Description: From an interactive forum session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Discussion of the major financial reporting issues and concerns of senior actuaries in life insurance companies. Discussion focused cash flow testing methods and interpretation of results.

Description: This panel discussion session focuses on a proposal to modify the Standard Valuation Law involving statutory maximum valuation interest rates.

Description: This paper proposes a combinatoric approach to express higher moments of the quadratic variation process in terms of higher order variations of the original process and autocorrelations of the original process.

Description: 1994 SOA Spring Meeting, Orlando. This session is about accounting models for actuarial reserves and related items for selected countries in the Far East, Europe, and Latin America.

Description: This presentation illustrates a calibration model against 60 years of historical data using a pragmatic mixture of filtering, maximum likelihood and method of moments techniques, and compare the resulting model with interest rates in contemporary economic scenario generators.

Description: In this article, the author gives us the recap of this year’s ARC conference, held at UConn.

Description: The behavior of extreme paths in the usual stochastic interest rate models is not nearly so plausible as the behavior of their expected values and variances. This paper proposes a new class of models that deliver more plausible extreme paths while preserving the usual expected value and variance behavior. Along the way we derive the closed form solution for the traditional mean-reverting lognormal process, including the drift compensation.

Description: 1993 SOA Spring Meeting, Boston. This session is about management of multinational organizations from a home office perspective. It discussed cultural issues, regulatory issues, marketing issues, repatriation of profits, investment and currency risks.

Description: The series expansion of a probability density function, known to actuaries by Esscher's name and to statisticians as the saddlepoint approximation, typically gets integrated to approximate probability values under the density, with a location parameter in the expansion chosen to optimize convergence of the integrated series. We review the general form, the accuracy and the derivation of the Esscher approximation. Then we propose using related series expansions for the derivative of a probability density function to approximate the value of the point of maximum likelihood for the density. The key is to make the value of the location parameter an unknown and assume it to be the point of maximum likelihood, which leads to a tractable optimization problem to find its value.

Description: This is a panel discussion session from the 1981 SOA Spring Meeting on the relationship of product design and investment philosophy. From Record of Society of Actuaries 1981, Vol. 7, No. 1.