constant Copula Estimation: Shanghai Container Freight Index and 12 Market Factors

Shanghai Containerized Freight Index (SCFI) futures launched in August 2023. This dataset contains results from a time-varying copula analysis exploring the nonlinear dynamic interdependence between the SCFI and 12 factors from stock, commodity, carbon, and other markets. The data was authored by Yanhui Chen and last updated on 2026-04-21.

Use Cases

• Modeling tail risk dependence between shipping freight futures and other assets based on the described copula method.
• Analyzing time-varying interdependence across short, medium, and long-term horizons as mentioned in the description.
• Investigating the impact of extreme risk events on freight rate correlations based on the findings.
• Building risk management portfolios for stakeholders with varying financial attributes in the shipping industry.

Strengths

• Dataset is openly licensed under CC-BY-4.0.
• Analysis is based on 12 factors from multiple markets (stock, commodity, carbon) as described.
• Methodology explicitly focuses on nonlinear dynamic interdependence and tail risk.

Limitations

• Dataset is very small at 9.5 KB, indicating limited scope.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare, authored by Yanhui Chen.

Collection Method

Results from a data decomposition–reconstruction-based time-varying copula method applied to SCFI and market factors.

Time Range

Analysis references the launch of SCFI futures in August 2023; specific data time range is not provided.

Freshness

Last updated 2026-04-21 17:52:31; freshness should be verified.

Geography

Focus is on the Shanghai Containerized Freight Index (SCFI).