Two-Stage Hybrid Feature Selection Approach Using Levy’s Flight Based Chicken Swarm Optimization for Stock Market Forecasting
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10614-023-10400-8.pdf
Reference70 articles.
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2. Ayala, J., García-Torres, M., Noguera, J. L. V., Gómez-Vela, F., & Divina, F. (2021). Technical analysis strategy optimization using a machine learning approach in stock market indices[Formula presented]. Knowledge-Based Systems, 225, 107119. https://doi.org/10.1016/j.knosys.2021.107119.
3. Barak, S., Arjmand, A., & Ortobelli, S. (2017). Fusion of multiple diverse predictors in stock market. Information Fusion, 36, 90–102. https://doi.org/10.1016/j.inffus.2016.11.006.
4. Basak, S., Kar, S., Saha, S., Khaidem, L., & Dey, S. R. (2019). Predicting the direction of stock market prices using tree-based classifiers. North American Journal of Economics and Finance, 47(June), 552–567. https://doi.org/10.1016/j.najef.2018.06.013.
5. Borovkova, S., & Tsiamas, I. (2019). An ensemble of LSTM neural networks for high-frequency stock market classification. Journal of Forecasting, 38(6), 600–619. https://doi.org/10.1002/for.2585.
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