Learning to trade autonomously in stocks and shares: integrating uncertainty into trading strategies
Abstract Machine learning, a revolutionary and advanced technology, has been widely applied in the field of stock trading. However, training an autonomous trading strategy which can effectively balance risk and Return On Investment without human supervision in the stock market with high uncertainty...
Saved in:
| Main Authors: | Yuyang Li, Minghui Liwang, Li Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-08-01
|
| Series: | Autonomous Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s43684-025-00101-4 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Trading robots on the Stock market
Published: (2020-01-01) -
Uncertainty, Deep Regional Trade Agreements, and Global Value Chain Trade
by: Soonchan Park
Published: (2025-06-01) -
What drives international trade? Robust analysis for the European Union
by: Krzysztof Beck
Published: (2020-09-01) -
Birobidzhan: historical transformations of trade spaces in the satellite city
by: Ju. V. Ordynskaya, et al.
Published: (2024-03-01) -
Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model
by: Reza Tehrani, et al.
Published: (2023-03-01)