The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index.
Retail investor attention and stock price crash risk: Evidence from China
Abstract
Abstract This paper investigates the effect of retail investor attention on stock price crash risk in China. Retail investor attention is measured by the search frequency from the Baidu Index. Using a large sample of Chinese listed firms from 2007 to 2017, the evidence shows that firms with higher retail investor attention tend to have a lower future stock price crash risk. The results are robust to alternative measures of retail investor attention and crash risk. Moreover, higher quality auditing can mitigate the impact of retail investor attention on firms' future crash risk. We further find that this relationship is less prominent for state-owned enterprises. Those findings not only enrich the extant literature on the determinants of stock price crash risk and the economic consequence of the retail investor attention, but also give some suggestions for investors in the emerging market.
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Theory of the firm: Managerial behavior, agency costs and ownership structure
Jensen, M. C., & Meckling, W. H. (1976) · Journal of Financial Economics · doi:10.1016/0304-405x(76)90026-x · Cited by 71,491
Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches
Petersen, M. A. (2009) · Review of Financial Studies · doi:10.1093/rfs/hhn053 · Cited by 10,746
Illiquidity and stock returns: cross-section and time-series effects
Amihud, Y. (2002) · Journal of Financial Markets · doi:10.1016/s1386-4181(01)00024-6 · Cited by 9,963
Egeth, H., & Kahneman, D. (1975) · The American Journal of Psychology · doi:10.2307/1421603 · Cited by 6,972
The economic implications of corporate financial reporting
Graham, J. R., Harvey, C. R., & Rajgopal, S. (2005) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2005.01.002 · Cited by 6,316
Noise Trader Risk in Financial Markets
De Long, J. B., Shleifer, A., Summers, L. H., & Waldmann, R. J. (1990) · Journal of Political Economy · doi:10.1086/261703 · Cited by 6,234
A Simple Model of Capital Market Equilibrium with Incomplete Information
MERTON, R. C. (1987) · The Journal of Finance · doi:10.1111/j.1540-6261.1987.tb04565.x · Cited by 5,811
Barber, B. M., & Odean, T. (2008) · Review of Financial Studies · doi:10.1093/rfs/hhm079 · Cited by 4,556
DA, Z., ENGELBERG, J., & GAO, P. (2011) · The Journal of Finance · doi:10.1111/j.1540-6261.2011.01679.x · Cited by 3,067
R2 around the world: New theory and new tests☆
JIN, L., & MYERS, S. (2006) · Journal of Financial Economics · doi:10.1016/j.jfineco.2004.11.003 · Cited by 2,816
Cited by
Effective strategies in short video advertising: leveraging influencer endorsements and discounts
Yuan, L., Shi, Y., Xia, H., & Ye, Q. (2025) · Industrial Management & Data Systems · doi:10.1108/imds-06-2024-0551 · Cited by 8
Metadata
- Authors
- Wen, F., Xu, L., Ouyang, G., & Kou, G.
- Venue
- International Review of Financial Analysis
- Publisher
- Elsevier BV
- Published
- 2019-10
- Volume
- 65
- Pages
- 101376
- ISSN
- 1057-5219 (ISSN-L)
- OpenAlex
- W2965813439
- Cited by
- 403
- References
- 57
- FWCI
- 51.82
- Type
- journal article
- Language
- en
- Open access
- closed
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