Law of large numbers for m-dependent random vectors under sublinear expectations  

作　　者：Mingcong Wu Guanghui Cheng 

机构地区：[1]Joint Laboratory of Data Science and Business Intelligence,Southwestern University of Finance and Economics,Chengdu 610000,China [2]Guangzhou Institute of International Finance,Guangzhou University,Guangzhou 510006,China

出　　处：《Probability, Uncertainty and Quantitative Risk》2025年第1期1-12,共12页概率、不确定性与定量风险(英文)

基　　金：funded by the National Nature Science Foundation of China(Grant No.12001128);the GuangDong Basic and Applied Basic Research Foundation(Grant No.2022A1515011899).

摘　　要：Sublinear expectation relaxes the linear property of classical expectation to subadditivity and positive homogeneity,which can be expressed as E(·)=sup_(θ∈θ) E_(θ)(·)for a certain set of linear expectations{E_(θ):θ∈θ}.Such a framework can capture the uncertainty and facilitate a robust method of measuring risk loss reasonably.This study established a law of large numbers for m-dependent random vectors within the framework of sublinear expectation.Consequently,the corresponding explicit rate of convergence were derived.The results of this study can be considered as an extension of the Peng's law of large numbers[22].

关 键 词：Law of large numbers m-dependence Sublinear expectations Rate of convergence Random vectors 

分 类 号：O211[理学—概率论与数理统计]