KNEU Logo Публікації КНЕУ імені Вадима Гетьмана Publications of KNEU named after Vadym Hetman
Switch to Ukrainian Switch to English
Neuro-Fuzzy Modeling Techniques in Economics

Neuro-Fuzzy Modeling Techniques in Economics

ISSN 2415-3516
Лук'яненко Дмитро Григорович  
Dmytro Lukianenko  
Стрельченко Інна  
Inna Strelchenko  

Neuromodeling of features of crisis contagion on financial markets between countries with different levels of economic development

DOI:

10.33111/nfmte.2021.136

Анотація:
Abstract: The study examines the problem of modeling the effects of the spread of crises between countries with different levels of economic development. The main focus is on the study of the spread of crisis contagions from the economy of the source country to the economies of the recipient countries. The authors conducted a fundamental analysis of the basic theoretical concepts, causes and mechanisms of crisis in the world economy. The relevant study was carried out in the context of certain types of financial crises.
A methodological approach to modeling the processes of crisis contagion through financial and trade transmission channels has been developed and substantiated. In particular, a method of classifying economies according to the level of behavioral similarity of individual indicators of resilience within two years after the end of the latency period is proposed. The practical implementation of the technique in the form of a cyclic algorithm in the MATLAB system is performed. Approbation of the created software is performed on the data of the world financial crisis of 2008-2009.
The obtained distribution of world economies and the calculation of statistical characteristics for each cluster made it possible to identify nine scenarios of economic development under the influence of crossborder processes of crisis. The influence of the type of exchange rate regime on the dynamics of the exchange rate during two years after the end of the latent period is analyzed separately. The analysis of the exchange rate in clusters showed that there is a certain relationship between the type of currency regime and the consequences of the crisis in domestic financial markets.
Ключові слова:
Key words: financial crisis, channels of crisis spreading, latency period, macroeconomic indicator, rank coefficient of concordance, neural network, Kohonen map
УДК:
UDC:

JEL: C45 F36 G01 G15 G17

To cite paper
In APA style
Lukianenko, D., & Strelchenko, I. (2021). Neuromodeling of features of crisis contagion on financial markets between countries with different levels of economic development. Neuro-Fuzzy Modeling Techniques in Economics, 10, 136-163. http://doi.org/10.33111/nfmte.2021.136
In MON style
Лук'яненко Д.Г., Стрельченко І. Neuromodeling of features of crisis contagion on financial markets between countries with different levels of economic development. Нейро-нечіткі технології моделювання в економіці. 2021. № 10. С. 136-163. http://doi.org/10.33111/nfmte.2021.136 (дата звернення: 15.07.2025).
With transliteration
Lukianenko, D., Strelchenko, I. (2021) Neuromodeling of features of crisis contagion on financial markets between countries with different levels of economic development. Neuro-Fuzzy Modeling Techniques in Economics, no. 10. pp. 136-163. http://doi.org/10.33111/nfmte.2021.136 (accessed 15 Jul 2025).
# 10 / 2021 # 10 / 2021
Download Paper
666
Views
118
Downloads
4
Cited by
Cited 8 times in Scopus

  1. Bank for International Settlement. (2011). The transmission channels between the financial and real sectors: a critical survey of the literature (Working Paper No. 18). Basel Committee on Banking Supervision. https://www.bis.org/publ/bcbs_wp18.pdf
  2. Forbes, K. (2012). The “Big C”: identifying contagion (Working Paper No. 18465). National Bureau of Economic Research. https://doi.org/10.3386/w18465
  3. Ahrend, R., & Goujard, A. (2015). Global banking, global crises? The role of the bank balance-sheet channel for the transmission of financial crises. European Economic Review, 80, 253–279. https://doi.org/10.1016/j.euroecorev.2015.10.003
  4. Buch, C., & Goldberg, L. (2017). Cross-Border Prudential Policy Spillovers: How Much? How Important? Evidence from the International Banking Research Network (Discussion Paper No. 02/2017). Deutsche Bundesbank. https://dx.doi.org/10.2139/ssrn.2915698
  5. Claessens, S. (2017). Global banking: recent developments and insights from research. Review of Finance, 21(4), 1513–1555. https://doi.org/10.1093/rof/rfw045
  6. Cetorelli, N., & Goldberg, L.S. (2012). Banking globalization and monetary transmission. Journal of Finance, 67(5), 1811–1843. https://doi.org/10.1111/j.1540-6261.2012.01773.x
  7. Billio, M., Getmansky, M., Lo, A. W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535–559. https://doi.org/10.1016/j.jfineco.2011.12.010
  8. Allen, F., & Gale, D. (2000). Financial contagion. Journal of Political Economy, 108(1), 1–33. https://doi.org/10.1086/262109
  9. De Bruyckere, V., Gerhardt, M., Schepens, G., & Vander Vennet, R. (2013). Bank/sovereign risk spillovers in the European debt crisis. Journal of Banking & Finance, 37(12), 4793–4809. https://doi.org/10.1016/j.jbankfin.2013.08.012
  10. Laeven, L., Ratnovski, L., & Tong, H. (2016). Bank size, capital, and systemic risk: Some international evidence. Journal of Banking & Finance, 69, S25–S34. https://doi.org/10.1016/j.jbankfin.2015.06.022
  11. Varotto, S., & Zhao, L. (2018). Systemic Risk and Bank Size. Journal of International Money and Finance, 82(C), 45–70. http://doi.org/10.1016/j.jimonfin.2017.12.002
  12. Babecký, J., Havránek, T., Matějů, J., Rusnák, M., Šmídková, K., & Vašíček, B. (2012). Banking, Debt, and Currency Crises: Early Warning Indicators for Developed Countries (Working Paper No. 1485). European Central Bank. http://doi.org/10.2139/ssrn.2162901
  13. Ferrari, S., & Pirovano, M. (2015). Early warning indicators for banking crises: a conditional moments approach (Paper No. 62406). MPRA. https://mpra.ub.uni-muenchen.de/62406/1/MPRA_paper_62406.pdf
  14. Behn, M., Detken, C., Peltonen, T., & Schudel, W. (2013). Setting countercyclical capital buffers based on early warning models: Would it work? (Working Paper No. 1604). European Central Bank. https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1604.pdf
  15. Ortiz, Á. & Ugarte, A. (2015). Introducing a New Early Warning System Indicator (EWSI) of banking crises (Working Paper No. 15/02). Banco Bilbao Vizcaya Argentaria. https://www.bbvaresearch.com/wp-content/uploads/2015/01/WP_EWS-SystemVersion-Sep2014_i.pdf
  16. Lukianenko, D. H., & Bakaiev, O. L. (2003). Hlobalizatsiia ekonomi­chnoho rozvytku: finansova kryza [Globalization of economic development: financial crises]. Rynok tsinnykh paperiv Ukrainy (Ukrainian securities market), 3-4, 3-14. http://securities.usmdi.org/?p=22&n=11&s=109 [in Ukrainian]
  17. Lukianenko, D. H., Poruchnyk, A. M., & Stoliarchuk, Ya. M. (2010). Hlobalni finansovi dysbalansy ta yikh makroekonomichni naslidky. Zhurnal yevropeiskoi ekonomiky (Journal of European Economy), 9(1), 73-92. http://jeej.wunu.edu.ua/index.php/ukjee/article/view/310 [in Ukrainian]
  18. Claessens, S. & Kose, M.A. (2013). Financial Crises: Explanations, Types, and Implications (Working Paper No. 13/28). International Monetary Fund. https://www.imf.org/external/pubs/ft/wp/2013/wp1328.pdf
  19. Krugman, P. (1979). Model of Balance-of-Payments Crises. Journal of Money, Credit and Banking, 11(3), 311-325. https://doi.org/10.2307/1991793
  20. Flood, R. & Garber, P. (1984). Collapsing Exchange-Rate Regimes: Some Linear Examples. Journal of International Economics, 17(1-2), 1-13. https://doi.org/10.1016/0022-1996(84)90002-3
  21. Obstfeld, M. (1986). Rational and Self-Fulfilling Balance-of-Payments Crises. American Economic Review, 76(1), 72-81. https://www.jstor.org/stable/1804128
  22. Corsetti, G., Pesenti, P., & Roubini, N. (1998). Paper Tigers?: A Model of the Asian Crises. European Economic Review, 43(7), 1211-1236. https://doi.org/10.1016/S0014-2921(99)00017-3
  23. McKinnon, R., & Pill, H. (1996). Credible Liberalizations and International Capital Flows: The “Overborrowing Syndrome”. In T. Ito, & A. O. Krueger (Eds.), NBER-East Asia Seminar on Economics: Vol. 5. Financial Deregulation and Integration in East Asia (pp. 7-50). University of Chicago Press. https://www.nber.org/system/files/chapters/c8557/c8557.pdf
  24. Krugman, P. (1999). Balance Sheets, the Transfer Problem, and Financial Crises. International Tax and Public Finance, 6, 459-472. https://doi.org/10.1023/A:1008741113074
  25. Blanco, H., & Garber, P. M. (1986). Recurrent Devaluation and Speculative Attacks on the Mexican Peso. Journal of Political Economy, 94(1), 148-166. https://doi.org/10.1086/261366
  26. Calvo, G. A., & Reinhart, C. M. (2000). When Capital Flows Come to a Sudden Stop: Consequences and Policy. In P. Kenen, & A. Swoboda (Eds.), Reforming the International Monetary and Financial System (pp. 175-201). International Monetary Fund. https://mpra.ub.uni-muenchen.de/6982/1/MPRA_paper_6982.pdf
  27. Reinhart, C. M., & Rogoff, K. S. (2009). The Aftermath of Financial Crises. American Economic Review, 99(2), 466–472. https://doi.org/10.1257/aer.99.2.466
  28. Lukianenko, D., & Yushko, I. (2016). Bankivska kryza v Ukraini: hlobalni faktory ta vnutrishni prychyny [Banking crisis in Ukraine: global factors and internal causes]. Rynok tsinnykh paperiv Ukrainy (Ukrainian securities market), 5–6, 43–53. http://securities.usmdi.org/PDF/975.pdf [in Ukrainian]
  29. Strelchenko, I.I. (2019). Modeliuvannia protsesiv transhranychnoho poshyrennia finansovykh kryz [Modeling of cross-border spreading of financial crises]. Neiro-Nechitki Tekhnolohii Modelyuvannya v Ekonomitsi (Neuro-Fuzzy Modeling Techniques in Economics), 8, 147-175. https://doi.org/10.33111/nfmte.2019.147 [in Ukrainian]
  30. International Monetary Fund. (2016, April). World Economic Outlook: Too Slow for Too Long. https://www.imf.org/en/Publications/WEO/Issues/2016/12/31/Too-Slow-for-Too-Long
  31. International Monetary Fund. (2020). IMF Data. Access to Macroeconomic & Financial Data [Data set]. Retrieved August 11, 2020, from http://data.imf.org/
  32. Kohonen, T. (2001). Self-Organizing Maps (3rd ed.). Springer.
  33. Strelchenko, I.I. (2017). Vybir optymalnoi topolohii neironnoi merezhi v zadachakh klasyfikatsii dynamichnykh ekonomichnykh system [Selection of a neural network optimum topology in problems of dynamic economic systems classification]. Neiro-Nechitki Tekhnolohii Modelyuvannya v Ekonomitsi (Neuro-Fuzzy Modeling Techniques in Economics), 6, 142–157. http://nfmte.com/assets/journal/6/Strelchenko.pdf [in Ukrainian]