Concentration in mutual fund equity holdings during global economic crises
Bibliographic record
Abstract
This study examines whether portfolio equity concentration at the country, industry, and security levels results in better performance of global mutual funds during periods of significant shocks to the global economy. We document that mutual funds’ equity portfolios are more concentrated across countries and industries during economic crises, and fund managers engage in more active security selection rather than passive benchmark investing. More concentrated equity allocations are associated with higher portfolio returns and appear to be driven by information advantage. Overall, results suggest that mutual fund managers employ information advantage and generate higher risk-adjusted returns with concentrated positions in global markets during times of negative shocks to the global economy. • Mutual funds increase portfolio concentration across countries, industries, and securities during global economic crises. • Greater concentration is associated with higher risk-adjusted returns. • Fund managers allocate more to geographically and culturally proximate markets during crises, generating higher returns. • Concentration benefits are driven by improved stock selection and market-timing, especially during crises. • Fund managers capitalize on global market uncertainty and actively exploit crises to generate higher risk-adjusted returns.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".