한국관련자료
Climate stress test for the German banking sector: Impact of the green transition on corporate loan portfolios
Climate risks are a priority issue for many central banks and supervisory authorities due to the potentially detrimental effects of climate risks on banks’ stability. However, measuring climate risks is fraught with challenges, because nature and magnitude of the shock transmission are plagued with uncertainty. Moreover, data limitations are widespread, further complicating measurement. This paper proposes a novel stress testing framework to quantify climate-related transition risks for the German banking sector. Our stress test allows the identification of vulnerabilities stemming from transition risks for both individual banks and the banking system as a whole.
This paper contributes to the literature by proposing a novel climate risk stress test framework, which allows to quantify climate transition risks for a large sample of German banks. We capture model uncertainty in a unique way by applying two standalone models (a micro and a macro model) for translating stress scenarios into credit risk parameters. Reporting ranges of estimates provides a quantitative indication of uncertainty in relation to the green transition. Another key strength of our framework is the granular modelling of default probabilities (PDs). While traditional stress testing models typically produce country- and/or portfolio-level estimates of scenario-dependent PDs, we can flexibly estimate them at firm- or sector-level. Through our targeted, multi-layered analytical framework, we thus address the heterogeneity of climate risks across economic sectors and firms.
This paper contributes to the literature by proposing a novel climate risk stress test framework, which allows to quantify climate transition risks for a large sample of German banks. We capture model uncertainty in a unique way by applying two standalone models (a micro and a macro model) for translating stress scenarios into credit risk parameters. Reporting ranges of estimates provides a quantitative indication of uncertainty in relation to the green transition. Another key strength of our framework is the granular modelling of default probabilities (PDs). While traditional stress testing models typically produce country- and/or portfolio-level estimates of scenario-dependent PDs, we can flexibly estimate them at firm- or sector-level. Through our targeted, multi-layered analytical framework, we thus address the heterogeneity of climate risks across economic sectors and firms.
많이 본 자료
![[팀튜링의 디지털 오디세이] 제1화 UAM의 미래](/userdata/main/incContent/sideLink/19/aaaGHKBjsPPI5g31szc-y20240605110816byhta.png)
![[2024.04] 물가상승](/userdata/main/incContent/sideLink/20/aaaGHKBjsPPI5g31szc-y20240605111046bpogp.jpg)
