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: Read the April 2020 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: Presented at May 2005 Spring Meeting. Panelists discuss the use of stochastic embedded value 'EV' in financial management and risk measurement, including considerations in reconciling period-to-period results.

Description: Producing a crystal-clear balance roll-forward on time, obtaining a fresh model output the first time or providing model results for your business partners with a tight turnaround all depend on one thing: how fast the model engine runs. Authors explored various reasons behind significant computational power consumption, and discussed different ways to speed the computational process such as in-force population compression, model use case consolidation, code simplification and streamlining, and infrastructure automation, etc.

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: Stochastic approximation is a powerful tool for sequential estimation of zero points of a function. In this paper, this methodology is defined and is shown to be related to a broad class of credibility formulae derived for the Exponential Dispersion Family. The authors further consider a Location Dispersion Family which is rich enough and for which no simple credibility formula exists. For this case, a Generalized Sequential Credibility Formula is suggested and an optimal stepwise gain sequence is derived.

Description: 1998 Valuation Actuary Symposium. The panelists discussed how asset liability management is synonymous with a dynamic financial analysis and quantitative risk management. Topics covered were systems implementations including asset risk exposure optimization given a company-specific set of liabilities and total risk exposure optimization, which includes stochastic analysis of alternative asset and liability strategies.

Description: This report is sponsored by the Society of Actuaries in collaboration with Ernst & Young. It examines the application of stochastic modeling techniques to non-market risks facing the life insurance industry.

Description: In December 2007, Goldman Sachs launched a product called QxX index swap, which is designed to allow market participants to hedge or gain exposure to longevity and mortality risks. This presentation offers a quantitative analysis of this brand new financial innovation. First of all, the presentation sets up a risk-neutral framework to price QxX index swaps. This framework, which is based on the dynamics of death rates under a two-factor stochastic mortality model in a risk-adjusted probability measure, yields prices [spreads] that are fairly close to the spreads that Goldman Sachs currently offers. The presentation then explores the uncertainty involved in this model-based pricing framework. Specifically, it studies parameter risk by using Markov Chain Monte Carlo [MCMC] and model risk by examining structural changes in mortality dynamics. The results indicate that both model risk and parameter risk are significant. Actuaries should therefore be aware of these issues when placing a value on a longevity index swap.

Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. This paper suggests the use of a policy event-based loss estimation method using expert input and simulation for forecasting long duration expenditures: that is to say, there is an efficient time, which is random and observable to replace a physical asset.