文献类型：期刊文献

英文题名：Market state transitions and crash early warning in the Chinese stock market

作者：Pang, Wu-Yue[1,2];Lin, Li[1,3]

机构：[1]East China Univ Sci & Technol, Business Sch, Dept Finance, Shanghai, Peoples R China;[2]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai, Peoples R China;[3]Swiss Fed Inst Technol, Risk Ctr, Zurich, Switzerland

年份：2025

卷号：13

外文期刊名：FRONTIERS IN PHYSICS

收录：;EI(收录号：20253419028650);WOS:【SCI-EXPANDED(收录号:WOS:001554013000001)】；

基金：The author(s) declare that financial support was received for the research and/or publication of this article. We acknowledge financial support from the National Natural Science Foundations of China (Grant No. 71771086).

语种：英文

外文关键词：market state transition; systemic risk; early warning; correlation structure; stock market

摘要：Understanding systemic risk in financial markets requires tools that capture both structural complexity and dynamic evolution. This study adopts a complex systems perspective to analyze the Chinese stock market through correlation-based state classification. Using multidimensional scaling and K-means clustering on rolling stock return correlations, we identify five distinct market states that reflect varying degrees of systemic co-movement and exhibit strong temporal persistence and local transition patterns. We find that transitions among these states encode meaningful information about market structural shifts and are closely linked to the emergence of crash conditions. Building on this insight, we construct an early warning model using decision trees trained on temporal features derived from market state transitions-including medium-term state distributions, directional change ratios, and short-term evolutionary paths. The model achieves high recall and precision across configurations, and supports real-time adaptability via projection-based state labeling. These results highlight the value of market state dynamics and their transitions as a basis for systemic risk monitoring and crash anticipation in complex financial systems.