Short-term institutional investors and the diffusion of supply chain information
Bibliographic record
Abstract
What informational advantage do short-term investors have? This paper demonstrates that short-term investors can benefit from the ability to process public, but slowly diffusing, supply chain information ahead of other market participants. In support of this argument, we find that short-term investors establish larger long and short positions in firms with high customer concentration. In addition, an increase in short-term institutional ownership is associated with higher stock returns in firms with high customer concentration, supporting the informational advantage hypothesis. Finally, the relationship between customer concentration and short-term institutional ownership strengthens in high information asymmetry environment. In contrast, we do not find preference towards high customer concentration firms among long-term institutions, who are less positioned to exploit short-lived informational benefits. • Short-term investors have skills to process public but slowly diffusing supply chain data. • Short-term investors take larger positions in firms with high customer concentration. • These positions, in turn, are associated with higher stock returns. • Long-term institutions show no preference for firms with high customer concentration.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".