Regulatory challenges in algorithmic trading and market manipulation: autonomous AI and EU market abuse law dual-track enforcement, legal attribution and the challenge of intent
Paparisto, Josefin (A.A. 2024/2025) Regulatory challenges in algorithmic trading and market manipulation: autonomous AI and EU market abuse law dual-track enforcement, legal attribution and the challenge of intent. Tesi di Laurea in FinTech, Luiss Guido Carli, relatore Fabiana Di Porto, pp. 85. [Master's Degree Thesis]
Full text for this thesis not available from the repository.
Abstract/Index
Autonomous AI and legal attribution challenges. AI in algorithmic and high-frequency trading. Spoofing, layering and crisis-prone AI behaviour. Attribution without intent: why criminal law fails. AI and insider trading: amplifying asymmetries. Policy and reform: what needs to change. The EU enforcement framework and its liabilities. Overview of administrative and criminal liability (MAR & MAD II). National competent authorities and enforcement structures. Dual proceedings and the ne bis in idem principle. Legal gaps in current frameworks. Enforcement conflicts and liability allocation in the age of autonomous AI. Structural problems: liability overlap, fragmentation, and uncertainty. Key case-law and attribution challenges. Administrative sanctions with criminal characteristics: liability implications. Diverging enforcement practices and gaps in liability allocation. Recommendations and future directions. Reforming EU liability: toward a future-proof model. Comparative models: UK, US and international practice. The AI Act and AI liability directive: scope and limits. Proposing a tiered, risk-based liability framework. Role of SupTech, explainability and governance duties.
References
Bibliografia: pp. 83-85.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Digital Innovation and Sustainability (LM/SC – GIUR) |
| Chair: | FinTech |
| Thesis Supervisor: | Di Porto, Fabiana |
| Thesis Co-Supervisor: | Fernandes Da Silva Ranchordas, Sofia Hina |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 29 May 2026 14:03 |
| Last Modified: | 29 May 2026 14:03 |
| URI: | https://tesi.luiss.it/id/eprint/46007 |
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