{"title":"Power law bond price and yield approximation","authors":"J. R. Barber","doi":"10.1108/jrf-10-2020-0217","DOIUrl":null,"url":null,"abstract":"PurposeThis paper determines a simple transformation that nearly linearizes the bond price formula. The transformed price can be used to derive a highly accurate approximation of the change in a bond price resulting from a change in interest rates.Design/methodology/approachA logarithmic transformation exactly linearizes the price function for a zero coupon bond and a reciprocal transformation exactly linearizes the price function for a perpetuity. A power law transformation combines aspects of both types of transformations and provides a superior approximation of the bond price sensitivity for both short-term and long-term bonds.FindingsIt is demonstrated that the new formula, based on power-law transformation, is a much better approximation than either the traditional duration-convexity approximation and the more recently developed approximations based on logarithmic transformation of the price function.Originality/valueThe new formula will be used by risk managers to perform stress-testing on bond portfolios. The new formula can easily be inverted, making it possible to relate the distribution of prices (which are observable in the market) to the distribution of yields (which are numerical solutions that are not directly observable).","PeriodicalId":46579,"journal":{"name":"Journal of Risk Finance","volume":"1 1","pages":""},"PeriodicalIF":5.7000,"publicationDate":"2021-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Risk Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/jrf-10-2020-0217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
PurposeThis paper determines a simple transformation that nearly linearizes the bond price formula. The transformed price can be used to derive a highly accurate approximation of the change in a bond price resulting from a change in interest rates.Design/methodology/approachA logarithmic transformation exactly linearizes the price function for a zero coupon bond and a reciprocal transformation exactly linearizes the price function for a perpetuity. A power law transformation combines aspects of both types of transformations and provides a superior approximation of the bond price sensitivity for both short-term and long-term bonds.FindingsIt is demonstrated that the new formula, based on power-law transformation, is a much better approximation than either the traditional duration-convexity approximation and the more recently developed approximations based on logarithmic transformation of the price function.Originality/valueThe new formula will be used by risk managers to perform stress-testing on bond portfolios. The new formula can easily be inverted, making it possible to relate the distribution of prices (which are observable in the market) to the distribution of yields (which are numerical solutions that are not directly observable).
期刊介绍:
The Journal of Risk Finance provides a rigorous forum for the publication of high quality peer-reviewed theoretical and empirical research articles, by both academic and industry experts, related to financial risks and risk management. Articles, including review articles, empirical and conceptual, which display thoughtful, accurate research and be rigorous in all regards, are most welcome on the following topics: -Securitization; derivatives and structured financial products -Financial risk management -Regulation of risk management -Risk and corporate governance -Liability management -Systemic risk -Cryptocurrency and risk management -Credit arbitrage methods -Corporate social responsibility and risk management -Enterprise risk management -FinTech and risk -Insurtech -Regtech -Blockchain and risk -Climate change and risk