Description: It has been twenty years since DeWit 1982 first applied fuzzy logic FL to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now the FL methodologies include used fuzzy set theory, fuzzy numbers and fuzzy arithmetic, fuzzy inference systems, fuzzy clustering algorithms, fuzzy linear programming, fuzzy regression, and hybrids involving other soft computing technologies. This article presents an overview of these studies.

Description: This article provides an overview of three diverse fuzzy logic methodologies that can be employed to compute the value-at-risk of a portfolio.

Description: editorial policy for ARCH

Description: This abstract describes a paper that presents preliminary observations with respect to probabilistic fuzzy systems.

Description: The Lee and Carter LC method is getting widely adopted for long-run forecasts of age specific mortality rates. That popularity is first due to the model simplicity. Moreover, the LC model has given successful results for various countries e.g. U.S., Chile, G7 countries. However, some difficulties arose when using population data from certain countries such as UK and Australia. In the present paper, the LC model is applied to data from four Nordic countries: Denmark, Finland, Norway and Sweden. The Singular Value Decomposition SVD, the Weighted Least Square WLS and the Maximum Likelihood estimate MLE are used. These approaches give satisfactory results. The appropriate fitting period needs, however, to be well chosen. The properties of the model's parameters are studied using a bootstrap simulation.

Description: The purpose of this article is to revise the fuzzy regression portions of earlier studies and to discuss issues related to the Tanaka approach, including a consideration of fuzzy least-squares regression models. From Actuarial Research Clearing House, 2006.

Description: Recent articles addressed the subject of fuzzy regression [FR] and the term structure of interest rates [TSIR]. Their approach relied on possibilistic regression. Although possibilistic regression has been used in many applications, it has a number of limitations, not the least of which is its nebulous relation to the least-squares concept. As an alternative to possibilistic regression, this paper uses fuzzy least square regression to investigate the TSIR.

Description: Editor's comments that discuss the editorial policy regarding the Actuarial Research Clearing House publication.

Description: This is the abstract for the study that focuses on the fuzziness in regression models.

Description: These are thte editor's comments in the 2011 edition of ARCH.