标题： 股票社区的动态结构：股票收益与换手率的比较研究 显示英文标题

标题： Dynamic structure of stock communities: A comparative study between stock returns and turnover rates

摘要： 股票市场中社区结构的检测对于金融动态研究和投资组合风险估计具有理论和实际意义。 我们在这里从价格收益和换手率两个方面研究中国股票市场的社区结构，采用基于距离矩阵的PMFG和infomap方法的组合。 我们发现，最大的几个社区由某些特定的行业或概念性部门组成，同一部门内的相关性通常大于不同部门之间的相关性。 与收益相比，换手率的社区结构更为复杂，部门效应相对较弱。 通过分析五个子时期的社区结构，进一步研究了金融动态。 在不同的子时期，银行、房地产、医疗保健和新上海等板块轮流构成收益和换手率的最大几个社区。 即使在同一个子时期，一些特定的部门在两个时间序列的社区中以不同的排名顺序出现。 对这些部门股票价格和换手率的演变进行比较，以更好地理解它们的差异。 我们发现，股票价格仅在一些重要事件周围出现大幅波动，而换手率在每个与特定部门相关的事件后都出现激增，这可能为换手率的股票社区的复杂性提供了一个可能的解释。 显示英文摘要

摘要： The detection of community structure in stock market is of theoretical and practical significance for the study of financial dynamics and portfolio risk estimation. We here study the community structures in Chinese stock markets from the aspects of both price returns and turnover rates, by using a combination of the PMFG and infomap methods based on a distance matrix. We find that a few of the largest communities are composed of certain specific industry or conceptional sectors and the correlation inside a sector is generally larger than the correlation between different sectors. In comparison with returns, the community structure for turnover rates is more complex and the sector effect is relatively weaker. The financial dynamics is further studied by analyzing the community structures over five sub-periods. Sectors like banks, real estate, health care and New Shanghai take turns to compose a few of the largest communities for both returns and turnover rates in different sub-periods. Several specific sectors appear in the communities with different rank orders for the two time series even in the same sub-period. A comparison between the evolution of prices and turnover rates of stocks from these sectors is conducted to better understand their differences. We find that stock prices only had large changes around some important events while turnover rates surged after each of these events relevant to specific sectors, which may offer a possible explanation for the complexity of stock communities for turnover rates.