arbiter
JournalsAccount

Analysing the Bankers’ Ratings Worldwide Using Machine Learning Techniques

Indranarain Ramlall & Moses Acquaah

International Journal of the Economics of Business2025https://doi.org/10.1080/13571516.2025.2531821article
AJG 2ABDC B
Weight
0.50

Abstract

No abstract available.

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.1080/13571516.2025.2531821

Or copy a formatted citation

@article{indranarain2025,
  title        = {{Analysing the Bankers’ Ratings Worldwide Using Machine Learning Techniques}},
  author       = {Indranarain Ramlall & Moses Acquaah},
  journal      = {International Journal of the Economics of Business},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/13571516.2025.2531821},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Analysing the Bankers’ Ratings Worldwide Using Machine Learning Techniques

Flags are reviewed by the Arbiter methodology team within 5 business days.

Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.