Cryptocurrency Markets and Financial Risk: A Systematic Review of Volatility, Contagion, and Regulation
DOI:
https://doi.org/10.61424/aj4wkv11Keywords:
Cryptocurrency markets, financial risk, market volatility, contagion, risk transmission, cryptocurrency regulationAbstract
Cryptocurrency markets have emerged as a significant component of the global financial system, while their high volatility, interconnectedness, and evolving regulatory environment have generated substantial financial risks for investors, financial institutions, and policymakers. This systematic review examines the major dimensions of financial risk in cryptocurrency markets, with particular emphasis on market volatility, contagion and risk transmission mechanisms, and regulatory responses. The review synthesizes findings from existing academic and empirical literature to identify the principal drivers of cryptocurrency price instability, including speculative trading, investor sentiment, market liquidity, macroeconomic conditions, technological developments, and information shocks. The analysis further demonstrates that cryptocurrency markets are increasingly interconnected, allowing financial stress originating in one cryptocurrency or market segment to propagate across other digital assets and, in some circumstances, to traditional financial markets. Regulatory developments are found to play a dual role: effective regulation can strengthen market integrity, investor protection, transparency, and financial stability, whereas fragmented or uncertain regulatory frameworks may increase market uncertainty and encourage regulatory arbitrage. Overall, the review indicates that cryptocurrency financial risk is multidimensional and cannot be adequately assessed through price volatility alone. A comprehensive risk-management framework should therefore integrate volatility monitoring, contagion analysis, liquidity assessment, market surveillance, and coordinated regulatory oversight. The study contributes to the literature by consolidating evidence on the interconnected nature of cryptocurrency risks and highlighting the need for adaptive regulatory and risk-management approaches as digital asset markets continue to evolve.
References
Adelopo, I., & Luo, X. (2025). Interconnectedness among cryptocurrencies and financial markets: A systematic literature review. Digital Finance, 7(4), 1119-1171.
Alam, M. I., Hemal, M. A. K. P., Sami, M. A., & Rahman, M. L. (2024). Robust and interpretable crop recommendation. European Journal of Ecology, Biology and Agriculture, 1(5), 168–184. https://doi.org/10.59324/ejeba.2024.1%285%29.14.
Alam, M. I., Sami, M. A., Al Masud, A., Ahmed, H., & Hossain, F. (2025). AI-driven big data analytics for personalized cancer treatment. Journal of Computer Science and Technology Studies, 7(11), 428–441. https://doi.org/10.32996/jcsts.2025.7.11.40.
Alam, M. I., Sami, M. A., Hemal, M. A. K. P., & Rahman, M. L. (2023). Predictive analytics and decision intelligence for climate-resilient agritech systems, 2(1), 44–56. https://doi.org/10.32996/agjcsts.2023.2.1.4.
Alam, M. I., Sikder, T. R., Sami, M. A., Rahman, M. L., et al. (2026). A robust and explainable approach to crop recommendation. Journal of Environmental and Agricultural Studies, 7(3), 1–15. https://doi.org/10.32996/jeas.2026.7.3.1.
Alasa, D. K., Hossain, D., Jiyane, G., Sarwer, M. H., & Saha, T. R. (2025b). AI-Driven Personalization in E-Commerce: The Case of Amazon and Shopify’s Impact on Consumer Behavior. Voice of the Publisher, 11(1), 104-116.https://doi.org/10.4236/vp.2025.111009
Alasa, D.K., Hossain, D., Jiyane, G. (2025a). Hydrogen Economy in GTL: Exploring the role of hydrogen-rich GTL processes in advancing a hydrogen-based economy. International Journal of Communication Networks and Information Security (IJCNIS), 17(1), 81–91. Retrieved from https://www.ijcnis.org/index.php/ijcnis/article/view/8021
Almeida, J., & Gonçalves, T. C. (2024). Cryptocurrency market microstructure: a systematic literature review. Annals of Operations Research, 332(1), 1035-1068.
Aniwa S.C. (2021). Impact of Supply Chain Integration on Operational Performance: Insights from Manufacturing Firms in Emerging Economies. Iconic Research And Engineering Journals, 5(4).
Ayrin, F. J., Rahman, M. M., Quader, M. A., Dass, A., Khondaker, M. M. H., & Chakraborty, M. (2025). MentalLLM: A transformer-based large language model framework for depression detection. In 2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE). https://doi.org/10.1109/WIECON-ECE69386.2025.11525902
Ayrin, F. J., Rahman, M. M., Quader, M. A., Dass, A., Khondaker, M. M. H., & Chakraborty, M. (2025). MentalLLM: A transformer-based large language model framework for depression detection. 2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), Dhaka, Bangladesh. IEEE. https://doi.org/10.1109/WIECON-ECE69386.2025.11525902
Bajaj, K. E. S. H. A. V., Gochhait, S. A. I. K. A. T., Pandit, S. A. N. G. E. E. T. A., Dalwai, T., & Justin, M. S. M. (2022). Risks and regulation of cryptocurrency during pandemic: a systematic literature review. WSEAS Transactions on Environment and Development, 18, 642-652.
Biswas, M., Rahman, M. M., Hossain, M. S., Rahman, R. U., & Saha, P. P. (2026). An optimized machine learning model for anemia classification: Integrating SHAP-based interpretability. 2026 International Conference on Circuit, Systems and Communication (ICCSC), Fez, Morocco. IEEE. https://doi.org/10.1109/ICCSC71566.2026.11650608
Bulbul, I. J., Zahir, Z., Ahmed, T., & Alam, P. (2019). Comparative study of the antimicrobial, minimum inhibitory concentrations (MIC), cytotoxic and antioxidant activity of methanolic extract of different parts of Phyllanthus acidus (L.) Skeels (family: Euphorbiaceae). World Journal of Pharmacy and Pharmaceutical Sciences, 8(1), 12–57. https://doi.org/10.20959/wjpps20191-10735
Das, K., Tanvir, A., Rani, S., & Aminuzzaman, F. M. (2025). Revolutionizing agro-food waste management: Real-time solutions through IoT and big data integration. Voice of the Publisher, 11(1), 17–36. https://doi.org/10.4236/vp.2025.111003
Dumas, J. G., Jimenez-Garces, S., & Șoiman, F. (2021, March). Risk analyses of the crypto-market: A literature review. In 12th International Conference on Complexity, Informatics and Cybernetics (IMCIC 2021) (Vol. 1, pp. 30-37).
Gantla, S. R. (2025, November). Enterprise Multi-Agent Memory Management: MCP Server Orchestration for Large-Scale AI System. In International Conference on Computational Technologies for Research in Data Analytics (pp. 319-335). Cham: Springer Nature Switzerland.
Gantla, S. R., & Devireddy, S. (2025, November). The Double-Edged Blade: Navigating Confidentiality in Context-Injected Language Generation. In 2025 International Conference on Computational Engineering, Sensing Technology and Management (ICCETM) (pp. 1-6). IEEE. https://doi.org/10.1109/ICCETM66557.2025.11557724
Habib, M. R., Yusuf, M. A., Warnasuriya, W. M. H. N., Sunny, K., Rahaman, M. M., & Khan, M. R. K. (2024). A comprehensive review on the advancement of home automation system. In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) (pp. 638–642). IEEE. https://doi.org/10.1109/ICoICI62503.2024.10696135
Hasan, M. M., Alam, M. I., Chowdhury, M. A. H., & Anwar, M. M. (2026). AI-driven big data analytics for precision medicine and healthcare intelligence. Frontiers in Computer Science and Artificial Intelligence, 5(2), 41–62. https://doi.org/10.32996/jcsts.2026.5.1.5.
Hemal, M. A. K. P., Sayeed, N., Sami, M. A., Alam, M. I., Sikder, T. R., Dipa, S. A., & Rahman, M. L. (2025). Leveraging data analytics to strengthen public health and global economic sustainability. European Journal of Medical and Health Research, 3(4), 253–263. https://doi.org/10.59324/ejmhr.2025.3%284%29.37.
Hossain D., Alasa D.K, Jiyane G. (2023). Water-based fire suppression and structural fire protection: strategies for effective fire control. International Journal of Communication Networks and Information Security (IJCNIS). 15(4):485-94. Available from: https://ijcnis.org/index.php/ijcnis/article/view/7982.
Hossain D., Alasa D.K. (2024a). Numerical modeling of fire growth and smoke propagation in enclosure. Journal of Management World. (5):186-96. https://doi.org/10.53935/jomw.v2024i4.1051.
Hossain D., Alasa D.K. (2024b). Fire detection in gas-to-liquids processing facilities: challenges and innovations in early warning systems. International Journal of Biological, Physical and Chemical Studies. 6(2):7-13. https://doi.org/10.32996/ijbpcs.2024.6.2.2.
Hossain, D. (2022). Fire dynamics and heat transfer: advances in flame spread analysis. Open Access Res J Sci Technol. 2022;6(2):70-5. https://doi.org/10.53022/oarjst.2022.6.2.0061.
Hossain, D. (2025). Water Efficient Suppression Material Fire Behaviour and AI Driven Safety in Future Fire Protection Research. EJSMT, 1(5), 62–76. https://doi.org/10.59324/ejsmt.2025.1(5).07
Hossain, D.(2021). A fire protection life safety analysis of multipurpose building. Available from: https://digitalcommons.calpoly.edu/fpe_rpt/135/.
Hossain, D., Asrafuzzaman, M., Dash, S., & Rani, S. (2024). Multi-Scale Fire Dynamics Modeling: Integrating Predictive Algorithms for Synthetic Material Combustion in Compartment Fires. Journal of Management World. (5): 363-374.https://doi.org/10.53935/jomw.v2024i4.1133
Hossain, M. J., Bakhsh, M. M., Sami, M. A., Alam, M. I., Melon, M. M. H., & Manik, M. M. T. G. (2026). Self-adaptive artificial intelligence systems for large-scale data-driven decision making. In 2026 IEEE I3CTCON (pp. 1–8). https://doi.org/10.1109/I3CTCON68242.2026.11507252.
Hossain, M. S., Rahman, M. M., Biswas, M., Rahman, R. U., & Saha, P. P. (2026). Explainable AI-driven diagnosis of Alzheimer's disease using SMOTEENN and SHAP interpretability. 2026 International Conference on Circuit, Systems and Communication (ICCSC), Fez, Morocco. IEEE. https://doi.org/10.1109/ICCSC71566.2026.11650129
Islam, A., & Jantan, A. H. B. (2023). The mediation effect of affective organizational commitment on the relationship between HRM practices and turnover intention in the RMG industry. Research Journal in Business and Economics, 1(1), 24-38.
Islam, A., Jantan, A. H. B., Khalifa, G. S., Islam, A., Islam, B., & Hossian, A. (2023). Effects of Decision Making and Work-life Balance on Productivity of Female Employees in the RMG Industry of Bangladesh. The Mediating Role of Work Motivation. Research Journal in Business and Economics, 1(1), 48-59.
Islam, M. A., & Sinniah, S. (2025). Exploring customer relationship management factors, customer trust, and innovation capacity: A quantitative study on customer retention. Accountancy Business and the Public Interest, 41(10), 12-29.
Islam, M. A., Islam, M. A., Amin, M. B., Hossain, M. M., Hassan, M. S., Afrin, S., & Oláh, J. (2025). Enhancing academic's performance: Exploring the interaction of innovative work behavior, intrinsic motivation, and self-efficacy in public universities. Social Sciences & Humanities Open, 12, 102210.
Kaur, J., Prabha, M., Samiun, M., Hasan, S. N., Hasan, R., Esa, H., et al. (2025). Comparative analysis of transformer and LSTM architectures for cybersecurity threat detection. EAI Endorsed Transactions on AI and Robotics, 4. https://publications.eai.eu/index.php/airo/article/view/9759.
Kyriazis, N., Papadamou, S., & Corbet, S. (2020). A systematic review of the bubble dynamics of cryptocurrency prices. Research in International Business and Finance, 54, 101254.
Pacelli, V., Di Tommaso, C., Foglia, M., & Ingannamorte, S. (2025). Cryptocurrencies and systemic risk. the spillover effects between cryptocurrency and financial markets. Systemic risk and complex networks in modern financial systems, 343.
Rahman, M. M., Juie, B. J. A., Tisha, N. T., & Tanvir, A. (2022). Harnessing predictive analytics and machine learning in drug discovery, disease surveillance, and fungal research. Eurasia Journal of Science and Technology, 4(2), 28-35. https://doi.org/10.61784/ejst3099[32].Rahman, M. M., Rahman, M. S., Islam, S., Khan, S. I., Ashik, A. A. M., Hossain, E., & Tanvir, A. (2025). Integrating data analytics into health informatics: Advancing equity, pharmaceutical outcomes, and public health decision-making. Eurasian Journal of Medicine and Oncology, 9(4), 284–295. https://doi.org/10.36922/EJMO025300319.
Rahman, M. M., Rahman, M. S., Islam, S., Khan, S. I., Ashik, A. A. M., Hossain, E., & Tanvir, A. (2025). Integrating data analytics into health informatics: Advancing equity, pharmaceutical outcomes, and public health decision-making. Eurasian Journal of Medicine and Oncology, 9(4), 284–295. https://doi.org/10.36922/EJMO025300319
Saha, P. P., Rahaman, M. M., Islam, M. T., & Chowdhury, N. I. (2025b). Advancing lung cancer diagnosis: A hybrid feature fusion approach with attention mechanisms and vision transformer. In 2025 2nd International Conference on Intelligent Systems for Cybersecurity (ISCS) (pp. 1–7). IEEE. https://doi.org/10.1109/ISCS69371.2025.11386016
Saha, P. P., Rone, P. D., Sarkar, D., Yusuf, M. A., Hossan, M. I., & Mazumder, M. S. J. (2025a). Advancing carbon emission prediction through machine learning: The impact of fossil, nuclear, and renewable energies. In 2025 International Conference on Emerging Smart Computing and Informatics (ESCI) (pp. 1–7). IEEE. https://doi.org/10.1109/ESCI63694.2025.10988213
Sami, M. A., Hemal, M. A. K. P., Alam, M. I., & Rahman, M. L. (2024). Data governance and analytics infrastructure for scalable decision-making. European Journal of Applied Science, Engineering and Technology, 2(2), 388–403. https://doi.org/10.59324/ejaset.2024.2%282%29.28.
Sami, M. A., Rahman, M. L., Tanni, Z. A., Munmun, Z. S., Nusrat, S., & Biswas, B. (2026). Artificial intelligence and big data for precision medicine. Frontiers in Computer Science and Artificial Intelligence, 5(6), 36–43. https://doi.org/10.32996/fcsai.2026.5.6.7.
Sarwer, M. H., Saha, T. R., & Hossain, D. (2022). Driving Business Innovation with Artificial Intelligence, Machine Learning and Blockchain Technology. Journal of Business and Management Studies, 4(3), 221-230. https://doi.org/10.32996/jbms.2022.4.3.21
Tanvir A, Jo J, Park SM. Targeting Glucose Metabolism: A Novel Therapeutic Approach for Parkinson's Disease. Cells. 2024 Nov 13;13(22):1876. doi: 10.3390/cells13221876. PMID: 39594624; PMCID: PMC11592965.
Tanvir, A., Juie, B. J. A., Tisha, N. T., & Rahman, M. M. (2020). Synergizing big data and biotechnology for innovation in healthcare, pharmaceutical development, and fungal research. International Journal of Biological, Physical and Chemical Studies, 2(2), 23–32. https://doi.org/10.32996/ijbpcs.2020.2.2.4
Yusuf, M. A., Chowdhury, N. M., Rone, P. D., Saha, P. P., Hossan, M. I., Sarkar, D., Paul, R., Hossain, M. R., & Chakraborty, M. (2025). Advancing Public Safety with Real-Time Life Jacket Detection and Demographic Profiling Using YOLOv8 and Age Classification. EAI Endorsed Trans AI Robotics. 4.1-12. https://doi.org/10.4108/airo.9785. Available from: https://publications.eai.eu/index.php/airo/article/view/978z5
Yusuf, M. A., Khan, M. R. K., Saha, P. P., & Rahaman, M. M. (2024). Data fusion of semantic and depth information in the context of object detection. In 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI) (pp. 1124–1129). IEEE. https://doi.org/10.1109/ICoICI62503.2024.10696627.
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