Description: A summary of a new feature in the newsletter: a forecasting application contest. The Forecasting and Futurism Section will award a 16GB iPad to the section member who develops the best actuarial application of a judgmental forecasting method, incorporating best practices outlined in this issue’s article titled “Best Practices in Judgmental Forecasting.” In addition, we will feature the winning application in an issue of the newsletter.

Description: At the 2009 SOA Annual Meeting in Boston, Nassim Nicholas Taleb shared some thoughts on Black Swans, operating in the fourth quadrant, and living in the world of Extremistan versus Mediocristan during his keynote speech, all of which can be found in his published work. The follow-up session, summarized in this article, addresses the real question: What do we actuaries do about these phenomena?

Description: The author discusses the use of genetic algorithms as they apply to actuaries, specifically the application of characteristics and their potential to solve life insurance asset and liability management problems. He also highlights various ways genetic algorithms can be used to solve a variety of actuarial problems.

Description: A summary of how the Forecasting and Futurism Section is networking with other SOA sections and with external organizations to collaborate on various projects. Also highlights new events and projects happening on the forecasting and futurism front.

Description: An introduction to Hidden Markov Models, which are used extensively in speech and facial recognition technology. They are a useful tool in forecasting time series and in developing categorizations of data based on the values of the data themselves.

Description: Describes what a Delphi study is and why actuaries might want to use one.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.

Description: Given the limits of classical actuarial modeling and forecasting techniques, this newsletter contains articles discussing several ways to supplement your toolset.

Description: Book review of: Social Science from the Bottom Up, by Joshua M. Epstein and Robert Axtell

Description: The article gives a brief history of the development of the Delphi method, and describes the use of the Delphi method in studies by the Society of Actuaries over the past 25 years.