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Record W3121767651 · doi:10.1111/1911-3846.12155

Individualism, Uncertainty Avoidance, and Earnings Momentum in International Markets

2015· article· en· W3121767651 on OpenAlexvenueno aff
Paul Dou, Cameron Truong, Madhu Veeraraghavan

Bibliographic record

VenueContemporary Accounting Research · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicAuditing, Earnings Management, Governance
Canadian institutionsnot available
Fundersnot available
KeywordsUncertainty avoidanceIndividualismEarningsProfitability indexRationalityMomentum (technical analysis)EconomicsHofstede's cultural dimensions theoryFinancial economicsStock (firearms)Emerging marketsAccountingPolitical scienceFinanceSocial psychologyPsychologyMarket economyGeographyCollectivism

Abstract

fetched live from OpenAlex

Abstract This study examines whether cultural dimensions such as individualism and uncertainty avoidance can explain the variation in the profitability of the earnings momentum strategies in international markets. Using the time‐varying cultural indices of Tang and Koveos (2008) for 30,383 firms from 41 countries over the period 1995–2008, we show that the level of individualism in a country is positively associated and the level of uncertainty avoidance is negatively associated with earnings momentum profits. Our findings are robust to the inclusion of a comprehensive set of control variables and alternative cultural metrics. The central message is that we emphasize the necessity to go beyond the assumption of perfect rationality and to account for innate differences among international investors to explain how accounting information is incorporated into stock prices. We recommend that cultural dimensions be included in cross‐country research to account for innate differences among international investors.

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)0.008
metaresearch head score (Gemma)0.020
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.002
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 head0.050
GPT teacher head0.301
Teacher spread0.251 · 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.

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

Citations75
Published2015
Admission routes1
Has abstractyes

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