Gold Price Prediction Based on CNN-LSTM
Jiaqi Li · Financial Engineering and Risk Management · 2024
Gold plays a significant role in global economic markets, and its price forecasts are of great significance to investors, policymakers, and economic analysts. The serious nonlinearity and high noise characteristics of financial series make it difficult to accurately predict their trends by traditional statistical models. This paper will select the spot price of gold in London as the original data, and make prediction based on the CNN-LSTM combination model, and make comparative analysis with SVM, LSTM and Ridge Regression model. The results show that the MAE of CNN-LSTM model is 2.1758, MSE is 9.4822, R^2is 0.9487, and the model can capture the price trend more effectively, so as to provide more accurate prediction results.