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Record W2580786116 · doi:10.1080/00036846.2017.1279268

How pervasive is the effect of culture on stock market linkages? Evidence across regions and economic cycles

2017· article· en· W2580786116 on OpenAlex
Vikkram Singh, Bin Li, Eduardo Roca

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

VenueApplied Economics · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicCulture, Economy, and Development Studies
Canadian institutionsSheridan College
Fundersnot available
KeywordsMarket liquidityEconomicsStock marketEquity (law)Quantile regressionFinancial economicsMarket depthStock (firearms)Hofstede's cultural dimensions theoryMonetary economicsEconometrics

Abstract

fetched live from OpenAlex

We conduct a comprehensive study on the effect of culture on stock market linkages. With data on 25 national stock markets, a quantile regression model is used to estimate the determinants of market linkages using culture variable/s such as language, religion and Hofstede’s cultural dimensions while controlling for distance, economic and legal variables. Further, we test whether these effects hold across regions and if changes are detected during periods of market crisis. We also test if market liquidity, an indicator of market efficiency, diminishes the impact of culture on market linkages. The main conclusion is that culture preferences shape investor choices, which affects integration between stock markets. The equity markets with similar cultural traits tend to increase market linkages; however, we observe differences across regions. Furthermore, liquidity and economic uncertainty fail to have an impact on the significance of culture variable/s as determinants of market linkages.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.269
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.037
GPT teacher head0.311
Teacher spread0.274 · 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