Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)

Exploration and Prediction of Factors Influencing China’s Foreign Exchange Fluctuations Based on Multiple Linear Regression Model

Authors
Singyi Chan1, *
1Statistics and Mathematics, Central University of Finance and Economics, Beijing, 100098, China
*Corresponding author. Email: irene0924xx@outlook.com
Corresponding Author
Singyi Chan
Available Online 26 June 2025.
DOI
10.2991/978-94-6463-770-0_73How to use a DOI?
Keywords
Foreign exchange reserves; exchange rate fluctuations; multiple linear regression; ARMA-GARCH model; market risk
Abstract

As China becomes increasingly globalized, foreign exchange reserves serve as a crucial indicator of economic strength and international standing, thereby shaping economic security, international payment capacity, and financial market stability. However, foreign exchange reserve fluctuations are driven by various macroeconomic factors, necessitating a deeper exploration of their underlying mechanisms. Therefore, the paper aims to explore the key factors affecting the fluctuation of China’s foreign exchange reserves and analyze the impact mechanisms of macroeconomic variables such as money supply, GDP, and interest rates on foreign exchange reserves. In particular, a multiple linear regression model is used for empirical analysis, with standardized macroeconomic indicator frequencies and outlier adjustments to improve model robustness. In addition, a ten-fold cross-validation method is implemented to refine the model, while the ARMA-GARCH model is utilized to predict exchange rate fluctuations for the next year, thus providing deeper insights into market risks. The results demonstrate that at a 0.05 confidence level, the logarithmic broad money supply (ln M2) and exchange rate (ER) exhibit a significant negative influence on foreign exchange reserves (FER), while the China-U.S. CPI difference, treasury bond yield difference (YS), and the logarithm of China’s GDP index do not show statistical significance. Furthermore, the ARMA-GARCH model predicts that the average exchange rate remains around 8.2765 over the next year, while volatility is expected to increase, indicating that despite a stable average exchange rate, market uncertainty and risk may rise.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
26 June 2025
ISBN
978-94-6463-770-0
ISSN
2352-5428
DOI
10.2991/978-94-6463-770-0_73How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Singyi Chan
PY  - 2025
DA  - 2025/06/26
TI  - Exploration and Prediction of Factors Influencing China’s Foreign Exchange Fluctuations Based on Multiple Linear Regression Model
BT  - Proceedings of the 2025 3rd International Conference on Digital Economy and Management Science (CDEMS 2025)
PB  - Atlantis Press
SP  - 634
EP  - 645
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-770-0_73
DO  - 10.2991/978-94-6463-770-0_73
ID  - Chan2025
ER  -