Description: This paper provides commentary on the paper entitled 'A Discrete Equilibrium Model of the Term Structure' by N. J. Macleod, and J. D. Thomison. From Actuarial Research Clearing House 1990, VOL. 2.

Description: Consider a portfolio of insurance policies where the mean frquency of claims for each policy may vary. A reasonable assumption is that the number of claims for a policy is a Poisson random variable. In this paper the author shows how to test this hypothesis under certain conditions. He then presents some nonparametric tests for this and other hypotheses about the risk distribution function. Actuarial Research Clearing House 1992, VOL. 1.

Description: In this paper, the authors show how probabilities and actuarial values may be calculated using a time-homogeneous Markov model. Piecewise constant transition intensities are suggested as a way to extend the approach to the inhomogeneous case. From Actuarial Research Clearing House 1993, VOL. 1.

Description: This paper considers the problem of parametric estimation of loss distributions in a very general context. It uses the minimum distance method with the Cramér-von Mises statistic as the particular choice of distance. The authors show how to compute the influence function for the estimator. They also use the influence function to obtain more information about the variance and the robustness of the estimator. They demonstrate, with an example, how much more resistant to contamination this estimator is compared with the more classical maximum likelihood estimator.

Description: This paper addresses the evaluation of long-term returns when the short interest rate is modeled by a general diffusion process. By deriving the long-term return dynamics and invoking the Feyman-Kac formula, the long-term return is represented as the solution of a partial differential equation. A finite difference method is derived for the valuation of the long-term return. The method could be used for hedging interest rate risk, pricing and managing interest rate derivatives and interest rate sensitive insurance products. Numerical examples are included.

Description: Genetic algorithms [GAs] and neural networks [NNs] are currently being used in actuarial and financial modeling. Nonetheless, while there is a general awareness of the nature of these techniques, there is often only vague familiarity with the details of how they are implemented. This paper is intended to help alleviate this situation. Its purpose is to present an overview of GAs and NNs, which includes an explanation of what they are, how they work, and an example of how they are implemented.

Description: The primary objective of the paper was to develop a straightforward method for constructing an interpolation formula of finite range with desired properties stipulated in advance. This paper had in view mainly the application to polynomial interpolation as used in actuarial work. Followed by 2 discussion papers submitted

Description: This report introduces quantum computing to actuaries. In addition, this research will assess and identify areas in the insurance field where quantum computing can make a difference, accompanied with suggested algorithms.

Description: The American Academy of Actuaries and the Society of Actuaries have joined resources to maintain this Economic Scenario Generators Excel Workbook tool for use in regulatory reserve and capital calculations. Please see the SOA website research pages for further information on this tool and how to use it.

Description: The Product Development Section, the Financial Reporting Section, the Modeling Section and the Committee on Life Insurance Research are pleased to present new research on modeling and forecasting cause-of-death mortality. Authored by a Milliman team led by Alexandre Boumezoued, the report develops a framework for forecasting cause specific death rates. Included also is a Cause of Deaths Forecasting Tool and a user guide for the tool.