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Record W2553631773 · doi:10.5539/ijef.v8n12p120

An Empirical Analysis of the Relationship between Oil Prices and Stock Markets

2016· article· en· W2553631773 on OpenAlexvenueno aff
Stelios Markoulis, Niki Neofytou

Bibliographic record

VenueInternational Journal of Economics and Finance · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
FundersUniversity of Cyprus
KeywordsBRICCointegrationEconomicsStock market indexStock (firearms)Stock marketChinaFinancial economicsDiversification (marketing strategy)Emerging marketsPortfolioMonetary economicsStock market bubbleOil priceBusinessEconometricsFinance

Abstract

fetched live from OpenAlex

This paper investigates the relationship between oil prices and stock market returns for the G7 and the BRIC countries for the period 1991-2016 using cointegration and a vector error correction model. Results reveal that there is no long-run relationship between oil prices and the stock market indices of the G7 countries. However, they also reveal that there is a long-run relationship between oil prices and the stock market indices of three out of the four BRIC countries (Brazil, China and Russia). This result appears to be broadly aligned with the idea that over the past quarter of a century emerging countries have been more exposed to oil prices (either as producers or consumers) than developed ones. Furthermore, from an investments’ and international portfolio management perspective, it seems that there might be benefits from diversification when holding the stock market index of a G7 country or India and oil assets since these appear to be segmented. On the other hand, such benefits might not be applicable in the case of the stock markets of Brazil, China or Russia and oil assets as these seem to be integrated.

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 score0.017
Threshold uncertainty score0.246

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 head0.048
GPT teacher head0.283
Teacher spread0.235 · 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

Citations8
Published2016
Admission routes1
Has abstractyes

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