Demand-Supply Mismatches and Stock Market Reaction: Evidence from Excess Inventory Announcements
Why this work is in the frame
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Bibliographic record
Abstract
This paper documents that excess inventory announcements, an indication of demand-supply mismatch, are associated with an economically and statistically significant negative stock market reaction. The results are based on a sample of 276 excess inventory announcements made during 1990–2002. Over a two-day period (the day of the announcement and the day before the announcement) the mean (median) stock market reaction ranges from −6.79% to −6.93% (−4.51% to −4.79%), depending on the benchmark used to estimate the market reaction. The percent of sample firms that experience negative market reaction ranges from 73% to 74%. When excess inventory is at the announcing firm's customers, the market reaction is more negative than when the excess inventory is at the announcing firm. The stock market reaction is less negative for excess inventory announcements made by larger firms but is more negative for firms with higher growth prospects and with higher debt-equity ratios.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| 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 it