MétaCan
Menu
Back to cohort
Record W3087444487 · doi:10.17016/ifdp.2020.1300

Investor Sentiment and the (Discretionary) Accrual-return Relation

2020· article· en· W3087444487 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Finance Discussion Paper · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
FundersPeking UniversityNational Natural Science Foundation of ChinaRoyal Economic SocietyCanadian Intensive Care Foundation
KeywordsStylized factAccrualEconomicsStock (firearms)Earnings managementEarningsEconometricsAggregate (composite)Relation (database)Financial economicsMonetary economicsStock marketAccountingComputer science

Abstract

fetched live from OpenAlex

Discretionary accruals are positively associated with stock returns at the aggregate level but negatively so in the cross section. Using Baker-Wurgler investor sentiment index, we find that a significant presence of sentiment-driven investors is important in accounting for both patterns. We document that the aggregate relation is only prominent during periods of high investor sentiment. Similarly, the cross-section relation is considerably stronger in high-sentiment periods in both economic magnitude and statistical significance. We then embed investor sentiment into a stylized model of earnings management, and illustrate that a positive (negative) relationship between stock returns and earnings management can endogenously emerge in the aggregate (cross section). Our analysis suggests that the (discretionary) accrual-return relation at both the aggregate and firm levels at least partially reflects mispricing that is related to market-wide investor sentiment.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.752
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.211
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it