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Record W7028512794

Factors that affect the fluctuation against oil price and its impact toward the stock price market in Malaysia / Muhamad Rizal Othman

2007· other· en· W7028512794 on OpenAlexaboutno aff

Bibliographic record

VenueUiTM Institutional Repositories (Universiti Teknologi MARA) · 2007
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicGeological Modeling and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil-storage tradeOil priceStock (firearms)Affect (linguistics)Stock marketStock priceCrude oilPrice levelCost priceMarket price
DOInot available

Abstract

fetched live from OpenAlex

The world lives on oil. The price of oil is reflected in most of the things we do. It impacts on the price of transport, the cost of goods and services, and the availability of many products, including food, water and shelter. On other hand, the fluctuation of oil price market might affect to the investor's prospect toward stock market. Many investors were worrying about the rising of oil price because the oil price might be a factor that affect of stock price decrease. As we noticed that the world's oil supply comes from a wide variety of sources. While the Middle East (home to the largest OPEC producers) was the largest producing region in 2004, with 29 percent of total world production, North America accounted for 19 percent, with the remaining 52 percent dispersed fairly evenly throughout the globe. OPEC member countries together accounted for about 40 percent of world total oil production in 2004, up from 38 percent in 2003. Of the 14 countries that produced more than 2 million bbl/d of total liquids in 2004, seven were OPEC members. The remaining seven were not OPEC members, including: the United States (the world's third-largest total oil producer for the year); Russia; Mexico; China; Canada; and North Sea countries Norway and the United Kingdom. This paper was study the factors that affect the fluctuation against oil price in Malaysia. Other than that this paper also was study about the effects of oil price shocks on the stock prices market in Malaysia. The intention to study was to know on how significant of oil price volatility will affect the stock prices market.

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)0.001
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 score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.236
Teacher spread0.210 · 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
Published2007
Admission routes1
Has abstractyes

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