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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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    3. 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.
    4. Gergana Taneva-Angelova & Stefan Raychev & Galina Ilieva, 2025. "A Framework for Gold Price Prediction Combining Classical and Intelligent Methods with Financial, Economic, and Sentiment Data Fusion," IJFS, MDPI, vol. 13(2), pages 1-25, June.
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    8. 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.
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    11. 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.
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