Description: As stochastic modeling has evolved, it has divided down two paths—real-world and risk-neutral. This article discusses this division and shows how these paths may be re-united through the use of deflators.

Description: This teaching session is about conveying to users of models and forecasts how uncertain the outcome of stochastic projections really is.

Description: Modeling experience sharing by David Yu who leads the retirement product and asset model development team within Prudential Financial

Description: Discusses the interactions between dynamic lapses and interest rates in stochastic modeling for variable annuities.

Description: This paper analyzes the optimal retention level with a portfolio of insurance risks, and premiums invested in risk-free and risky assets. Optimality is defined here as maximizing expected utility of terminal payout.

Description: Commentary on practical observations resulting from constructing and running Economic Capital models. Possible standardization of assumptions and result interpretation are morphing even though use of E.C. models has now been around for years.

Description: This article deals with enterprise risk management and how the techniques contained within the discipline can help prevent unforeseen large mistakes in strategy, product design, and product management

Description: A discussion of methods used to determine the liability of segregated fund or separate account investment guarantees.

Description: Feature article discussing how insurers have reflected volatility in asset return assumptions when determining capital requirements, but have largely disregarded the impact of mortality volatility on their liability assumptions when performing stochastic analysis.

Description: Provides a metric based on the concept of "entropy" from information theory/signal processing, for modifying a stochastic scenario set to meet pre-defined targets on average across the set. Explains the concept and develops it in simple examples. Illustrates why an optimal adjustment to the scenario set is one that maximizes entropy. Provides guidelines to limit use of the technique appropriately and avoid invalid application of the tool.