Gold Prices Forecasting Using Bidirectional LSTM Model Based on SPX500 Index, USD Index, Crude Oil Prices and CPI

The objective of this research is to develop an accurate gold price forecasting model using Bidirectional LSTM model, taking into account significant factors such as the SPX500 Index, USD Index, Crude Oil Prices, and Consumer Price Index (CPI). Previous studies suggested the potential for improved performance when utilizing a Bidirectional LSTM model. To optimize the models, a random search tuner was employed to identify the best hyperparameters for Bidirectional LSTM model. The results demonstrate that the Bidirectional LSTM model exhibited a marked potential for enhancing the accuracy of gold price predictions. This advanced forecasting model can provide valuable insights for governments, policymakers, and investors, empowering them to make well-informed decisions in the gold market.