Analýza vývoje měnových kurzů (případ zemí exportujících a importujících suroviny)
Bibliographic record
Abstract
This bachelor thesis´s objective is to analyze a possible relationship between exchange rates of selected countries and prices of commodities that these countries export. The thesis aims to describe this relationship and to quantify it. The selected countries are Canada, Japan, Norway, Australia, Zambia and Burundi. This thesis first describes theoretically the relationships between the exchange rates and fundamental quantities. The method of empirical analysis is described in the second part. Correlation and regression analysis is carried out and some problems that I have encountered during the econometric analysis are described as well. I study the aforementioned relationship on monthly data of nominal effective exchange rates from 2000 to 2015 in case of Canada, Japan, Australia and Norway. In case of Zambia and Burundi I study the relationship on yearly data of real effective exchange rates from 1980 to 2014. During my analysis I learned that these exchange rates really show some dependence on the commodity prices. The relationship is strongest in case of Norwegian Krone and oil prices. On the other hand the relationship is the weakest in case of Japanese Yen and oil prices.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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".