MODELLING THE DYNAMICS OF THE ADEQUACY OF BANK’S REGULATORY CAPITAL

MODELLING THE DYNAMICS OF THE ADEQUACY OF BANK’S REGULATORY CAPITAL

Katranzhy, Leonid;Podskrebko, Oleksandr;Krasko, Vitaliy;
baltic journal of economic studies 2018 Vol. 4 pp. 188-194
169
katranzhy2018modellingbaltic

Abstract

The purpose of the article is to develop scientific and methodological recommendations for modelling the dynamics of the level of capital adequacy for ensuring the financial balance of the bank, sufficient controllability and increasing the efficiency of its activities. The article explores peculiarities of banking regulation and supervision in the process of capital formation. It is shown that the issue of formation of capital by banking institutions is actualized in the context of management reform and target tasks of the development of the banking industry of Ukraine. Given the state of the banking services market and its development trends, the unsettled problem of the capitalization of banks, it becomes important to improve the mechanism of capital formation. In order to improve the efficiency of bank regulation and management of capital formation, recommendations are proposed for modelling the dynamics of the adequacy of regulatory capital on the basis of determining the forecast values of its components. Research methodology: the feasibility of using predictive models with the use of artificial neural networks is substantiated. In contrast to the classic trend, discussed in the article, the models with the architecture of the multilayer perceptron proved to be the most adequate and accurate. In addition to a point forecast of the dynamics of regulatory capital, the overall risk and the amount of the net foreign exchange position, their pessimistic and optimistic forecasts were constructed. The author’s proposals are formalized by appropriate calculation algorithms. Modelling the dynamics of the adequacy of regulatory capital and its components in practice will allow more efficiently manage systemic and individual banking risks.

Citation

ID: 18516
Ref Key: katranzhy2018modellingbaltic
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
18516
Unique Identifier:
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet