Market manipulation in Kuwait stock exchange : an analysis of the regulation of market manipulation prior and under Law no. 7 of 2010
Bibliographic record
Abstract
There are many practises that affect and harm the integrity of financial markets. These\nacts fall under the general title of ”Market Abuse”. This title can be divided into two\nmain forms, insider dealing and market manipulation. This research primarily aimed at\nexploring the regulation of market manipulation in Kuwaiti law. Market manipulation\npractises came under regulation for the first time via Law No. 7 in 2010. Therefore, it is\nessential to differentiate between the periods; before and after the issuance of this law.\nHence, there are four main objectives to this study: 1) define market manipulation and\nits common forms, 2) explore the applicability of criminal and civil Kuwaiti law to\nmarket manipulation practises prior Law No. 7, 3) critically evaluate how well this law\ncovers the forms of market manipulation identified and 4) evaluate how effective the\nlaw is through its enforcement and implementation.\nTo achieve these objectives, different methods have been followed. Overall, this\nresearch follows a critical analysis approach. In addition, the extant literature has been\nexplored. The evaluation of Law No. 7 has been conducted using the more established\nregulatory law, the FSMA 2000, was taken as a basis for the analysis and evaluation.\nIt has been found that prior to Law No. 7 of 2010, regulation of market manipulation\npractises was almost non-existent. Law No. 7 of 2010 does largely cover most forms of\nmarket manipulation, excluding stabilizing the security price and information based on\nmanipulation of forms. Civil penalties, as compared with those in the UK, tend to be\nlenient, which may prove problematic in deterring manipulative practises. Judges in\ngeneral also lack the experience and confidence to apply and enforce sanctions\nregarding manipulative practises yet it must be noted that the law has not been in action\nfor very long. Thus, it is recommended that the fourth objective of the study be repeated\nafter the law has been in place for several years to reassess its success in combating\nmanipulative practises.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".