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Record W2105630118 · doi:10.1111/jifm.12003

Earnings Benchmarks and the Information Content of Quarterly Foreign Earnings of U.S. Multinational Companies

2013· article· en· W2105630118 on OpenAlexaboutno aff
Michael Lacina, Barry R. Marks, Haeyoung Shin

Bibliographic record

VenueJournal of International Financial Management and Accounting · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsEarningsEarnings response coefficientPost-earnings-announcement driftEarnings surpriseFinancial statementBusinessEarnings per shareMultinational corporationPrice–earnings ratioEarnings before interest, taxes, depreciation, and amortizationQuarter (Canadian coin)AccountingEconomicsFinanceAudit

Abstract

fetched live from OpenAlex

Abstract The meeting of earnings benchmarks is considered important for investors. The chief financial officers of U.S. companies state that the three most important earnings thresholds to meet are the earnings in the same quarter last year, the analysts' earnings forecast for the current quarter, and zero earnings. These earnings benchmarks have been defined in terms of total earnings. For U.S. multinational firms, total earnings consist primarily of domestic earnings and foreign earnings. We conduct an event study where we examine (1) the stock market reaction to meeting or beating quarterly domestic and foreign earnings benchmarks and (2) the market reaction to the changes in quarterly domestic and foreign earnings, while we control for meeting or beating the analysts' earnings forecast and the analysts' earnings forecast surprise. We find that the quarterly financial statement disclosure of domestic and foreign earnings under Statement of Financial Accounting Standards No. 131 supplies investors with valuable information that was not previously disseminated through financial analysts or other sources. The stock market reaction to meeting or beating foreign earnings from the same quarter in the prior year is stronger than the market reaction to meeting or beating domestic earnings from the same quarter in the prior year.

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.

How this classification was reachedexpand

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.004
Open science0.0000.000
Research integrity0.0000.000
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 head0.006
GPT teacher head0.183
Teacher spread0.178 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2013
Admission routes1
Has abstractyes

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