Yuan, Yigong (2023) Comparing the Efficiency of Stock and Index Price Prediction Between FNN and LSTM Scenarios. In: Proceedings of the International Conference on Financial Innovation, FinTech and Information Technology, FFIT 2022, October 28-30, 2022, Shenzhen, China.
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Abstract
Predicting the trend of changes in stock prices serves as a crucial role in the quantitative investment industry, and few previous empirical analysis studies choose the underlying assets from Hong Kong Stock Exchange. This study compares the performance of two machine learning approaches (i.e., FNN
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 16:10 |
| Last Modified: | 17 Apr 2026 03:25 |
| URI: | http://eprints.eai.eu/id/eprint/42599 |
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