Managerial Timing and Corporate Liquidity: Evidence from Actual Share Repurchases
Bibliographic record
Abstract
The purpose of this paper is to investigate the timing of open market share repurchases and its resultant impact on corporate liquidity. We identify the exact implementation dates for over 5,000 equity buybacks on the Stock Exchange of Hong Kong between November 1991 and August 1999. A bootstrapping method is used to distinguish managerial timing ability from a naive accumulation plan. The results show that managers exhibit substantial timing ability. Consistent with the information-asymmetry hypothesis (Barclay and Smith (1988 Journal of Financial Economics 22, 61-82)), we find strong evidence that bid-ask spreads widen and depths narrow during repurchase periods. We further decompose bid-ask spreads and show that the adverse selection component increases substantially when market participants respond to the presence of informed managerial trading. Overall, our market timing, spread and depth, and decomposition results reveal a coherent picture of managerial buyback behavior and its impact on firm liquidity. Our results have significant implications for corporate payout and disclosure policies.
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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 | 0.001 | 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".