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Record W3124368942 · doi:10.2308/accr.2010.85.3.937

Accruals Quality, Stock Returns, and Macroeconomic Conditions

2010· article· en· W3124368942 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Accounting Review · 2010
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsConcordia University
Fundersnot available
KeywordsEconomicsAccrualCost of capitalRisk premiumCost of equityRecessionCapital asset pricing modelEquity (law)PortfolioMonetary economicsSystematic riskStock (firearms)EarningsEconometricsFinancial economicsFinanceMicroeconomicsMacroeconomicsProfit (economics)

Abstract

fetched live from OpenAlex

ABSTRACT: This study examines whether and how earnings quality, measured as accruals quality (AQ), affects the cost of equity capital. Using two-stage cross-sectional regression tests, we find that the AQ risk factor is significantly priced, after controlling for low-priced stocks. This result is robust in tests using individual stocks, various portfolio formations, and different beta estimations. Furthermore, we show that AQ and its pricing effect systematically vary with business cycles and macroeconomic variables. In particular, this pricing effect is prominent in total AQ and innate AQ but not in discretionary AQ. The risk premium associated with AQ exists only in economic expansion but not in recession periods. Poorer AQ firms are more vulnerable to macroeconomic shocks. The risk premium and the dispersion of AQ are also related to future economic activity. Overall, our results suggest that AQ contributes to the cost of equity capital and that its pricing effect is associated with fundamental risk.

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)0.003
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.605
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.019
GPT teacher head0.284
Teacher spread0.265 · 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