Measuring systemic risk using vine-copula

Armin Pourkhanali; Jong Min Kim; Laleh Tafakori; Farzad Alavi Fard

doi:10.1016/j.econmod.2015.11.010

Measuring systemic risk using vine-copula

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

Statistics (Morris)

Research output: Contribution to journal › Article › peer-review

45 Scopus citations

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.

Original language	English (US)
Pages (from-to)	63-74
Number of pages	12
Journal	Economic Modelling
Volume	53
DOIs	https://doi.org/10.1016/j.econmod.2015.11.010
State	Published - Feb 1 2016

Bibliographical note

Funding Information:
The authors would like to thank the editor and two anonymous referees for their constructive suggestions that greatly improved the paper. The third author would like to thank the Australian Research Council for supporting this work through Laureate Fellowship FL130100039 .

Keywords

Credit risk
Partial correlation
Vine copula

Publisher link

10.1016/j.econmod.2015.11.010

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title = "Measuring systemic risk using vine-copula",

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.",

keywords = "Credit risk, Partial correlation, Vine copula",

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note = "Funding Information: The authors would like to thank the editor and two anonymous referees for their constructive suggestions that greatly improved the paper. The third author would like to thank the Australian Research Council for supporting this work through Laureate Fellowship FL130100039 .",

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AU - Pourkhanali, Armin

AU - Kim, Jong Min

AU - Tafakori, Laleh

AU - Fard, Farzad Alavi

N1 - Funding Information: The authors would like to thank the editor and two anonymous referees for their constructive suggestions that greatly improved the paper. The third author would like to thank the Australian Research Council for supporting this work through Laureate Fellowship FL130100039 .

PY - 2016/2/1

Y1 - 2016/2/1

N2 - 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.

AB - 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.

KW - Credit risk

KW - Partial correlation

KW - Vine copula

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VL - 53

SP - 63

EP - 74

JO - Economic Modelling

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ER -

Measuring systemic risk using vine-copula

Abstract

Bibliographical note

Keywords

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