Parametric Models and Their Tails

  • Henrik Hult
  • Filip Lindskog
  • Ola Hammarlid
  • Carl Johan Rehn
Part of the Springer Series in Operations Research and Financial Engineering book series (ORFE)


In this chapter we consider approaches to selecting a parametric family of distributions for a random variable and approaches to estimating the parameters. We also present techniques for analyzing the tails of the chosen probability distribution and the effect of the tails on the estimation of risk measures. Finally, we consider a semiparametric approach to the estimation of tail probabilities. It provides an alternative to relying on a full parametric model in order to produce estimates of tail probabilities beyond the range of the sample data.


Parametric Family Tail Probability Generalize Pareto Distribution Reference Distribution Parametric Bootstrap 
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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Henrik Hult
    • 1
  • Filip Lindskog
    • 1
  • Ola Hammarlid
    • 2
  • Carl Johan Rehn
    • 3
  1. 1.Department of MathematicsRoyal Institute of TechnologyStockholmSweden
  2. 2.Swedbank AB (publ)StockholmSweden
  3. 3.E. Öhman J:or Fondkommission ABStockholmSweden

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