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Record W2509652892 · doi:10.5430/afr.v5n3p190

Growth of Stock Market in the UAE through Merger: A Comparative Study of GCC Stock Markets

2016· article· en· W2509652892 on OpenAlexvenueno aff
Robinson Joseph, Manuel Trinidad‐Fernández

Bibliographic record

VenueAccounting and Finance Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicIslamic Finance and Banking Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStock exchangeBusinessMarket capitalizationProfitability indexRevenueStock marketStock (firearms)Abu dhabiCapitalizationFinancePrimary marketIndustrial organizationEconomics

Abstract

fetched live from OpenAlex

In recent years, stock exchanges have increasingly been forming alliances or merging with each other. This study is carried out with the objective of finding out the benefits of having a larger single stock market in the UAE instead of the present two separate markets: Abu Dhabi Securities Exchange and Dubai Financial Market. The study covers a period of five years from 2010 to 2014. This study is based on secondary data collected from various stock exchanges in the GCC. The various stock markets in the GCC are compared against each other on the basis of volume and value of trading, market capitalization, number of shares listed and number of days traded. Then, a similar analysis is carried out with the combined ADX and DFM. It is observed that the merger of ADX and DFM brings in benefits on all these parameters. The study also shows that the merger will benefit all the stakeholders by reducing cost of operations facilitated by the large scale operations, sophisticated technology, single trading platform, one investor number, lower trading cost and earlier break-even. Moreover, through the merger the UAE will be able to attract more local and regional companies which will enhance the revenue, profitability and presence in the region.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.068
GPT teacher head0.335
Teacher spread0.267 · 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

Citations3
Published2016
Admission routes1
Has abstractyes

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