Description: When fitting a model to any data, there is some uncertainty about which model is best. Green [1995] quantifies this uncertainty through the Reversible Jump Markov Chain Monte Carlo [RJMCMC] method. When using the RJMCMC method in a regime-switching situation, the chain determines the optimal number of regimes by jumping between various possibilities. This method gives each model its posterior probability of being the best. After an overview of the methodology, the authors apply it to various datasets and discuss the applications in modern actuarial science.

Description: This paper addresses the fuzziness in regression models. The goal is to present a test procedure to explicitly examine whether an independent variable has a clear functional relationship with the dependent variable in a specific regression model, or whether their relationship is fuzzy. To this end, the authors interpret the spread of the regression coefficients as a statistic measuring the fuzziness of the relationship between the corresponding independent variable and the dependent variable. They then derive test distributions based on the null hypothesis that such spreads could have been obtained with data generated by a classical regression model with random errors. The analysis is presented in conceptual rather than technical terms.

Description: The theme of this paper relates to solving portfolio selection problems using linear programming. The authors extend the linear optimization framework for Conditional Value-at-Risk-based portfolio selection problems to optimization over a more general class of risk measure known as the class of Coherent Distortion Risk Measure. From Actuarial Research Clearing House, 2012 Vol. 1.

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.

Description: These files shows the Schelling Segregation model. It accompanies the report Complexity Science - an introduction and invitation for actuaries, and supports the material in Chapter six: Cellular automata.

Description: This paper develops explicit relationships connecting these reserve bases, and, in the course of this development, derives several new and interesting actuarial relationships, all of which can be generalized to the case of monthly premium payment computations. Followed by a discussion paper submitted

Description: This people provides a derivation of continuous and curtate inequalities of life contingent functions and shows how the proofs of the continuous inequalities are of an entirely different nature from the usual proofs for the curtate inequalities Followed by discussion papers submitted by several authors

Description: The net premium for insurance for expected loss in excess of a retention limit may be small, but the resulting variance of excess losses produces a standard deviation several times that of the premium. The purpose of this paper is to give a derivation and evaluation of the standard deviation of the excess losses.

Description: This paper is an attempt to examine transmission and incubation period models. Results are used to estimate the risk of HIV+ exposure of an individual company and the resulting reserve needs. From Transactions of Society of Actuaries 1989, Vol. 41.

Description: This paper presents a statistical methodology based upon information theory, for adjusting mortality tables to obtain exactly some known individual characteristics, while obtaining a table that is as close as possible to a standard one. Followed by a discussion paper submitted