Description: The purpose of this paper is to explore pension plan metrics— – measuring the behavior of a defined- benefit pension plan in an uncertain environment. Our goal is to measure and evaluate the quantitative impact of competing policy choices. We proceed by investigating some basic pension metrics, evaluating the characteristics of each using a simulated pension plan. We find that some typical metrics— – such as the mean and standard deviation— – are useful only in certain circumstances and that other less traditional measurements are sometimes better suited to evaluating policy choices.

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: One of the first projects undertaken by Claim Analytics was to create a model to predict return to work for group insurance claimants with long term disabilities. This report, sponsored in part by the Society of Actuaries Health Section , is a case study on creating such a model.

Description: An Overview of Stochastic Simulation modeling techniques and usages

Description: At this session 114 PD of the Toronto Spring Meeting, participants learn how to create efficient simulation models in Excel for various problems arising in finance and insurance. From the Record of the Society of Actuaries, Volume 27, No. 2, Session

Description: Panelists discuss the methods HMOs employ to measure their providers' quality of care, outcomes, compliance with best practice guidelines, and cost control. From the Record of the Society of Actuaries, Vol. 25, No. 2.

Description: This paper introduces and illustrates a new version of the Monte Carlo method that has attractive properties for the numerical valuation of derivatives. Quasi-Monte Carlo methods use deterministic sequences that are quasi-random sequences that result in better convergence and deterministic error bounds.

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

Description: This is a record of a session at the October 1975 Annual Meeting of the SOA. It discusses what can be done with a corporate model and how it can be used to solve problems. 1975 Record Vol. 1, No 4.

Description: Article discusses the conference on mathematical simulation models at Duke University on Oct. 31, 1968.