Ren Xiao, Hua Jie, Chi Xin, Tan Yao
Faculty of Information Engineering, Shaoyang University, Shaoyang 422000, China.
School of Information, Southwest Petroleum University, Nanchong 637001, China.
Math Biosci Eng. 2023 Jan;20(1):1229-1250. doi: 10.3934/mbe.2023056. Epub 2022 Oct 26.
The COVID-19 pandemic is one of the most severe infectious diseases in recent decades, and has had a significant impact on the global economy, and the stock market. Most existing studies on stock market volatility during the pandemic have been conducted from a data science perspective, with statistical analysis and mathematical models often revealing the superficial relationship between Covid and the stock market at the data level. In contrast, few studies have explored the relationship between more specialised aspects of the pandemic. Specifically, the relationship found between major social events and the stock market. In this work, a multi-source, data-based relationship analysis method is proposed, that collects historical data on significant social events and related stock data in China and the USA, to further explore the potential correlation between stock market index fluctuations and the impact of social events by analysing cross-timeline data. The results suggest and offer more evidence that social events do indeed impact equity markets, and that the indices in both China and the USA were also affected more by the epidemic in 2020 than in 2021, and these indices became less affected by the epidemic as it became the world adapted. Moreover, these relationships may also be influenced by a variety of other factors not covered in this study. This research, so far, is in its initial stage, and the methodology is not rigorous and cannot be applied as an individual tool for decision; however, it could potentially serve as a supplementary tool and provide a multi-dimensional basis for stock investors and policymakers to make decisions.
新冠疫情是近几十年来最严重的传染病之一，对全球经济和股票市场产生了重大影响。大多数关于疫情期间股市波动的现有研究都是从数据科学的角度进行的，统计分析和数学模型往往揭示了新冠疫情与股市在数据层面的表面关系。相比之下，很少有研究探讨疫情更具体方面之间的关系。具体而言，重大社会事件与股市之间的关系。在这项工作中，提出了一种基于多源数据的关系分析方法，该方法收集了中国和美国重大社会事件的历史数据以及相关股票数据，通过分析跨时间线数据来进一步探索股市指数波动与社会事件影响之间的潜在相关性。结果表明并提供了更多证据，证明社会事件确实会影响股票市场，而且中国和美国的指数在2020年比2021年受疫情影响更大，随着世界适应疫情，这些指数受疫情的影响变小。此外，这些关系可能还受到本研究未涵盖的多种其他因素的影响。到目前为止，这项研究尚处于初始阶段，方法并不严谨，不能作为独立的决策工具应用；然而，它有可能作为一种辅助工具，为股票投资者和政策制定者提供多维度的决策依据。
