重大公共事件下中国股票动态相关性的拓扑数据分析

IF 1.9 3区 物理与天体物理 Q2 PHYSICS, MULTIDISCIPLINARY
Hongfeng Guo, Ziwei Ming, Bing Xing
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引用次数: 0

摘要

拓扑数据分析已被公认为是许多领域中最成功的数学数据分析方法之一。此外,它也逐渐应用于金融时间序列分析中,并被证明在探索此类数据的拓扑特征方面是有效的。我们从中国市场中选取100只股票,构建点云数据进行拓扑数据分析。我们从持久性景观的lp规范中检测关键日期。我们的研究结果表明,这些日期与样本时期一些重大事件的过渡时间高度一致。我们通过复杂的网络来比较事件之前和事件期间股票的相关性和统计特性,以描述市场情况。在重大事件期间,股票之间的联系强度和变化明显不同。我们还从拓扑的角度研究了种群的邻域特征。这有助于确定重要的股票,并探索他们在每个事件下的情况。最后,基于邻域特征对种群进行聚类,显示出不同事件对种群的异质性影响。我们的工作表明,拓扑数据分析在股票动态相关性中具有很强的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Topological data analysis of Chinese stocks’ dynamic correlations under major public events
Topological data analysis has been acknowledged as one of the most successful mathematical data analytic methodologies in many fields. Additionally, it has also been gradually applied in financial time series analysis and proved effective in exploring the topological features of such data. We select 100 stocks from China’s markets and construct point cloud data for topological data analysis. We detect critical dates from the Lp-norms of the persistence landscapes. Our results reveal the dates are highly consistent with the transition time of some major events in the sample period. We compare the correlations and statistical properties of stocks before and during the events via complex networks to describe the markets’ situation. The strength and variation of links among stocks are clearly different during the major events. We also investigate the neighborhood features of stocks from topological perspectives. This helps identify the important stocks and explore their situations under each event. Finally, we cluster the stocks based on the neighborhood features, which exhibit the heterogeneity impact on stocks of the different events. Our work demonstrates that topological data analysis has strong applicability in the dynamic correlations of stocks.
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来源期刊
Frontiers in Physics
Frontiers in Physics Mathematics-Mathematical Physics
CiteScore
4.50
自引率
6.50%
发文量
1215
审稿时长
12 weeks
期刊介绍: Frontiers in Physics publishes rigorously peer-reviewed research across the entire field, from experimental, to computational and theoretical physics. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, engineers and the public worldwide.
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