Tail variance premium with applications for elliptical portfolio of risks

Edward Furman, Zinoviy Landsman

Research output: Contribution to journalArticlepeer-review


In this paper we consider the important circumstances involved when risk managers are concerned with risks that exceed a certain threshold. Such conditions are well-known to insurance professionals, for instance in the context of policies involving deductibles and reinsurance contracts. We propose a new premium called tail variance premium (TVP) which answers the demands of these circumstances. In addition, we suggest a number of risk measures associated with TVP. While the well-known tail conditional expectation risk measure provides a risk manager with information about the average of the tail of the loss distribution, tail variance risk measure (TV) estimates the variability along such a tail. Furthermore, given a multivariate setup, we offer a number of allocation techniques which preserve different desirable properties (sub-additivity and full-additivity, for instance). We are able to derive explicit expressions for TV and TVP, and risk capital decomposition rules based on them, in the general framework of multivariate elliptical distributions. This class is very popular among actuaries and risk managers because it contains distributions with marginals whose tails are heavier than those of normal distributions. This distinctive feature is desirable when modeling financial datasets. Moreover, according to our results, in some cases there exists an optimal threshold, such that by choosing it, an insurance company minimizes its risk.

Original languageEnglish
Pages (from-to)433-462
Number of pages30
JournalASTIN Bulletin
Issue number2
StatePublished - Nov 2006


  • Elliptical distributions
  • Premium calculation principle
  • Risk capital allocation
  • Risk measure
  • Tail conditional expectation
  • Tail covariance premium
  • Tail standard deviation premium
  • Tail variance premium

ASJC Scopus subject areas

  • Accounting
  • Finance
  • Economics and Econometrics


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