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Optimal portfolio for a robust financial system

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  • Yoshiharu Maeno
  • Kenji Nishiguchi
  • Satoshi Morinaga
  • Hirokazu Matsushima
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    Abstract

    This study presents an ANWSER model (asset network systemic risk model) to quantify the risk of financial contagion which manifests itself in a financial crisis. The transmission of financial distress is governed by a heterogeneous bank credit network and an investment portfolio of banks. Bankruptcy reproductive ratio of a financial system is computed as a function of the diversity and risk exposure of an investment portfolio of banks, and the denseness and concentration of a heterogeneous bank credit network. An analytic solution of the bankruptcy reproductive ratio for a small financial system is derived and a numerical solution for a large financial system is obtained. For a large financial system, Large diversity among banks in the investment portfolio makes financial contagion more damaging on the average. But large diversity is essentially effective in eliminating the risk of financial contagion in the worst case of financial crisis scenarios. A bank-unique specialization portfolio is more suitable than a uniform diversification portfolio and a system-wide specialization portfolio in strengthening the robustness of a financial system.

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    File URL: http://arxiv.org/pdf/1211.5235
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    Bibliographic Info

    Paper provided by arXiv.org in its series Papers with number 1211.5235.

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    Date of creation: Nov 2012
    Date of revision: Feb 2013
    Publication status: Published in presented at the IEEE Workshop on Computational Intelligence for Financial Engineering and Economics, Singapore, April 2013
    Handle: RePEc:arx:papers:1211.5235

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    Web page: http://arxiv.org/

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    1. Upper, Christian, 2011. "Simulation methods to assess the danger of contagion in interbank markets," Journal of Financial Stability, Elsevier, Elsevier, vol. 7(3), pages 111-125, August.
    2. Maeno, Yoshiharu, 2010. "Discovering network behind infectious disease outbreak," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 389(21), pages 4755-4768.
    3. Nier, Erlend & Yang, Jing & Yorulmazer, Tanju & Alentorn, Amadeo, 2008. "Network models and financial stability," Bank of England working papers, Bank of England 346, Bank of England.
    4. Kimmo Soramaki & Morten L. Bech & Jeffrey Arnold & Robert J. Glass & Walter Beyeler, 2006. "The topology of interbank payment flows," Staff Reports, Federal Reserve Bank of New York 243, Federal Reserve Bank of New York.
    5. Maeno, Yoshiharu, 2011. "Discovery of a missing disease spreader," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 390(20), pages 3412-3426.
    6. Gai, Prasanna & Haldane, Andrew & Kapadia, Sujit, 2011. "Complexity, concentration and contagion," Journal of Monetary Economics, Elsevier, Elsevier, vol. 58(5), pages 453-470.
    7. G. De Masi & G. Iori & G. Caldarelli, 2006. "A fitness model for the Italian Interbank Money Market," Papers physics/0610108, arXiv.org.
    8. Domenico Delli Gatti & Mauro Gallegati & Bruce Greenwald & Alberto Russo & Joseph E. Stiglitz, 2010. "Business fluctuations in a credit-network economy," Papers 1006.3521, arXiv.org.
    9. Inaoka, Hajime & Takayasu, Hideki & Shimizu, Tokiko & Ninomiya, Takuto & Taniguchi, Ken, 2004. "Self-similarity of banking network," Physica A: Statistical Mechanics and its Applications, Elsevier, Elsevier, vol. 339(3), pages 621-634.
    10. Becher, Christopher & Millard, Stephen & Soramäki, Kimmo, 2008. "The network topology of CHAPS Sterling," Bank of England working papers, Bank of England 355, Bank of England.
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