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Are the Islamic Banks Really more Profitable than the Conventional Banks in a Financial Stable Period?

2019· article· en· W2974089393 on OpenAlexaff
Achraf Haddad, Anis El Ammari, Abdelfettah Bouri

Bibliographic record

VenueAsian Economic and Financial Review · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsProfitability indexFinancial systemBusinessIslamPopulationSample (material)Stock marketEconomicsMonetary economicsFinance

Abstract

fetched live from OpenAlex

The international banking sector is dominated by the conventional banks but the global market share of the Islamic banks is increasing gradually. This study determines which model maximizes a bank’s profitability in several heterogeneous contexts and over a financial stable period (2010-2018). Most previous studies examined banking profitability in commercial conventional and Islamic banks providing a limited literature. We retained three categories for each type of banks (commercial, investment and universal) because of the predominance of these categories in the money market. Within the framework of this study, two samples were taken from two reference populations. Basic populations were composed of all active conventional and Islamic banks existing in the selected countries. The choice of the banks is limited to the countries whose banking structures incorporate simultaneously the two types of banks independently of the proportion of each system in each country banking market. We then reduced the size of each population focusing on qualitative and quantitative filtering criteria, so that each conventional bank had its Islamic equivalence in terms of capital and size in the same country. This restriction reduced the sample size to 63 large banks for each type. The two banks’ samples were selected from sixteen countries and were listed in different stock exchanges around the world. Consequently, the empirical results showed that the conventional banks were more profitable than the Islamic banks during the period of financial stability.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.668

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.009
GPT teacher head0.213
Teacher spread0.204 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations12
Published2019
Admission routes1
Has abstractyes

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