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Impacto de la comercialización de futuros sobre el índice Colcap en la volatilidad asimétrica del mercado de acciones en Colombia

2020· article· es· W3107848458 on OpenAlexaff
Julian A. RANGEL, Alexander Giraldo Blandón, Jose V. PINZON

Bibliographic record

VenueESPACIOS · 2020
Typearticle
Languagees
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsImpact
Fundersnot available
KeywordsHumanitiesEconomicsPhilosophy

Abstract

fetched live from OpenAlex

La pregunta motivadora de esta investigación fue medir el impacto sobre la volatilidad asimétrica en el mercado de acciones como consecuencia de la entrada en operación del mercado de futuros sobre el indicador bursátil COLCAP de la Bolsa de Valores de Colombia. Con base en modelos estadísticos del tipo GARCH, se analizaron los retornos diarios del indicador desde principios del 2008 hasta finales del año 2018. Los hallazgos revelan la existencia de un efecto de apalancamiento y un mayor nivel de asimetría después que los futuros comenzaron a ser comercializados.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.232

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.261
Teacher spread0.249 · 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 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
Published2020
Admission routes1
Has abstractyes

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Same venueESPACIOSSame topicMarket Dynamics and VolatilityFrench-language works237,207