Improved Hoeffding inequality for dependent bounded or sub-Gaussian random variables  

作　　者：Yuta Tanoue 

机构地区：[1]Institute for Business and Finance,Waseda University,3rd Floor,Bldg.111-6-1 Nishi-Waseda,Shinjuku-ku,169-8050 Tokyo,JP Full list of author information is available at the end of the article

出　　处：《Probability, Uncertainty and Quantitative Risk》2021年第1期53-60,共8页概率、不确定性与定量风险（英文）

基　　金：This work was supported by JSPS Grant-in-Aid for Young Scientists(Grant No.18K12873);Waseda University Grants for Special Research Projects(“Tokutei Kadai”)(Grant No.2019C-688).

摘　　要：When addressing various financial problems,such as estimating stock portfolio risk,it is necessary to derive the distribution of the sum of the dependent random variables.Although deriving this distribution requires identifying the joint distribution of these random variables,exact estimation of the joint distribution of dependent random variables is difficult.Therefore,in recent years,studies have been conducted on the bound of the sum of dependent random variables with dependence uncertainty.In this study,we obtain an improved Hoeffding inequality for dependent bounded variables.Further,we expand the above result to the case of sub-Gaussian random variables.

关 键 词：α-mixing coefficient Hoeffding inequality BOUNDED SUB-GAUSSIAN 

分 类 号：O17[理学—数学]