Bibliographic record
Abstract
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. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".