Exploring Market State and Stock Interactions on the Minute Timescale

A stock market is a non-stationary complex system. The stock interactions are important for understanding the state of the market. However, our knowledge on the stock interactions on the minute timescale is limited. Here we apply the random matrix theory and methods in complex networks to study the stock interactions and sector interactions. Further, we construct a new kind of cross-correlation matrix to investigate the correlation between the stock interactions at different minutes within one trading day. Based on 50 million minute-to-minute price data in the Shanghai stock market, we discover that the market states in the morning and afternoon are significantly different. The differences mainly exist in three aspects, i.e. the co-movement of stock prices, interactions of sectors and correlation between the stock interactions at different minutes. In the afternoon, the component stocks of sectors are more robust and the structure of sectors is firmer. Therefore, the market state in the afternoon is more stable. Furthermore, we reveal that the information of the sector interactions can indicate the financial crisis in the market, and the indicator based on the empirical data in the afternoon is more effective.

股票市场是一类非平稳复杂系统。个股间的交互关系对于理解市场整体状态至关重要。然而，当前学界对于分钟级尺度下的个股交互机制的认知仍较为有限。
为此，本文采用随机矩阵理论（random matrix theory）与复杂网络（complex networks）分析方法，对个股交互与行业板块间交互展开研究。进一步，我们构建了一种新型互相关矩阵（cross-correlation matrix），以探究单个交易日内不同分钟时段下的个股交互之间的关联。
基于上海证券市场总计5000万条逐分钟股价数据，我们发现早盘与午盘的市场状态存在显著差异。此类差异主要体现在三个维度：个股价格联动性、行业板块间交互特征，以及不同分钟时段下个股交互间的相关性。
午盘时段，行业内成分股的稳定性更强，行业整体结构也更为稳固，因此午盘的市场状态更为稳定。
此外，我们还发现行业板块间交互的相关信息能够有效表征市场的金融危机风险，且基于午盘实证数据构建的预警指标表现更为优异。