Description: From a session at the Spring meeting of the Society of Actuaries held in San Antonio, Texas, June 14-15, 2004 This session covers different methods for estimating future volatility of financial markets, how to predict the effect of volatility on insurance company results, alternative approaches to managing volatility and the impact on volatility management on the choice of modeling method.

Description: It is well-known that reinsurance can be an effective risk management technique for an insurer. An appropriate use of reinsurance reduces the adverse risk exposure of an insurer and improves the overall viability of the underlying business. The use of reinsurance, on the other hand, incurs additional cost to the insurer in the form of reinsurance premium. This implies that an insurer is faced with a classic tradeoff between risk spreading and risk retaining. The thrust of my research is to propose some reinsurance designs that are optimal from the perspective of an insurer. This presentation describes an empirical approach to optimal reinsurance designs. This new method has the advantage that it does not need to make any explicit assumptions on the distribution of the underling risk. More importantly, it provides a simple and yet practical way of obtaining solution on a wide range of optimal reinsurance models.

Description: From the 1985 Valuation Actuary Symposium Discussion of the practical application of cash flow testing in the valuation process.

Description: Regime switching models have become a popular tool in econometric time series modeling since their introduction in Hamilton [1989].These models have been widely applied for equity-returns for investment guarantees. A prominent risk management challenge is hedging these guarantees, given the equity regime switching process. This presentation develops some methodologies for regime-switching portfolio replication and use real world data to demonstrate and evaluate their effects. A Bayesian approach for regime switching model fitting is used, which allows for the examination of the robustness of each of the optimization methods when parameter uncertainty is present.