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Claims Reserving with a Stochastic Vector Projection

Portugal, L., Pantelous, A.A., Assa, H. (2017) Claims Reserving with a Stochastic Vector Projection. North American Actuarial Journal, 22 (1). pp. 22-39. (doi:10.1080/10920277.2017.1353429) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:87564)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. (Contact us about this Publication)
Official URL:
http://dx.doi.org/10.1080/10920277.2017.1353429

Abstract

In the last three decades, a variety of stochastic reserving models have been proposed in the general insurance literature mainly using (or reproducing) the well-known Chain-Ladder claims-reserving estimates. In practice, when the data do not satisfy the Chain-Ladder assumptions, high prediction errors might occur. Thus, in this article, a combined methodology is proposed based on the stochastic vector projection method and uses the regression through the origin approach of Murphy, but with heteroscedastic errors instead, and different from those that used by Mack. Furthermore, the Mack distribution-free model appears to have higher prediction errors when compared with the proposed one, particularly, for data sets with increasing (regular) trends. Finally, three empirical examples with irregular and regular data sets illustrate the theoretical findings, and the concepts of best estimate and risk margin are reported.

Item Type: Article
DOI/Identification number: 10.1080/10920277.2017.1353429
Subjects: H Social Sciences
Divisions: Divisions > Kent Business School - Division > Department of Accounting and Finance
Depositing User: Hirbod Assa
Date Deposited: 29 Apr 2021 11:30 UTC
Last Modified: 04 Mar 2024 16:26 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/87564 (The current URI for this page, for reference purposes)

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