The price, liquidity and information asymmetry changes associated with new S&P 500 additions
Bibliographic record
Abstract
Purpose Using S&P 500 additions, the purpose of this paper is to test the permanence of abnormal returns around the index inclusion announcement and effective implementation dates to differentiate among competing explanations for the index inclusion premia puzzle. Design/methodology/approach The event study methodology is used to examine abnormal returns and volume effects around the announcement dates (ADs) and implementation dates of index additions. Findings This study documents a twofold increase in trading volume and significant permanent abnormal returns at the ADs that are correlated with subsequent decreases in bid‐ask spreads. There is a fivefold increase in trading volume, but only temporary abnormal returns, around the effective dates (EDs). Taken collectively, the evidence indicates that the permanent return at announcement is best explained by liquidity/information cost explanation, but the temporary return and large trading increases at the ED can best be attributed to the price pressure hypothesis. Research limitations/implications These results do not support the well documented long‐run downward‐sloping demand curve as the primary explanation for the abnormal returns observed on these dates. Originality/value This study contributes to the body of literature on the index inclusion effect by providing supporting evidence for the liquidity/information cost explanation, and by extending the previously analyzed index additions with an additional five‐year period from 2000‐2004.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".