Economics at your fingertips  

Forecasting aggregate claims using score‐driven time series models

Mariana Arozo B. de Melo, Cristiano A. C. Fernandes and Eduardo F. L. de Melo

Statistica Neerlandica, 2018, vol. 72, issue 3, 354-374

Abstract: In the insurance industry, premium estimation and ruin probability valuation depend fundamentally on the aggregate claims distribution. From the mathematical point of view, the aggregated claims variable is a random sum of random variables. Obtaining the analytical expression for its probability distribution is a hard task. In this paper, a new approach is proposed for the modeling of the aggregated claims predictive distribution. The newly proposed generalized autoregressive score models are combined to specify non‐Gaussian distributions for both the number of claims and the claims severity. In all models, appropriate parameters were made time varying according to a score‐driving mechanism. By the use of the fast Fourier transform, we are then able to numerically obtain the aggregated claims distribution. The proposed method is applied to real data, provided by a Brazilian motor insurer.

Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0039-0402

Access Statistics for this article

Statistica Neerlandica is currently edited by P. H. Franses

More articles in Statistica Neerlandica from Netherlands Society for Statistics and Operations Research
Bibliographic data for series maintained by Wiley Content Delivery ().

Page updated 2019-02-23
Handle: RePEc:bla:stanee:v:72:y:2018:i:3:p:354-374