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

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: 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: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: This is a short story on the retirement income calculator.

Description: This is the abstract of the paper Quasi-Monte Carlo Methods in Numerical Finance. This paper introduces and illustrates a new version of the Monte Carl method that has attractive properties for the numerical valuation of derivatives. The traditional Monte Carlo method has proven to be a powerful and flexible tool for many types of derivatives calculations.

Description: A recent Society of Actuaries study calculates safety and stability for current Long Term Care Insurance premiums.

Description: This article talks about replicating portfolios, a basket of financial instruments designed to replicate, as closely as possible, the value and market sensitivity of a target portfolio of liabilities in different economic scenarios.

Description: The article warns against treating the results of a stochastic model with more deference than other actuarial analysis, and describes some hidden risks involved with choice of model and calibration.

Description: Actuaries understand the technical benefits of converting their models to a modern actuarial system, such as new capabilities and upgraded technology. This article highlights additional, non-technical benefits that also come with model conversion. These benefits include advancements in attitudes and capacities among the team and across the company.