Description: From a session at the annual meeting of the Society of Actuaries held in Chicago, Illinois, October 15-18, 2000 Discussion of purposes and approaches for creating interest-rate scenarios.

Description: This is a thank you note sent out by Sarah Christiansen of the Principal Financial Group and Stuart Klugman of Drake University for the opportunity of hosting the 34th Annual Actuarial Research Conference. The Conference was held Aug. 8-11, 1999, in Des Moines, Iowa. The theme of the conference, jointly sponsored by Drake University and The Principal Financial Group, was building bridges between theory and practice. From Actuarial Research Clearing House 2000, Vol. 1.

Description: Presented at May 1996 Spring Meeting. Teaching session on various types of algorithms that can be used, their applications and their pros and cons.

Description: The primary focus of this 1997 presentation from the 32nd Actuarial Research Conference is the adaptation of the representative scenario method such that the distribution of the primary rates used for product pricing, are consistent, regardless of the initial random number seed. A preliminary question is how many stochastically generated scenarios are required for consistency. This presentation looks at the implications of: the use of antithetic random normal deviates upon the scenario process, ways of modifying the candidate list, and the choice function within the representative scenario process.

Description: This paper discusses interest rate generators which vary by intended purpose. The primary focus is on fairly elementary generators for studying C-3 risk, with major emphasis on parametric, mean reversionary generators.

Description: The paper discusses the role of a regulatory actuarial auditor, the risk focused examination process and the policyholder protection provided by the states, and the impact of varying state laws on the valuation process, and the importance of avoiding actuarial software becoming a black box. There is a discussion of the potential problems presented by the potential use of artificial intelligence, as well as suggestions for academic researchers to answer the pressing questions of whether artificial intelligence can potentially be used for valuation purposes.

Description: This paper suggests a possible flexible solution to the time and resource problems of running a large number of stochastic interest rate scenarios, by selecting a representative subset. Each interest rate scenario consists of 30 future spot yield curves, where a reasonable number of points are specified on each curve such as 12. The distribution of the scenarios is approximated by the subset and each scenario in the subset has equal weight. The method is independent of the interest rate generator used.

Description: This is the abstract for the paper on credit risk simulation.

Description: The complete Expanding Horizons newsletter for May 2002.