Publicação
On the behavior of some estimators for the index of stability
| Resumo: | Heavy-tailed distributions have been used to model phenomena in which extreme events occur with high probability. In these type of occurrences, it is likely that extreme events are not observable after a certain threshold. Appropriate estimators are needed to deal with this type of truncated data. By means of simulation, it is shown that the well-known Hill-Hall estimator yields highly biased estimates in the presence of truncated data. An unbiased modified maximum likelihood estimator and the tail regression estimator are studied. The expected value and variance of the estimators is assessed in the cases of stable- and Pareto-distributed data. |
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| Autores principais: | Crato, Nuno |
| Outros Autores: | Dowling-DaCosta, Leslie |
| Assunto: | Stock Market Cost Pareto-distributed Data Nonlinear Model |
| Ano: | 1998 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório da Universidade de Lisboa |
| Resumo: | Heavy-tailed distributions have been used to model phenomena in which extreme events occur with high probability. In these type of occurrences, it is likely that extreme events are not observable after a certain threshold. Appropriate estimators are needed to deal with this type of truncated data. By means of simulation, it is shown that the well-known Hill-Hall estimator yields highly biased estimates in the presence of truncated data. An unbiased modified maximum likelihood estimator and the tail regression estimator are studied. The expected value and variance of the estimators is assessed in the cases of stable- and Pareto-distributed data. |
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