The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.
Measuring Investors' Opinion Divergence
Open accessAbstract
Numerous proxies for divergence of investors' opinions have been suggested in the empirical accounting and finance literatures. I offer a new proxy constructed from proprietary limit order and market order data. This allows me to capture additional information on investors' private valuations. Proxies from the extant literature, based on publicly available data, do not contain such information. Given my new measure, I ask which of the extant proxies correlates best with it. In my regression analysis, unexplained volume is the best proxy for opinion divergence. Conditioning on various firm‐specific and order‐specific characteristics generally does not change this conclusion. The main exception is the sample of firms without IBES forecast dispersion data, for which bid‐ask spread is the best proxy for opinion divergence. Factor analysis also suggests that unexplained volume is the preferred proxy for opinion divergence.
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The Information Content of Annual Earnings Announcements
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Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies
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Toward an Implied Cost of Capital
Gebhardt, W. R., Lee, C. M. C., & Swaminathan, B. (2001) · Journal of Accounting Research · doi:10.1111/1475-679x.00007 · Cited by 2,000
Is Information Risk a Determinant of Asset Returns?
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Information Uncertainty and Stock Returns
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Dissecting Characteristics Nonparametrically
Freyberger, J., Neuhierl, A., & Weber, M. (2020) · The Review of Financial Studies · doi:10.1093/rfs/hhz123 · Cited by 619
Individual investors and financial disclosure
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Metadata
- Authors
- GARFINKEL, J. A.
- Venue
- Journal of Accounting Research
- Publisher
- Wiley
- Published
- 2009-10-12
- Volume
- 47
- Issue
- 5
- Pages
- 1317-1348
- ISSN
- 0021-8456 (ISSN-L)
- 1475-679X
- OpenAlex
- W3125120201
- Cited by
- 257
- References
- 63
- FWCI
- 11.20
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.