Shifts in the portfolio holdings of euro area investors in the midst of COVID‐19: Looking‐through investment funds
Bibliographic record
Abstract
Abstract We study the impact of the COVID‐19 shock on the portfolio exposures of euro area investors. The analysis “looks‐through” holdings of investment fund shares to first gauge euro area investors' full exposures to global debt securities and listed shares by sector at end‐2019 and to subsequently analyse the portfolio shifts in the first and second quarters of 2020. We show heterogeneous patterns across asset classes and sectors, but also across less and more vulnerable euro area countries. In particular, we find a broad‐based rebalancing towards domestic sovereign debt at the expense of extra‐euro area sovereigns in the first quarter of 2020, consistent with heightened home bias, which however levelled off in the second quarter. On the contrary, for listed shares we find that euro area investors rebalanced away from domestic towards extra‐euro area securities in both the first and the second quarter, which may be associated with better relative foreign stock market performance. Many of these shifts were only due to indirect holdings, corroborating the importance of investment funds in assessing investors' exposures—especially for households, insurance companies and pension funds—in particular in times of large shocks. We also confirm the important intermediation role played by investment funds in an analysis focusing on the large‐scale portfolio rebalancing observed between 2015 and 2017 during the ECB's Asset Purchase Programme.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".