Digital finance and stock price crash: Evidence from China
Ping Zhang and
Yiru Wang
Emerging Markets Review, 2025, vol. 66, issue C
Abstract:
In this paper, we study the impact of digital finance on stock price crash risk based on 293 Chinese city-level digital finance indexes and all A-share listed companies from 2011 to 2022. We find that digital finance can decrease stock price crash risk by the Generalized Method of Moments (GMM) dynamic panel regression model. The promotion of digital transformation, the increase of information transparency, and the decrease of financial risks are three plausible channels that allow digital finance to reduce stock price crash risk. These mechanisms shed light on the pathways through which digital finance can enhance market stability. Furthermore, our investigation reveals that the reducing effect is more pronounced in higher competitive industries and new technology firms. The conclusion enriches and expands the research on digital finance and corporate stock price crash risk, providing a theoretical basis for improving and stabilizing the Chinese capital market and promoting the development strategy of digital finance.
Keywords: Digital finance; Stock price crash risk; Digital transformation; Information transparency; Financial risk (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1566014125000366
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:ememar:v:66:y:2025:i:c:s1566014125000366
DOI: 10.1016/j.ememar.2025.101287
Access Statistics for this article
Emerging Markets Review is currently edited by Jonathan A. Batten
More articles in Emerging Markets Review from Elsevier
Bibliographic data for series maintained by Catherine Liu ().