The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.
Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms
Abstract
Summary: Security indices are the main tools for evaluation of the status of financial markets. Moreover, a main part of the economy of any country is constituted of investment in stock markets. Therefore, investors could maximize the return of investment if it becomes possible to predict the future trend of stock market with appropriate methods. The nonlinearity and nonstationarity of financial series make their prediction complicated. This study seeks to evaluate the prediction power of machine‐learning models in a stock market. The data used in this study include the daily close price data of iShares MSCI United Kingdom exchange‐traded fund from January 2015 to June 2018. The prediction process is done through four models of machine‐learning algorithms. The results indicate that the deep learning method is better in prediction than the other methods, and the support vector regression method is in the next rank with respect to neural network and random forest methods with less error.
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Cites
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Cited by
Sonkavde, G., Dharrao, D. S., Bongale, A. M., Deokate, S. T., Doreswamy, D., & Bhat, S. K. (2023) · International Journal of Financial Studies · doi:10.3390/ijfs11030094 · Cited by 262
“Generally, these chart patterns are identified based on the perceptions of traders.”
BackgroundSawhney, R., Agarwal, S., Wadhwa, A., & Shah, R. R. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/2020.emnlp-main.676 · Cited by 146
Stock Price prediction using LSTM and SVR
Bathla, G. (2020) · 2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC) · doi:10.1109/pdgc50313.2020.9315800 · Cited by 139
Sawhney, R., Goyal, M., Goel, P., Mathur, P., & Shah, R. R. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · doi:10.18653/v1/2021.acl-long.526 · Cited by 8
Metadata
- Authors
- Nikou, M., Mansourfar, G., & Bagherzadeh, J.
- Venue
- Intelligent Systems in Accounting, Finance and Management
- Publisher
- Wiley
- Published
- 2019-10
- Volume
- 26
- Issue
- 4
- Pages
- 164-174
- ISSN
- 1055-615X (ISSN-L)
- 1550-1949
- 2160-0074
- OpenAlex
- W2993491036
- Cited by
- 292
- References
- 41
- FWCI
- 16.99
- Type
- journal article
- Language
- en
- Open access
- closed
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- Nikou, M., Mansourfar, G., & Bagherzadeh, J. (2019). Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms. Intelligent Systems in Accounting, Finance and Management. https://doi.org/10.1002/isaf.1459
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