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Impacts of Investor Attention and Accounting Information Comparability on Stock Returns: Empirical Evidence from Chinese Listed Companies

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  • Li Zhao

    (International College of Digital Innovation, Chiang Mai University, Chiang Mai 50200, Thailand
    School of Business, Chengdu University, Chengdu 610106, China)

  • Nathee Naktnasukanjn

    (International College of Digital Innovation, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Ahmad Yahya Dawod

    (International College of Digital Innovation, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Bin Zhang

    (School of Business, Chengdu University, Chengdu 610106, China)

Abstract

The efficient capital markets hypothesis (EMH) posits that security prices incorporate all available information in capital markets. Nevertheless, real stock markets often exhibit speculative behavior due to information asymmetry and the limited rationality of investors. This paper employs statistical analysis, a multiple regression approach, and robustness tests to investigate the impact of investor attention and accounting information comparability on stock returns. We collected monthly data from all Chinese A-share stocks listed on the main board of the Shanghai Stock Exchange for the period 2017–2021. Our findings reveal a significant positive correlation between current investor attention and current monthly stock returns and a significant negative correlation between lagged investor attention and current monthly stock returns. Moreover, accounting information comparability serves as a substantial moderator, amplifying the positive effect of current investor attention on current stock returns and mitigating the negative impact of lagged investor attention. We investigate the indicator of accounting information comparability from the perspective of investor attention. Significantly, we use accounting information comparability as a moderating variable for the first time to assess its influence on stock returns. Our results demonstrate that accounting information comparability significantly contributes to mitigating excessive share price declines and stimulating share price increases. This discovery also acts as an internal driver for listed companies to proactively improve accounting information comparability.

Suggested Citation

  • Li Zhao & Nathee Naktnasukanjn & Ahmad Yahya Dawod & Bin Zhang, 2024. "Impacts of Investor Attention and Accounting Information Comparability on Stock Returns: Empirical Evidence from Chinese Listed Companies," IJFS, MDPI, vol. 12(1), pages 1-25, February.
    • Handle: RePEc:gam:jijfss:v:12:y:2024:i:1:p:18-:d:1338750
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    References listed on IDEAS

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    1. Nian Li & Chunling Li & Runsen Yuan & Muhammad Asif Khan & Xiaoran Sun & Nosherwan Khaliq, 2021. "Investor Attention and Corporate Innovation Performance: Evidence from Web Search Volume Index of Chinese Listed Companies," Mathematics, MDPI, vol. 9(9), pages 1-23, April.
    2. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    3. G. Andrew Karolyi & Dawoon Kim & Rose Liao, 2020. "The Theory and Practice of Investor Relations: A Global Perspective," Management Science, INFORMS, vol. 66(10), pages 4746-4771, October.
    4. Xu, Yongxin & Xuan, Yuhao & Zheng, Gaoping, 2021. "Internet searching and stock price crash risk: Evidence from a quasi-natural experiment," Journal of Financial Economics, Elsevier, vol. 141(1), pages 255-275.
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