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Enregistrement W3123094324

Australan Coal Company Risk Factors: Coal and Oil Prices

2014· article· en· W3123094324 sur OpenAlexaboutno aff
M.Z. Hasan, Ronald A. Ratti

Notice bibliographique

Revue˜The œinternational journal of business and finance research · 2014
Typearticle
Langueen
DomaineEconomics, Econometrics and Finance
ThématiqueMarket Dynamics and Volatility
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésEconomicsStock (firearms)CoalPortfolioOil-storage tradeFinancial economicsRate of returnOil priceStock exchangeCost priceMonetary economicsStock marketFinanceEngineering
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

ABSTRACTExamination of panel data on listed coal companies on the Australian exchange over January 1999 to February 2010 suggests that market return, interest rate premium, foreign exchange rate risk, and coal price returns are statistically significant in determining the excess return on coal companies' stock. Coal price return and oil price return increases have statistically significant positive effects on coal company stock returns. A one per cent rise in coal price raises coal company returns by between 0.15% and 0.17%. A one per cent rise in oil price raises coal company returns by between 0.06% and 0.08%. The sensitivity of stock prices to oil price shocks suggest a role for investment in stocks that rise when energy prices increase in a well balanced portfolio and in pursuing profitable investment strategies.JEL: G12; G15; Q4KEYWORDS: Coal Stock Price; Coal Price; Oil Price(ProQuest: ... denotes formulae omitted.)INTRODUCTIONEnergy companies are very dominant in the stock markets of the developed countries. In the literature close attention has been paid to the effect of oil prices on the stock prices of oil and gas companies. Sadorsky (2001) and Boyer and Filion (2007) find that positive oil price shocks significantly raise stocks returns for Canadian oil and gas companies and El-Sharif et al. (2005) find a similar result for UK oil and gas companies. In contrast to work identifying the risk factors of oil and gas companies and evaluating the effect of energy prices on the stock returns of oil and gas companies, relatively little similar work has appeared on coal companies despite the importance of coal as a source of energy. Coal provides over 23 percent of global primary energy needs (compared to 36% for oil) and accounts for producing 39 percent of the world's electricity industry.In this paper, we examine the risk factors of Australian coal company stock returns. We pool the stock return data on coal companies listed on the Australian stock exchange. Coal price returns strongly influence coal stock returns. Oil price returns also significantly influence stock return of coal companies. A one per cent rise in coal (oil) price raises coal company returns by between 0.15% and 0.17% (between 0.06% and 0.08%). Market return, interest rate premium, and foreign exchange rate risk are statistically significant in determining the excess return on coal companies' stock. The beta coefficient of market return is significantly greater than 1 confirming that firms in the primary energy sector are more risky than the market. The depreciation of Australian dollar has a negative impact on the return of coal companies, a result similar to that found by comparable country studies for oil and gas companies. The remainder of the paper is organized as follows. Section 2 discusses the risk factors and the models of coal company returns to be estimated in our study. Section 3 describes the data and the variables. Section 4 presents the results of the research and section 5 concludes the study.LITERATURE REVIEWStudies on the determinants of returns of coal companies in Australia or other countries is comparatively sparse compared to the number of studies on Australian mining and other companies and on oil and companies for other countries. In addition to the studies already mentioned, Dayanandan and Donker (2011) and Mohanty and Nandha (2011) report that oil price increases have a positive and statistically significant impact on oil and gas companies in North America and the U.S., respectively. Ramos and Veiga (2011) find that the returns of the oil and gas sector in 34 countries are significantly impacted by oil price returns.In the production and the trade of coal, Australia has a significant role. Australia ranks fourth in the world in proven coal reserves after the US, Russia and China, and ranks third in the world in coal production after China and the US. Australian is the world's largest coal exporter and accounts for around a third of world coal trade. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,045
Score d'incertitude au seuil0,089

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,002
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,057
Tête enseignante GPT0,296
Écart entre enseignants0,239 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2014
Routes d'admission1
Résumé présentoui

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