Description: From a session at the Spring meeting of the Society of Actuaries held in San Antonio, Texas, June 14-15, 2004 This session discusses emerging capital and reserve requirements on Variable annuities with guaranteed benefits and the effect that hedging/capital management strategies can have.

Description: In this paper, a mathematical model is constructed to study the deviations of claims, investment performance, operating expenses, and lapse expenses as random stochastic processes. Discussions of the paper submitted by 2 readers follows

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: An Overview of Stochastic Simulation modeling techniques and usages

Description: This article describes the key elements of a review of an economic scenario generator (ESG), including scoping, parameters, models, and model efficiency.

Description: This article provides an overview of the different types of real world interest rate scenarios that practitioners use in the life insurance industry and explores different approaches to building those generators.

Description: Panelists discuss economic capital, capital modeling, and hedge modeling, especially for guaranteed living benefits [GLBs] on variable annuities. Session 34PD of the 2005 Valuation Actuary Symposium.

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: Presentation from the 41st Actuarial Research Conference held in August, 2006 in Montreal. This presentation extends the traditional Sparre Anderson model of ruin theory, using an Erlang distribution for inter-claim times and geometric Brownial motion for asset returns.

Description: This paper introduces a rich stochastic modeling framework for understanding risks in multiple-decrement contracts. The example in the paper is a 20-year Term insurance contract. Not only are mortality and lapsation considered stochastic, but the parameters governing them are. For example, mortality risk is composed of four risk elements, including error generated in the underwriting process, volatility around the best estimate, catastrophic events that impact mortality, and the trend in mortality improvement or deterioration. When stochastically modeled, the relative contribution and risk profile of each risk element can be evaluated. Generating stochastic mortality results provides a distribution of results that an organization faces and the severity and incidence of the tail events.