Predicting Price Trends Combining Kinetic Energy and Deep Reinforcement Learning

It is important to approach investing in the stock market and Forex with caution and to understand the potential risks involved. Predicting the direction of prices in financial markets is a complex task, and there is no guaranteed way to do it. A promising approach that has been proposed involves using a combination of the kinetic energy formula and indicator signals as our first sub-approach to predict prices movement. Another approach uses deep reinforcement learning (DRL) as the second sub-approach. The third sub-approach incorporates the kinetic energy of stocks as a condition rule in the Trading Deep Q-Network algorithm, leading to the development of the TDQN method. The proposed TKDQN method has demonstrated promising results in terms of accuracy and profitability, outperforming previous version based on several metrics