Tail risk measures using flexible parametric distributions

• José María Sarabia ^[1] ; Montserrat Guillen ^[2] ; Helena Chuliá ^[2] ; Faustino Prieto ^[1]
  1. [1] Universidad de Cantabria

     Universidad de Cantabria

     Santander, España

     
  2. [2] Universitat de Barcelona

     Universitat de Barcelona

     Barcelona, España

     
• Localización: Sort: Statistics and Operations Research Transactions, ISSN 1696-2281, Vol. 43, Nº. 2, 2019, págs. 223-236
• Idioma: inglés
• Enlaces
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• Resumen

  • We propose a new type of risk measure for non-negative random variables that focuses on the tail of the distribution. The measure is inspired in general parametric distributions that are well-known in the statistical analysis of the size of income. We derive simple expressions for the conditional moments of these distributions, and we show that they are suitable for analysis of tail risk. The proposed method can easily be implemented in practice because it provides a simple one-step way to compute value-at-risk and tail value-at-risk. We show an illustration with currency exchange data. The data and implementation are open access for reproducibility.

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