The Underpricing of Initial Public Offerings: Further Canadian Evidence
Bibliographic record
Abstract
Evidence of underpricing of initial public offerings (IPOs) has spawned a considerable theoretical literature attempting to explain the apparent contradiction to market efficiency. This article reassesses that evidence by examining not just common shares Canadian IPOs, but also unit and Junior stock IPOs from the period 1991-1998. Our study shows that Canadian IPOs as major IPOs in the world are underpriced. However, the degree of underpricing depends on the type of the issue. Unit IPOs and Junior Capital Pool (JCP) IPOs are more underpriced than common shares IPOs. Our results also suggest that the IPO market in Canada is «good» only for large offerings. We have entertained a number of possible explanations for the high initial return of Canadian issuing firms. We find that the underpricing is significantly related to the size and the period of the issue and to whether the IPO is a JCP or not. On the other hand, the prestige of the underwriter is positively related to the underpricing but this relationship is not significant. La présente étude propose une analyse en profondeur du comportement des émissions initiales canadiennes de 1991 à 1998, en incluant les titres émis dans le cadre des programmes de Capital Pool. Les résultats montrent que la sous évaluation initiale persiste au Canada, en moyenne. Toutefois, le degrés de sous-évaluation est fortement lié au type d'émission: les émissions d'unités et celles qui se font dans le cadre des programmes de Capital Pool sont davantage sous évaluées que les émissions d'actions ordinaires hors Capital pool. Les émissions de taille moyenne et de grande taille semblent correctement évalués au Canada, contrairement à ce que l'on observe sur la plupart des marchés et notamment aux États-Unis. La sous-évaluation initiale concerne donc essentiellement les émissions de 20 millions de $ et moins, qui représentent toutefois 76, 3 p. cent des émissions analysées. La sous-évaluation initiale reste donc un problème majeur pour les petites et moyennes entreprises canadiennes. Parmi les autres explications possibles à la sous-évaluation initiale, seule la période d'émission semble jouer un rôle significatif, en plus de la taille et de l'appartenance ou non au programme des Capital Pool.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".