Description: An overview of guaranteed lifetime withdrawal benefits (GLWB) on registered index-linkedannuity (RILA) products and a stochastic analysis of market risks.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).

Description: Describes using the new multi-risk scenario generator to create sensitivity tests at moderately adverse probability levels, resulting in margins to use for PBR.

Description: A summary of Modeling Section-sponsored sessions at the 2016 Life/Annuity Symposium, covering model risk management, model governance, and model efficiency.

Description: The article explores impact of resetting cap vs static cap choice for the GLWB rider for a Fixed Index Annuity for a Point to Point. Moreover, analysis of a Monthly Sum Cap is provided showing impacts of particular choices of market models (e.g. Black, Heston, Bates) used to price this deal.

Description: The next evolution of actuarial systems in the U.S. will likely be a move toward a single system solution. This article defines a single system solution and illustrates how models can be shared across actuarial functions, the potential benefits of a single system solution, and describes potential mitigation strategies to address typical actuarial concerns.

Description: In physics and engineering education, Fermi problems require solutions based on good approximate calculations with little or no actual data, involving making justified guesses and deducing bounds without using sophisticated tools. The idea of Fermi problems are of particular relevance to today's actuaries, as pricing, reserving, and financial reporting involve more and more complex stochastic components. The paper discusses some approximate solutions developed in academia in the spirit of Fermi problems.

Description: Using the recent West Africa Ebola outbreak as an example, the authors discuss several modeling approaches that can be useful for estimating pandemic risk.

Description: Feature article discussing how insurers have reflected volatility in asset return assumptions when determining capital requirements, but have largely disregarded the impact of mortality volatility on their liability assumptions when performing stochastic analysis.

Description: Discusses methods to efficiently run stochastic models in light of AG 43.

Description: Discusses the interactions between dynamic lapses and interest rates in stochastic modeling for variable annuities.

Description: Appendix to the Critical Review of Stochastic Simulation Literature and Applications for Health Actuaries. The Development of a Simulation Model of Primary Prevention Strategies for Coronary Heart Disease

Description: A study on stochastic simulation literature as it applies to a health actuary.

Description: This paper first derives the fair participation rate based on a fair value of the equity-indexed annuity EIA. Then using risk measures, a new participation rate is obtained, based on the tail loading of the hedging error distribution. Risk management strategies reducing risk related to the hedging error are also presented. A detailed numerical analysis is performed for a point-to-point EIA.

Description: The purpose of this discussion is to introduce a few additional points and discuss how different assumptions will alter the results in some cases.

Description: This paper analyzes the optimal retention level with a portfolio of insurance risks, and premiums invested in risk-free and risky assets. Optimality is defined here as maximizing expected utility of terminal payout.

Description: Are Your Scenarios on Target?From Risks and Rewards Newsletter, August 2005, Issue No. 47. Actuaries are faced with the dilemma of how to incorporate advances in insurance products and modeling technology into their work. Increasingly, this means looking at a large number of potential outcomes using stochastic simulations.

Description: An Overview of Stochastic Simulation modeling techniques and usages

Description: Discussion of Capital Market Modeling techniques