Effect of Liquidity on Size Premium and its Implications for Financial Valuations
Bibliographic record
Abstract
Courts are often required to determine a stock’s “fair value,” which by definition excludes any reduction to value because of a lack of liquidity. The method of computing fair value most frequently used by practitioners is the discounted cash flow analysis, which requires calculating the cost of equity. Over the last decade, many practitioners have included a size premium in the computation of the cost of equity based on the finding that historic returns for firms with lower market capitalization are greater than the returns implied by the standard capital asset pricing model. Our findings show that a substantial fraction of the measurement of size premiums reflects a lack of liquidity, which disproportionately affects smaller sized companies. Because a reduction to value from illiquidity should not be reflected in the measurement of fair value, this finding has implications for assessments of fair value that employ the commonly used size premiums. Specifically, our findings suggest that valuations of small capitalization stocks that reflect these size premiums will cause the fair value to be underestimated because of the effect of lower liquidity. The smaller the size, the greater is the underestimation in value.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".