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Record W3210799274

Risk Factors in the Oil Industry: An Upstream and Downstream Analysis

2014· article· en· W3210799274 on OpenAlexaboutno aff
Sofía B. Ramos, Helena Veiga, Chih‐Wei Wang

Bibliographic record

VenueSSRN Electronic Journal · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsVolatility (finance)Stock (firearms)Upstream (networking)Downstream (manufacturing)Liberian dollarMonetary economicsPetroleum industryOil-storage tradeBusinessOil priceUpstream and downstream (DNA)EconomicsFinancial economicsEconometricsFinanceEnvironmental scienceEngineeringOperations management
DOInot available

Abstract

fetched live from OpenAlex

In this paper we examine the drivers of stock market value in the upstream (producers) and downstream segments (petroleum refiners) of the oil industry.Using a sample of U.S. firms we find that stock returns of upstream and downstream firms follow stock market and oil price returns. Moreover, the upstream firm stock returns are sensitive to changes in the Canadian dollar, an important oil trade partner of the U.S., to natural gas returns and its volatility, but not to oil return volatility.Both the upstream and downstream segments present asymmetric changes regarding oil return changes. Stock returns of the oil industry respond asymmetrically to oil returns, i.e., positive oil returns had a greater impact than oil price drops in the period 1998-2004. Before 1997 we do not find any asymmetric effects, and after 2004, they are only statistically significant in the upstream segment. Overall, the evidence for asymmetric effects is more consistent across measures and time in the upstream than in the downstream segment.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.212
Teacher spread0.203 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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