Sistema de Recomendação de Investimento em Ativos de Renda variável usando Técnicas de Inteligência Artificial

Abstract

This paper presents the development of a stock investment recommendation system based on fundamental indicators and artificial intelligence techniques. By collecting financial data on shares from financial indicators of stocks traded on the Brazilian stock exchange, clustering methods are applied to group similar assets. The system allows the creation of a synthetic stock profile based on investor preferences, which is then matched to the most similar real asset using the nearest neighbor approach. The proposed method avoids rigid filters and provides a personalized recommendation based on real data, offering a more flexible and accurate tool for asset selection in the stock market.