{"title":"Climate stress testing for mortgage default probability","authors":"","doi":"10.1016/j.irfa.2024.103497","DOIUrl":null,"url":null,"abstract":"<div><p>Extreme natural disasters, such as tropical cyclones, have a low probability of materialising, but a high social and economic impact, including spillover to financial institutions. We propose a framework for performing a climate-stress testing exercise for the default probability of mortgage loans. We estimated a dynamic credit scoring model based on survival analysis with a relative damage index built using the wind speed of tropical cyclones. We considered scenarios involving tropical cyclone wind speeds with different return periods. We analyse a portfolio of approximately 190,000 mortgage loans granted in Louisiana, one of the US states most affected by tropical cyclones. Our findings suggest that coastline areas are most exposed to severe damage from tropical cyclones. If the geographical area is exposed to an event with a very large return period of 1-in-1,000 years, the probability of default increases by approximately nine percentage points compared to a baseline scenario in the absence of tropical cyclones. However, this finding was mitigated by the insurance coverage. This percentage increases to almost 20 percent in the absence of insurance coverage.</p></div>","PeriodicalId":48226,"journal":{"name":"International Review of Financial Analysis","volume":null,"pages":null},"PeriodicalIF":7.5000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1057521924004290/pdfft?md5=dcfd7dc747991cb360e93606e6ef633b&pid=1-s2.0-S1057521924004290-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Review of Financial Analysis","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1057521924004290","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
Extreme natural disasters, such as tropical cyclones, have a low probability of materialising, but a high social and economic impact, including spillover to financial institutions. We propose a framework for performing a climate-stress testing exercise for the default probability of mortgage loans. We estimated a dynamic credit scoring model based on survival analysis with a relative damage index built using the wind speed of tropical cyclones. We considered scenarios involving tropical cyclone wind speeds with different return periods. We analyse a portfolio of approximately 190,000 mortgage loans granted in Louisiana, one of the US states most affected by tropical cyclones. Our findings suggest that coastline areas are most exposed to severe damage from tropical cyclones. If the geographical area is exposed to an event with a very large return period of 1-in-1,000 years, the probability of default increases by approximately nine percentage points compared to a baseline scenario in the absence of tropical cyclones. However, this finding was mitigated by the insurance coverage. This percentage increases to almost 20 percent in the absence of insurance coverage.
期刊介绍:
The International Review of Financial Analysis (IRFA) is an impartial refereed journal designed to serve as a platform for high-quality financial research. It welcomes a diverse range of financial research topics and maintains an unbiased selection process. While not limited to U.S.-centric subjects, IRFA, as its title suggests, is open to valuable research contributions from around the world.