Cheng, Hao (2023) A Study of Daily K-Level Quantitative Trading Based on Deep Learning. In: Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Hangzhou, China.
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Abstract
This paper proposes a Daily K-Level Quantitative Trading Strategy (DKTS) based on deep learning, which aims to predict the future stock price trends in the daily K-level and conduct corresponding quantitative trading using historical data and LSTM networks. We use Long Short-Term Memory (LSTM) for f
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 16:33 |
| Last Modified: | 17 Apr 2026 02:32 |
| URI: | http://eprints.eai.eu/id/eprint/44311 |
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