| dc.contributor.author | Efremo, A. | ru |
| dc.contributor.author | Yu, Guo. | ru |
| dc.coverage.spatial | Минск | ru |
| dc.date.accessioned | 2026-02-06T05:58:52Z | |
| dc.date.available | 2026-02-06T05:58:52Z | |
| dc.date.issued | 2025 | |
| dc.identifier.citation | Efremo, A. Systematic analysis of artificial intelligence technology in the alpha arena cryptocurrency trading competition = / A. Efremo, Guo Yu // Материалы 2-ой Международной научно-технической конференции «Инженерная экономика», 20-21 ноября 2025 = Materials of 2nd International Scientific and Technical Conference «Engineering Economics», November 20-21 2025 / Белорусский национальный технический университет, Машиностроительный факультет ; редкол.: К. В. Якушенко (пред.), А. В. Арабей, С. Н. Ковшар [и др.] ; сост. К. Н. Шкаровская. – Минск : БНТУ, 2025. – С. 852-861. | ru |
| dc.identifier.uri | https://rep.bntu.by/handle/data/163711 | |
| dc.description.abstract | The rise of Large Language Models (LLMs) represents not only a revolution in the field of Natural Language Processing (NLP) but also has a disruptive impact on the financial sector, which heavily relies on information processing and decision-making optimization. Traditional quantitative trading strategies often fail when faced with shifting market regimes and nonlinear dynamics. In contrast, LLMs, with their powerful capabilities in semantic understanding, logical reasoning, and complex pattern recognition, offer the potential to build a new generation of adaptive trading systems. \The participating models in the competition are: Claude 4.5 Sonnet, DeepSeek V3.1 Chat, Gemini 2.5 Pro, GPT 5, Grok 4, and Qwen 3 Max. | ru |
| dc.language.iso | en | ru |
| dc.publisher | БНТУ | ru |
| dc.title | A systematic analysis of artificial intelligence technology in the alpha arena cryptocurrency trading competition | ru |
| dc.type | Working Paper | ru |
