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Stock Market Analysis: A Review and Taxonomy of Prediction Techniques

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Cited by:

  1. Namitha Yeldho & Dany Thomas & Vimal George Kurian & Chandralekha Arathy & Ajithakumari Vijayappan Nair Biju, 2025. "Are machine learning models effective in predicting emerging markets? Investigating the accuracy of predictions in emerging stock market indices," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 839-904, February.
  2. Hakan Pabuccu & Adrian Barbu, 2023. "Feature Selection with Annealing for Forecasting Financial Time Series," Papers 2303.02223, arXiv.org, revised Feb 2024.
  3. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
  4. Azaz Hassan Khan & Abdullah Shah & Abbas Ali & Rabia Shahid & Zaka Ullah Zahid & Malik Umar Sharif & Tariqullah Jan & Mohammad Haseeb Zafar, 2023. "A performance comparison of machine learning models for stock market prediction with novel investment strategy," PLOS ONE, Public Library of Science, vol. 18(9), pages 1-19, September.
  5. Reo Yamagata, 2025. "Expected and realized returns for dividend-targeting investors: CAPM-DDM conceptual framework using Australian REITs," SN Business & Economics, Springer, vol. 5(4), pages 1-27, April.
  6. Arjun Prakash & Nick James & Max Menzies & Gilad Francis, 2020. "Structural clustering of volatility regimes for dynamic trading strategies," Papers 2004.09963, arXiv.org, revised Nov 2021.
  7. Francis Magloire Peujio Fozap, 2025. "Hybrid Machine Learning Models for Long-Term Stock Market Forecasting: Integrating Technical Indicators," JRFM, MDPI, vol. 18(4), pages 1-21, April.
  8. Faraz Sasani & Ramin Mousa & Ali Karkehabadi & Samin Dehbashi & Ali Mohammadi, 2023. "TM-vector: A Novel Forecasting Approach for Market stock movement with a Rich Representation of Twitter and Market data," Papers 2304.02094, arXiv.org.
  9. Matteo Prata & Giuseppe Masi & Leonardo Berti & Viviana Arrigoni & Andrea Coletta & Irene Cannistraci & Svitlana Vyetrenko & Paola Velardi & Novella Bartolini, 2023. "LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study," Papers 2308.01915, arXiv.org, revised Sep 2023.
  10. Dominik Stempie'n & Janusz Gajda, 2025. "Comparative analysis of financial data differentiation techniques using LSTM neural network," Papers 2505.19243, arXiv.org.
  11. Hakan Pabuccu & Adrian Barbu, 2024. "Feature selection with annealing for forecasting financial time series," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-26, December.
  12. Zhang, Peng & Li, Zeyun & Ghardallou, Wafa & Xin, Yan & Cao, Jie, 2023. "Nexus of institutional quality and technological innovation on renewable energy development: Moderating role of green finance," Renewable Energy, Elsevier, vol. 214(C), pages 233-241.
  13. Saqib Farid & Rubeena Tashfeen & Tahseen Mohsan & Arsal Burhan, 2023. "Forecasting stock prices using a data mining method: Evidence from emerging market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(2), pages 1911-1917, April.
  14. Dushmanta Kumar Padhi & Neelamadhab Padhy & Akash Kumar Bhoi & Jana Shafi & Muhammad Fazal Ijaz, 2021. "A Fusion Framework for Forecasting Financial Market Direction Using Enhanced Ensemble Models and Technical Indicators," Mathematics, MDPI, vol. 9(21), pages 1-31, October.
  15. L.J. Basson & Sune Ferreira-Schenk & Zandri Dickason-Koekemoer, 2022. "Fractal Dimension Option Hedging Strategy Implementation During Turbulent Market Conditions in Developing and Developed Countries," International Journal of Economics and Financial Issues, Econjournals, vol. 12(2), pages 84-95, March.
  16. Dominik Stempie'n & Robert 'Slepaczuk, 2025. "Hybrid Models for Financial Forecasting: Combining Econometric, Machine Learning, and Deep Learning Models," Papers 2505.19617, arXiv.org.
  17. Marian Pompiliu Cristescu & Raluca Andreea Nerisanu & Dumitru Alexandru Mara & Simona-Vasilica Oprea, 2022. "Using Market News Sentiment Analysis for Stock Market Prediction," Mathematics, MDPI, vol. 10(22), pages 1-12, November.
  18. Mahsa Ghorbani & Edwin K. P. Chong, 2022. "A dimension reduction method for stock-price prediction using multiple predictors," Operational Research, Springer, vol. 22(3), pages 2859-2878, July.
  19. Htet Htet Htun & Michael Biehl & Nicolai Petkov, 2024. "Forecasting relative returns for S&P 500 stocks using machine learning," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-16, December.
  20. Shahsuzan Zakaria & Suhaily Maizan Abdul Manaf & Mohd Talmizie Amron & Mohd Taufik Mohd Suffian, 2023. "Has the World of Finance Changed? A Review of the Influence of Artificial Intelligence on Financial Management Studies," Information Management and Business Review, AMH International, vol. 15(4), pages 420-432.
  21. Jiwook Kim & Minhyeok Lee, 2023. "Portfolio Optimization using Predictive Auxiliary Classifier Generative Adversarial Networks with Measuring Uncertainty," Papers 2304.11856, arXiv.org.
  22. Veronika Staňková, 2021. "Can Machine Learning Be Useful in Corporate Finance and Business Valuation? Overview of Current Research [Může být strojové učení užitečné ve financích podniku a jeho ocenění? Přehled současného vý," Oceňování, Prague University of Economics and Business, vol. 14(4), pages 53-66.
  23. Htet Htet Htun & Michael Biehl & Nicolai Petkov, 2023. "Survey of feature selection and extraction techniques for stock market prediction," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-25, December.
  24. Jean Jacques Ohana & Eric Benhamou & David Saltiel & Beatrice Guez, 2021. "Is the Covid equity bubble rational? A machine learning answer," Working Papers hal-03189799, HAL.
  25. Hulusi Mehmet Tanrikulu & Hakan Pabuccu, 2024. "The Effect of Data Types' on the Performance of Machine Learning Algorithms for Financial Prediction," Papers 2404.19324, arXiv.org.
  26. Akpokerere Othuke Emmanuel & Osevwe-Okoroyibo Elizabeth Eloho & Alexander Olawumi Dabor & Eyesan Leslie Dabor & Meshack Aggreh, 2024. "Tax Revenue, Capital Market Performance and Foreign Direct Investment in an Emerging Economy," International Journal of Economics and Financial Issues, Econjournals, vol. 14(4), pages 290-298, July.
  27. Fengyu Han & Yue Wang, 2022. "Predicting Stock Price Movement after Disclosure of Corporate Annual Reports: A Case Study of 2021 China CSI 300 Stocks," Papers 2206.12528, arXiv.org, revised Jul 2022.
  28. Shalini Sharma & Víctor Elvira & Emilie Chouzenoux & Angshul Majumdar, 2021. "Recurrent Dictionary Learning for State-Space Models with an Application in Stock Forecasting," Post-Print hal-03184841, HAL.
  29. Daiki Matsunaga & Toyotaro Suzumura & Toshihiro Takahashi, 2019. "Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis," Papers 1909.10660, arXiv.org, revised Nov 2019.
  30. Wai Khuen Cheng & Khean Thye Bea & Steven Mun Hong Leow & Jireh Yi-Le Chan & Zeng-Wei Hong & Yen-Lin Chen, 2022. "A Review of Sentiment, Semantic and Event-Extraction-Based Approaches in Stock Forecasting," Mathematics, MDPI, vol. 10(14), pages 1-20, July.
  31. Aurora Skrame & Claudio Ciancio & Vincenzo Corvello & Roberto Musmanno, 2020. "A Quantitative Model Supporting Socially Responsible Public Investment Decisions for Sustainable Tourism," IJFS, MDPI, vol. 8(2), pages 1-9, June.
  32. V. Lanzetta, 2024. "Transfer learning for financial data predictions: a systematic review," Papers 2409.17183, arXiv.org.
  33. Jasleen Kaur & Khushdeep Dharni, 2022. "Application and performance of data mining techniques in stock market: A review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(4), pages 219-241, October.
  34. H. T. Shehzad & M. A. Anwar & M. Razzaq, 2023. "A Comparative Predicting Stock Prices using Heston and Geometric Brownian Motion Models," Papers 2302.07796, arXiv.org.
  35. Nick James & Max Menzies, 2021. "Collective correlations, dynamics, and behavioural inconsistencies of the cryptocurrency market over time," Papers 2107.13926, arXiv.org, revised Dec 2021.
  36. Perry Sadorsky, 2021. "A Random Forests Approach to Predicting Clean Energy Stock Prices," JRFM, MDPI, vol. 14(2), pages 1-20, January.
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