Description: It is worth the effort to obtain a pricing surface. It helps make an informed decision and facilitate the pricing conversation within and outside a company.

Description: Abstract of Research Project on Interest Rate Risk

Description: In this paper we propose a model that can be used to analyze correlated claims data. In the process we introduce a class of multivariate generalized Poisson distributions. Then we present posterior distributions of its parameters. These distributions are difficult to manipulate, so we employ Markov chain Monte Carlo methods to draw random numbers from posteriors and predictive distributions. We present a collection of EXCEL VBA functions and subroutines to perform the simulations.

Description: Excerpts from a conversation with Alan Mills regarding his work in complexity science and agent-based modeling.

Description: Reviewing a text covering multiple statistical modeling topics: e.g., generalized linear models, decision trees, clustering, using the statistical language R.

Description: The purpose of this paper is to explore pension plan dynamics— – the behavior of a defined- benefit pension plan over time in an uncertain environment. We proceed by simulating the behavior of a model plan in a stochastically varying economic environment. While both the model and its environment are simplified, the model displays interesting behavior suggesting policy considerations that should be included in the design and funding of these plans.

Description: In 2003, the American Academy of Actuaries Life Capital Adequacy Subcommittee LCAS published a set of 10,000 stochastic scenarios that was intended to be used to support the publication, “Recommended Approach for Setting Regulatory Risk-Based Capital Requirements for Variable Products with Guarantees Excluding Index Guarantees.” The primary purpose of this article is to illustrate statistical measures that can be used to evaluate stochastic simulations.

Description: This article discusses the pending elimination of Section 7 exemption for small companies.

Description: Presented at October 1986 Annual Meeting. This session discussion is about the use of simulation, or Monte Carlo, techniques to analyze complex insurance models such as estimating reserves, solvency considerations, and estimation of mortality and distribution of aggregate losses with the aid of a computer program