The Impact of Foreign Oil Companies’ Stock Price Movement on Kazakhstan Oil Sector: Empirical Evidence
Bibliographic record
Abstract
This study investigates the vibrant interrelationship amid national and global oil companies (the United States, United Kingdom, Norway, Russia, China, France, Italy, Japan, Netherlands, and Canada) and the state-owned KazMunaiGas oil company of Kazakhstan. In order to examine the impact of foreign companies‟ equity price shocks on the Kazakhstan oil company, the researcher applied the closing price of firms‟ shares for the period February 15, 2007 to August 2, 2010. According to the preceding literature, world capital markets are becoming strongly integrated. Hence, there is a risk for the financial market participants to diversify their portfolios. On top of that, most of the existing literature focused on industrialized economies. This paper strives to fill the gap in the range of emerging markets research. The main focus of this thesis will concentrate on transition economy of Kazakhstan. Republic of Kazakhstan highly relies on the production and export of oil and gas and mineral resources industry. Consequently, this country‟s economy heavily depends on the exploration of oil and gas reserves. Furthermore, with respect to the accelerating foreign investments in Kazakhstan, it is central for the international investors and stakeholders to comprehend the extent of responsiveness of KazMunaiGas equity shares and level of interdependence amongst regional and foreign oil firms. The research findings revealed that KMG was quite cointegrated as well as Granger-caused by regional (Russia and China) and the rest of the world oil companies. The analysis demonstrated that KMG equity prices were especially sensitive to external innovations and to some extent tended to overreact to the foreign and regional shocks.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".