| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP14525 |
| DP14525 Artificial Intelligence in Asset Management | |
| Söhnke Bartram; Jürgen Branke; Mehrshad Motahari | |
| 发表日期 | 2020-03-24 |
| 出版年 | 2020 |
| 语种 | 英语 |
| 摘要 | Artificial intelligence (AI) has a growing presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and returns forecasts and under more complex constraints. Trading algorithms utilize AI to devise novel trading signals and execute trades with lower transaction costs, and AI improves risk modelling and forecasting by generating insights from new sources of data. Finally, robo-advisors owe a large part of their success to AI techniques. At the same time, the use of AI can create new risks and challenges, for instance as a result of model opacity, complexity, and reliance on data integrity. |
| 主题 | Financial Economics ; International Macroeconomics and Finance |
| 关键词 | Algorithmic trading Machine learning Lasso Neural networks Deep learning Decision trees Random forests Svm Evolutionary algorithms Nlp |
| URL | https://cepr.org/publications/dp14525-1 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/543428 |
| 推荐引用方式 GB/T 7714 | Söhnke Bartram,Jürgen Branke,Mehrshad Motahari. DP14525 Artificial Intelligence in Asset Management. 2020. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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