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

Yuta Tanoue*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)53-60
Number of pages8
JournalProbability, Uncertainty and Quantitative Risk
Volume6
Issue number1
DOIs
Publication statusPublished - 2021 Mar

Keywords

  • Bounded
  • Hoeffding inequality
  • Sub-Gaussian
  • α-mixing coefficient

ASJC Scopus subject areas

  • Statistics and Probability
  • Applied Mathematics
  • Statistics, Probability and Uncertainty

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