{"title":"The Crypto Risk Composite Index (CCRI)-advancing risk management in the digital asset space","authors":"Xiaochun Guo , Kun Guo , Shouyang Wang","doi":"10.1016/j.irfa.2026.105136","DOIUrl":null,"url":null,"abstract":"<div><div>Cryptocurrency markets exhibit higher risk than traditional financial markets. Their technology-driven, weak-fundamental nature makes risk formation more heterogeneous, fast-evolving, and difficult to quantify using conventional tools. This creates an urgent need for a comprehensive and forward-looking risk management framework. In response, this paper proposes a novel Cryptocurrency Composite Risk Index (CCRI) that systematically measures, monitors, and signals market-wide risk in the cryptocurrency ecosystem. The CCRI integrates multiple and heterogeneous sources of risk information, including crypto market dynamics, network fundamentals, market sentiments and uncertainties, and comparative performance with traditional assets. To aggregate these diverse risk dimensions in an objective and data-driven manner, we employ a dynamic Entropy-CRITIC weighting approach, which effectively captures both the informational content and the structural heterogeneity across indicators. We further conduct a comprehensive validation framework using multiple complementary methods, including time-varying predictive regressions, ROC-AUC analysis, Granger causality tests, CoVaR-based systemic risk assessment, and volatility correlation analysis to evaluate the ability of CCRI to identify both systemic risk and extreme tail events across different types of cryptocurrencies. The results demonstrate that CCRI is able to capture contemporaneous risk and has short-term predictive power for systematic and extreme risk events. The evidence highlights the potential of CCRI as a practical and scalable early-warning tool for proactive risk management, offering valuable insights for market participants, institutional investors, and regulators in navigating the rapidly evolving and highly uncertain cryptocurrency landscape.</div></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":"113 ","pages":"Article 105136"},"PeriodicalIF":9.8000,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1057521926000633","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/2/22 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Cryptocurrency markets exhibit higher risk than traditional financial markets. Their technology-driven, weak-fundamental nature makes risk formation more heterogeneous, fast-evolving, and difficult to quantify using conventional tools. This creates an urgent need for a comprehensive and forward-looking risk management framework. In response, this paper proposes a novel Cryptocurrency Composite Risk Index (CCRI) that systematically measures, monitors, and signals market-wide risk in the cryptocurrency ecosystem. The CCRI integrates multiple and heterogeneous sources of risk information, including crypto market dynamics, network fundamentals, market sentiments and uncertainties, and comparative performance with traditional assets. To aggregate these diverse risk dimensions in an objective and data-driven manner, we employ a dynamic Entropy-CRITIC weighting approach, which effectively captures both the informational content and the structural heterogeneity across indicators. We further conduct a comprehensive validation framework using multiple complementary methods, including time-varying predictive regressions, ROC-AUC analysis, Granger causality tests, CoVaR-based systemic risk assessment, and volatility correlation analysis to evaluate the ability of CCRI to identify both systemic risk and extreme tail events across different types of cryptocurrencies. The results demonstrate that CCRI is able to capture contemporaneous risk and has short-term predictive power for systematic and extreme risk events. The evidence highlights the potential of CCRI as a practical and scalable early-warning tool for proactive risk management, offering valuable insights for market participants, institutional investors, and regulators in navigating the rapidly evolving and highly uncertain cryptocurrency landscape.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.