Issue |
SHS Web Conf.
Volume 170, 2023
2023 International Conference on Digital Economy and Management Science (CDEMS 2023)
|
|
---|---|---|
Article Number | 01022 | |
Number of page(s) | 5 | |
Section | Artificial Intelligence and Digital Economy | |
DOI | https://doi.org/10.1051/shsconf/202317001022 | |
Published online | 14 June 2023 |
The Prediction of the exchange rate between the us dollar and rmb through liner regression and arima model
Mathmatics, Fudan University, Shanghai, 200433, China
* Corresponding author: 20300180043@fudan.edu.cn
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.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.