The Emergence of Concentrated Ownership and the Rebalancing of Portfolios due to Shareholder Activism in a Financial Market Equilibrium
Bibliographic record
Abstract
Consider a …nancial market equilibrium with correlated …rms and risk averse investors holding diversi…ed portfolios. When an activist investor has the ability to perform valueenhancing activities in a single …rm, and these activities increase with ownership, we show that optimizing behavior by all investors leads to a concentration of shares in the hands of this activist. This concentration arises in the presence of complete information and is a consequence of Walrasian equilibrium mechanisms that include all investors and give no special powers to any of them in the equilibrium process. By yielding more ownership to the activist, all investors alter the risk pro…les of their holdings, ending with less balanced portfolios. This rebalancing e¤ect is accompanied by an increase in the price of the security that the activist can a¤ect, as well as in the total value of the market. When the activist can a¤ect more than one …rm, rebalancing of all portfolios again occurs. Although the activist may not acquire increased concentration in all the …rms she might a¤ect, prices change for all those …rms, and we give conditions under which at least one price must increase. We …nd that equilibrium results in a sharing of the costs and bene…ts of activism among all market participants, mitigating the free-rider problem. When we study multiple activists in many
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".