+7 925 966 4690, 9am6pm (GMT+3), Monday – Friday
ИД «Финансы и кредит»

JOURNALS

  

FOR AUTHORS

  

SUBSCRIBE

    
Financial Analytics: Science and Experience
 

A study of the market share of loan portfolio through a neural network

Vol. 10, Iss. 11, NOVEMBER 2017

PDF  Article PDF Version

Received: 17 May 2017

Received in revised form: 30 August 2017

Accepted: 21 September 2017

Available online: 15 November 2017

Subject Heading: MATHEMATICAL ANALYSIS AND MODELING IN ECONOMICS

JEL Classification: C45, C58, C81

Pages: 1220–1233

https://doi.org/10.24891/fa.10.11.1220

Lomakin N.I. Volgograd State Technical University, Volgograd, Russian Federation
tel9033176642@yahoo.com

Femelidi Yu.V. Volgograd State Technical University, Volgograd, Russian Federation
yul010294@gmail.com

Subject The article studies the evolution of the credit portfolios of Russian banks during the period under review using the self-organizing map (SOM).
Objectives The article aims to prove or refute the hypothesis that by using a neural network, i.e. self-organizing map, it is possible to predict the changes in the market share of bank's credit portfolio.
Methods For the study, we used the self-organizing map.
Results We have developed and now present a neural network model that helps predict the market share of an advances portfolio in a changing market under economic uncertainty environment.
Conclusions and Relevance The application of the self-organizing map is important for obtaining some statistical information on commercial banks in the model clusters, as well as for forecasting the market share of the organization in a changing market environment. The results of the study can be used in the area of bank marketing to generate predictions of the market share of the bank when the size of its portfolio changes.

Keywords: market share, portfolio, Kohonen map, neural network, marketing policy

References:

  1. Belyaev V.I., Krotova M.V. [Marketing strategies of the development of enterprises in the service sector: Methods of formation and justification]. Vestnik Altaiskogo gosudarstvennogo agrarnogo universiteta = Bulletin of Altai State Agricultural University, 2015, no. 1, pp. 156–159. URL: Link (In Russ.)
  2. Kukhlev B.E. [Application of Porter's Five Forces Framework and SWOT analysis for planning of an agrarian enterprise's activities: Evidence from OAO Del'ta-Agro]. Regional'naya ekonomika: teoriya i praktika = Regional Economics: Theory and Practice, 2012, no. 5, pp. 52–56. URL: Link (In Russ.)
  3. Balyberdin V.A., Belevtsev A.M., Benderskii G.P. Prikladnye metody otsenki i vybora reshenii v strategicheskikh zadachakh innovatsionnogo menedzhmenta [Applied methods of assessment and decision making in strategic problems of innovation management]. Moscow, Dashkov i Ko Publ., 2014, 240 p.
  4. Grebenik T.V. [Modern features of effective management of loan portfolio quality]. Naukovedenie, 2014, no. 5, p. 145. (In Russ.) URL: Link
  5. Grishankin A.I., Lomakin N.I. [Financial risk management algorithm based business method of fuzzy]. V mire nauchnykh otkrytii = In the World of Scientific Discoveries, 2013, no. 12, pp. 115–140. (In Russ.)
  6. Yakovenko S.N., Markelova A.S. [Optimization of quality assessment and management of the loan portfolio of commercial bank]. Ekonomika i predprinimatel'stvo = Journal of Economy and Entrepreneurship, 2015, no. 6-2, pp. 596–601. (In Russ.)
  7. Miranda M.J., Gonzalez-Vega C. Systemic Risk, Index Insurance, and Optimal Management of Agricultural Loan Portfolios in Developing Countries. American Journal of Agricultural Economics, 2010, vol. 93, iss. 2, pp. 399–406. URL: Link
  8. Marshall J., Evans N., Currie A. et al. Portfolio Management Shores Up Loan Books. Euromoney, 2002, no. 7, pp. 122–124.
  9. Lucas A., Klaassen P., Spreij P., Straetmans S. An Analytic Approach to Credit Risk of Large Corporate Bond and Loan Portfolios. Journal of Banking & Finance, 2001, vol. 25, iss. 9, pp. 1635–1664. URL: Link00147-3
  10. Kadyrov A.N. [A methodology for determining the risk category of the borrower to manage the risk level of bank's loan portfolio]. Finansy i kredit = Finance and Credit, 2002, no. 7, pp. 46–51. URL: Link (In Russ.)
  11. Maksimova O.N., Zagornaya T.O. et al. Nauchnye otvety na vyzovy sovremennosti: ekonomika [Scientific answers to the challenges of modernity: economics: a monograph. In 2 volumes]. Odessa, Kuprienko S.V. Publ., 2016, vol. 2, 185 p.
  12. Knight F.H. Risk, neopredelennost' i pribyl' [Risk, Uncertainty, and Profit]. Moscow, Delo Publ., 2003, 360 p.
  13. Van Eyden R.J. The Application of Neural Networks in the Forecasting of Share Prices. National Research Foundation: Nexus-Current & Completed Projects. URL: Link handle/20.500.11892/177210
  14. Lomakin N.I. Innovatsii v bankovskoi sfere – faktor povysheniya konkurentosposobnosti s pozitsii steikkholderskoi teorii firmy: monografiya [Innovation in the banking sector is a factor for increasing the competitiveness from the standpoint of stakeholder theory of firm: a monograph]. Saarbrucken, Germany, LAP LAMBERT Academic Publishing, 2015, 197 p.

View all articles of issue

 

ISSN 2311-8768 (Online)
ISSN 2073-4484 (Print)

Journal current issue

Vol. 17, Iss. 1
March 2024

Archive