Description: From a session at the Spring meeting of the Society of Actuaries held in San Antonio, Texas, June 14-15, 2004 The panelists discuss the benefits of hedging variable annuity guarantees, the challenges they face and how they keep score.

Description: This report describes a stochastic simulation approach used to estimate the amount of a level-payment annuity payable as long as the person is alive and living in his/her house. A discussion of the paper follows. From Transactions of Society of Actuaries 1991, Vol. 43.

Description: This paper shows how the results of copula based capital aggregation models can always be locally approximated by relatively simple formulas. The paper defines the concepts of diversification factor and tail correlation matrix and describes methods for estimating these quantities from simulated data. We show how these ideas can be put into practice as both computational shortcuts and presentation tools.

Description: This paper studies the tail probability of discounted aggregate claims in a continuous-time renewal model. For the case that the common claim-size distribution is subexponential, the authors obtain an asymptotic formula, which holds uniformly for all time horizons within a finite interval. Then, with some additional mild assumptions on the distributions of the claim sizes and inter-arrival times, the authors further prove that this formula holds uniformly for all time horizons.

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: 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: This paper develops a new technique, which allows the analyst to maximally use all thte historical interest rate information available in forecasting interest rates. Interest rates' daily change do not follow a stationary random process over long time periods. Instead, the process is comprised of stationary periods, each a few years long, with relatively short transitional periods between different stationary periods.

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.