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<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>Mathematical Sciences</JournalTitle>
<Issn>2251-7456</Issn>
<Volume>19</Volume>
<Issue>3</Issue>
<PubDate PubStatus="epublish">
<Year>2025</Year>
<Month>09</Month>
<Day>30</Day>
</PubDate>
</Journal>
<ArticleTitle>Exact Expressions for Dependence Measures of Bivariate Extreme Value Copulas</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage></FirstPage>
<LastPage></LastPage>
<ELocationID EIdType="doi">10.57647/mathsci.2025.1903.12</ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Saralees</FirstName>
<LastName>Nadarajah</LastName>
<Affiliation>Department of Mathematics, University of Manchester, Manchester M13 9PL, UK</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Victor</FirstName>
<LastName>Nawa</LastName>
<Affiliation>Department of Mathematics and Statistics, University of Zambia, Lusaka, Zambia</Affiliation>
<Identifier Source="ORCID">https://orcid.org/0000-0001-6019-7325</Identifier>
</Author>
<Author>
<FirstName>Adamu Abubakar</FirstName>
<LastName>Umar</LastName>
<Affiliation>Department of Mathematics, University of Manchester, Manchester M13 9PL, UK; Department of Statistics, Ahmadu Bello University, Zaria, Nigeria</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2025</Year>
<Month>09</Month>
<Day>30</Day>
</PubDate>
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<Abstract>Extreme value copulas are important because they model the dependence structure between extreme events, allowing for accurate risk assessment in fields such as finance, insurance, and environmental studies. In this paper, we derive exact expressions for four of the most popular dependence measures of bivariate extreme value copulas and check their correctness numerically. Over twenty families of bivariate extreme value copulas are considered.</Abstract>
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<Param Name="value">Hoeffding’s Φ²</Param>
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<Param Name="value">Kendall’s τ</Param>
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<Param Name="value">Spearman’s ρ</Param>
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