Description: In session 119 CS of the Washington Annual Meeting panelists discuss techniques for analyzing and developing investment strategies based on the mathematical approach of linear programming are presented. From the Record of the Society of Actuaries, Vol. 23, No. 3.

Description: This research report summarizes methodologies used for yield curve extrapolation to value liability cash flows that extend beyond the maximum observavble portion of the yield curve.

Description: This session at the 1998 Valuation Actuary Symposium gives an overview of risk management. Two example company programs are described. The use of value at risk as a measure is discussed.

Description: Presentation from the Actuarial Research Conference describing risk management at a leading Canadian Bank.

Description: Risk Management and Actuaries—SOA Risk Management Task Force Update

Description: A central problem for regulators and risk managers concerns the risk assessment of an aggregate portfolio defined as the sum of d individual dependent risks Xi. This problem is mainly a numerical issue once the joint distribution of (X1,X2, . . . ,Xd) is fully specified. Unfortunately, while the marginal distributions of the risks Xi are often known, their interaction (dependence) is usually either unknown or only partially known, implying that any computed risk measure of the portfolio is subject to model uncertainty. Previous academic research has focused on the maximum and minimum possible values of a given risk measure of the portfolio, in the case in which only the marginal distributions are known. This approach leads to wide bounds, as all information on the dependence is ignored. In this paper, we integrate in a natural way available information on the multivariate dependence and provide easy-to-compute bounds for the risk measure at hand. We observe that incorporating the information of a well-fitted multivariate model may, or may not, lead to much tighter bounds, a feature that also depends on the risk measure used. We illustrate this point by showing that the Value-at-Risk at a very high confidence level (as used in Basel II) is typically prone to very high model risk, even if one knows the multivariate distribution almost completely. Our results make it possible to determine which risk measures can benefit from adding dependence information (i.e., leading to narrower bounds when used to assess portfolio risk), and, hence, to identify those models for which it would be meaningful to develop accurate multivariate models.

Description: The author makes 10 predictions of how risk management will change over the next decade.

Description: Panelists at this session of the SOA 1998 Maui I Spring Meeting presents their approach to an integrated risk management framework that assesses the level of risk in the organization and where it lies on the balance sheet.

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.

Description: This paper reviews the Value At Risk concept, a financial risk management tool and discusses its application to insurance. Difficulties with this application are described and modifications suggested. An alternative tool, expressed as a risk adjustment to economic value, is suggested as an additional measure.