MACHINE LEARNING APLICADO EM AÇÕES NO MERCADO FINANCEIRO B3

Abstract

Every day CPFs are registered on the stock exchange. People seeking greater profitability, exposing themselves to great risks without even knowing how to analyze the best opportunities. Whenever you start to learn something, it is normal to have many difficulties and challenges, because the act of knowing something “new” is challenging, even more so when it involves money. Therefore, a comparative analysis was carried out between some of the Artificial Intelligence methods, applied in standards on the stock exchange, aiming to improve the assertiveness of the operations carried out and seeking their statistically proven efficiency. In this way, increasing the chances of the operations being winners. The algorithms were trained separately from historical data of five stocks, namely: Petrobras, Itaú, Bradesco, Vale and Ambev. And the algorithms of Linear Regression, Support Vector Machine (SVM), K Nearest Neighbor (KNN), Random Forest and Decision Trees were used.