CANADIAN WATER TREATMENT COMPANY COMPLETES IPO
Bibliographic record
Abstract
In this paper, we empirically investigate Korean initial public offerings (IPOs) to provide one case of the international evidence on the long-run performance of IPOs. Our sample consists of 169 firms listed on the Korea Stock Exchange during the period 1985–1989. Unlike previous international evidence, our results reveal that the Korean IPOs outperform seasoned firms with similar characteristics. Much of the overperformance, however, takes place during the first month of seasoning and the long-run performance of Korean IPOs exclusive the first month of seasoning is not statistically different from that of seasoned firms. Our results also suggest that the existing theories on the long-run performance (Miller (1977) and Shiller (1990)) do not apply to the case of Korean IPOs. Finally, we find that the deregulation of June 1988 had a mixed impact on the aftermarket performance of Korean IPOs. It reduced the degree of initial underpricing but had no impact on IPOs' long-run performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads 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".