MétaCan
Menu
Back to cohort
Record W3091938849 · doi:10.1002/ijfe.2285

Does culture play a role in the stock market's response to uncertainty?

2020· article· en· W3091938849 on OpenAlexaff
Jingjing Xu

Bibliographic record

VenueInternational Journal of Finance & Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsCarleton University
Fundersnot available
KeywordsUncertainty avoidanceEconomicsProxy (statistics)Stock marketStock (firearms)EconometricsStock market indexFinancial economicsIndex (typography)Market economyStatisticsGeography

Abstract

fetched live from OpenAlex

Abstract While a growing body of literature documents a decrease in stock returns with an increase in economic uncertainty, the magnitude of this decrease may differ across countries. This paper examines whether a national culture that shapes its people's views towards uncertainty can serve as an explanation if there are heterogeneous responses of the stock market responses to an increase in economic uncertainty at the country level. Using the economic policy uncertainty (EPU) index to proxy for economic uncertainty and employing an SVAR model, this paper first finds that the magnitude of a stock market's response to an increase in uncertainty varies across countries. This paper then adopts the uncertainty avoidance index (UAI) as a proxy measure of culture relating to people's views towards uncertainty and finds that the observed cross‐country heterogeneity is correlated with the degree of a society's uncertainty avoidance. The stock market index is likely to drop more in response to an increase in uncertainty in countries with higher uncertainty avoidance.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.700
Threshold uncertainty score0.430

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.235
Teacher spread0.220 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Finance & EconomicsSame topicMarket Dynamics and VolatilityFrench-language works237,207