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Record W1468389345 · doi:10.1300/j282v01n03_06

Price Change Causation Across International Stock Markets

2008· article· en· W1468389345 on OpenAlexaboutno aff
Dan W. Hess, Anthony Kilduff

Bibliographic record

VenueJournal of International Financial Markets Institutions and Money · 2008
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsCausationEquity (law)EconomicsStock (firearms)Financial economicsInternational marketGranger causalityClosing (real estate)Stock marketEconometricsGeographyPolitical scienceInternational economicsFinance

Abstract

fetched live from OpenAlex

This study investigatees whether and to what extent a causal relationship exists among international equity markets. Daily closing values from 1987 to 1989 for markets in New York, London, Tokyo, Toronto, Frankfurt and Hong Kong are examined using Geweke's extension of Granger's causality test. The results suggest that any groupings of five markets significantly influences the sixth market; however, with the exception of New York, individual markets do not causally influence the group. The failure of London and Tokyo to influence the groups from which they were excluded is interesting. Because these causal effects vary over time, it may be difficult to use these results for predictive purposes; nevertheless, this study should enhance understanding of pricing interactions across international stock markets.

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)0.003
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.059
GPT teacher head0.280
Teacher spread0.221 · 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 designSimulation or modeling
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

Citations2
Published2008
Admission routes1
Has abstractyes

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