Demutualization in Developing and Developed Country Stock Exchanges
Bibliographic record
Abstract
This study considers seven different stock exchanges in order to measure the impact of demutualization announcements on stock market return volatility. This is measured based on the daily index prices of all seven indices: the Toronto Stock Exchange (TSX) in Canada, the FTSE 100 in the UK, the Straits Times Index (STI) in Singapore, the Nikkei 225 in Japan, the Kuala Lumpur Composite Index (KLCI) in Malaysia, the SENSEX in India, and the Hang Seng Index (HSI) in Hong Kong, China. A dummy variable is used to differentiate between pre- and post-event data. We use the augmented Dickey–Fuller test, the ARCH LM test and GARCH (1, 1) methodology to measure return volatility due to demutualization announcements. The results show that the decision to demutualize did not affect the UK, Singapore, and Indian stock markets, where volatility is explained by other factors. It did, however, affect the Canadian, Japanese, Hong Kong, and Malaysian stock markets. Moreover, the Canadian and Malaysian market swere negatively affected, while the Hong Kong and Japanese markets reacted positively to the demutualization announcements.
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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 | 0.000 |
| 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 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".