AI‑Driven Financial Econometrics and Risk Management
A special issue of Risks (ISSN 2227-9091).
Deadline for manuscript submissions: 31 October 2026 | Viewed by 52
Special Issue Editors
Interests: risk management; behavioral finance; experimental economics; financial intermediation; human-algorithm interaction; decision science
2. University of Chinese Academy of Sciences, Beijing, China
Interests: economic forecasting; machine learning; finance risk management; decision analysis; intelligent computing; operational optimization
Special Issue Information
Dear Colleagues,
Rapid advances in artificial intelligence, machine learning, and data science are reshaping the landscape of financial econometrics and modern risk management. Financial markets now generate unprecedented volumes of granular, high‑frequency, and unstructured data, while institutions face increasingly complex risks arising from geopolitical uncertainty, climate transitions, digital assets, algorithmic trading, and systemic interconnectedness. Traditional econometric models, though foundational, are often insufficient for fully capturing nonlinear dynamics, real‑time dependencies, and structural breaks that characterize today’s financial systems.
This Special Issue aims to bring together cutting‑edge theoretical, methodological, and empirical research at the intersection of AI technologies and financial risk analysis. We welcome contributions that develop novel econometric models enhanced by machine learning, explore data‑driven approaches to risk measurement, or apply AI tools to credit risk, market risk, systemic risk, insurance analytics, and portfolio optimization. Studies integrating the interpretability, robustness, fairness, and regulatory implications of AI-driven modeling are particularly encouraged. Both methodological innovations and high‑impact practical applications are welcome. By bridging financial econometrics with modern AI methodologies, this Special Issue seeks to advance the next generation of risk modeling tools and promote informed decision‑making in increasingly complex financial environments.
Dr. Difang Huang
Prof. Dr. Jue Wang
Guest Editors
Manuscript Submission Information
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Keywords
- financial econometrics
- machine learning
- artificial intelligence
- risk management
- systemic risk
- volatility modeling
- credit and market risk
- high frequency data
- model uncertainty and robustness
- data analytics in finance
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