Description: This presentation, session number 83CS at the 1999 Spring Meeting of the Society of Actuaries, held June 16-18 in Seattle, is a preview of an actual Course 7. The presenters, two experienced researchers, lead the discussion and a demonstration of a case study from the modeling Course 7. Discussion from participants is included. From the Record of the Society of Actuaries, Vol. 25, No. 2.

Description: Presented at May 2005 Spring Meeting. Panelists discuss strategies for increased modeling speed as risk management, valuation and product development activities have been requiring increasingly complex financial models.

Description: This panel discussion session focused on the practical applications of risk theory.

Description: 1988 Valuation Actuary Symposium, In this session, the presenter suggests the value of the Reg 126 testing is a function of the attitude of the company toward the process. He also explored the differences in results by product of using deterministic versus stochastic scenarios.

Description: This session from the 1993 Valuation Actuary Symposium looks at asset models and economic scenario generation.

Description: From a teaching session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Panelists analyze the modeling considerations in projecting asset cash flows and asset valuations.

Description: This paper shows that Balucci hypothesis imposed on a survivorship function over a closed interval is dual to the uniform distribution of deaths hypothesis imposed on the survivorship function over the same interval.

Description: It is assumed that the force of interest varies as an auto-regressive process of order 2, AR[2]. The moments of the accumulated value of 1 paid at the beginning of each period, for n periods, are developed using moment generating functions.

Description: This article summarizes a method for measuring the credibility of a prediction from a logistic generalized linear model (GLM).

Description: Summary of SOA research report "Optimizing Risk Retention" which applies parametric survival models and Monte Carlo simulation to a block of term life business.