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Record W3085956393 · doi:10.1108/jdqs-02-2007-b0002

Information Contents of Call-Put Options Trading Value Ratio

2007· article· en· W3085956393 on OpenAlexaff
Sol Kim

Bibliographic record

VenueJournal of Derivatives and Quantitative Studies 선물연구 · 2007
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicFinancial Markets and Investment Strategies
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsPoolingEquity (law)EconomicsPrice discoveryFinancial economicsCall optionEconometricsFutures contractComputer science

Abstract

fetched live from OpenAlex

This paper investigates the lead-lag relationship between the call-put options trading value ratio and the KOSPI 200 returns using Chen, Lung, and Tay (2005, 2006)’s model. We report the evidence conSistent with a pooling equilibrium or that informed trades are executed in both equity and options markets when using all options. That is, KOSPI 200 index options and KOSPI 200 are closely interrelated. However, in case of using the short-term or out-of-the-money options, call-put oPtions trading value ratio uni-directionally leads KOSPI 200 index returns. Also under the volatile market condition, the lead effect of call-put options trading value ratio to KOSPI 200 index returns becomes stronger.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.093
GPT teacher head0.309
Teacher spread0.216 · 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 designTheoretical or conceptual
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

Citations4
Published2007
Admission routes1
Has abstractyes

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