科技提升金融市场表现:人工智能对新兴市场股价暴跌风险的影响

IF 2.7 4区 管理学 Q2 BUSINESS
Shuangyan Li, Muhammad Waleed Younas, Umer Sahil Maqsood, R. M. A. Zahid
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引用次数: 0

摘要

目的对技术,尤其是人工智能(AI)的认识和采用不断提高,重塑了各行各业和日常生活,促进了积极主动的风险管理方法,并利用先进的分析技术,这可能会影响股价暴跌风险(SPCR)。本研究采用普通最小二乘法(OLS)固定效应回归模型,探讨 2010 年至 2020 年人工智能对中国 A 股上市公司 SPCR 的影响。此外,还使用了一些稳健性分析(2SLS、PSM 和 Sys-GMM)和渠道分析来验证研究结果。此外,渠道分析表明,采用人工智能提高了内部控制质量,有助于降低公司 SPCR。此外,与国有企业相比,在非国有企业中观察到的这种关系更为明显。同样,非外资企业(non-FEs)与外资企业(FEs)相比,这种区别也更为明显。研究结果还支持财务分析师提高透明度、降低 SPCR 的观点。此外,研究结果与不同的统计方法一致,包括 2SLS、PSM 和 Sys-GMM,以有效解决内生性问题。通过信息不对称理论、代理理论以及将人工智能融入金融市场的经济影响的视角,我们的研究为减轻 SPCR 做出了重大贡献。采用数字化战略、提高透明度和优先发展人才是获得巨大收益的关键。本研究建议监管机构和服务提供商在加强金融监管和确保市场稳定的过程中促进人工智能的应用,并强调了技术投资和人才培养的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Tech for stronger financial market performance: the impact of AI on stock price crash risk in emerging market
PurposeThe increasing awareness and adoption of technology, particularly artificial intelligence (AI), reshapes industries and daily life, fostering a proactive approach to risk management and leveraging advanced analytics, which may affect the stock price crash risk (SPCR). The main objective of the current study is to explore how AI adoption influences SPCR.Design/methodology/approachThis study employs an Ordinary Least Squares (OLS) fixed-effect regression model to explore the impact of AI on SPCR in Chinese A-share listed companies from 2010 to 2020. Further, number of robustness analysis (2SLS, PSM and Sys-GMM) and channel analysis are used to validate the findings.FindingsThe primary findings emphasize that AI adoption significantly reduces SPCR likelihood. Further, channel analysis indicates that AI adoption enhances internal control quality, contributing to a reduction in firm SPCR. Additionally, the observed relationship is notably more pronounced in non-state-owned enterprises (non-SOEs) compared to state-owned enterprises (SOEs). Similarly, this distinction is heightened in nonforeign enterprises (non-FEs) as opposed to foreign enterprises (FEs). The study finding also supports the notion that financial analysts enhance transparency, reducing the SPCR. Moreover, the study results consistently align across different statistical methodologies, including 2SLS, PSM and Sys-GMM, employed to effectively address endogeneity concerns.Research limitations/implicationsOur study stands out for its distinctive focus on the financial implications of AI adoption, particularly how it influences firm-level SPCR, an area that has been overlooked in previous research. Through the lens of information asymmetry theory, agency theory, and the economic implications of integrating AI into financial markets, our study makes a substantial contribution in mitigating SPCR.Originality/valueThis study underscores the pivotal role of AI adoption in influencing stock markets for enterprises in China. Embracing digital strategies, fostering transparency and prioritizing talent development are key for reaping substantial benefits. The study recommends regulatory bodies and service providers to promote AI adoption in strengthening financial supervision and ensure market stability, emphasizing the importance of investing in technologies and advancing talent development.
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来源期刊
CiteScore
5.90
自引率
14.80%
发文量
206
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