Machine Learning Stock Market Prediction Studies: Review and Research Directions

Troy J. Strader · John J. Rozycki · Thomas H. Root · Yu-Hsiang John Huang

162 citations0/0 files storedJournal of international technology and information management

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

Abstract

Stock market investment strategies are complex and rely on an evaluation of vast amounts of data. In recent years, machine learning techniques have increasingly been examined to assess whether they can improve market forecasting when compared with traditional approaches. The objective for this study is to identify directions for future machine learning stock market prediction research based upon a review of current literature. A systematic literature review methodology is used to identify relevant peer-reviewed journal articles from the past twenty years and categorize studies that have similar methods and contexts. Four categories emerge: artificial neural network studies, support vector machine studies, studies using genetic algorithms combined with other techniques, and studies using hybrid or other artificial intelligence approaches. Studies in each category are reviewed to identify common findings, unique findings, limitations, and areas that need further investigation. The final section provides overall conclusions and directions for future research.

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References

1995Task-Technology Fit and Individual Performance 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques 2017Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies 2011Using artificial neural network models in stock market index prediction 2009Textual analysis of stock market prediction using breaking financial news 2000Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index 2005The use of data mining and neural networks for forecasting stock market returns 2009Using support vector machine with a hybrid feature selection method to the stock trend prediction

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