Bibliographic record
Abstract
Purpose – This study aims to explore information asymmetry (IA) (as measured by the adverse selection component of the bid-ask spread) around S&P 500 revisions. Design/methodology/approach – The authors use adverse selection cost of trading measures to examine the effects of S&P 500 index composition changes on the trading environment from 2001 to 2010. Findings – The authors find that the adverse selection cost of trading significantly decreases post-addition and increases post-deletion. However, the intraday price dynamics of additions to the index seem to be distinct from those of deletions from the index. The event period cumulative abnormal returns (CARs) for additions are significantly associated with the change in the adverse selection cost of trading. However, this association is non-significant for deletions. The CARs for deletion events are found to be significantly associated with the change in realized spreads. Realized spreads are a measure of revenue earned by liquidity providers in the market. Originality/value – This study helps better understand the dynamics of two types of IA – one from a firm to investor and the other between investors – and presents evidence of the role of adverse selection in index changes. By doing so, it helps better understand the mechanism driving price formation post-addition to and deletion from an index.
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 | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".