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

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Cited by:

  1. 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.
  2. Ritika Chopra & Gagan Deep Sharma, 2021. "Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda," JRFM, MDPI, vol. 14(11), pages 1-34, November.
  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. Paraskevas Panagiotidis & Andrew Effraimis & George A Xydis, 2019. "An R-based forecasting approach for efficient demand response strategies in autonomous micro-grids," Energy & Environment, , vol. 30(1), pages 63-80, February.
  5. Fuli Feng & Huimin Chen & Xiangnan He & Ji Ding & Maosong Sun & Tat-Seng Chua, 2018. "Enhancing Stock Movement Prediction with Adversarial Training," Papers 1810.09936, arXiv.org, revised Jun 2019.
  6. 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.
  7. Lin, Yu & Yan, Yan & Xu, Jiali & Liao, Ying & Ma, Feng, 2021. "Forecasting stock index price using the CEEMDAN-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
  8. Subhranginee Das & Sarat Chandra Nayak & Biswajit Sahoo, 2022. "Towards Crafting Optimal Functional Link Artificial Neural Networks with Rao Algorithms for Stock Closing Prices Prediction," Computational Economics, Springer;Society for Computational Economics, vol. 60(1), pages 1-23, June.
  9. Seung Hwan Jeong & Hee Soo Lee & Hyun Nam & Kyong Joo Oh, 2021. "Using a Genetic Algorithm to Build a Volume Weighted Average Price Model in a Stock Market," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
  10. Jaydip Sen & Sidra Mehtab, 2021. "Design and Analysis of Robust Deep Learning Models for Stock Price Prediction," Papers 2106.09664, arXiv.org.
  11. 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.
  12. Duan, Yunlong & Mu, Chang & Yang, Meng & Deng, Zhiqing & Chin, Tachia & Zhou, Li & Fang, Qifeng, 2021. "Study on early warnings of strategic risk during the process of firms’ sustainable innovation based on an optimized genetic BP neural networks model: Evidence from Chinese manufacturing firms," International Journal of Production Economics, Elsevier, vol. 242(C).
  13. Axelsson, Birger & Song, Han-Suck, 2023. "Univariate Forecasting for REITs with Deep Learning: A Comparative Analysis with an ARIMA Model," Working Paper Series 23/10, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance, revised 14 Nov 2023.
  14. Vásquez Sáenz, Javier & Quiroga, Facundo Manuel & Bariviera, Aurelio F., 2023. "Data vs. information: Using clustering techniques to enhance stock returns forecasting," International Review of Financial Analysis, Elsevier, vol. 88(C).
  15. Abdullahi Osman Ali & Jama Mohamed, 2022. "The optimal forecast model for consumer price index of Puntland State, Somalia," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4549-4572, December.
  16. Xiaowen Wang & Ying Ma & Wen Li, 2021. "The Prediction of Gold Futures Prices at the Shanghai Futures Exchange Based on the MEEMD-CS-Elman Model," SAGE Open, , vol. 11(1), pages 21582440211, March.
  17. Farman Ullah Khan & Faridoon Khan & Parvez Ahmed Shaikh, 2023. "Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms," Future Business Journal, Springer, vol. 9(1), pages 1-11, December.
  18. Meftah Elsaraiti & Adel Merabet, 2021. "A Comparative Analysis of the ARIMA and LSTM Predictive Models and Their Effectiveness for Predicting Wind Speed," Energies, MDPI, vol. 14(20), pages 1-16, October.
  19. 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.
  20. Madeline Hui Li Lee & Yee Chee Ser & Ganeshsree Selvachandran & Pham Huy Thong & Le Cuong & Le Hoang Son & Nguyen Trung Tuan & Vassilis C. Gerogiannis, 2022. "A Comparative Study of Forecasting Electricity Consumption Using Machine Learning Models," Mathematics, MDPI, vol. 10(8), pages 1-23, April.
  21. Nicole Koenigstein, 2022. "Dynamic and Context-Dependent Stock Price Prediction Using Attention Modules and News Sentiment," Papers 2205.01639, arXiv.org.
  22. Muhammad Nadim Hanif & Khurrum S. Mughal & Javed Iqbal, 2018. "A Thick ANN Model for Forecasting Inflation," SBP Working Paper Series 99, State Bank of Pakistan, Research Department.
  23. Nwokike Chukwudike C. & Ugoala & Chukwuma B. & Obubu Maxwell & Uche-Ikonne Okezie O. & Offorha Bright C. & Ukomah Henry I., 2020. "Forecasting Monthly Prices of Gold Using Artificial Neural Network," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(3), pages 1-2.
  24. 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.
  25. Yoojeong Song & Jae Won Lee & Jongwoo Lee, 2022. "Development of Intelligent Stock Trading System Using Pattern Independent Predictor and Turning Point Matrix," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 27-38, January.
  26. Phillips Edomwonyi Obasohan, 2020. "Comparing Weighted Markov Chain and Auto-Regressive Integrated Moving Average in the Prediction of Under-5 Mortality Annual Closing Rates in Nigeria," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 9(3), pages 1-13, May.
  27. Sehrish Kayani & Usman Ayub & Imran Abbas Jadoon, 2019. "Adaptive Market Hypothesis and Artificial Neural Networks: Evidence from Pakistan," Global Regional Review, Humanity Only, vol. 4(2), pages 190-203, June.
  28. Muhammad Nadim Hanif & Muhammad Jahanzeb Malik, 2015. "Evaluating the Performance of Inflation Forecasting Models of Pakistan," SBP Research Bulletin, State Bank of Pakistan, Research Department, vol. 11, pages 43-78.
  29. Alebachew Abebe & Aboma Temesgen & Belete Kebede, 2023. "Modeling inflation rate factors on present consumption price index in Ethiopia: threshold autoregressive models approach," Future Business Journal, Springer, vol. 9(1), pages 1-12, December.
  30. 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.
  31. Zheng Fang & Jianying Xie & Ruiming Peng & Sheng Wang, 2021. "Climate Finance: Mapping Air Pollution and Finance Market in Time Series," Econometrics, MDPI, vol. 9(4), pages 1-15, December.
  32. Raehyun Kim & Chan Ho So & Minbyul Jeong & Sanghoon Lee & Jinkyu Kim & Jaewoo Kang, 2019. "HATS: A Hierarchical Graph Attention Network for Stock Movement Prediction," Papers 1908.07999, arXiv.org, revised Nov 2019.
  33. 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.
  34. Mohammad Javad Bazrkar & Soodeh Hosseini, 2023. "Predict Stock Prices Using Supervised Learning Algorithms and Particle Swarm Optimization Algorithm," Computational Economics, Springer;Society for Computational Economics, vol. 62(1), pages 165-186, June.
  35. Chulwoo Han, 2022. "Bimodal Characteristic Returns and Predictability Enhancement via Machine Learning," Management Science, INFORMS, vol. 68(10), pages 7701-7741, October.
  36. Berthine Nyunga Mpinda & Jules Sadefo-Kamdem & Salomey Osei & Jeremiah Fadugba, 2021. "Accuracies of Model Risks in Finance using Machine Learning," Working Papers hal-03191437, HAL.
  37. Huicheng Liu, 2018. "Leveraging Financial News for Stock Trend Prediction with Attention-Based Recurrent Neural Network," Papers 1811.06173, arXiv.org.
  38. Hongyu Yang & Lei Guo & Qingqing Tian, 2025. "Water Quality Prediction Model Based on Temporal Attentive Bidirectional Gated Recurrent Unit Model," Sustainability, MDPI, vol. 17(20), pages 1-28, October.
  39. Gourav Kumar & Uday Pratap Singh & Sanjeev Jain, 2022. "Swarm Intelligence Based Hybrid Neural Network Approach for Stock Price Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 60(3), pages 991-1039, October.
  40. Hassan Oukhouya & Aziz Lmakri & Mohamed El Yahyaoui & Raby Guerbaz & Said El Melhaoui & Moustapha Faizi & Khalid El Himdi, 2025. "Predictive modeling for the Moroccan financial market: a nonlinear time series and deep learning approach," Future Business Journal, Springer, vol. 11(1), pages 1-19, December.
  41. Andreea-Mihaela NICULAE, 2022. "Analysis of Romanian Air Quality using Machine Learning Techniques," Database Systems Journal, Academy of Economic Studies - Bucharest, Romania, vol. 13(1), pages 1-10.
  42. Ahmed Ramzy Mohamed, 2022. "Artificial Neural Network for Modeling the Economic Performance: A New Perspective," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 555-575, September.
  43. Huijian Dong & Xiaomin Guo & Han Reichgelt & Ruizhi Hu, 2020. "Predictive power of ARIMA models in forecasting equity returns: a sliding window method," Journal of Asset Management, Palgrave Macmillan, vol. 21(6), pages 549-566, October.
  44. Alam, Md Shabbir & Murshed, Muntasir & Manigandan, Palanisamy & Pachiyappan, Duraisamy & Abduvaxitovna, Shamansurova Zilola, 2023. "Forecasting oil, coal, and natural gas prices in the pre-and post-COVID scenarios: Contextual evidence from India using time series forecasting tools," Resources Policy, Elsevier, vol. 81(C).
  45. Chaoran Cui & Xiaojie Li & Juan Du & Chunyun Zhang & Xiushan Nie & Meng Wang & Yilong Yin, 2021. "Temporal-Relational Hypergraph Tri-Attention Networks for Stock Trend Prediction," Papers 2107.14033, arXiv.org, revised Mar 2022.
  46. Fuli Feng & Xiangnan He & Xiang Wang & Cheng Luo & Yiqun Liu & Tat-Seng Chua, 2018. "Temporal Relational Ranking for Stock Prediction," Papers 1809.09441, arXiv.org, revised Jan 2019.
  47. Zhenni Jin & Kun Guo & Yi Sun & Lin Lai & Zhewen Liao, 2020. "The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(7), pages 1166-1178, November.
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