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: This document provides answers to the exercises in the report titled Complexity Science – an introduction and invitation for actuaries:.

Description: This tool created graphs of Google's mobility Data. This version of the tool contains global, country-level data through July 31, 2020

Description: This report provides actuaries and other finance professionals with an example of running the Medicaid Unwinding model with results at the national level on projected changes in both acuity and enrollment for Medicaid and Children’s Health Insurance Program.

Description: This project models and forecasts premature cardiovascular mortality, with a focus on two main risk factors - obesity status and education attainment level. It investigates the role of obesity and education in determining age-sex-specific premature cardiovascular mortality.

Description: This report explores the behavioral factors influencing insurance purchase among Gen Z and Millennials for forward-looking purposes, leveraging a rich dataset spanning 22 markets across six continents.

Description: This abstract describes a paper that presents preliminary observations with respect to probabilistic fuzzy systems.

Description: Appendix E is round 2 on comments on application of judgmental methods from the Delphi study. See the SOA Website Research section for the full Delphi Study of Economic Variables Report along with all the variables.

Description: This paper provides actuaries with background and scientific knowledge to understand global climate change and climate model projections for the 21st century.

Description: Using data from the Mexican Social Security Institute for labor risks, this paper classifies the severity of sequels in three categories: mild, moderate and high, and attempts to relate this level with the characteristics of the worker and his activities at work. Toward this goal, a model was built using a multilogistic regression, which allowed predicting the severity of physical sequels caused by a labor risk. From Actuarial Research Clearing House, 2006.