The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index.
The Power of Voice: Managerial Affective States and Future Firm Performance
Abstract
We measure managerial affective states during earnings conference calls by analyzing conference call audio files using vocal emotion analysis software. We hypothesize and find that, when managers are scrutinized by analysts during conference calls, positive and negative affects displayed by managers are informative about the firm's financial future. Analysts do not incorporate this information when forecasting near‐term earnings. When making stock recommendation changes, however, analysts incorporate positive but not negative affect. This study presents new evidence that managerial vocal cues contain useful information about a firm's fundamentals, incremental to both quantitative earnings information and qualitative “soft” information conveyed by linguistic content.
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
Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
A Theory of Cognitive Dissonance
Festinger, L. (1957) · doi:10.1515/9781503620766 · Cited by 24,241 · cited 3×
“The theory of cognitive dissonance, developed by Festinger (1957), is based on the notion that inconsistency between an individual’s beliefs and their actions creates a feeling of discomfort and anxiety.”
A Theory of Cognitive Dissonance
(2017) · Macat Library eBooks · doi:10.4324/9781912282432 · Cited by 18,122
On Persistence in Mutual Fund Performance
Carhart, M. M. (1997) · The Journal of Finance · doi:10.1111/j.1540-6261.1997.tb03808.x · Cited by 17,283
Praat: Doing Phonetics by Computer
(2011) · Ear & Hearing · doi:10.1097/aud.0b013e31821473f7 · Cited by 7,863
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
When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks
LOUGHRAN, T., & MCDONALD, B. (2011) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01625.x · Cited by 6,015
Giving content to investor sentiment: The role of media in the stock market
TETLOCK, P. C. (2007) · The Journal of Finance · doi:10.1111/j.1540-6261.2007.01232.x · Cited by 4,827
Corporate governance, chief executive officer compensation, and firm performance
Core, J. E., Holthausen, R. W., & Larcker, D. F. (1999) · Journal of Financial Economics · doi:10.1016/s0304-405x(98)00058-0 · Cited by 4,335
On the impossibility of informationally efficient markets
Stiglitz, J. E., & Grossman, S. J. (1980) · Columbia University · doi:10.7916/d8765r99 · Cited by 3,645
Cited by
The Causal Impact of Media in Financial Markets
ENGELBERG, J. E., & PARSONS, C. A. (2011) · The Journal of Finance · doi:10.1111/j.1540-6261.2010.01626.x · Cited by 1,121
Earnings quality: Evidence from the field
Dichev, I. D., Graham, J. R., Harvey, C. R., & Rajgopal, S. (2013) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2013.05.004 · Cited by 1,103
Disclosure processing costs, investors’ information choice, and equity market outcomes: A review
Blankespoor, E., deHaan, E., & Marinovic, I. (2020) · Journal of Accounting and Economics · doi:10.1016/j.jacceco.2020.101344 · Cited by 1,076
Earnings conference calls and stock returns: The incremental informativeness of textual tone
Price, S. M., Doran, J. S., Peterson, D. R., & Bliss, B. A. (2012) · Journal of Banking & Finance · doi:10.1016/j.jbankfin.2011.10.013 · Cited by 666
How Big Data Will Change Accounting
Warren, J. D., Moffitt, K. C., & Byrnes, P. (2015) · Accounting Horizons · doi:10.2308/acch-51069 · Cited by 615
Metadata
- Authors
- MAYEW, W. J., & VENKATACHALAM, M.
- Venue
- The Journal of Finance
- Publisher
- Wiley
- Published
- 2012-01-17
- Volume
- 67
- Issue
- 1
- Pages
- 1-43
- ISSN
- 0022-1082 (ISSN-L)
- 1540-6261
- OpenAlex
- W2075051605
- Cited by
- 622
- References
- 71
- FWCI
- 87.42
- Type
- journal article
- Language
- en
- Open access
- closed
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: The Power of Voice: Managerial Affective States and Future Firm Performance. https://app.cochat.ai/papers/10.1111/j.1540-6261.2011.01705.x
- The paper
- MAYEW, W. J., & VENKATACHALAM, M. (2012). The Power of Voice: Managerial Affective States and Future Firm Performance. The Journal of Finance. https://doi.org/10.1111/j.1540-6261.2011.01705.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.
