Description: The instructors in this boot camp session will highlight the SOA's work on an updated Medicaid underwriting margin model. This research project includes an excel model, a set of instructions and a paper describing the key components of underwriting margin, including cost of capital and risk margin.

Description: Read the April 2020 issue of The Modeling Platform, published by the Modeling Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: This article discusses facts and issues related to the selection of a stock’s price distribution.

Description: Read the November 2019 issue of The Modeling Platform, published by the Modeling Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Summary of the modeling-related sessions from some of the major 2018 Society of Actuaries (SOA) meetings: Life & Annuity Symposium, Health Meeting and the Valuation Actuary Symposium.

Description: A Summary of the UVS Project by Dave Sandberg from The Financial Reporter, March 2001, Issue No. 45.

Description: Given the limits of classical actuarial modeling and forecasting techniques, this newsletter contains articles discussing several ways to supplement your toolset.

Description: Introduces readers to the R language used for statistics and modeling of data.

Description: This paper reviews the general methodology of capture-recapture procedures and describes some applications such as estimating the size of the undercount in censuses and estimating the number of duplicate records on in a database. From Actuarial Research Clearing House 2006.

Description: Logistic-type models for the force of mortality like those introduced by Perks or Kannisto provide better fit to mortality data of people aged over 85 than Makeham’s model where the force of mortality increases exponentially with age. However, the difficulty in estimating their parameters by the maximum likelihood method makes their use less popular among actuaries. For Kannisto’s model, this paper proposes a weighted least-squares estimator which can easily be calculated with any regression software. The estimator is shown to be consistent, asymptotically unbiased and normally distributed. For Perks’ model, using a Taylor’s series expansion, the estimation problem is again reduced to a least-squares problem. The various estimators proposed in the paper are compared numerically using Canadian mortality data.