{"title":"Financial Risk Management","authors":"T. Roncalli","doi":"10.1142/9789811241284_0011","DOIUrl":null,"url":null,"abstract":"where Φ (x) is the distribution function of univariate standard normal distribution while Φ2 (x, y; ρ) is the distribution function of the bivariate standard normal distribution with correlation ρ. Let (X1, X2) be a random Gaussian vector of distribution Φ2. Show that the copula of (X1, X2) is the same with the one of the random vector (Φ (X1) ,Φ(X2)). Deduce an algorithm to simulate the Gaussian copula of parameter ρ.","PeriodicalId":179602,"journal":{"name":"Introduction to Finance","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Introduction to Finance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9789811241284_0011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
where Φ (x) is the distribution function of univariate standard normal distribution while Φ2 (x, y; ρ) is the distribution function of the bivariate standard normal distribution with correlation ρ. Let (X1, X2) be a random Gaussian vector of distribution Φ2. Show that the copula of (X1, X2) is the same with the one of the random vector (Φ (X1) ,Φ(X2)). Deduce an algorithm to simulate the Gaussian copula of parameter ρ.