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Record W3161502010 · doi:10.3390/jrfm14050226

The Influence of Oil Prices on Equity Returns of Canadian Energy Firms

2021· article· en· W3161502010 on OpenAlexvenueaboutno aff
Sourav Batabyal, Robert N. Killins

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicMarket Dynamics and Volatility
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)West Texas IntermediateOil priceEconomicsFinancial economicsOil-storage tradeEmpirical evidenceBusinessPetroleum industryBenchmark (surveying)Monetary economicsGeographyEnvironmental science

Abstract

fetched live from OpenAlex

Using monthly data from January 2000 to August 2018, this paper examines how the Canadian oil and gas industry and individual firms’ equity prices react to oil price fluctuations, which are measured by the traditional West Texas Intermediate (WTI) benchmark and the Canada-specific Western Canadian Select (WCS) benchmark. The findings provide support for the view that oil price movements are an important factor in explaining the equity returns of the overall industry and for many individual oil and gas firms in Canada. Both WTI and WCS measures provide statistically significant evidence, but the results support that WTI may still be the more relevant measure for Canadian-based firms. We also find that the spread between WTI and WCS has a minimal impact on the firms’ equity returns. Additional tests for asymmetric impacts of oil price movements on Canadian oil and gas equity returns have provided little evidence, whereas time-varying impacts are found for a handful of firms. The empirical findings predicated on the holistic view of the impacts of oil price fluctuations on equity market returns will enhance investor confidence and strengthen the Canadian economy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.616
Threshold uncertainty score0.997

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 head0.012
GPT teacher head0.205
Teacher spread0.193 · 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

Citations6
Published2021
Admission routes2
Has abstractyes

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