Quantifying and correcting the bias in estimated risk measures

Joseph Hyun Tae Kim, Mary R. Hardy

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)


In this paper we explore the bias in the estimation of the Value at Risk and Conditional Tail Expectation risk measures using Monte Carlo simulation. We assess the use of bootstrap techniques to correct the bias for a number of different examples. In the case of the Conditional Tail Expectation, we show that application of the exact bootstrap can improve estimates, and we develop a practical guideline for assessing when to use the exact bootstrap.

Original languageEnglish
Pages (from-to)365-386
Number of pages22
JournalASTIN Bulletin
Issue number2
Publication statusPublished - 2007 Nov

All Science Journal Classification (ASJC) codes

  • Accounting
  • Finance
  • Economics and Econometrics


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