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Record W3017005047 · doi:10.1111/ajfs.12297

International Market Integration: A Survey

2020· article· en· W3017005047 on OpenAlexaff
Amir Akbari, Lilian Ng

Bibliographic record

VenueAsia-Pacific Journal of Financial Studies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Risk and Volatility Modeling
Canadian institutionsYork UniversityOntario Tech University
Fundersnot available
KeywordsMarket integrationEquity (law)Market researchEmpirical researchMarket microstructureEconomicsFinancial economicsBusinessMarketingOrder (exchange)Political scienceMicroeconomicsFinanceMathematics

Abstract

fetched live from OpenAlex

Abstract Market integration is a canonical topic in international finance. The question of whether and to what extent markets are integrated with the global economy has motivated one of the largest literatures in this field. Given this vast body of research, this survey shall only focus on the theoretical and empirical studies on one aspect of market integration – equity market integration. It reviews the evolution of various approaches employed in studying market integration. This survey discusses the recent empirical findings on cross‐sectional and time‐series dynamics of integration across developed and emerging markets. It also describes the empirical estimation of three current measures of market integration and discusses their usefulness as well as limitations. Finally, the survey provides a few future directions for this line of research.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0140.030
Science and technology studies0.0000.001
Scholarly communication0.0030.005
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.003

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 head0.105
GPT teacher head0.277
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations22
Published2020
Admission routes1
Has abstractyes

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