Deep Learning Techniques for Stock Market Prediction in the European Union: A Systematic Review

摘要

Undoubtedly, stock market prediction constitutes one of the most popular and prominent problems that concerns a multidisciplinary audience. Indeed, various disciplines participate in this intriguing exercise including Economics, Statistics and Computer Science. Furthermore, the proliferation and high performance of machine learning methodologies and especially, deep learning techniques, have led the research community to adopt them in time-series forecasting such as stock prices. For this reason, a Systematic Literature Review (SLR) is conducted including primary studies that deal with the prediction of stock markets in the European Union (EU), using deep learning techniques. The proposed SLR involves 12 papers, indicating that there is not yet intense activity in this field, which thus appears open for further research.