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Tech for stronger financial market performance: the impact of AI on stock price crash risk in emerging market

Shuangyan Li (School of Economics and Finance, Xi’an Jiaotong University, Xi’an, China)
Muhammad Waleed Younas (School of Economics and Finance, Xi’an Jiaotong University, Xi’an, China)
Umer Sahil Maqsood (School of Economics and Finance, Xi’an Jiaotong University, Xi’an, China)
R. M. Ammar Zahid (The Business School, RMIT University, Ho Chi Minh City, Vietnam)

International Journal of Emerging Markets

ISSN: 1746-8809

Article publication date: 3 June 2024

113

Abstract

Purpose

The 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/approach

This 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.

Findings

The 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/implications

Our 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/value

This 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.

Keywords

Acknowledgements

Funding: This study is a part of Ph.D. dissertation of corresponding author at Xi’an Jiaotong University, School of Economics and Finance. This research is supported by the Social Science Fund of Shaanxi Major Project (Grant No. 2023ZD10).

Citation

Li, S., Younas, M.W., Maqsood, U.S. and Zahid, R.M.A. (2024), "Tech for stronger financial market performance: the impact of AI on stock price crash risk in emerging market", International Journal of Emerging Markets, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOEM-10-2023-1717

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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