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Random thinning with credit quality vulnerability factor for better risk management of credit portfolio in a top-down framework

  • Suguru YamanakaEmail author
  • Hidetoshi Nakagawa
  • Masaaki Sugihara
Original Paper Area 4
  • 110 Downloads

Abstract

In the top-down approach of portfolio credit risk modeling, we assess credit risks of sub-portfolios with the so-called random thinning model, which dissects the portfolio risk into sub-portfolio contributions. In this paper, we provide a random thinning model incorporating the sub-portfolio size and the factor called “credit quality vulnerability factor”, in order to take into account credit quality vulnerability of sub-portfolios. With our random thinning model, we estimate credit quality vulnerability of industrial sectors. Numerical examples on assessing the risks of several credit portfolios show that our random thinning model is useful to detect how the proportions of constituent industrial sectors affect portfolio credit risks.

Keywords

Credit risk Top-down approach Credit event intensity Random thinning 

Mathematics Subject Classification

91G40 

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Copyright information

© The JJIAM Publishing Committee and Springer Japan 2016

Authors and Affiliations

  • Suguru Yamanaka
    • 1
    • 2
    Email author
  • Hidetoshi Nakagawa
    • 3
  • Masaaki Sugihara
    • 4
  1. 1.Bank of JapanTokyoJapan
  2. 2.Mitsubishi UFJ Trust Investment Technology Institute Co., LtdTokyoJapan
  3. 3.Graduate School of International Corporate StrategyHitotsubashi UniversityTokyoJapan
  4. 4.Graduate School of Science and EngineeringAoyama Gakuin UniversitySagamiharaJapan

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