Tail Conditional Expectations for Exponential Dispersion Models

Zinoviy Landsman, Emiliano A. Valdez

Research output: Contribution to journalArticlepeer-review


There is a growing interest in the use of the tail conditional expectation as a measure of risk. For an institution faced with a random loss, the tail conditional expectation represents the conditional average amount of loss that can be incurred in a fixed period, given that the loss exceeds a specified value. This value is typically based on the quantile of the loss distribution, the so-called value-at-risk. The tail conditional expectation can therefore provide a measure of the amount of capital needed due to exposure to loss. This paper examines this risk measure for “exponential dispersion models”, a wide and popular class of distributions to actuaries which, on one hand, generalizes the Normal and shares some of its many important properties, but on the other hand, contains many distributions of nonnegative random variables like the Gamma and the Inverse Gaussian.

Original languageEnglish
Pages (from-to)189-209
Number of pages21
JournalASTIN Bulletin
Issue number1
StatePublished - May 2005


  • Exponential dispersion family
  • Tail conditional expectations
  • Tail value-at-risk

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics


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