The Performance of Two Anchor Domestic Malaysian Banks before and after Acquisition
Bibliographic record
Abstract
This article is undertaken to assess the performance of domestic Malaysian banks before and after acquisition. This paper focuses on two pairs of anchor banks which merged and acquired other minor banks in Malaysia from year 2001 until 2013. The research period is 2 years before and 2 years after the acquisitions. The method being used in this research is financial ratios and event study. Nine selected financial ratios were used in this research to find the difference between pre and post acquisitions. Whereas event study is used to find the abnormal return, average abnormal return, cumulative abnormal return, and t-test hypothesis. The event window in this research is a total of 21 days before and after the acquisitions including the actual day of the event announcement. The results for this research indicate that there was improvement for Hong Leong Bank and EON Bank. RHB Bank on the other hand was outperforming by Bank Utama. There were limitation when carrying out this research such as difficulties to retrieve the needed annual report and historical price to conduct the investigation. The time lag on certain banks performance may need more time to see a better result while others may perform well in short period.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".