How Syndicate Short Sales Affect the Informational Efficiency of IPO Prices and Underpricing
Bibliographic record
Abstract
Abstract When a company goes public, it is standard practice that the underwriting syndicate allocates more shares than are issued. The underwriter thus holds a short position that it commonly fills by aftermarket trading when market prices fall or, when prices rise, by executing the so-called overallotment option. This option is a standard feature of initial public offering (IPO) arrangements that allows the underwriter to purchase more shares from the issuer at the original offer price. We propose a theoretical model to study the implications of this combination of short position and overallotment option on the pricing of the IPO. Maximizing the sum of both the profits from their share of the offer revenue and the potential profits from aftermarket trading, we show that underwriters strategically distort the offer price. This results either in exacerbated underpricing when favorably informed underwriters lower prices to secure a signaling benefit, or in informationally inefficient offer prices when underwriters pool in offer prices irrespective of their information.
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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 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".