Gold Price Forecast by Different Models

Abstract

In recent years, the gold investment market has a dramatic effect on the world. So being able to predict gold price accurately has become an urgent demand for economic development. This paper gives three different models including the regression analysis model, back propagation neural network (BP neural network) model, and time series analysis model to realize the prediction of gold price. Firstly, this paper verifies that the data applies to each model respectively. Secondly, through training the models, the corresponding gold price prediction formulas are output. Finally, through the test of the models, it can be concluded that the three models all have high reliability and accuracy, which means that they are suitable for the prediction of gold prices. In the end, this paper compares the prediction effects of the three models, and finds that compared with the regression analysis model, the BP neural network model and the time series analysis model have certain errors and limitations for long-term prediction, while they are more suitable for the short-term forecast. Since there are certain risks in gold investment, grasping the trend and fluctuation of the gold price accurately is the concern of both all gold investors and academic circles.