Anomalous Price Behaviour around Open Market Stock Repurchase Announcements in India
Bibliographic record
Abstract
Executive Summary This article examines the impact of open market share repurchase announcements on stock returns in the Bombay Stock Exchange (BSE). The main objective is to examine whether share repurchase announcements under the open market route have any significant impact on the returns of the stocks traded in the BSE. The article covers the period from 2009 to 2013. For sample selection, two criteria were used: first, the firm should have been listed in the BSE for at least 28 trading days before the repurchase announcement date, and second, the firm should have all relevant data required by this study. A total of 95 repurchase announcements fulfilled these criteria. The analysis period extended from –28 to +28 trading days relative to the repurchase announcement date ( t = 0). The findings of the study will help us to understand how the market responds to share repurchase announcements in India and whether a firm actually benefits by repurchasing its own shares from the market. This study uses a standard event methodology based on an ordinary least squares market model with the aim of finding out whether repurchase announcements generate any abnormal return around the repurchase announcement date. While applying the market model for estimating the abnormal returns, the regression is estimated based on the stock return of the firm and market return of the previous 120 trading days. So, here the estimation window takes into account 120 observations. Using this, the expected returns are generated and then the abnormal returns are derived for the event window, 28 days prior to the event date and 28 days after the event date. The findings of the study indicate that share repurchase announcements do not necessarily generate abnormal stock returns in the Indian equity market unlike developed economies like the US, Canada, and Australia. The whole sample is further divided into various subsamples on the basis of firm size and size of repurchase. The subsample analyses reveal that smaller firms do not necessarily experience higher abnormal stock returns following repurchase announcements than that of the larger firms. The findings weakly support the view that larger repurchase size generates greater abnormal stock returns than the smaller ones.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".