Asymptotic distribution of the sample average value-at-risk

Stoyan V. Stoyanov, Svetlozar T. Rachev

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


In this paper, we prove a result for the asymptotic distribution of the sample average value-at-risk (AVaR) under certain regularity assumptions. The asymptotic distribution can be used to derive asymptotic confidence intervals when AV aR(X) is calculated by the Monte Carlo method which is adopted in many risk management systems. We study the effect of the tail behavior of the random variable X on the convergence rate and the improvement of a tail truncation method.

Original languageEnglish
Pages (from-to)465-482
Number of pages18
JournalJournal of Computational Analysis and Applications
Issue number4
StatePublished - Oct 2008


  • Asymptotic distribution
  • Average value-at-risk
  • Heavy-tails
  • Monte Carlo
  • Risk measures


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