Concentration inequality of sums of dependent subexponential random variables and application to bounds for value-at-risk

Yuta Tanoue*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Concentration inequalities are widely used tools in many fields such as high-dimensional statistics, machine learning, optimization, signal processing, time series analysis, and finance. Therefore, various types of concentration inequalities have been derived so far. In this study, we derived new concentration inequalities for the sum of subexponential random variables. First one is the concentration inequalities for the sum of subexponential random variables with partial dependence structure. Second one is the concentration inequalities with Pearson’s (Formula presented.) By applying obtained concentration inequalities to the problem of portfolio risk management, we obtained upper bound for the value-at-risk of financial portfolio.

Original languageEnglish
JournalCommunications in Statistics - Theory and Methods
DOIs
Publication statusAccepted/In press - 2022

Keywords

  • Concentration inequality
  • dependence
  • sub-exponential
  • value at risk

ASJC Scopus subject areas

  • Statistics and Probability

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