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Measuring systemic risk using vine-copula

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  • Pourkhanali, Armin
  • Kim, Jong-Min
  • Tafakori, Laleh
  • Fard, Farzad Alavi

Abstract

We present an intuitive model of systemic risk to analyse the complex interdependencies between different borrowers. We characterise systemic risk by the way that financial institutions are interconnected. Using their probability of default, we classify different international financial institutions into five rating groups. Then we use the state-of-the-art canonical (C-) and D-vine copulae to investigate the partial correlation structure between the rating groups. Amongst many interesting findings, we discover that the second tier financial institutions pay a larger contribution to the systemic risk than the top tier borrowers. Further, we discuss an application of our methodology for pricing credit derivative swaps.

Suggested Citation

  • Pourkhanali, Armin & Kim, Jong-Min & Tafakori, Laleh & Fard, Farzad Alavi, 2016. "Measuring systemic risk using vine-copula," Economic Modelling, Elsevier, vol. 53(C), pages 63-74.
  • Handle: RePEc:eee:ecmode:v:53:y:2016:i:c:p:63-74
    DOI: 10.1016/j.econmod.2015.11.010
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    13. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    14. Kim, Jong-Min & Kim, Dong H. & Jung, Hojin, 2020. "Modeling non-normal corporate bond yield spreads by copula," The North American Journal of Economics and Finance, Elsevier, vol. 53(C).
    15. Bukre Yildirim Kulekci & Gulden Poyraz & Ismail Gur & Ozan Evkaya, 2023. "Dependence Analysis of the ISE100 Banking Sector Using Vine Copula," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 73(73-1), pages 55-81, June.
    16. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    17. Mezei, József & Sarlin, Peter, 2018. "RiskRank: Measuring interconnected risk," Economic Modelling, Elsevier, vol. 68(C), pages 41-50.
    18. Jiang, Cuixia & Li, Yuqian & Xu, Qifa & Liu, Yezheng, 2021. "Measuring risk spillovers from multiple developed stock markets to China: A vine-copula-GARCH-MIDAS model," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 386-398.
    19. Dai, Xingyu & Wang, Qunwei & Zha, Donglan & Zhou, Dequn, 2020. "Multi-scale dependence structure and risk contagion between oil, gold, and US exchange rate: A wavelet-based vine-copula approach," Energy Economics, Elsevier, vol. 88(C).
    20. Mejdoub, Hanène & Ben Arab, Mounira, 2018. "Impact of dependence modeling of non-life insurance risks on capital requirement: D-Vine Copula approach," Research in International Business and Finance, Elsevier, vol. 45(C), pages 208-218.
    21. Yao, Yanzhen & Li, Jianping & Zhu, Xiaoqian & Wei, Lu, 2017. "Expected default based score for identifying systemically important banks," Economic Modelling, Elsevier, vol. 64(C), pages 589-600.
    22. Joshua Eklund & Jong-Min Kim, 2022. "Examining Factors That Affect Movie Gross Using Gaussian Copula Marginal Regression," Forecasting, MDPI, vol. 4(3), pages 1-14, July.
    23. Boako, Gideon & Alagidede, Paul, 2017. "Currency price risk and stock market returns in Africa: Dependence and downside spillover effects with stochastic copulas," Journal of Multinational Financial Management, Elsevier, vol. 41(C), pages 92-114.
    24. Kumar, Satish & Tiwari, Aviral Kumar & Chauhan, Yogesh & Ji, Qiang, 2019. "Dependence structure between the BRICS foreign exchange and stock markets using the dependence-switching copula approach," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 273-284.
    25. 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.

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