PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
2017 | 10 | nr 3 | 273--284
Tytuł artykułu

Stability Analysis of the Banking System : a Complex Systems Approach

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The present work deals with the stability analysis of a banking system with the structure in the form of Apollonian graph based on such characteristics of the banking system as the modularity and inhomogeneous distribution of banks by degree, on the basis of the extended mean-field Nier model (a static approach based on a simplified balance sheet of assets and liabilities of the bank) which was used to analyze the extent of the process of bankruptcy of banks after the default of one of the banks in the banking system. The obtained results of research of stability of banking systems based on the Apollonian graphs indicate that such characteristics as modularity (i.e. clustering), and the heterogeneity of banks in the structure of the model of banking systems allow them to conform «isomorphous structure» typical of the majority of real social and biological complex adaptive systems. (original abstract)
Rocznik
Tom
10
Numer
Strony
273--284
Opis fizyczny
Twórcy
autor
  • Financial University under the Government of the Russian Federation
  • Financial University under the Government of the Russian Federation
autor
  • Kaspersky Lab Moscow, Russian Federation
  • Rzeszow University of Technology, Poland
Bibliografia
  • Albert, R., Jeong, H., & Barabási, A. L. (2000). Error and attack tolerance of complex networks. Nature, 406(6794), 378-382.
  • Allen, F., & Gale, D. (2000). Financial contagion. Journal of Political Economy, 108(1), 1-33.
  • Anderson, P. (1999). Perspective: Complexity theory and organization science. Organization science, 10(3), 216-232.
  • Balitskiy, S., Bilan, Y., Strielkowski, W., & Štreimikienė, D. (2016). Energy efficiency and natural gas consumption in the context of economic development in the European Union. Renewable and Sustainable Energy Reviews, 55, 156-168. doi: 10.1016/j.rser.2015.10.053
  • Barabasi, A.-L. (2015). Network Science. Cambridge, UK: Cambridge University Press.
  • Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512.
  • Barrat, A., Barthelemy, M., & Vespignani, A. (2008). Dynamical processes on complex networks. Cambridge university press.
  • Bassett, D. S., & Gazzaniga, M. S. (2011). Understanding complexity in the human brain. Trends in Cognitive Sciences, 15(5), 200-209.
  • Brodzicki, T. (2015). Does variety matter? Export pattern of Poland prior and after accession to the EU. International Economics Letters, 4(2), 103-118. https://doi.org/10.24984/iel.2015.4.2.5
  • Bobrikova, M. (2017). Financial Engineering With Options and Its Implementation for Issuing of New Financial Innovations. Montenegrin Journal of Economics, 13(3), 7-18.
  • Bullmore, E., & Sporns, O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10(3), 186-198.
  • Čajka, P., Jaroszewicz, M., & Strielkowski, W. (2014). Migration incentives and flows between Belarus, Moldova, Ukraine and the European Union: A forecasting model. Economics & Sociology, 7(4), 11-25. http://dx.doi.org/10.14254/2071-789X.2014/7-4/1.
  • Cieślik, A., Michałek, J., & Mycielski, J. (2016). Globalization, international trade, and human development: a case of Central and Eastern Europe. Czech Journal of Social Sciences, Business and Economics,5(2), 6-15. doi: 10.24984/cjssbe.2016.5.2.1
  • Cohen, R., Erez, K., Ben-Avraham, D., & Havlin, S. (2001). Breakdown of the Internet under intentional attack. Physical review letters, 86(16), 3682-3685.
  • Cohen, R., & Havlin, S. (2010). Complex networks: structure, robustness and function. Cambridge university press.
  • Da Silva, L. F., Costa Filho, R. N., Soares, D. J. B., Macedo-Filho, A., Fulco, U. L., & Albuquerque, E. L. (2013). Critical properties of contact process on the Apollonian network. Physica A: Statistical Mechanics and its Applications, 392(6), 1532-1537.
  • Eriksen, K. A., Simonsen, I., Maslov, S., & Sneppen, K. (2003). Modularity and extreme edges of the Internet. Physical review letters, 90(14), 148701.
  • Gai, P., & Kapadia, S. (2010, August). Contagion in financial networks. In Proceedings of the Royal Society of London A: Mathematical, Physical and Engineering Sciences (Vol. 466, No. 2120, pp. 2401-2423). The Royal Society.
  • Gallos, L. K., Makse, H. A., & Sigman, M. (2012). A small world of weak ties provides optimal global integration of self-similar modules in functional brain networks. Proceedings of the National Academy of Sciences, 109(8), 2825-2830.
  • Girvan, M., & Newman, M. E. (2002). Community structure in social and biological networks. Proceedings of the national academy of sciences, 99(12), 7821-7826.
  • Guimera, R., Sales-Pardo, M., & Amaral, L. A. N. (2004). Modularity from fluctuations in random graphs and complex networks. Physical Review E, 70(2), 025101.
  • Haldane, A. G., & May, R. M. (2011). Systemic risk in banking ecosystems. Nature, 469(7330), 351-355.
  • Haldane, A. G. (2009). Rethinking the financial network. Speech delivered at the Financial Student Association, Amsterdam, April, 28.
  • Herrmann, H. J., Schneider, C. M., Moreira, A. A., Andrade Jr, J. S., & Havlin, S. (2011). Onion-like network topology enhances robustness against malicious attacks. Journal of Statistical Mechanics: Theory and Experiment, 2011(01), P01027.
  • Holland, J.H. (1998). The global economy as an adaptive process, SFI Studies in the Sciences of Complexity. Perseus Books Publishing.
  • Kambhu, J., Weidman, S. & Krishnan, N. (2007). New Directions for Understanding Systemic Risk. Economic Policy Review, 13(2), 1-83.
  • Karaev, A. K. & Melnichuk, M. V. (2016). Network effects and systemic risks in the banking system. Problems of economics and legal practice, 4, 27-35.
  • Karaev, A.K. & Melnichuk, M.V. (2015). Theoretical model of financial instability of Russian interbank credit market: network approach. Problems of economics and legal practice, 5, 222-226.
  • Kirsiene, J., & Miseviciute, G. (2017). Comparative Analysis of Liability Cases for Bankruptcies of Financial Institutions. Montenegrin Journal of Economics, 13(3), 85-99.
  • Kravchuk, I. (2017). Interconnectedness and Contagion Effects in International Financial Instruments Markets. Montenegrin Journal of Economics, 13(3), 161-174.
  • Čábelková, I., Strielkowski, W., & Mirvald, M. (2015). Business influence on the mass media: a case study of 21 countries. Transformation in Business & Economics, 14(1), 65-75. doi: http://dx.doi.org/10.14254/2071- 789X.2014/7-4/1.
  • Leon, C. & Machado, C. (2013). Designing an expert-knowledge-based systemic importance index for financial institutions. Journal of Financial Market Infrastructures, 1(2), 215.
  • Leon, C., Machado, C. & Murcia, A. (2013). Macro-prudential assessment of Colombian financial institutions systemic importance. Borradores de Economia, 800.
  • Leon, C. & Perez, J. (2014). Authority Centrality and Hub Centrality as Metrics of Systemic Importance of Financial Market Infrastructures. Borradores de Economia, 754.
  • Li, R. Q., Sun, S. W., Ma, Y. L., Wang, L., & Xia, C. Y. (2015). Effect of clustering on attack vulnerability of interdependent scale-free networks. Chaos, Solitons & Fractals, 80, 109-116.
  • Maevskii, V. I. & Chernavskii, D. S. (2003). Hierarchically organized sampling. Retrieved from: http://spkurdyumov.ru/economy/ierarxicheski-organizovannyj-vybor/.
  • Markose, M. S. M. (2012). Systemic risk from global financial derivatives: A network analysis of contagion and its mitigation with super-spreader tax (No. 12-282). International Monetary Fund.
  • Matisziw, T. C., Grubesic, T. H., & Guo, J. (2012). Robustness elasticity in complex networks. Plos one, 7(7), e39788.
  • May, R. M., & Arinaminpathy, N. (2010). Systemic risk: the dynamics of model banking systems. Journal of the Royal Society Interface, 7(46), 823-838.
  • Newman, M. (2010). Networks: an introduction. Oxford university press.
  • Nier, E., Yang, J., Yorulmazer, T., & Alentorn, A. (2007). Network models and financial stability. Journal of Economic Dynamics and Control, 31(6), 2033-2060.
  • Pan, R. K., & Sinha, S. (2008). Modular networks with hierarchical organization: The dynamical implications of complex structure. Pramana: Journal of Physics, 70(8), 331-340.
  • Pastor-Satorras, R., Castellano, C., Van Mieghem, P., & Vespignani, A. (2015). Epidemic processes in complex networks. Reviews of modern physics, 87(3), 925.
  • Pastor-Satorras, R. & Vespignani, A. (2004). Evolution and Structure of the Internet: A Statistical Physics Approach. Cambridge: Cambridge University Press.
  • Roland Molontay (2013). Networks and fractals BSc Thesis. Budapest University of Technology and Economics Institute of Mathematics, Department of Stochastics.
  • Spirin, V., & Mirny, L. A. (2003). Protein complexes and functional modules in molecular networks. Proceedings of the National Academy of Sciences, 100(21), 12123-12128.
  • Strielkowski, W., Tumanyan, Y., & Kalyugina, S. (2016). Labour Market Inclusion of International Protection Applicants and Beneficiaries. Economics & Sociology, 9(2), 293-302. doi: http://dx.doi.org/10.14254/2071-789X.2016/9-2/20.
  • Strielkowski, W . (2017). Social and economic implications for the smart grids of the future. Economics & Sociology, 10(1), 310-318. doi: 10.14254/2071-789X.2017/10-1/22
  • Sun, S., Li, R., Wang, L., & Xia, C. (2015). Reduced synchronizability of dynamical scale-free networks with onion-like topologies. Applied Mathematics and Computation, 252, 249-256.
  • Sun, S., Liu, Z., Chen, Z., & Yuan, Z. (2007). Error and attack tolerance of evolving networks with local preferential attachment. Physica A: Statistical Mechanics and its Applications, 373, 851-860.
  • Tanizawa, T., Havlin, S., & Stanley, H. E. (2012). Robustness of onion like correlated networks against targeted attacks. Physical Review E, 85(4), 046109.
  • Wu, Z. X., & Holme, P. (2011). Onion structure and network robustness. Physical Review E, 84(2), 026106.
  • Yuan, X., Shao, S., Stanley, H. E., & Havlin, S. (2015). How breadth of degree distribution influences network robustness: Comparing localized and random attacks. Physical Review E, 92(3), 032122.
  • Zhou, X., Peng, W., Xu, Z., & Yang, B. (2015). Hardness analysis and empirical studies of the relations among robustness, topology and flow in dynamic networks. PloS one, 10(12), e0145421.
  • Zhang, Z., Rong, L., & Comellas, F. (2006). High-dimensional random Apollonian networks. Physica A: Statistical Mechanics and its Applications, 364, 610-618.
  • Zhang, Z., Rong, L., & Zhou, S. (2006). Evolving Apollonian networks with small-world scale-free topologies. Physical Review E, 74(4), 046105.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171492792

Zgłoszenie zostało wysłane

Zgłoszenie zostało wysłane

Musisz być zalogowany aby pisać komentarze.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.