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Volume 39 Issue 2
Apr.  2025
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Article Navigation >  Accounting and Economic Research  > 2025  >  39(2): 51-75
Cai Xiaotong, Lin Peiyang, Wang Rui, Wang Wenhua. 2025. Can Artificial Intelligence Applications Improve the Capital Market Information Environment? An Investigation from the Perspective of Analyst Behaviors. Accounting and Economic Research, 39(2): 51-75.
Citation: Cai Xiaotong, Lin Peiyang, Wang Rui, Wang Wenhua. 2025. Can Artificial Intelligence Applications Improve the Capital Market Information Environment? An Investigation from the Perspective of Analyst Behaviors. Accounting and Economic Research, 39(2): 51-75.
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Can Artificial Intelligence Applications Improve the Capital Market Information Environment? An Investigation from the Perspective of Analyst Behaviors

  • 1.

    School of Accounting, Guangdong University of Finance, Guangzhou Guangdong 510521, China

  • 2.

    School of Finance, Nanjing Agricultural University, Nanjing Jiangsu 210095, China

  • 3.

    School of Accounting, Yunnan University of Finance and Economics, Kunming Yunnan 650221, China

  • Received Date: 2024-05-15
    Available Online: 2025-11-25
  • Publish Date: 2025-04-25
    Abstract
  • The deep integration of artificial intelligence (AI) with real-economy enterprises is profoundly altering the production and transmission of traditional corporate information. As key users and disseminators of information in the capital market, whether analysts are affected by these changes in information production dissemination driven by AI applications has been a crucial issue for understanding the evolution of the capital market information environment. Using a sample of Shanghai and Shenzhen A-share listed companies from 2011 to 2022, this study employs text mining methods to construct micro-level AI application metrics. From the perspective of analyst behaviors, it empirically examines the impact of corporate AI applications on the capital market information environment. The findings indicate that AI applications by listed companies significantly increases both the demand for and supply of analysts in the capital market, attracts more analyst coverage, reduces analyst earnings forecast errors and dispersion, thereby improving the capital market information environment. Further pathway tests reveal that AI applications by listed companies enhances their accounting information quality and attracts more analysts to conduct on-site visits, which in turn increases analyst attention and reduces earnings forecast errors and dispersion. The conclusions of this study not only enrich the research on the economic consequences of micro-level AI applications and the factors influencing analyst behaviors, but also hold significant implications for capital market participants in deeply understanding the integration of AI with real-economy enterprises, thereby promoting the enhancement of resource allocation efficiency in the capital market.

     

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