Mandatory Disclosures and Market Reaction: Evidence from Qatar Stock Exchange
Bibliographic record
Abstract
Information disclosure, inter alia, has a tremendously increasing impact on the stock market. This study aims to investigate the reaction of stock market to the mandatory disclosures in Qatar Stock Exchange (QSE) for the period 2020-2022. To be precise, the paper investigates the market reaction as indicated by the trading volume and stock price change to disclosure of periodic financial reports (quarterly, semi-annual, and annual) and company news and, subordinately, the relationship between trade volume and stock price change of the 47 (±1) traded listed companies on the QSE for the period spans from January 2020 to October 2022. Trading volume, all market share index value and stock price change were descriptively analyzed, then investigated using a one-to-one period approach, pre and post disclosure. In consistency with a priori predictions, the result shows significant market reaction as indicated by the volatility of both trade volume and stock price change. Moderate evidence is given to support the market reaction to the periodic disclosure other than annual financial reports. Additionally, findings show a weak positive relationship between trade volume and stock price change. Interestingly, the investigation provides substantial support to the weak form market efficiency, at least for the widely traded stocks. This indicates that insiders are not being better informed about the company’s true value than outsiders in the QSE. Finally, results support to the widely held belief, but heretofore undocumented evidence from the region, that permanent disclosures provide information benefits to investors and, hence, greater benefit.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".