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: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: Summary of the SOA's research report Modern Deterministic Scenarios for Interest Rates, which developed interest rate scenarios for use in cash flow testing.

Description: Read the November 2019 issue of The Modeling Platform, published by the Modeling Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).

Description: When Is It Right To Use Arbitrage-Free Scenarios? by Stephen Britt from Risks and Rewards Newsletter, September 2000, Issue No. 35.

Description: The research investigates the challenges associated with determining a “fair value” assessment for embedded options in two product types and incorporates the process into product pricing and liability valuation

Description: Summary of the SOA research project on PBR Simplified Methods. Describes the multi-risk scenario generator, central estimate assumptions, assumption objectivity measures, and regulatory demonstrations per VM-20.

Description: The article warns against treating the results of a stochastic model with more deference than other actuarial analysis, and describes some hidden risks involved with choice of model and calibration.