Predicting price trends combining kinetic energy and deep reinforcement learning

Investing in the stock market and Forex can be lucrative, but it is important to approach it with caution and a clear understanding of the risks involved. Predicting the direction of prices in financial markets is a complex task, and there is no guaranteed way to do it. One innovative approach that has been proposed involves using a combination of the kinetic energy formula and indicator signals to predict prices, besides another predictions using deep reinforcement learning (DRL). This approach has led to the development of the Trading Deep Q-Network algorithm (TDQN), which incorporates the kinetic energy of stocks/currencies as a condition rule. The proposed approach, TKDQN method, has shown promising results in terms of accuracy and profitability, outperforming previous versions based on several metrics.