Description: The goal of this paper is to examine similarities between value investing and enterprise risk management (ERM) methods.

Description: The SOA is pleased to make available a report updating the 2012 risk assessment performed by Porteous et al. The report also provided an economic capital analysis for a stylized US plan with the same member profile and the USS provisions modified to reflect a typical US DB plan.

Description: The Society of Actuaries Research Institute’s Catastrophe and Climate Strategic Research Program is pleased to release two essays addressing sustainability and sustainable development goals.

Description: This study attempts to measure incidence rates, loss severity, and expected basis-point loss associated with credit risk events. The study identifies asset characteristics believed to influence credit risk and develops a process for gathering and evaluating intercompany credit risk data.

Description: This paper presents a theoretical approach to the valuation of options on bonds, a computer model for valuing such options, an application of options theory to evaluate the risk of call options on corporate bonds, and an application of options theory to price the risk of deposit antiselection on certain GICs sold to employee savings plans. From Transactions of Society of Actuaries 1985, Vol. 37.

Description: This paper presents the probabilistic concepts underlying measurement of asset adequacy in a simplified way. Discussions of this paper are included.

Description: The purpose of this paper is to provide a method for calculating special contingency reserves for investment losses. The method is derived by first building a stochastic investment model and then utilizing its probabilistic structure. From Transactions of Society of Actuaries 1980, Vol. 32.

Description: The Stochastic Volatility, SV, model is used for capturing the empirical properties of financial time series. This paper overviews those properties and compares the SV model with the heavy-tailed error distribution Student t-distribution and the SV model with the normal error distribution. The Simulated Maximum Likelihood, SML, method is applied to estimate the parameters and the latent volatility.

Description: This research was funded by the Natural Sciences and Engineering Research Council of Canada [NSERC] Discovery Grant 36860–06. Loss reserving is one of the most challenging tasks facing actuaries. Numerous approaches have been developed to give reasonable estimates. Generalized linear models [GLMs] are becoming quickly popular statistical analysis methods to estimate loss reserves. However, most of these models are aggregate reserving methods based on loss development triangles, without using information with regard to the actual claims processes. This paper establishes a more sophisticated structural reserving method incorporating more detailed information, such as the premium exposure emergence pattern, the loss emergence pattern and the loss development pattern, within the framework of GLMs.

Description: The method described in this paper is to allocate surplus to each category of business and reserves in proportion to its estimated effect on an insurer's surplus variation. Risk load for each category of business is then selected so that the return on allocated surplus for each category is equal to the overall return on surplus. From Actuarial Research Clearing House 1993, VOL. 3.