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

IF 1 2区 数学 Q3 STATISTICS & PROBABILITY Probability Uncertainty and Quantitative Risk Pub Date : 2021-01-01 DOI:10.3934/PUQR.2021003
Y. Tanoue
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引用次数: 2

Abstract

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.
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依赖有界或亚高斯随机变量的改进Hoeffding不等式
在处理各种金融问题时,例如估计股票投资组合风险,有必要推导出相关随机变量和的分布。虽然导出这种分布需要识别这些随机变量的联合分布,但准确估计相关随机变量的联合分布是困难的。因此,近年来人们对具有相关不确定性的相关随机变量和的界进行了研究。在本研究中,我们得到了一个改进的有界变量的Hoeffding不等式。进一步,我们将上述结果推广到亚高斯随机变量的情况。
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来源期刊
CiteScore
1.60
自引率
13.30%
发文量
29
审稿时长
12 weeks
期刊介绍: Probability, Uncertainty and Quantitative Risk (PUQR) is a quarterly academic journal under the supervision of the Ministry of Education of the People's Republic of China and hosted by Shandong University, which is open to the public at home and abroad (ISSN 2095-9672; CN 37-1505/O1). Probability, Uncertainty and Quantitative Risk (PUQR) mainly reports on the major developments in modern probability theory, covering stochastic analysis and statistics, stochastic processes, dynamical analysis and control theory, and their applications in the fields of finance, economics, biology, and computer science. The journal is currently indexed in ESCI, Scopus, Mathematical Reviews, zbMATH Open and other databases.
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