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Can strict financial regulation improve analysts’ forecast accuracy? Evidence based on a quasi-natural experiment in China

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  • Jiang, Tao
  • Wu, Gang

Abstract

The necessity of strict regulation in financial activities remains a topic of ongoing debate. Using China’s New Regulation on Asset Management (NRAM) as a quasi-natural experiment, we find that strict financial regulation can improve analysts’ forecast accuracy. Mechanism analysis shows that strict financial regulation increases analysts’ forecast accuracy by reducing the risk-taking level and increasing the media attention. We further show that this effect is stronger in firms that are followed by more analysts and those with more complex operations. Our findings support the theory regarding the effectiveness of strict financial supervision from the perspective of capital market information efficiency.

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  • Jiang, Tao & Wu, Gang, 2025. "Can strict financial regulation improve analysts’ forecast accuracy? Evidence based on a quasi-natural experiment in China," Finance Research Letters, Elsevier, vol. 74(C).
    • Handle: RePEc:eee:finlet:v:74:y:2025:i:c:s1544612325000170
    DOI: 10.1016/j.frl.2025.106752
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    1. Xia, Changyuan & Ye, Yingzi & Yu, Haizong, 2025. "RegTech and regulators’ error detection activities: Evidence from China," Finance Research Letters, Elsevier, vol. 78(C).

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    Keywords

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    JEL classification:

    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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