Stock Exchange Demutualization, Self-Listing and Performance: The Case of the Australian Stock Exchange
Bibliographic record
Abstract
This paper examines the effects of the recent spate of financial exchange mutual-to-stock conversion phenomenon on the performance of listed exchanges and the quality of the stock market using the Australian Stock Exchange (ASX) as a case study. We find that the ASX stock significantly outperformed the stock index and the control group on a market-adjusted return basis. The stock market performance is driven by strong operating performance. The profitability ratios of the ASX have significantly improved in the five years following the demutualization and self-listing. The performance improvements remain significant even after controlling for growth in the Australian economy. From a market quality perspective, we document evidence of increased trading activity by foreign investors after ASX's demutualization and self-listing. Interestingly, we also find that bid-ask spreads of the stock market have narrowed in the post-conversion period. In particular, small-cap firms have become more liquid. The results show that stock exchange conversion from mutual to publicly traded exchange is not only value enhancing for the exchange and its shareholders, but it is also beneficial for the stock market as a whole.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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 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".