报告人简介：
武汉大学数学与统计学院教授,博士生导师。1993年7月博士毕业于武汉大学数学系、并留校任教，现主要从事金融风险度量、保险数学等相关领域的教学与科研工作。2004年入选教育部“新世纪优秀人才支持计划”，先后主持完成国家自然科学基金项目5项，目前主持在研国家自然科学基金面上项目1项。近年来，在Insurance: Mathematics and Economics, Stochastic Models, Statistics and Probability Letters等国内外专业刊物上发表学术论文40余篇；先后应邀访问美国Maryland大学、加拿大York大学、芬兰Helsinki大学、香港大学、香港科技大学、香港浸会大学。曾任中国数学会理事、中国概率统计学会理事；现任中国概率统计学会保险精算专业委员会委员、湖北省金融统计学会常务理事。
报告内容：In this talk, we will introduce two new classes of multivariate risk measures, which are referred to as multivariate copula-dependent distortion risk measures. We define and axiomatically characterize the class of multivariate scalar copula-dependent distortion risk measures through the tool of multivariate Choquet integral. As a by-product, this characterization can also be regarded as a multivariate extension of the univariate Greco's Representation Theorem. Furthermore, based on the representations for the multivariate scalar copula-dependent distortion risk measures, we will introduce the class of multivariate vector-valued copula-dependent distortion risk measures, and their properties of copula-dependent monotonicity, translation invariance, positive homogeneity and pi-comonotone additivity are shown. Finally, we present several examples, among which one example introduces a new class of vector-valued risk measures, while the others demonstrate the comparisons of the introduced multivariate vector-valued distortion risk measures with those vector-valued risk measures known as in the literature. This talk is based on a joint work with Suo Gong and Linxiao Wei.
