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Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction
Open accessAbstract
This paper examines the forecasting performance of ARIMA and artificial neural networks model with published stock data obtained from New York Stock Exchange. The empirical results obtained reveal the superiority of neural networks model over ARIMA model. The findings further resolve and clarify contradictory opinions reported in literature over the superiority of neural networks and ARIMA model and vice versa.
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Citations
Cited by
Chong, E., Han, C., & Park, F. C. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.04.030 · Cited by 834
Wang, L., Zeng, Y., & Chen, T. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.08.018 · Cited by 631
A systematic review of fundamental and technical analysis of stock market predictions
Nti, I. K., Adekoya, A. F., & Weyori, B. A. (2020) · Artificial Intelligence Review · doi:10.1007/s10462-019-09754-z · Cited by 547
Integrating metaheuristics and Artificial Neural Networks for improved stock price prediction
Göçken, M., Özçalıcı, M., Boru, A., & Dosdoğru, A. T. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2015.09.029 · Cited by 324
Hao, Y., & Gao, Q. (2020) · Applied Sciences · doi:10.3390/app10113961 · Cited by 95
Metadata
- Authors
- Adebiyi, A. A., Adewumi, A. O., & Ayo, C. K.
- Venue
- Journal of Applied Mathematics
- Publisher
- Hindawi Limited
- Published
- 2014
- Volume
- 2014
- Pages
- 1-7
- ISSN
- 1110-757X (ISSN-L)
- 1687-0042
- OpenAlex
- W1966676388
- Cited by
- 577
- References
- 0
- FWCI
- 14.38
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction. https://app.cochat.ai/papers/10.1155/2014/614342
- The paper
- Adebiyi, A. A., Adewumi, A. O., & Ayo, C. K. (2014). Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction. Journal of Applied Mathematics. https://doi.org/10.1155/2014/614342
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
