Gold Price Prediction Based on Stock Analysis Using CNN-Bidirectional LSTM

Due to its timeless appeal, gold has always been a popular investment option. This paper presents a fresh method to gold price prediction by combining the Bidirectional Long Short-Term Memory (LSTM) model with Convolutional Neural Networks (CNNs) to analyze stocks. Future gold price analysis and prediction are expertly handled by the Bidirectional LSTM Networks. Combining them with CNNs enhances the model’s capacity to identify various aspects of fluctuations in the price of gold. Overall, this results in more accurate forecasts. We believe that this approach demonstrates the strength of the stock market and greatly aids in our understanding of gold price fluctuations. These insights can assist governments, banks, and investors in making more informed decisions on gold investments and hedging techniques.