Analysis of Financial Time Series ARMA-GARCH Model Based on China’s Treasury Bond Yield

DOI

10.2991/978-94-6239-801-6_49How to use a DOI?

Keywords

Treasury Bond Yields; ARMA-GARCH Model; Volatility Characteristics; Time Series Analysis

Abstract

As the core component of China’s financial market, the Treasury bond market exhibits fluctuation characteristics that directly affect macroeconomic regulation, financial institutions’ risk management, and investors’ asset allocation decisions. With the advancement of market-oriented interest rate reform, Treasury bond yields present significant time-varying and clustering features, and traditional linear models fail to accurately depict their volatility patterns. Therefore, this paper takes the daily yield of China’s 10-year treasury bonds in 2018–2026 as the research sample, and uses the ARMA-GARCH combination model to carry out empirical analysis. The results show that the combined model has high goodness of fit and can effectively capture the linear trend and volatility agglomeration characteristics of treasury bond yields. The volatility persistence parameter indicates that the fluctuation of the Treasury bond yield has strong persistence, and the impact of market shocks will be transmitted in the long run. The absolute mean error and root mean square error indicate that the prediction accuracy of the combined model is better. This paper verifies the applicability of the ARMA-GARCH model in the analysis of bond yield volatility and provides a quantitative reference for investors, financial institutions, and macro-control departments.

Copyright

© 2026 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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TY  - CONF
AU  - Xiangyi Meng
PY  - 2026
DA  - 2026/10/23
TI  - Analysis of Financial Time Series ARMA-GARCH Model Based on China’s Treasury Bond Yield
BT  - Proceedings of the 2026 2nd International Conference on Financial Innovation and Marketing Management (FIMM 2026)
PB  - Atlantis Press
SP  - 451
EP  - 460
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-801-6_49
DO  - 10.2991/978-94-6239-801-6_49
ID  - Meng2026
ER  -