Description: This article discusses the Modeling Actuarial Standard of Practice. Intent and questions related to a model across all practice areas is discussed

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Presenters offer a preview of an actual Course 7 dealing with applied modeling.

Description: Article from The Actuary, June 1983, volume no. 17, issue no. 6, that discusses eras in life contingencies theory. In the history of actuarial education on this continent, the subject of life contingencies has been successively presented to students in four major textbooks embracing almost exactly a century of instruction.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Year 2000 and Beyond: Society of Actuaries New Course: Applied Modeling Demonstration Charts 1 & 2 from that presentation

Description: Discussion of the skills actuaries need going forward to be successful, and hence, incorporated into the new actuarial exam syllabus.

Description: Two breakout sessions were held. Their goal was to explore ways in which researchers and practitioners could be brought closer together. The following summaries were edited by Stuart Klugman from notes taken by the indicated participants: Session #1 - Bridging the gap with regard to modality and morbidity and Session #2 - Bridging the gap with regard to financial modeling.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, GA May 24-25, 1999: Year 2000 and Beyond: Society of Actuaries New Course: Applied Modeling Demonstration: Charts 3 & 4 from that presentation

Description: During the last decade, a vast activity had been observed in generalizing of the classical discrete distributions. The main idea was to apply the extended versions fur modeling different kinds of dependent count or frequency data structure in various fields. In the present paper we suggest extensions of the classical univariate geometric, negative binomial, Poisson, Bernoulli, binomial and logarithmic series distributions, by including an additional parameter. It has a natural interpretation in terms of zero-inflation, and because of this we named the corresponding generalized versions adding inflated-parameter.

Description: View the complete issue for the August 2014 Reinsurance News newsletter.

Description: In the copula literature there are many bivariate distribution families but very few higher dimensional ones. Moreover, most of these are difficult to work with. Some of the bivariate families can be extended to more dimensions but in general the construction of distribution functions with more than two variables is a difficult problem. This paper introduces a construction method that is straightforward to implement and can produce multivariate distribution functions of any dimension.