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Record W3191091484 · doi:10.1111/1475-679x.12394

How is Earnings News Transmitted to Stock Prices?

2021· article· en· W3191091484 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

VenueJournal of Accounting Research · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsUniversity of TorontoHEC Montréal
Fundersnot available
KeywordsPrice discoveryEarningsEconomicsAsk priceStock (firearms)Financial economicsMonetary economicsStock priceEconometricsBusinessFinance

Abstract

fetched live from OpenAlex

ABSTRACT We examine the speed and mechanism of the price discovery process following earnings announcements in the after‐hours market, a very illiquid trading environment. Prices reflect earnings surprises mostly through changes in quotes rather than through trades. Following positive announcement surprises, ask prices adjust quickly while bid prices are slower to adjust, and vice versa for negative surprises. Returns computed from trade prices underestimate the speed and magnitude of price reactions following announcements relative to returns computed from quotes. These findings emphasize the importance of using quotes and not trade prices when examining intraday price discovery. Because firm announcements such as earnings generally occur in the after‐hours market, using quotes is crucial as trading is sparse. We further illustrate the importance of quotes when examining the price discovery process around analyst recommendation revisions.

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)0.002
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: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.081
GPT teacher head0.307
Teacher spread0.227 · 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