Description: 1994 SOA Spring Meeting, Orlando. This session focused on the possible impacts of a return to higher interest rates and explored risk management strategies that may be appropriate.

Description: The evolving specialty pharmacy environment has created difficulties for actuaries pricing and forecasting pharmacy coverage. Unpredictable specialty pharmacy trends have increased insurers' earnings volatility and affected members' health care affordability. The presenters will highlight the current specialty drug development pipeline and explore specialty pharmacy drug trend management strategies. They will also provide concepts to help manage the coming wave of gene and cell therapies.

Description: Interest rates steadily declining ever since the Volcker Fed tackled inflation in the early eighties. Ten years of stimulating monetary policy brought new lows. We should have braced ourselves for a return to neutrality, but that concept remains elusive. We will explore structural issues that have brought rates to these low levels and the potential impacts on the insurance business.

Description: 1994 SOA meeting, Orlando. This session is entitled survivorship in finance. This was a free flowing discussion about finance and economics.

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 1997 presentation from the 32nd Actuarial Research Conference develops a stochastic generator for the generation of scenarios of the S&P 500 index, dividend yield, consumer price index, and U.S. Treasury yields. The authors first create a set of 'stylized facts' for these series. They estimate statistical models for these series. These in-sample statistical models are themselves not suitable for generation of scenarios for decision making, but instead are additional 'stylized facts' that assist in model development. The 'best' statistical model according to standard statistical model selection criteria can easily lead to a model that is highly unsuitable for generation of scenarios for decision making. The authors develop a stochastic generator that is suitable for decision making under uncertainty.