| Autor: |
Beirlant, J., Joossens, E., Segers, J.J.J. |
| Přispěvatelé: |
Research Group: Econometrics, Research Group: Finance, Econometrics and Operations Research |
| Jazyk: |
angličtina |
| Rok vydání: |
2009 |
| Zdroj: |
Journal of Statistical Planning and Inference, 139, 2800-2815. Elsevier |
| ISSN: |
0378-3758 |
| Popis: |
Modelling excesses over a high threshold using the Pareto or generalized Pareto distribution (PD/GPD) is the most popular approach in extreme value statistics. This method typically requires high thresholds in order for the (G)PD to fit well and in such a case applies only to a small upper fraction of the data. The extension of the (G)PD proposed in this paper is able to describe the excess distribution for lower thresholds in case of heavy-tailed distributions. This yields a statistical model that can be fitted to a larger portion of the data. Moreover, estimates of tail parameters display stability for a larger range of thresholds. Our findings are supported by asymptotic results, simulations and a case study. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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