Fostering a Predictive Model with Neural Networks Trading in the Forex Market using AI Technology

This research article investigates the potential of Artificial Intelligence (AI) and neural networks to enhance Forex trading strategies. In order to provide profitable trade alerts, historical data is analyzed first to construct a predictive model. It is found that the prediction model was quite accurate, as shown by its small Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). In addition, the model-based trading strategy outperforms the baseline approach, which randomly decides when to purchase and sell, in terms of return on investment and sharpe ratio. These findings contribute to the expanding body of research literature on the use of AI technology in the financial sector and are valuable for traders and buyers on the Forex market. Some restrictions and future research directions are also discussed, such as the need for developing more practical and user-friendly AI tools and the need for considering the societal impacts.