Unlock Day Expiration and Mandatory IPOs Lock up Among ACE Firms in Malaysia
Bibliographic record
Abstract
This research studied the role of lockup in assessing price and volume of IPOs during the expiration of lockup in Malaysian market. The reaction of price is measured by the abnormal return while the reaction of volume is measured by the abnormal volume. The companies were selected from the years 2010 to 2018 and only companies that were still listed in Bursa Malaysia were chosen. The time frame of the study was 30 days before and 30 days after the expiration date of lock up provision. The results may show for these circumstances of i) the volume will remain and the price will decrease; ii) volume will be decreased and price will be decreased too and iii) promoters retain percentage of shares during expiration date. For situation number i), it might show the sign of a quite good quality of performance of IPOs in stock market. Evidently, the second circumstance shows decrease in price and volume of IPOs after expiration date. The scenario actually leads by demand and supply of stock. Another important evidence which supports the insignificant result is promoters retain percentage of shares during expiration date. The amounts that should be released by the companies are not offered to the market during that time. By looking at the Signaling Theory, insiders of IPOs firms who are previously restricted from selling their holdings have the first chance to sell large propositions of their shares. Investors will know the dates of IPO lockup expiration and numbers of shares by looking at the prospectus. Due to the scenario, the price and volume of IPOs will be reacting during expiration date based on this theory. It is hoped that this study will help investors or any Malaysian market participation especially in the IPOs market to notice the situation in Malaysian market regarding the lock up provision.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".