Bibliographic record
Abstract
This paper considers a financier contemplating a venture capital investment in a firm whose true value is unknown. The financier must make information-gathering and investment decisions on an ongoing basis to decide whether to undertake the investment and, later, if he chooses to finance the firm, how to manage his investment. We characterize how the financier's information acquisition is affected by the liquidity of the market for his claims to the firm, and derive the implications for the pricing of the firm. We distinguish between two qualitatively different types of information acquisition: evaluation efforts made prior to a potential investment; and monitoring efforts of already-funded firms that impact upon the financier's decisions about whether to take an active position in the firm (e.g. replace management) and whether to change its financial stake. We investigate the effects of liquidity on share price, describing why the market responds more favorably to less liquid forms of finance, and explore the consequences for investor activism. Finally, we characterize the socially optimal levels of evaluation and monitoring in order to determine when a marginal increase in liquidity has welfare-enhancing effects on the financier's behavior.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".