A Stock Price Trend Prediction Method Based on Market Sentiment Factors and Multi-layer Stacking Ensemble Learning with Dual-CNN-LSTM Models and Nested Heterogeneous Learners
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-57808-3_29
Reference16 articles.
1. Song, Z., Gong, X., Zhang, C., Yu, C.: Investor sentiment based on scaled PCA method: a powerful predictor of realized volatility in the Chinese stock market. Int. Rev. Econ. Finance 83(C), 528–545 (2023). Elsevier
2. Ma, H., Ma, J., Wang, H., Li, P., Du, W.: A comprehensive review of investor sentiment analysis in stock price forecasting. In: 2021 IEEE/ACIS 20th International Fall Conference on Computer and Information Science (ICIS Fall), Xi’an, China, pp. 264–268 (2021). https://doi.org/10.1109/ICISFall51598.2021.9627470
3. Shen, J., Shafiq, M.O.: Short-term stock market price trend prediction using a comprehensive deep learning system. J Big Data 7, 66 (2020). https://doi.org/10.1186/s40537-020-00333-6
4. Zhang, L., Wu, T., Lahrichi, S., Salas-Flores, C.G., Li, J.: A data science pipeline for algorithmic trading: a comparative study of applications for finance and cryptoeconomics. arXiv preprint arXiv:2206.14932 (2022)
5. Fang, H., Chung, C.-P., Lu, Y.-C., Lee, Y.-H., Wang, W.-H.: The impacts of investors’ sentiments on stock returns using fintech approaches. Int. Rev. Financ. Anal. 77(C) (2021). Elsevier
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