Abstract
In order to predict the trend of the exchange rate between USD and RMB in the financial world, a method for predicting the exchange rate between USD and RMB based on wavelet neural network and grey relational analysis was proposed. The grey relational analysis was used to calculate the correlation degree between the influencing factors and the exchange rate of USD, and several parameters with high correlation degree were optimized. The wavelet neural network was used to find the mapping relationship between the influencing factors and the exchange rate of USD. The method was tested by selecting the data related to the exchange rate of USD in the third quarter of 2018. The experimental results showed that the average relative error of the calculated exchange rate of USD was 1.43%. After the gray correlation analysis method was used, the experimental convergence speed and calculation accuracy were also improved. Therefore, the wavelet neural network method can use the known data of dollar exchange rate to predict the change trend of USD exchange rate, which has a high reliability, practicality and application prospect in the field of financial research.
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