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Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction

Author

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  • Ayodele Ariyo Adebiyi
  • Aderemi Oluyinka Adewumi
  • Charles Korede Ayo

Abstract

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.

Suggested Citation

  • Ayodele Ariyo Adebiyi & Aderemi Oluyinka Adewumi & Charles Korede Ayo, 2014. "Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    • Handle: RePEc:wly:jnljam:v:2014:y:2014:i:1:n:614342
    DOI: 10.1155/2014/614342
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    References listed on IDEAS

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    Cited by:

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    2. Yong Zhang & Jianping Qin & Bocun Lin & Yongbin Su & Xingyu Yang, 2026. "Wavelet Denoising and Double-Layer Feature Selection for Stock Trend Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 67(2), pages 1203-1231, February.
    3. Konstantinos N. Konstantakis & Panayotis G. Michaelides & Panos Xidonas & Arsenios-Georgios N. Prelorentzos & Aristeidis Samitas, 2025. "Responsible artificial intelligence for measuring efficiency: a neural production specification," Annals of Operations Research, Springer, vol. 354(1), pages 399-425, November.
    4. T. O. Olatayo & T. J. Adejumo & Y. A. Rasaki & T. A. Lasisi & W. A. Abdulrouf, 2026. "Predicting the average price of some selected food items in Nigeria using time series analysis," Quality & Quantity: International Journal of Methodology, Springer, vol. 60(1), pages 2063-2076, February.
    5. Ying Liu & Zengyu Wei & Long Chen & Cai Xu & Ziyu Guan, 2025. "Multi-Modal Temporal Dynamic Graph Construction for Stock Rank Prediction," Mathematics, MDPI, vol. 13(5), pages 1-20, March.
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    8. Tichaona W. Mapuwei & Oliver Bodhlyera & Henry Mwambi, 2020. "Univariate Time Series Analysis of Short‐Term Forecasting Horizons Using Artificial Neural Networks: The Case of Public Ambulance Emergency Preparedness," Journal of Applied Mathematics, John Wiley & Sons, vol. 2020(1).
    9. V. Kuppulakshmi & C. Sugapriya & D. Nagarajan & A. Kanchana, 2025. "Modelling with Neural Networks and Time-Series Forecasting Inventory Control and Cost Reduction in Supply Chain Process," SN Operations Research Forum, Springer, vol. 6(2), pages 1-23, June.
    10. Xavier Martínez-Barbero & Roberto Cervelló-Royo & Javier Ribal, 2025. "Portfolio Optimization with Prediction-Based Return Using Long Short-Term Memory Neural Networks: Testing on Upward and Downward European Markets," Computational Economics, Springer;Society for Computational Economics, vol. 65(3), pages 1479-1504, March.
    11. Keshab Raj Dahal & Nawa Raj Pokhrel & Santosh Gaire & Sharad Mahatara & Rajendra P Joshi & Ankrit Gupta & Huta R Banjade & Jeorge Joshi, 2023. "A comparative study on effect of news sentiment on stock price prediction with deep learning architecture," PLOS ONE, Public Library of Science, vol. 18(4), pages 1-19, April.
    12. Nicole Königstein, 2023. "Dynamic and context-dependent stock price prediction using attention modules and news sentiment," Digital Finance, Springer, vol. 5(3), pages 449-481, December.
    13. Jun Shu & Xinyu Xia & Suyue Han & Zuli He & Ke Pan & Bin Liu, 2024. "Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China," PLOS ONE, Public Library of Science, vol. 19(5), pages 1-23, May.
    14. Pei-Jun Liao & Hung-Shin Lee & Yao-Fei Cheng & Li-Wei Chen & Hung-yi Lee & Hsin-Min Wang, 2026. "Generalized Stock Price Prediction for Multiple Stocks Combined with News Fusion," Papers 2603.19286, arXiv.org.

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