Research on exchange rate risk prediction model based on neural network

Against the backdrop of the continuous appreciation of the renminbi, foreign exchange risk management is crucial. Therefore, it is necessary to adopt scientific and reasonable methods to predict and optimize the exchange rate risk prediction model. According to the specific characteristics of the exchange rate model, this paper selects the analysis method of fusing time-frequency signal analysis and neural network model, and preliminarily analyzes and preprocesses the price level of the RMB exchange rate. By using the ensemble empirical mode decomposition method, the signals are effectively screened and reconstructed, and then the neural network is used to predict the price level of the RMB exchange rate. The model accurately captures the trend of fluctuations, which verifies the effectiveness of the proposed prediction method. This is of far-reaching practical significance for the foreign exchange management department to avoid market risks and cope with various impacts brought about by interest rate and exchange rate fluctuations.