{"title":"What Interbank Rates Tell Us About Time-Varying Disaster Risk","authors":"Hitesh Doshi, Hyung-joo Kim, S. Seo","doi":"10.2139/ssrn.3469087","DOIUrl":null,"url":null,"abstract":"We characterize time-varying disaster risk using interbank rates and their options. The identification of disaster risk has remained a significant challenge due to the rarity of macroeconomic disasters. We make an identification assumption that macroeconomic disasters coincide with banking disasters -- extremely unlikely events in which the interbank market fails and investors suffer significant losses. Based on our flexible reduced-form setup, interbank rates together with their options allow us to extract the short-run and long-run components of disaster risk. Our estimation results serve as an external validity test of rare disaster models, which are typically calibrated to match stock moments.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Asset Pricing Models (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3469087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
We characterize time-varying disaster risk using interbank rates and their options. The identification of disaster risk has remained a significant challenge due to the rarity of macroeconomic disasters. We make an identification assumption that macroeconomic disasters coincide with banking disasters -- extremely unlikely events in which the interbank market fails and investors suffer significant losses. Based on our flexible reduced-form setup, interbank rates together with their options allow us to extract the short-run and long-run components of disaster risk. Our estimation results serve as an external validity test of rare disaster models, which are typically calibrated to match stock moments.