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Record W4380874038 · doi:10.18374/jibe-23-1.3

RETURN AND VOLATILITY SPILLOVER ACROSS STOCK MARKETS OF THE US AND ITS MAJOR TRADING PARTNERS

2023· article· en· W4380874038 on OpenAlexaboutno aff
Jae-Kwang Hwang

Bibliographic record

VenueJournal of International Business and Economics · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsSpillover effectStock marketEconomicsVolatility (finance)Stock market indexFinancial economicsStock (firearms)Monetary economicsMacroeconomics

Abstract

fetched live from OpenAlex

Hypothesis That The Us Market Has Been The Most Influential In Terms Of Return Spillover (259.5) To Other Stock Indexes, With The Biggest Return Spillovers Occurring In The Canadian Market (58.4)And The German Market (57.0).In A Similar Manner, The Us Market Has Been The Biggest Transmitter Of Volatility Spillover (202.3)To Other Stock Indexes, With The Highest Volatility Spillovers Occurring In The Canadian Market (51.8)And The German Market (45.8).The Us Market Has Been The Most Influential Based On Return And Volatility Spillovers.This Finding Also Suggests That The Us And Chinese Markets Are The Least Vulnerable To Foreign Shocks.In Contrast, The Canadian Market Is The Most Vulnerable To External In Terms Of Return Spillover And Volatility Spillover.As A Consequence, Chinese Stock Market Participants Can Still Reap The Rewards Of Diversity.During The Sample Period, However, Integration Across Developed Stock Markets Has Increased, Reducing The Benefits Of Diversity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.370

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.030
GPT teacher head0.259
Teacher spread0.230 · 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

Citations1
Published2023
Admission routes1
Has abstractyes

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