Full text
| |
| Author(s): |
Fernando Ferraz do Nascimento
Total Authors: 1
|
| Document type: | Master's Dissertation |
| Press: | Campinas, SP. |
| Institution: | Universidade Estadual de Campinas (UNICAMP). Instituto de Matemática, Estatística e Computação Científica |
| Defense date: | 2006-03-17 |
| Examining board members: |
Nancy Lopes Garcia;
Helio dos Santos Migon;
Francisco Louzada Neto
|
| Advisor: | Nancy Lopes Garcia; Ronaldo Dias |
| Abstract | |
We compare several forecast techniques for IBNR(Incurred But Not Reported) from a Run-Off triangle data, since the most simple techniques like Chain-Ladder and Separation Technique, to the more complex using Log-Normal models and Compound Poisson distribution. Therefore, exist the necessity of the use of Nonparametric techniques, using a model that consider variable Truncation. It was possible shown that, when we don't have any information about the data, it's possible estimate de IBNR forecasting with less mistake and variability than the usual techniques. For make the forecasting, we used claims simulations occurring by a nonhomogeneous Poisson process and with dependence entry the time to report and value paid for one claim. The measure of comparison used was the Mean Square Error (MSE) of simulated values and forecasting values for each technique. The parametric boarding when the data come from a Compound Poisson distribution, was the best MSE entry all techniques. However, when we don't have any information about the data, the Truncation Technique was the best of the nonparametric techniques (AU) | |