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Record W2051685161 · doi:10.1142/s2335680413500026

OIL PRICES AND STOCK MARKET CORRELATION: A TIME-VARYING APPROACH

2013· article· en· W2051685161 on OpenAlexaboutno aff
Nikolaos Antonakakis, George Filis

Bibliographic record

VenueInternational Journal of Energy and Statistics · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsStock marketEconometricsStock (firearms)CorrelationEconomicsFinancial economicsMathematicsMaterials scienceGeography

Abstract

fetched live from OpenAlex

This paper examines the influence oil prices on stock market time-varying correlation. We consider five stock market indices from both oil-importing (US, UK and Germany) and oil-exporting economies (Canada and Norway) for the period 1988-2011. The findings from the DCC-GARCH framework suggest that the effects of oil price changes on stock market correlation are not constant over time and they depend on the status of the economy, i.e. whether it is oil-importing or oil-exporting. In addition, utilising the identification of oil price shocks by Kilian (2009) and Hamilton (2009a; 2009b) we find that the aggregate demand shocks and precautionary demand shocks tend to exercise a negative effect on stock market correlation, whereas no effects from the supply-side oil price shocks can be reported. These findings have important implications for international portfolio diversification and risk management.

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)0.002
metaresearch head score (Gemma)0.011
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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

Citations61
Published2013
Admission routes1
Has abstractyes

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