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Cited by 373

The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.

Does Silence Speak? An Empirical Analysis of Disclosure Choices During Conference Calls

Open access
HOLLANDER, STEPHAN, PRONK, MAARTEN, ROELOFSEN, ERIK·2010·Journal of Accounting Research

Abstract

In this paper, we exploit the open nature of conference calls to explore whether managers withhold information from the investing public. Our evidence suggests that managers regularly leave participants on the conference call in the dark by not answering their questions. We find that the best predictors of such an event are firm size, a CEO's stock price–based incentives, company age, firm performance, litigation risk, and whether analysts are actively involved during the call's Q&A section. Finally, we document strong support for the assumption maintained in the literature that investors interpret silence negatively. That is, investors seem to interpret no news as bad news.

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Crossref · 10.1111/j.1475-679x.2010.00365.x

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Metadata

Authors
HOLLANDER, S., PRONK, M., & ROELOFSEN, E.
Venue
Journal of Accounting Research
Publisher
Wiley
Published
2010-04-09
Volume
48
Issue
3
Pages
531-563
ISSN
  • 0021-8456 (ISSN-L)
  • 1475-679X
OpenAlex
W3122294539
Cited by
373
References
78
FWCI
27.01
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Does Silence Speak? An Empirical Analysis of Disclosure Choices During Conference Calls. https://app.cochat.ai/papers/10.1111/j.1475-679x.2010.00365.x
The paper
HOLLANDER, S., PRONK, M., & ROELOFSEN, E. (2010). Does Silence Speak? An Empirical Analysis of Disclosure Choices During Conference Calls. Journal of Accounting Research. https://doi.org/10.1111/j.1475-679x.2010.00365.x

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.