International Development Banks as Centers of Technological Exchange: Is Future Here?

Gobareva, Yana L.; Gorodetskaya, Olga Yu.; Karp, Marina V.; Guliev, Igbal А.

doi:10.13189/ujaf.2021.090306

Cited by 2 publications

(3 citation statements)

References 9 publications

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“…When processing the data, we used the winsorization method and our experiments with its limits (tails) agree with the recommendations of researches [46][47][48][49][50]: a two-way limit of 1% for further work with the UMAP algorithm showed an excellent result. We also conducted a number of our own experiments with limits, reducing the dimensionality of different datasets, and found an improvement in the quality of t-SNE clustering at the lower and upper limits of 2% and 5%, respectively.…”

Section: Discussionsupporting

confidence: 73%

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Application of Clustering in the Dimensionality Reduction Algorithms for Separation of Financial Status of Commercial Banks in Ukraine

Velykoivanenko¹,

Korchynskyi²

2022

ujaf

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The issue of determining the financial condition of commercial banks and separating investment-attractive banks from problem banks on this ground is extremely important for developing countries. The aim of this study is to make sure on the example of Ukraine that commercial banks really form separate clusters, where more reliable, stable and efficient banks are well separable from less successful ones in this regard. The study used the t-SNE and UMAP dimensionality reduction algorithms, and the Ward's Agglomerative Hierarchical Clustering algorithm. The results of visual analysis of two-dimensional t-SNE projections show that banks of different degrees of risk are well separable and have their own specifics. Clustering in the UMAP algorithm allowed distinguishing clusters with banks of Class A, "mid-tier" and problematic banks by different parameters. The t-SNE and UMAP algorithms for solving the problem are compared. The results show that a purely visual analysis of the two-dimensional map for the banks over the last period is best made using the t-SNE algorithm. UMAP, on the other hand, is proved to be excellent when used in tandem with the clustering algorithm.

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Section: Discussionsupporting

confidence: 73%

“…This allows you to track changes in the dynamics and respond quickly to changes. An important role in this is played by central banks, which stimulate technology transfer [50]. Communication of central banks at the international level provides an exchange of new technologies and methods of assessing financial condition.…”

Section: Discussionmentioning

confidence: 99%