Application of Artificial Intelligence to Stock Market Investments: RSI Analysis with Genetic Algorithms and Neural Networks

This paper presents an innovative methodology for optimizing and predicting investment performance in the stock market by combining genetic algorithms and neural networks. First, the parameters of the Relative Strength Index (RSI) are optimized using genetic algorithms, allowing for the efficient adjustment of overbought and oversold levels. These optimized parameters are then used as input for a neural network, which is trained to predict market behavior in future periods. The results demonstrate that this combination of techniques can significantly outperform traditional analysis methods, providing higher and more accurate returns. This study highlights the ability of neural networks to capture complex market dynamics and offers an advanced tool for investors and financial analysts.