Description: In this paper, we derive three important longevity Greeks on the basis of an extended version of the Lee-Carter model that incorporates stochastic volatility.

Description: Discussion of the movement toward principle-based reserves for LTC insurance.

Description: Discussion that developing credibility factors for group health insurance can be accomplished empirically through the use of stochastic models with appropriate parameters and fairly readily obtainable data, without the need for unrealistic assumptions.

Description: This paper illustrates the application of stochastic control methods in managing the risk associated with an insurance business. We present the Hamilton-Jacobi-Bellman HJB equation and demonstrate its use in finding the optimal investment strategy based on some given criteria. Here we consider an insurance business with a fixed amount available for investment in a portfolio consisting of one non-risky asset and one risky asset. The object of the resulting control problem is to determine the investment strategy that minimizes infinite time ruin probability. The existence of a solution to the resulting HJB equation is shown. The relevant verification lemma is not presented in this paper and a numerical algorithm is given instead. Examples applied to exponential claims are also presented.

Description: The series expansion of a probability density function, known to actuaries by Esscher's name and to statisticians as the saddlepoint approximation, typically gets integrated to approximate probability values under the density, with a location parameter in the expansion chosen to optimize convergence of the integrated series. We review the general form, the accuracy and the derivation of the Esscher approximation. Then we propose using related series expansions for the derivative of a probability density function to approximate the value of the point of maximum likelihood for the density. The key is to make the value of the location parameter an unknown and assume it to be the point of maximum likelihood, which leads to a tractable optimization problem to find its value.

Description: This paper proposes the use of stochastic compartment model methods for estimating both the current direct and current indirect costs of specific cancers and for forecasting future direct and indirect costs. From Transactions of Society of Actuaries 1982, Vol. 34.

Description: This article explains why stochastic modeling is becoming more pervasive, and describes a specific stochastic application with metrics to measure results.

Description: Looking for volunteer organizations to help Academy test new modeling techniques for PBR.

Description: An Overview of Stochastic Simulation modeling techniques and usages

Description: From a session at a meeting of the Society of Actuaries held in San Diego, CA, June 22-23, 2000 A discussion of how stochastic modeling techniques can be used to efficiently and effectively consider a wide variety of scenarios and outcomes and how these tools can be used to optimize portfolio performance?