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Record W2792630860 · doi:10.5539/ibr.v11n4p96

CAMEL Analysis on Performance of ASEAN Public Listed Banks

2018· article· en· W2792630860 on OpenAlexvenueno aff
Rossazana Ab-Rahim, Norlina Kadri, Amy-Chin Ee-Ling, Abdul Alim Dee

Bibliographic record

VenueInternational Business Research · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicBanking stability, regulation, efficiency
Canadian institutionsnot available
FundersUniversiti Malaysia Sarawak
KeywordsAsset qualityBusinessMarket liquidityCapital adequacy ratioAsset (computer security)Quality (philosophy)Financial systemFinanceAccountingEconomicsIncentive

Abstract

fetched live from OpenAlex

The study is conducted to measure the performance of public listed banks in five ASEAN countries. This study covers 63 public listed banks from Malaysia, Singapore, Thailand, and the Philippines over the period of 1997 to 2011. The CAMEL analysis which is based on Capital Adequacy, Asset Quality, Management Efficiency, Earning Quality, and Liquidity is employed in this study. The objectives of the study are to measure the performance of public listed banks as well as to compare the performance across countries. The results of the CAMEL analysis show that Singaporean public listed banks are the top performer as compared to their counterparts. Next, the comprehensive results reveal that Public Bank in Malaysia, United Overseas Bank in Singapore, Bank ArthaGraha in Indonesia, Bank of Ayudhya in Thailand and Union Bank of the Philippines are the top performed banks.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.094
GPT teacher head0.339
Teacher spread0.244 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2018
Admission routes1
Has abstractyes

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