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.
Citation: Xiao Ren, Jie Hua, Xin Chi, Yao Tan. Visual analysis of social events and stock market volatility in China and the USA during the pandemic[J]. Mathematical Biosciences and Engineering, 2023, 20(1): 1229-1250. doi: 10.3934/mbe.2023056
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.
| [1] |
L. Yang, S. Liu, J. Liu, Z. Zhang, X. Wan, B. Huang, et al., COVID-19: immunopathogenesis and immunotherapeutics, Signal Trans. Targeted Ther., 5 (2020), 1–8. https://doi.org/10.1038/s41392-020-00243-2 doi: 10.1038/s41392-020-00243-2
|
| [2] |
K. Yuki, M. Fujiogi, S. Koutsogiannaki, COVID-19 pathophysiology: A review, Clin. Immunol., 215 (2020), 108427. https://doi.org/10.1016/j.clim.2020.108427 doi: 10.1016/j.clim.2020.108427
|
| [3] |
F. Saldaña, H. Flores-Arguedas, J. A. Camacho-Gutiérrez, I. Barradas, Modeling the transmission dynamics and the impact of the control interventions for the COVID-19 epidemic outbreak, Math. Biosci. Eng., 17 (2020), 4165–4183. https://doi.org/10.3934/mbe.2020231 doi: 10.3934/mbe.2020231
|
| [4] |
A. S. Fauci, H. C. Lane, R. R. Redfield, Covid-19-navigating the uncharted, N. Engl. J. Med., 382 (2020), 1268–1269. https://doi.org/10.1056/NEJMe2002387 doi: 10.1056/NEJMe2002387
|
| [5] |
S. Pokhrel, R. Chhetri, A literature review on impact of COVID-19 pandemic on teaching and learning, Higher Edu. Future, 8 (2021), 133–141. https://doi.org/10.1177/2347631120983481 doi: 10.1177/2347631120983481
|
| [6] |
R. Siche, What is the impact of COVID-19 disease on agriculture?, Sci. Agropecu., 11 (2020), 3–6. http://dx.doi.org/10.17268/sci.agropecu.2020.01.00 doi: 10.17268/sci.agropecu.2020.01.00
|
| [7] |
A. Kumar, V. Jain, A. Deovanshi, A. Lepcha, C. Das, K. Bauddh, S. Srivastava, Environmental impact of COVID-19 pandemic: more negatives than positives, Environ. Sustainability, 4 (2021), 447–454. https://doi.org/10.1007/s42398-021-00159-9 doi: 10.1007/s42398-021-00159-9
|
| [8] |
L. Sher, The impact of the COVID-19 pandemic on suicide rates, QJM Int. J. Med., 113 (2020), 707–712. https://doi.org/10.1093/qjmed/hcaa202 doi: 10.1093/qjmed/hcaa202
|
| [9] |
J. Xiong, O. Lipsitz, F. Nasri, L. M. Lui, H. Gill, L. Phan, et al., Impact of COVID-19 pandemic on mental health in the general population: A systematic review, J. Affect. Disord., 277 (2020), 55–64. https://doi.org/10.1016/j.jad.2020.08.001 doi: 10.1016/j.jad.2020.08.001
|
| [10] |
W. Hong, X. Lu, L. Wu, X. Pu, Analysis of factors influencing public attention to masks during the COVID-19 epidemic-Data from Sina Weibo, Math. Biosci. Eng., 19 (2022), 6469–6488. https://doi.org/10.3934/mbe.2022304 doi: 10.3934/mbe.2022304
|
| [11] | P. K. Ozili, T. Arun, Spillover of COVID-19: Impact on the global economy, in Managing Inflation and Supply Chain Disruptions in the Global Economy, IGI Global, (2020). https://doi.org/10.4018/978-1-6684-5876-1.ch004 |
| [12] | B. Bagchi, S. Chatterjee, R. Ghosh, D. Dandapat, Impact of COVID-19 on global economy, in Coronavirus Outbreak and the Great Lockdown, Springer, (2020), 15–26. https://doi.org/10.1007/978-981-15-7782-6_3 |
| [13] |
W. Thorbecke, The impact of the COVID-19 pandemic on the USA Economy: evidence from the stock market, J. Risk Financ. Manage., 13 (2020), 233. https://doi.org/10.3390/jrfm13100233 doi: 10.3390/jrfm13100233
|
| [14] |
L. Tan, X. Wu, J. Guo, E. D. Santibane-Gonzalez, Assessing the impacts of COVID-19 on the industrial sectors and economy of China, Risk Anal., 42 (2022), 21–39. https://doi.org/10.1111/risa.13805 doi: 10.1111/risa.13805
|
| [15] |
P. A. Vitenu-Sackey, R. Barfi, The impact of COVID-19 pandemic on the Global economy: emphasis on poverty alleviation and economic growth, Econ. Finance Lett., 8 (2021), 32–43. https://doi.org/10.18488/journal.29.2021.81.32.43 doi: 10.18488/journal.29.2021.81.32.43
|
| [16] | R. Vaishya, M. Javaid, I. H. Khan, A. Haleem. Artificial Intelligence (AI) applications for COVID-19 pandemic, Diabetes Metab. Syndr. Clin. Res. Rev., 14 (2020), 337–339. |
| [17] |
W. Dong, C. Zhao, Stock price forecasting based on Hausdorff fractional grey model with convolution and neural network, Math. Biosci. Eng., 18 (2021), 3323–3347. https://doi.org/10.3934/mbe.2021166 doi: 10.3934/mbe.2021166
|
| [18] |
N. L. Bragazzi, H. Dai, G. Damiani, M. Behzadifar, M. Martini, J. Wu, How big data and artificial intelligence can help better manage the COVID-19 pandemic, Int. J. Environ. Res. Public Health, 17 (2020), 3176. https://doi.org/10.3390/ijerph17093176 doi: 10.3390/ijerph17093176
|
| [19] | V. Tkachuk, Y. Yechkalo, S. Semerikov, M. Kislova, Y. Hladyr, Using mobile ict for online learning during covid-19 lockdown, in International Conference on Information and Communication Technologies in Education, Research, and Industrial Applications, (2020), 46–67. https://doi.org/10.1007/978-3-030-77592-6_3 |
| [20] |
M. Allam, S. Cai, S. Ganesh, M. Venkatesan, S. Doodhwala, Z. Song, et al., COVID-19 diagnostics, tools, and prevention, Diagnostics, 10 (2020), 409. https://doi.org/10.3390/diagnostics10060409 doi: 10.3390/diagnostics10060409
|
| [21] |
J. L. Comba, Data visualisation for the understanding of COVID-19, Comput. Sci. Eng., 22 (2020), 81–86. https://doi.org/10.1109/MCSE.2020.3019834 doi: 10.1109/MCSE.2020.3019834
|
| [22] | C. K. Leung, T. N. Kaufmann, Y. Wen, C. Zhao, H. Zheng, Revealing COVID-19 data by data mining and visualization, in International Conference on Intelligent Networking and Collaborative Systems, (2021), 70–83. https://doi.org/10.1007/978-3-030-84910-8_8 |
| [23] |
A. H. M.Hassan, A. A. M.Qasem, W. F. M. Abdalla, O. H. Elhassan, Visualisation & prediction of COVID-19 future outbreak by using machine learning, Int. J. Inf. Technol. Comput. Sci., 13 (2021), 16–32. https://doi.org/10.5815/ijitcs.2021.03.02 doi: 10.5815/ijitcs.2021.03.02
|
| [24] | A. N. Roy, J. Jose, A. Sunil, N. Gautam, D. Nathalia, A. Suresh, Prediction and spread visualisation of COVID-19 pandemic using machine learning, 2020 (2020), https://doi.org/10.20944/preprints202005.0147.v1 |
| [25] |
Z. Deng, J. Chen, T. Wang, Bibliometric and visualisation analysis of human coronaviruses: prospects and implications for COVID-19 research, Front. Cell. Infect. Microbiol., 529 (2020). https://doi.org/10.3389/fcimb.2020.581404 doi: 10.3389/fcimb.2020.581404
|
| [26] |
M. M. Hossain, Current status of global research on novel coronavirus disease (Covid-19): A bibliometric analysis and knowledge mapping, F1000 Res., 9 (2020), 374. https://doi.org/10.12688/f1000research.23690.1 doi: 10.12688/f1000research.23690.1
|
| [27] |
M. Mazur, M. Dang, M. Vega, COVID-19 and the march 2020 stock market crash. Evidence from S & P1500, Finance Res. Lett., 38 (2021), 101690. https://doi.org/10.1016/j.frl.2020.101690 doi: 10.1016/j.frl.2020.101690
|
| [28] |
F. Zeren, A. Hizarci, The impact of COVID-19 coronavirus on stock markets: evidence from selected countries, Muhasebe Finans İncelemeleri Dergisi, 3 (2020), 78–84. https://doi.org/10.32951/mufider.706159 doi: 10.32951/mufider.706159
|
| [29] | H. Liu, A. Manzoor, C. Wang, L. Zhang, Z. Manzoor, The COVID-19 outbreak and affected countries stock markets response, Int. J. Environ. Res. Public Health, 17 (2020), 2800. https://www.mdpi.com/1660-4601/17/8/2800 |
| [30] |
M. Topcu, O. S. Gulal, The impact of COVID-19 on emerging stock markets, Finance Res. Lett., 36 (2020), 101691. https://doi.org/10.1016/j.frl.2020.101691 doi: 10.1016/j.frl.2020.101691
|
| [31] |
P. K. Narayan, N. Devpura, H. Wang, Japanese currency and stock market-What happened during the COVID-19 pandemic?, Econ. Anal. Policy, 68 (2020), 191–198. https://doi.org/10.1016/j.eap.2020.09.014 doi: 10.1016/j.eap.2020.09.014
|
| [32] | The Beijing News. Available from: https://www.bjnews.com.cn/. |
| [33] | CCTV NEWS. Available from: https://news.cctv.com/. |
| [34] | Xinhuanet. Available from: http://m.news.cn/. |
| [35] | Investing. Available from: https://cn.investing.com/. |
| [36] |
A. W. Lo, What is an index?, J. Portfolio Manag., 4 (2016), 21–36. https://doi.org/10.3905/jpm.2016.42.2.021 doi: 10.3905/jpm.2016.42.2.021
|
| [37] | J. Heinrich, D. Weiskopf, State of the art of paralle coordinates, in Eurographics (State of the Art Reports); The Eurographics Association: Geneva, Switzerland, (2013), 95–116. |
| [38] |
T. Blascheck, K. Kurzhals, M. Raschke, M. Burch, D. Weiskopf, T. Ertl, Visualization of eye tracking data: A taxonomy and survey, Comput. Graph. Forum, 36 (2017), 260–284. https://doi.org/10.1111/cgf.13079 doi: 10.1111/cgf.13079
|
| [39] |
T. Blascheck, L. M. Vermeulen, J. Vermeulen, C. Perin, W. Willett, T. Ertl, et al., Exploration strategies for discover ofinteractivity in visualisations, IEEE Trans. Vis. Comput. Graph., 25 (2018), 1407–1420. https://doi.org/10.1109/TVCG.2018.2802520 doi: 10.1109/TVCG.2018.2802520
|
| [40] |
S. Latif, F. Beck, VIS author profiles: Interactive descriptions of publication records combining text and visualization, IEEE Trans. Vis. Comput. Graph., 25 (2018), 152–161. https://doi.org/10.1109/TVCG.2018.2865022 doi: 10.1109/TVCG.2018.2865022
|
| [41] | N. Akhtar, N. Tabassum, A. Perwej, Y. Perwej, Data analytics and visualisation using Tableau utilitarian for COVID-19-(Coronavirus), Glob. J. Eng. Technol. Adv., 3 (2020), 28–50. https://dx.doi.org/10.30574/gjeta.2020.3.2.0029 |
| [42] |
S. Batt, T. Grealis, O. Harmon, P. Tomolonis, Learning tableau: A data visualisation tool, J. Econ. Edu., 51 (2020), 317–328. https://doi.org/10.1080/00220485.2020.1804503 doi: 10.1080/00220485.2020.1804503
|
| [43] |
A. A. Porsse, K. B. de Souza, T. S. Carvalho, V. A. Vale, The economic impacts of COVID‐19 in Brazil based on an interregional CGE approach, Reg. Sci. Policy Prac., 12 (2020), 1105–1121. https://doi.org/10.1111/rsp3.12354 doi: 10.1111/rsp3.12354
|
| [44] | C. C. Ngwakwe, Effect of COVID-19 pandemic on global stock market values: A differential analysis, Acta Univ. Danubius, 16 (2020). |
| [45] |
D. Bora, D. Basistha, The outbreak of COVID-19 pandemic and its impact on stock market volatility: Evidence from a worst-affected economy, J. Public Affairs, 21 (2021), e2623. https://doi.org/10.1002/pa.2623 doi: 10.1002/pa.2623
|
| [46] |
M. Hasan, M. Mahi, T. Sarker, M. Amin, Spillovers of the COVID-19 pandemic: Impact on global economic activity, the stock market, and the energy sector, J. Risk Financ. Manage., 14 (2021), 200. https://doi.org/10.3390/jrfm14050200 doi: 10.3390/jrfm14050200
|
| [47] |
C. Zehri, Stock market comovements: Evidence from the COVID-19 pandemic, J. Econ. Asymmetries, 24 (2021), e00228. https://doi.org/10.1016/j.jeca.2021.e00228 doi: 10.1016/j.jeca.2021.e00228
|
| [48] | NetEase News, On the eve of Wuhan lockdown, 29.9 million people left, and it was difficult to find a bed for severe patients. Available from: https: //www.163.com/dy/article/F3K4AE3F0525W7OM.html. |
| [49] | Sina Finance, Shuanghuanglian should be snapped up or not? Can Chinese traditional medicine such as capsule of Hua Qing Wen fight new coronavirus pneumonia? The experts have spoken, 2020. Availavel from: https://baijiahao.baidu.com/s?id=1657292587311187004&wfr=spider&for=pc. |
| [50] | N. Fernandes, Economic effects of coronavirus outbreak (COVID-19) on the world economy, IESE Business School Working Paper, 2020 (2020). https://dx.doi.org/10.2139/ssrn.3557504 |
| [51] |
S. Corbet, Y. G. Hou, Y. Hu, L. Oxley, D. Xu, Pandemic-related financial market volatility spillovers: Evidence from the Chinese COVID-19 epicentre, Int. Rev. Econ. Finance, 71 (2021), 55–81. https://doi.org/10.1016/j.iref.2020.06.022 doi: 10.1016/j.iref.2020.06.022
|
| [52] |
J. Sheng, J. Amankwah-Amoah, Z. Khan, X. Wang, COVID-19 pandemic in the new era of big data analytics: Methodological innovations and future research directions, Br. J. Manage., 32 (2021), 1164–1183. https://doi.org/10.1111/1467-8551.12441 doi: 10.1111/1467-8551.12441
|
Figures(8) / Tables(6)
Xiao Ren, Jie Hua, Xin Chi, Yao Tan. Visual analysis of social events and stock market volatility in China and the USA during the pandemic[J]. Mathematical Biosciences and Engineering, 2023, 20(1): 1229-1250. doi: 10.3934/mbe.2023056
DownLoad: