The DOI matches its Crossref record.
Underwriting relationships, analysts' earnings forecasts and investment recommendations
Open accessAbstract
We examine the effect of underwriting relationships on analysts' earnings forecasts and recommendations. Lead and co-underwriter analysts' growth forecasts and recommendations are significantly more favorable than those made by unaffiliated analysts, although their earnings forecasts are not generally greater. Investors respond similarly to lead underwriter and unaffiliated `Strong buy' and `Buy' recommendations, but three-day returns to lead underwriter `Hold' recommendations are significantly more negative than those to unaffiliated `Hold' recommendations. The findings suggest investors expect lead analysts are more likely to recommend `Hold' when `Sell' is warranted. The post-announcement returns following affiliated and unaffiliated analysts' recommendations are not significantly different.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Healy, P. M., & Palepu, K. G. (2001) · Journal of Accounting and Economics · doi:10.1016/s0165-4101(01)00018-0 · Cited by 8,097
Kothari, S. P., Li, X., & Short, J. E. (2009) · The Accounting Review · doi:10.2308/accr.2009.84.5.1639 · Cited by 1,019
Voluntary Disclosure and Equity Offerings: Reducing Information Asymmetry or Hyping the Stock?*
LANG, M. H., & LUNDHOLM, R. J. (2000) · Contemporary Accounting Research · doi:10.1506/9n45-f0jx-axvw-lbwj · Cited by 894
Do analysts matter for governance? Evidence from natural experiments
Chen, T., Harford, J., & Lin, C. (2015) · Journal of Financial Economics · doi:10.1016/j.jfineco.2014.10.002 · Cited by 747
Testing Asymmetric-Information Asset Pricing Models
Kelly, B., & Ljungqvist, A. (2012) · Review of Financial Studies · doi:10.1093/rfs/hhr134 · Cited by 580
Metadata
- Authors
- Lin, H.-W., & McNichols, M. F.
- Venue
- Journal of Accounting and Economics
- Publisher
- Elsevier BV
- Published
- 1998-02
- Volume
- 25
- Issue
- 1
- Pages
- 101-127
- ISSN
- 0165-4101 (ISSN-L)
- OpenAlex
- W2160841369
- Cited by
- 1,248
- References
- 0
- FWCI
- 82.50
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Underwriting relationships, analysts' earnings forecasts and investment recommendations. https://app.cochat.ai/papers/10.1016/s0165-4101(98)00016-0
- The paper
- Lin, H.-W., & McNichols, M. F. (1998). Underwriting relationships, analysts' earnings forecasts and investment recommendations. Journal of Accounting and Economics. https://doi.org/10.1016/s0165-4101(98)00016-0
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
