INVESTORS’ BEHAVIOR IN THE CONTEXT OF STOCK MARKET— \nA REACTION TO THE CHANGE OF CEO ANNOUNCEMENTS
Bibliographic record
Abstract
ABSTRACT \nCEO is the most eye-catching person to the investors, scholars, and practitioners. The impact of changing a new CEO on the movement in the value of the relevant share price is studied in this dissertation. An event study has been applied to capture the effect of CEO change event through a cross-country and industry level with unique hand-collected data. This work extends existing work that focuses on CEO succession issue. \n \nMain findings of this dissertation are: UK and Oceania investors generally view CEO change as a positive event, which relevant share price increase after that change, while investors from west Europe are indifferent with the CEO change announcement or news. However, the North American stock markets (US and Canada) basically view CEO change as negative information to the company and its security. Securities from financials industry show positive reactions to CEO change, while securities from consumer discretionary industry and utilities industry present negative reactions to CEO change event. The largest abnormal return of a CEO event-related share price appears on the day following announcement date. New information will be incorporated into price slowly in 5 to 7 trading days whatever in which country.
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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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".