Do ESG fund managers pump and dump the stocks in their portfolios? European evidence
Bibliographic record
Abstract
Abstract We investigate portfolio pumping around quarter-ends by ESG equity mutual funds domiciled in the largest European markets in sustainable investments, i.e., the UK, France and Germany, for the period from January 2010 to December 2022. We find strong evidence that the UK funds inflate quarter-end returns, with price spikes being stronger at year-ends; nevertheless, the magnitude of price inflation is less than that of their conventional counterparts. On the contrary, results indicate that German and French funds do not engage in portfolio pumping. The COVID-19 pandemic strengthened the propensity of fund managers to cause a profound artificial enhancement to the performance of the investment portfolio. Further analysis shows that portfolio pumping is more prominent among the worst-performing funds, funds that charge investors with lower fees and achieve a poor ESG rating. However, managers that pump fund returns do not attract significantly more flows. Our results have produced valuable insights for regulators and investors participating in ESG markets, highlighting the necessity for a rigorous surveillance of the UK ESG equity market.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".