Computational intelligence in the financial market: a review of techniques for automating operations
DOI:
https://doi.org/10.33448/rsd-v12i5.41793Keywords:
Machine learning; Artificial neural networks; Genetic algorithms; Fuzzy logic.Abstract
The field of financial applications has become increasingly complex and challenging, with non-linear and uncertain behaviors that change over time. Therefore, computational intelligence techniques, including neural networks, genetic algorithms and fuzzy logic, have gained prominence as promising solutions for automating decisions in the financial market. This article aims to explore recent studies that address the use of these techniques and discuss their applications, advantages and limitations. This is a narrative literature review, with an exploratory descriptive character. Literature collection was carried out in the Science Direct and Scopus databases, using keywords related to the theme. It is concluded that computational intelligence techniques have been shown to be capable of solving highly non-linear and time-varying problems, thus becoming an effective approach to automate operations in the financial market.
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