A study on the effect of stock liquidity and stock liquidity risk on information asymmetry: Evidence from Tehran Stock Exchange
Bibliographic record
Abstract
This study investigates the effect of stock liquidity and stock liquidity risk on information asymmetry in Tehran Stock Exchange (TSE) listed companies.In this study, the bid-ask spread is considered as the criterion of information asymmetry.In addition, stock trade volume and the number of stock trades are considered as the criteria of stock liquidity.Some variables such as size, stock price, beta and growth are also considered as control variables.To test the hypotheses of the survey, 202 TSE listed companies over the period 2007-2012 are considered based on the multiple regression (Panel) method.The evidence shows that both proposed criteria, stock liquidity criterion as well as the stock trade volume and the number of stock trades, had negative effects on information asymmetry, but this effect is not statistically meaningful.In addition, evidence shows that stock liquidity risk had positive effect on information asymmetry, which is statistically meaningful.Research results also show that firm size and beta had positive and meaningful effects on information asymmetry.Finally, the results show that growth and stock price had negative meaningful effects on information asymmetry.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".