Machine Learning Techniques And The Use Of Event Information For Stock Market Forecasting: A Review

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Astelio Silvera Sarmiento , Darwin Daniel Ordoñez-Iturralde , Johanna Maribel Ochoa-Herrera , Jorge Armando de la Hoz Hernandez , Ana Maria Echeverria


A documentary review was carried out on the production and publication of research papers related to the study of Machine Learning Techniques and the Stock Market. The purpose of the bibliometric analysis proposed in this document is to know the main characteristics of the volume of publications registered in the Scopus database during the period 2016-2021, identifying a total of 576 publications. The information provided by the said platform was organized through tables and figures, categorizing the information by Year of Publication, Country of Origin, Area of Knowledge and Type of Publication. Once these characteristics were described, the position of different authors regarding the proposed topic was referenced by employing a qualitative analysis. Among the main findings of this research, it is found that India, with 209 publications, was the country with the highest scientific production registered in the name of authors affiliated with institutions of that country. The Knowledge Area that made the greatest contribution to the construction of bibliographic material referring to the study of Machine Learning Techniques for Stock Market prediction was Computer Science with 459 published documents, and the type of publication that was most used during the aforementioned period was the Conference Article, representing 50% of the total scientific production.

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