Description: Presented at October 1985 Annual Meeting. This session discusses a study by the Center for Futures Research 'CFR' at the University of California and possible users of CFR and similar studies in the strategic planning process.

Description: A description of how to use Deep Learning and TensorFlow

Description: In this article, we are going to discuss the AR model by making connections to time-dependent ordinary differential equations.

Description: The purpose of this delightful and stimulating book is the identification of new products for the marketplace. Anyone interested in predicting the future should read it. The book surveys the batting average of futurists, which IS amazingly low. About 20 years ago, Herman Kahn predicted 100 changes that would occur by the end of the century.

Description: The Study was designed to elicit reasons behind the participants’ judgments about the future course of the four variables. In the first round participants were asked to provide judgments about the value of the four variables in 2024 and the reasons behind their judgments. The four variables were 1. Increase in CPI, 2. 10 Year Treasury Yield, 3. S&P500 Total Rate of Return, and 4.Corporate Baa yield. In addition, they were asked to list future developments that could cause historical trends in the variables to change. Finally they were asked to express their views on how the judgmental process employed in this study might influence the use and interpretation of traditional actuarial e.g., stochastic, deterministic estimation processes or to aid in planning. The data were collated between rounds and in the second Round, the responses of the group were provided to the participants.

Description: Information about a social insurance modeling mini-seminar at the SOA’s 2010 Annual Meeting

Description: The author discusses the field of artificial intelligence, as well as some of the key definitions along with some possible applications.

Description: In Complexity: A Guided Tour, readers are given a short history lesson on the roots of dynamical systems theory, chaos and prediction.

Description: The direct and indirect effects of the pandemic have impacted many actuaries’ work since the spring of 2020. This article addresses three considerations actuaries should account for when using risk evaluation models which are focused on projecting remote, highly unlikely losses: model effectiveness, asset risk, and insurance (mortality and mortality) risk.

Description: This paper addresses rainfall insurance using financial derivatives. Usual modeling is done for temperature related products. The authors gathered rainfall data in Mexico City over a period of five decades. This showed that the time series data is stationary and normally distributed. Therefore, the authors applied a closed-form solution to value swaps, calls and puts, with and without limits. The model can be used for practical purpose of pricing rainfall derivatives. From Actuarial Research Clearing House, 2006.