posted on 2023-08-30, 20:33authored bySrinivas Devarajula, Vitaliy Milke, Cristina Luca
Financial market forecasting is used to assess the future value of financial instruments in various exchange and over-the-counter markets. Investors have a high interest in the most accurate prediction of the financial instruments’ prices. Inaccurate forecasting might result in a significant financial loss in certain circumstances. This research aims to determine the most probabilistic deep learning model that can improve price forecasting in the financial markets. In this research, Convolutional Neural Networks and Long Short-Term Memory are used for the experiments to forecast the Gold price movements on the Forex market. The Gold(XAU/USD) dataset is used in this research to predict the prices for the next minute. The models proposed have been evaluated using Mean squared error, Mean absolute error, and Mean absolute percentage error metrics. The results show that the Convolutional Neural Network has performed better than the Long Short-Term Memory network and has the potential to (More)