期刊名：Risks

期刊主页：https://www.mdpi.com/journal/risks

Risks 本期文献精选聚焦加密货币领域的风险与金融研究，涵盖风险度量、市场联动、投资组合优化、反洗钱与监管、绿色加密货币等多个方向。相关研究既关注收益率与成交量尾部风险、时变关联等市场实证问题，也探讨加密货币相关洗钱风险及监管机制，并进一步拓展至气候风险、绿色金融等新兴交叉领域，为数字资产风险评估、投资组合管理及相关政策研究提供了多样化的方法与实证参考。

希望本期文献精选能够为相关领域研究者提供新的研究视角，拓展研究思路。

同时，Risks 诚邀加密货币、金融风险管理、气候金融、保险精算、风险建模及相关领域的研究者积极投稿，共同探讨数字资产与金融风险领域的新方法、新模型与新应用。

1. Robust Tail Risk Estimation in Cryptocurrency Markets: Addressing GARCH Misspecification with Block Bootstrapping

加密货币市场的稳健尾部风险估计 —— 基于分块自助法修正 GARCH 模型设定偏误

https://www.mdpi.com/2227-9091/13/9/166

Christodoulou-Volos, C. Robust Tail Risk Estimation in Cryptocurrency Markets: Addressing GARCH Misspecification with Block Bootstrapping. Risks 2025, 13, 166. https://doi.org/10.3390/risks13090166

2. Entropic Geometry and Information Dynamics in Green Cryptocurrency Markets

绿色加密货币市场中的熵几何与信息动力学

http://www.mdpi.com/2227-9091/14/2/30

Gaied Chortane, S.; Naoui, K. Entropic Geometry and Information Dynamics in Green Cryptocurrency Markets. Risks 2026, 14, 30. https://doi.org/10.3390/risks14020030

3. Cryptocurrencies as a Tool for Money Laundering: Risk Assessment and Perception of Threats Based on Empirical Research

作为洗钱工具的加密货币：基于实证研究的风险评估与威胁认知

https://www.mdpi.com/2227-9091/13/10/189

Spyra, M.; Balina, R.; Idasz-Balina, M.; Zaj?c, A.; Ró?yński, F. Cryptocurrencies as a Tool for Money Laundering: Risk Assessment and Perception of Threats Based on Empirical Research. Risks 2025, 13, 189. https://doi.org/10.3390/risks13100189

4. Asymmetric and Time-Varying Connectedness of FinTech with Equities, Bonds, and Cryptocurrencies: A Quantile-on-Quantile Perspective

金融科技与股票、债券和加密货币之间的非对称时变关联：基于分位数对分位数方法

https://www.mdpi.com/2227-9091/13/12/246

Karimi, M.S.; Esqueda, O.; Weerasinghe, N.M. Asymmetric and Time-Varying Connectedness of FinTech with Equities, Bonds, and Cryptocurrencies: A Quantile-on-Quantile Perspective. Risks 2025, 13, 246. https://doi.org/10.3390/risks13120246

5. From Placement to Integration: A Parametric Study of Cryptocurrency-Based Money Laundering Techniques

从资金置入到资金整合：基于加密货币的洗钱技术参数化研究

https://www.mdpi.com/2227-9091/13/12/249

Almeida, H.; Pinto, P.; Fernández Vilas, A. From Placement to Integration: A Parametric Study of Cryptocurrency-Based Money Laundering Techniques. Risks 2025, 13, 249. https://doi.org/10.3390/risks13120249

6. Maximizing Portfolio Diversification via Weighted Shannon Entropy: Application to the Cryptocurrency Market

基于加权香农熵的投资分散化优化：加密货币市场应用

https://www.mdpi.com/2227-9091/13/12/253

?erban, F.; Dedu, S. Maximizing Portfolio Diversification via Weighted Shannon Entropy: Application to the Cryptocurrency Market. Risks 2025, 13, 253. https://doi.org/10.3390/risks13120253

7. Cryptocurrency Market Dynamics: Copula Analysis of Return and Volume Tails

加密货币市场的动态特征：收益率与成交量尾部的 Copula 建模分析

https://www.mdpi.com/2227-9091/13/9/168

De Luca, G.; Montanino, A. Cryptocurrency Market Dynamics: Copula Analysis of Return and Volume Tails. Risks 2025, 13, 168. https://doi.org/10.3390/risks13090168

8. Regulating the Crypto-Laundering Chain: A Comparative Study of Scam Compounds and Money Mule Mechanisms Within Criminal Networks

加密货币洗钱链条监管—— 犯罪网络中诈骗园区与钱骡机制的比较研究

https://www.mdpi.com/2227-9091/14/4/96

Arnone, G. Regulating the Crypto-Laundering Chain: A Comparative Study of Scam Compounds and Money Mule Mechanisms Within Criminal Networks. Risks 2026, 14, 96. https://doi.org/10.3390/risks14040096

9. Deep Reinforcement Learning for Cryptocurrency Portfolio Management: A Free-Energy Framework with Geometry-Based Transaction Costs and Efficiency Bounds

基于深度强化学习的加密货币投资组合管理：融合几何交易成本与效率边界的自由能框架

https://www.mdpi.com/2227-9091/14/5/103

Moroke, N.D. Deep Reinforcement Learning for Cryptocurrency Portfolio Management: A Free-Energy Framework with Geometry-Based Transaction Costs and Efficiency Bounds. Risks 2026, 14, 103. https://doi.org/10.3390/risks14050103

10. Quantile Domain Connectedness Between Climate Risks and Cryptocurrency Classes

气候风险与不同类别加密货币之间的分位数域关联性

https://www.mdpi.com/2227-9091/14/4/93

Tabash, M.I.; Issa, S.S.; Shaheen, L.M.; Alnahhal, M.; Mamadiyarov, Z. Quantile Domain Connectedness Between Climate Risks and Cryptocurrency Classes. Risks 2026, 14, 93. https://doi.org/10.3390/risks14040093

Risks 期刊介绍

主编：Steven Haberman教授，英国伦敦大学，城市圣乔治学院

期刊专注于发表和传播保险和金融风险管理领域的文章。目前已被Scopus、ESCI (Web of Science)、EconLit, EconBiz, RePEc等数据库收录。

2025 Impact Factor: 1.8

2025 CiteScore: 4.5

Time to First Decision: 21.8 Days

Acceptance to Publication: 7.6 Days