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Measuring the default risk of sovereign debt from the perspective of network

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  • Hongwei Chuang
  • Hwai-Chung Ho

Abstract

Recently, there has been a growing interest in network research, especially in these fields of biology, computer science, and sociology. It is natural to address complex financial issues such as the European sovereign debt crisis from the perspective of network. In this article, we construct a network model according to the debt--credit relations instead of using the conventional methodology to measure the default risk. Based on the model, a risk index is examined using the quarterly report of consolidated foreign claims from the Bank for International Settlements (BIS) and debt/GDP ratios among these reporting countries. The empirical results show that this index can help the regulators and practitioners not only to determine the status of interconnectivity but also to point out the degree of the sovereign debt default risk. Our approach sheds new light on the investigation of quantifying the systemic risk.

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  • Hongwei Chuang & Hwai-Chung Ho, 2013. "Measuring the default risk of sovereign debt from the perspective of network," Papers 1304.3814, arXiv.org.
    • Handle: RePEc:arx:papers:1304.3814
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    Cited by:

    1. Paolo Giudici & Laura Parisi, 2017. "Sovereign risk in the Euro area: a multivariate stochastic process approach," Quantitative Finance, Taylor & Francis Journals, vol. 17(12), pages 1995-2008, December.
    2. Arazmuradov, Annageldy, 2016. "Assessing sovereign debt default by efficiency," The Journal of Economic Asymmetries, Elsevier, vol. 13(C), pages 100-113.
    3. Silva, Walmir & Kimura, Herbert & Sobreiro, Vinicius Amorim, 2017. "An analysis of the literature on systemic financial risk: A survey," Journal of Financial Stability, Elsevier, vol. 28(C), pages 91-114.
    4. Chuang, Hongwei, 2016. "Brokers’ financial network and stock return," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 172-183.
    5. Chen, Tingqiang & Wang, Jiepeng & Liu, Haifei & He, Yuanping, 2019. "Contagion model on counterparty credit risk in the CRT market by considering the heterogeneity of counterparties and preferential-random mixing attachment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 458-480.

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