Bibliographic record
Abstract
The conventional assumption in the asset pricing literature is that the identity of a company's owners is largely irrelevant, but studies of companies with “blockholders”—shareholders with large positions in a particular company—provide grounds for questioning this assumption. Unlike the well‐diversified investors of modern portfolio theory, blockholders have strong incentives to monitor corporate performance and, when necessary, to exert control over ineffective managements and boards. The findings of many studies support the idea that blockholders have a positive effect on rates of return. The authors of this article report the findings of their recent investigation of whether blockholders might also have a positive effect on shareholder value by reducing the risk of the companies in which their holdings are concentrated. After distinguishing between companies with individual as opposed to corporate blockholders, and those with one share, one vote as opposed to those with dual‐class shares, the authors find that ownership of large positions by individuals—but not corporations—was associated with lower systematic risk (when using both Fama‐French multiple factor and CAPM models). At the same time, they find that the firm‐specific risk of such companies was higher, but “biased” toward positive outcomes—that is, smaller downsides with larger upsides. What's more, this upward shift in performance and risk‐profile was achieved at least partly through increases in productivity as reflected in higher profit margins, profitability, profit per employee, and operating leverage, and lower costs of goods sold, SGA, and cash holdings. By contrast, in the case of blockholders in companies with dual‐class share structures, all of these positive associations with blockholders were either significantly weaker, or reversed. That is, whereas the presence of individual blockholders appears to increase productivity and value under a one share, one vote governance regime, blockholders in companies with dual‐class structures were associated with higher systematic risk and reduced productivity and value.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".