Earnings Management and Underpricing of Initial Public Offerings (IPO), Evidence from Iran
Bibliographic record
Abstract
The aim of this study is to answer an important but unanswered question about manipulation of earnings before initial public offerings. Several studies have examined earnings management in IPOs. In previous studies, researchers did not examine that firms manipulating income figures have seen little underpricing or confronted with larger underpricing despite aggressive earning management. We used somewhat new proxy of earnings management to test whether approximately high degree of earnings manipulation before IPO cause larger underpricing or not. This assertion is based on asymmetric information theory in underpricing literature that claims firms with approximately high degree of earnings manipulation have increased ex-ante uncertainty. As we know from research literature, increase in ex-ante uncertainty leads to steeper price discounts. However this is despite the prevailing hypothesis that firms going public can fool the market by offering higher prices for their shares. We did not find any significant relationship between earnings management and underpricing and thus our finding is consistent with the hypothesis that suggests high degree of earnings manipulation before going public leads to little underpricing.
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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 | 0.002 | 0.013 |
| 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 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".