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 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.

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: Discussion of the appropriate use of geometric versus arithmetic average returns to use in a stochastic interest rate generator to be equivalent to a deterministic single interest rate scenario.

Description: The April 2016 Issue of The Modeling Platform

Description: For the purposes of risk management and stress testing, we characterize a spectrum of plausible extreme events, that we dub Grey Swans, by introducing a probabilistic method involving the concentration of measure phenomenon. As a result, stress tests can be triaged according to severity, probability and, now, information-based plausibility.

Description: This article describes the key elements of a review of an economic scenario generator (ESG), including scoping, parameters, models, and model efficiency.

Description: Target volatility, as an investment strategy, has been used by many funds not only as a way to smooth return but also as a way to manage risks of the VA guarantees. Contrary to existing research which favors volatility targeting over fixed allocation, this article shows that because of the existence of market jump risk, target volatility strategy does not necessarily offer an improved risk profile for VA writers. Further, target volatility coupled with leveraging can significantly increase tail risk for insurance companies.

Description: This article looks at stochastic techniques actuaries can use to quantify the non-market risks in insurance products and how stochastic techniques can be used in the evaluation of reinsurance arrangements.

Description: Summary of NAIC's Winter National Meeting