Cryptocurrency Systemic Risk Spillovers and Political Uncertainty

Zhecheng Wang's dataset contains a correlation matrix from a study analyzing the nonlinear impact of political uncertainty on systemic risk spillovers in the cryptocurrency market. The data was last updated on 2026-05-28 and is shared under a CC-BY-4.0 license. The underlying research decomposes risk into short-, medium-, and long-term components and quantifies spillovers between specific cryptocurrencies.

Use Cases

• Modeling systemic risk spillovers between cryptocurrencies based on the described network topology approach.
• Analyzing asymmetric responses of cryptocurrency risk to political uncertainty shocks.
• Identifying stable risk transmitters (e.g., Bitcoin, Ethereum) and vulnerable risk receivers (e.g., Peercoin, Namecoin) as indicated in the description.

Strengths

• The dataset is derived from a study employing wavelet packet decomposition and forecast error variance decomposition, as described.
• The analysis specifically identifies Bitcoin, Ethereum, and Monero as stable risk transmitters and Peercoin and Namecoin as vulnerable receivers.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 5.5 KB, indicating limited scope.

Provenance

Source

Zhecheng Wang via figshare.

Collection Method

Generated from a smooth transition vector autoregressive model and network topology analysis of cryptocurrency market data.

Freshness

Last updated 2026-05-28 17:28:54; freshness should be verified.