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控制人的违法行为对股票价格回报的影响:来自 Elman 神经网络模型的证据。

The effect of controlling person's illegalities on stock price returns: Evidence from Elman neural network model.

机构信息

School of Economics and Management, University of Science and Technology Beijing, Beijing, People's Republic of China.

CITIC Group Corporation, Beijing, People's Republic of China.

出版信息

PLoS One. 2022 Apr 20;17(4):e0266741. doi: 10.1371/journal.pone.0266741. eCollection 2022.

DOI:10.1371/journal.pone.0266741
PMID:35443002
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9020737/
Abstract

Controlling persons are the ultimate decision-makers of listed companies. Their illegalities have impacts on investors' wealth, firm development, and capital market's quality. Against this backdrop, we provide a quantitative analysis of the short-term stock price reaction to the criminal detention announcements of controlling persons throughout 2007-2019. We applied the Elman neural network (ENN) model into the classical event study methodology and demonstrated that the combination of them helps to improve the estimation accuracy of the stock price reaction. The results show that the stock price has a significant negative reaction to the criminal detention announcements of listed companies' controlling persons on the announcement day, and the average reaction level is -6.67%. Additionally, the crisis communication measures of the firms could diminish the negative impact of such mandatory disclosure information on their stock price, but the effect is limited. Finally, the 31 companies in our sample cause a total loss of RMB 21.1 billion in market capitalization on the announcement day alone. The above results indicate that the impact of listed companies' controlling persons on the capital market is tremendous, although the number of this group is small. Our work enriches the listed companies' illegalities research and provides a reference for investors' investment choices and follow-up decision making of regulatory authorities. It also provides some guidance for most of the researchers to further explore the application of data mining techniques in nonlinear problems.

摘要

控制人是上市公司的最终决策者。他们的违法行为会对投资者的财富、公司的发展和资本市场的质量产生影响。在此背景下,我们对 2007 年至 2019 年期间控制人被拘留公告对股票短期价格的反应进行了定量分析。我们将 Elman 神经网络(ENN)模型应用于经典事件研究方法,并证明了它们的结合有助于提高股票价格反应的估计准确性。结果表明,股票价格对上市公司控制人被拘留公告有显著的负面反应,平均反应水平为-6.67%。此外,公司的危机沟通措施可以减轻此类强制性信息披露对其股价的负面影响,但效果有限。最后,我们样本中的 31 家公司仅在公告日就导致市值损失 211 亿元人民币。上述结果表明,尽管该群体数量较少,但上市公司控制人对资本市场的影响是巨大的。我们的工作丰富了上市公司违法行为的研究,并为投资者的投资选择和监管机构的后续决策提供了参考。它还为大多数研究人员进一步探索数据挖掘技术在非线性问题中的应用提供了一些指导。

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Forecasting stock prices with long-short term memory neural network based on attention mechanism.
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