Impact of Number of Security Analysts in Liquidity of Brazilian Stocks
Bibliographic record
Abstract
This study investigates impacts of sell-side analysts in the liquidity of firm’s shares of Brazilian Capital Markets. Liquidity hypothesis studied by Brennan and Subrahmanyan (1995), Brennan and Tamarowski (2000), Amihud and Mendelson (1986, 2000) and Amihud et al. (1997) defines that an increase in the number of analysts covering a particular stock increases its liquidity causing a positive impact on the stocks prices. This work investigates empirically whether increasing number of securities analysts impacts stock market liquidity, as observed in the American market by Brennan and Tamarowski (2000), using a sample of 179 listed stocks in the Brazilian stock exchange, BM&FBovespa. This work determines liquidity-measuring firm’s Lambda dollar derived by Kyle (1985) and then applying cross section regression of Lambda dollar as dependent variable and number of analysts as independent variable. Results indicate that stock market liquidity increased with number of securities stock analysts in favor of liquidity hypothesis.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".