Bibliographic record
Abstract
The background of organized commodity exchanges dates back to the 17th century when grain merchants in Japan stored rice in warehouses for future use.The concept propounds that futures contract should have a good contract design in order to enhance performance of the commodity exchange.However, there is no consensus on the importance of contract specifications on commodity exchange.The increasing role of the agricultural commodity exchange and financial sector, on both economic development and poverty alleviation, has seen the concept being applied more on the financial sector than before; this has been further aggravated by world financial crisis, hunger and its consequences.In this regard, Zimbabwe is no exception, by the year 2002, the Zimbabwe Agricultural Commodity Exchange ceased to operate due to number of issues; but chief among them has been cited as poor contract specifications.The paper presents the findings of the study that was conducted to determine the futures contract specifications that would make Zimbabwe agricultural commodity exchange thrive again.It applies both primary and secondary data in gathering the necessary information, to assess the causal relationship between contract design and exchange market (Price quotations, trading system, trading hours, contract sizes, delivery days and exchange fees).The study extended the knowledge of commodity and financial sectors to the stakeholders.The research was motivated by the fact that, most nascent commodity exchanges.The study showed that contract design affect commodity exchange; poor contract design would cause the business activities, to "shut doors.Field research was beneficial to obtain an in-depth understanding of the contract designs from local experts in the commodities markets.Therefore, in order to improve commodity exchange, good contract designs must be implemented, this includes improving trading system, trading hours, contract sizes.On the hand, the Reserve Bank of Zimbabwe should ensure or put in place robust supervisory and regulatory policies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.971 | 0.965 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".