A study on market interdependence of futures markets with its underlying assets: analysis on Latin America Developed & Emerging Market (Canada, Mexico and United State) / Nurul Hidayah Hamid
Bibliographic record
Abstract
There are many research have been conduct in order to investigate the relationship between spot and futures market in Latin America region. The objective of the investigation is to identify the market interdependence relationship between the futures and spot market in the Latin America which is Canada, Mexico and United State. The study use Single Linear regression Model in order to find the relationship among stock market index and to describe the relationship between a single dependent variable y and a single independent variable x. The Canada use S&P 60 Index, IPC stock index is from Mexico country while United State use S&P 500 stock Index for the spot and futures Market. The weekly closing price of stock index and weekly settlement price from 1st January 2005 until 31st December 2010 are collected from the data stream. The result shows that there is bidirectional relationship between Canada stock Market, Mexico stock market and United State stock market. Furthermore, the result also evidence that there are significance relationship between spot and futures index in three of the country Canada, Mexico and United State. On the other hand, the result from this study has some potential to be used by the market analyst for predicting country market movement and also useful to regulators of stock markets in regulating policies to control the price relationship between those markets.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".