Analysis of Macro Factors Influencing Cryptocurrency Price Fluctuations
Research Article
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Analysis of Macro Factors Influencing Cryptocurrency Price Fluctuations

Yangxi Song 1*
1 SWUFE
*Corresponding author: xhswdy@outlook.com
Published on 28 October 2025
Journal Cover
AEMPS Vol.233
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-80590-485-4
ISBN (Online): 978-1-80590-486-1
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Abstract

With the upgrading of blockchain technology, cryptocurrency has already become an important financial product. However, due to its unpredictable nature of price volatility, it rarely appears in asset allocation. This article uses the Pearson correlation coefficient and the Autoregressive Integrated Moving Average (ARIMA) model to quantify monetary policy in macro factors, study its time-varying correlation with Bitcoin price fluctuations, and observe whether it can accurately predict cryptocurrency prices through macro variables. In the study, the Pearson correlation coefficient was used to find that M2 money supply, Consumer Price Index (CPI), Producer Price Index (PPI), and US dollar index are correlated with Bitcoin price, with a significant correlation with M2 money supply. The prediction performance of the ARIMA model is poor, and the research method still needs improvement. The purpose of this study is to quantify macro monetary policy, reflect the impact of cryptocurrency price fluctuations, and construct a more stable asset framework.

Keywords:

cryptocurrency, macroeconomic indicators, Pearson correlation coefficient, ARIMA model prediction

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Song,Y. (2025). Analysis of Macro Factors Influencing Cryptocurrency Price Fluctuations. Advances in Economics, Management and Political Sciences,233,59-65.

References

[1]. Mi, J., & Wang, Y. (2022). New progress in research on digital currency and its economic impact. Economic Dynamics, 5, 127–142.

[2]. Yang, X. (2024). Research on price volatility of distributed finance (DeFi) platform tokens (Master’s thesis). Beijing University of Posts and Telecommunications.

[3]. Guo, C., & Chen, G. (2018). Can Bitcoin be used as a tool to control inflation? Business Research, 5, 96–102.

[4]. Guo, K. (2022). Can Bitcoin become a safe haven asset? China Economic Weekly, 7, 105–106.

[5]. Tan, J. (2025). US cryptocurrency policy adjustment: Reasons, effects, and responses. Open Report, 2, 75–85.

[6]. Shen, J., & Zhu, T. (2025). The policy evolution and development prospects of cryptocurrency in Russia. International Finance, 4, 60–66.

[7]. Gao, D., & Tong, Q. (2024). Research on the difference between gold and bitcoin in hedging against China’s stock market during COVID-19—Based on the DCC-GARCH t-Copula model. Systems Science and Mathematics, 44(2), 326–341.

[8]. CoinGecko. (2025, July 26). Cryptocurrency prices. Retrieved July 26, 2025, from https: //www.coingecko.com

[9]. Federal Reserve Bank of St. Louis. (2025, July 13). Economic data (FRED). Retrieved July 26, 2025, from https: //fred.stlouisfed.org

[10]. Zhao, X., & Qin, J. (2025). Research on the decomposition and integration framework of cryptocurrency price prediction. Journal of Chongqing Technology and Business University (Natural Science Edition), 1–13. Advance online publication.

[11]. Liu, Q. (2023). Research on the linkage and risk spillover effects of cryptocurrencies and global stock markets during COVID-19 (Doctoral dissertation). Shanghai University of Finance and Economics.

References

[1]. Mi, J., & Wang, Y. (2022). New progress in research on digital currency and its economic impact. Economic Dynamics, 5, 127–142.

[2]. Yang, X. (2024). Research on price volatility of distributed finance (DeFi) platform tokens (Master’s thesis). Beijing University of Posts and Telecommunications.

[3]. Guo, C., & Chen, G. (2018). Can Bitcoin be used as a tool to control inflation? Business Research, 5, 96–102.

[4]. Guo, K. (2022). Can Bitcoin become a safe haven asset? China Economic Weekly, 7, 105–106.

[5]. Tan, J. (2025). US cryptocurrency policy adjustment: Reasons, effects, and responses. Open Report, 2, 75–85.

[6]. Shen, J., & Zhu, T. (2025). The policy evolution and development prospects of cryptocurrency in Russia. International Finance, 4, 60–66.

[7]. Gao, D., & Tong, Q. (2024). Research on the difference between gold and bitcoin in hedging against China’s stock market during COVID-19—Based on the DCC-GARCH t-Copula model. Systems Science and Mathematics, 44(2), 326–341.

[8]. CoinGecko. (2025, July 26). Cryptocurrency prices. Retrieved July 26, 2025, from https: //www.coingecko.com

[9]. Federal Reserve Bank of St. Louis. (2025, July 13). Economic data (FRED). Retrieved July 26, 2025, from https: //fred.stlouisfed.org

[10]. Zhao, X., & Qin, J. (2025). Research on the decomposition and integration framework of cryptocurrency price prediction. Journal of Chongqing Technology and Business University (Natural Science Edition), 1–13. Advance online publication.

[11]. Liu, Q. (2023). Research on the linkage and risk spillover effects of cryptocurrencies and global stock markets during COVID-19 (Doctoral dissertation). Shanghai University of Finance and Economics.

Cite this article

Song,Y. (2025). Analysis of Macro Factors Influencing Cryptocurrency Price Fluctuations. Advances in Economics, Management and Political Sciences,233,59-65.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of ICFTBA 2025 Symposium: Data-Driven Decision Making in Business and Economics

ISBN: 978-1-80590-485-4(Print) / 978-1-80590-486-1(Online)
Editor: Lukášak Varti
Conference website: https://2025.icftba.org/Bratislava.html
Conference date: 12 December 2025
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.233
ISSN: 2754-1169(Print) / 2754-1177(Online)

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