The Paradox of “Fraud‐on‐the‐Market Theory”: Who Relies on the Efficiency of Market Prices?
Bibliographic record
Abstract
Our evidence points to an inconsistency between the efficient markets hypothesis and the way U.S. courts have applied the hypothesis in cases involving allegations of fraud on the market. Based on a sample of securities class action cases, we find that (1) some cases certified for class action status do not satisfy the conditions for even weak‐form efficiency; (2) numerous opportunities exist for cost‐effective investors (those who can trade quickly and at low cost) to profit by using simple momentum‐based strategies; (3) including such investors as class members effectively subsidizes their strategies and overstates damages from reliance on market efficiency; (4) when such investors can profit by rejecting market efficiency, standard measures of damage overstate the fraud‐related damage of other investors; and (5) because of endogeneity, the factors that commonly are relied on by the courts for determining market efficiency bear little or no relation to weak‐form efficiency.
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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 | 0.057 | 0.172 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.030 |
| Scholarly communication | 0.012 | 0.024 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 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".