Does sustainability affect performance and systematic risk of IPO-focused mutual funds?
Bibliographic record
Abstract
Previous studies have shown that environmental, social, and governance (ESG) commitment affects the underpricing level of new issues. In this study, we argue that ESG’s impact on mutual fund performance could depend on funds’ strategy in investing in initial public offerings (IPOs). We focus on the performance and systematic risk exposure of IPO funds compared to matched non-IPO funds according to their ESG risk ratings. Using a sample of 184 U.S. funds between 2015 and 2021, we find that ESG factors negatively (positively) affect IPO (non-IPO) fund performance during the full period. However, for the pandemic crisis period, our results support the outperformance of low ESG-risk funds, regardless of whether they were focused on IPOs. It appears that investors require a much higher systematic risk premium to invest in high-ESG-risk funds compared to low-ESG-risk funds during crisis periods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| 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".