Asymétrie d’information et marchés financiers : une synthèse de la littérature récente
Bibliographic record
Abstract
Cet article est une synthèse des recherches récentes en matière d’asymétrie d’informations sur les marchés financiers. L’impact de différentes hypothèses sur l’existence et l’efficience informationnelle des équilibres est étudié. Le cas de la concurrence parfaite est d’abord analysé (Grossman et Stiglitz, 1980). Puis la concurrence imparfaite est analysée. On distingue deux cas, selon que le bruit qui empêche le prix d’être parfaitement révélateur provient d’une offre exogène (KyIe, 1985, 1989), ou d’une dotation aléatoire des agents informés (Glosten, 1989; Bhattacharya et Spiegel, 1990; Bossaerts et Hughson, 1991). Dans le premier cas, l’équilibre existe toujours. Dans le second cas, il n’existe que si le bruit est assez élevé ou si le support de sa distribution est borné.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; both teacher heads agree on what is shown here.
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".