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Systemic-risk-efficient asset allocation: Minimization of systemic risk as a network optimization problem

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  • Pichler, Anton
  • Poledna, Sebastian
  • Thurner, Stefan
Abstract
Systemic risk arises as a multi-layer network phenomenon. Layers represent direct financial exposures of various types, including interbank liabilities, derivativeor foreign exchange exposures. Another network layer of systemic risk emerges through common asset holdings of financial institutions. Strongly overlapping portfolios lead to similar exposures that are caused by price movements of the underlying financial assets. Based on the knowledge of portfolio holdings of financial agents we quantify systemic risk of overlapping portfolios. We present an optimization procedure, where we minimize the systemic risk in a given financial market by optimally rearranging overlapping portfolio networks, under the constraints that the expected returns and risks of the individual portfolios are unchanged. We explicitly demonstrate the power of the method on the overlapping portfolio network of sovereign exposure between major European banks by using data from the European Banking Authority stress test of 2016. We show that systemic-risk-efficient allocations are accessible by the optimization. In the case of sovereign exposure, systemic risk can be reduced by more than a factor of two, without any detrimental effects for the individual banks. These results are confirmed by a simple simulation of fire sales in the government bond market. In particular we show that the contagion probability is reduced dramatically in the optimized network.

Suggested Citation

  • Pichler, Anton & Poledna, Sebastian & Thurner, Stefan, 2018. "Systemic-risk-efficient asset allocation: Minimization of systemic risk as a network optimization problem," INET Oxford Working Papers 2018-11, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    • Handle: RePEc:amz:wpaper:2018-11
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    File URL: https://www.inet.ox.ac.uk/files/1801_10515_copy.pdf
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    3. Aymeric Vié & Alfredo J. Morales, 2021. "How Connected is Too Connected? Impact of Network Topology on Systemic Risk and Collapse of Complex Economic Systems," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1327-1351, April.
    4. Abhijit Chakraborty & Tobias Reisch & Christian Diem & Pablo Astudillo-Estévez & Stefan Thurner, 2024. "Inequality in economic shock exposures across the global firm-level supply network," Nature Communications, Nature, vol. 15(1), pages 1-8, December.
    5. Zheng, Kexian & Liu, Ying & Gong, Jie & Wang, Wei, 2022. "Robustness of circularly interdependent networks," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
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    7. Yan, Chun & Ding, Yi & Liu, Wei & Liu, Xinhong & Liu, Jiahui, 2023. "Multilayer interbank networks and systemic risk propagation: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 628(C).
    8. Wang, Chao & Liu, Xiaoxing & He, Jianmin, 2022. "Does diversification promote systemic risk?," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    9. Chao, Wang & Jing, Ma & Xiaoxing, Liu, 2023. "Optimizing systemic risk through credit network reconstruction," Emerging Markets Review, Elsevier, vol. 57(C).
    10. Kamil Fortuna & Janusz Szwabi'nski, 2023. "The Unified Framework for Modelling Credit Cycles with Marshall-Walras Price Formation Process And Systemic Risk Assessment," Papers 2305.06337, arXiv.org.
    11. Wang, Ze & Gao, Xiangyun & Huang, Shupei & Sun, Qingru & Chen, Zhihua & Tang, Renwu & Di, Zengru, 2022. "Measuring systemic risk contribution of global stock markets: A dynamic tail risk network approach," International Review of Financial Analysis, Elsevier, vol. 84(C).
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    14. Aymeric Vi'e & Alfredo J. Morales, 2019. "How connected is too connected? Impact of network topology on systemic risk and collapse of complex economic systems," Papers 1912.09814, arXiv.org.

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