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Record W3085796557 · doi:10.1108/jdqs-04-2010-b0001

The Lead-Lag Relationship between the Stock Market and CDS Market in Korea

2010· article· en· W3085796557 on OpenAlexaff
Kwangil Bae, Hankil Kang, Changjun Lee

Bibliographic record

VenueJournal of Derivatives and Quantitative Studies 선물연구 · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCredit Risk and Financial Regulations
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsStock marketEquity (law)Stock exchangeLead–lag compensatorLagMonetary economicsEconomicsSample (material)BusinessFinancial economicsEconometricsFinanceGeography

Abstract

fetched live from OpenAlex

This study examines the lead-lag relationship between the stock market and CDS market in Korea using the firm-level data during 2006-2009. Our main findings can be summarized as follows. First, our empirical finding shows that stock returns Granger cause CDS spread changes for a larger number of firms than vice versa. Second, the sub-sample analysis reveals that while the stock market leads the CDS market in each sub-sample, the lead-lag relationship is more pronounced in the post-crisis period. Finally, our main findings remain the same even in the presence of controlling variables such as equity volatilities, absolute bid-ask spreads, and CDS premium on foreign exchange stabilization bonds issued by Korean government. In sum, consistent with the U. S. and U. K. evidence, it appears that the stock market leads the CDS market in Korea.

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)0.003
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 score0.111
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.091
GPT teacher head0.322
Teacher spread0.231 · 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
Published2010
Admission routes1
Has abstractyes

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