Recognition versus Disclosure of Stock Option Compensation: An Analysis of Judgements and Decisions of Nonprofessional Investors*/CONSTATER OU PRÉSENTER PAR VOIE DE NOTE LA RÉMUNÉRATION SOUS FORME D'OPTIONS D'ACHAT D'ACTIONS: UNE ANALYSE DES JUGEMENTS ET DES DÉCISIONS DES INVESTISSEURS NON PROFESSIONNELS
Bibliographic record
Abstract
ABSTRACT Given the importance of stock options in the aggregate compensation of chief executive officers and other firm employees in the 1990s and early 2000s, the International Accounting Standards Board issued an International Financial Reporting Standard on stock‐based payments on February 19, 2004, requiring that all share‐based payment transactions be recognized at fair value in entities' financial statements. The Canadian Institute of Chartered Accountants' Accounting Standards Board had already agreed to this principle and amended section 3870 of the CICA Handbook (stock‐based compensation) for financial periods beginning on or after January 1, 2004, making Canada the first major jurisdiction to require all public companies to expense employee stock‐based compensation awards. The revised section eliminated the possibility of disclosing pro forma net income and earnings per share only by way of a note. This research, conducted as a between‐subjects experiment with executive MBA students as nonprofessional investors, examines whether changes in the way stock option compensation is reported (recognition as an expense in the income statement or note disclosure of pro forma net income and earnings per share) affect financial statement users' judgements and investment decisions. Our results indicate that, consistent with the functional fixation hypothesis, the reporting method does indeed significantly influence subjects' judgement of the expected stock price direction, but has no material influence on their investment decisions.
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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 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".