The Prediction of the exchange rate between the us dollar and rmb through liner regression and arima model

Abstract

The exchange rate between the US dollar and the RMB has been changing over the past year. Through the analysis of daily changing data, the direct calculation of linear regression will lead to the overall upward trend of the data, but not the rise and fall of the exchange rate. Therefore, it is necessary to introduce a more accurate ARIMA model to predict the possible development and change of data in a short period of time and analyze what policy causes the sharp fluctuations of data in a short period of time. In the process of applying the ARIMA model, this paper analyzed the shortcomings of ordinary linear regression and therefore proposed how to select the appropriate model for different data processing. The research results of this article provide more beginners in statistics with ideas for solving problems: prediction problems that cannot be solved by simple linear regression and existing elementary models can be analyzed using certain time series models, and reasonable explanations for data changes can be given based on existing policy reasons, Including irresistible inflation and the United States' own adjustment to the Federal Reserve's interest rate hike.