Aplicando técnicas de inteligencia artificial en el reconocimiento de patrones para gestión de inversiones en el mercado del Bitcoin

The cryptocurrency market is well-known for its constant evolution, high volatility, uncertainty, and frequent pricefluctuations. This exposes investors to considerable risks but also offers great profit opportunities. Given this scenario, investors seek strategies that maximize gains, minimize risks, and reduce operating costs. The complexity of these decisions makes the use of machine learning techniques highly attractive. These techniques explore large volumes of data to develop predictive models, based on the identification of patterns, which can assist in decision-making.This study proposes an investment strategy model based on computational intelligence and financial data. The proposed model aims to make investments lasting three days, with the goal of maximizing profits and mitigating risks associated with price volatility, especially during periods of sharp and rapid drops that are common in the cryptocurrency market. For this, artificial neural networks, and historical price data were used; data pre-processing and analysis of statistical indices were carried out.The results obtained were promising, demonstrating the ability of the proposed strategy to generate significant profits during the test period. The profits were higher and with less exposure to risk when compared to the results obtained by the buy-and-hold market strategy, highlighting the potential of machine learning-based approaches for optimizing investments in the cryptocurrency market.