Description: The Risk Management Task Force polled the Risks & Rewards readers and asked the following questions related to Monte Carlo models: 1 How many scenarios do you run? 2 How did you determine the number? and 3 What confidence interval does your result have? The results are summarized in this article.

Description: Feature article discussing numerical short cuts, rules of thumb, estimators, modeling tips, etc. The featured problem is fitting the intermediate points for a real-world stochastic model of interest rates.

Description: The author notes “a telescope and a kaleidoscope both provide a view but that is where the similarities end. A telescope shows us an actual view whereas a kaleidoscope creates a view from broken pieces of glass. This article will analyze which analogy is closer to the stochastic modeling of interest rate or stock market projections.”

Description: A paper entitled “A Regime-Switching Model of Long-Term Stock Returns” appears in the April 2001 issue of the North American Actuarial Journal. In it, Dr. Mary Hardy describes a model for future equity returns and some reasons why that model might better reflect real equity price movements than the often-used lognormal model. The purpose of this article is to apply a two-regime model to variable annnuity GMDB pricing and compare the results to those from a lognormal model.

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.

Description: Are Your Scenarios on Target?From Risks and Rewards Newsletter, August 2005, Issue No. 47. Actuaries are faced with the dilemma of how to incorporate advances in insurance products and modeling technology into their work. Increasingly, this means looking at a large number of potential outcomes using stochastic simulations.

Description: The article discusses that drawbacks of the HJM Heath-Jarrow-Morton class of stochastic interest models and suggests the use of the Longstaff-Schwartz string model. It describes the use and benefits of the Lonstaff-Schwartz string model.

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: 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.