Short-Term Price Effects of Stock Repurchases in Turkish Capital Markets
Bibliographic record
Abstract
Stock repurchase, as a corporate finance tool and a substitute for cash dividends, plays an important role in distributing excess cash. Following a prohibited period due to its potentially negative outcomes for shareholders and creditors, stock repurchase has recently been regulated within the company law systems of many countries pursuant to its increasing popularity in satisfying special financing requirements of companies. That the regulatory improvements have removed the uncertainty inherent in such transactions has increased the volume of, especially, the open market stock repurchases. Turkish legislation, i.e. Commercial Code and Capital Markets Law, has latterly been updated in accordance with EU acquis communautaire in order to allow stock repurchase for listed firms. We analyse movements in stock prices after stock repurchase transactions in order to make inferences about why stock repurchase is used and what its impacts/signals are in Turkish market at their infancy stage. Having followed a standard event study methodology, the results reveal that investor reaction to stock repurchase transactions is generally positive in the short-term. These results support the notion of a signaling hypothesis as a motivator behind stock repurchase decisions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".