Impact of Transaction for Institutional and Non-Institutional Persons for Rising Magnet Effect on Price Limit at Tehran Stock Exchange
Bibliographic record
Abstract
At many stock exchanges of world, it is applied from price limit for different purposes including: reducing frequency and manipulation of stock. One of the most important effects of price limit is magnet effect that is available in most of stock exchanges of world. The magnet effect on Tehran stock exchange is proved and in this article we decide to study this effect on Tehran stock exchange and role of active investors at stock market. Studies on 24 companies as case study including: Kesaveh, Ghalrest, Shomal Excavation, Betras, Khazamia, Khasapa, Sefars, Sina, Fazer, Fasmin, Ghapira, Ghanisha, Kermasha, Koravi, Vitro, Sapa, Sakht, Sepah, Sandogh, Lesapa, Melat and Madan reveal that except one case (Gheshkar) in all of the companies the role of institutional investors on magnet effect is higher than non-institutional investors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 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".