Description: While the major market crash subsequent to the widespread contagion of the COVID-19 virus was readily predictable, the rapid recovery and ongoing growth subsequent to it was not. Market dynamics around the recovery resist characterization by most traditional analytical approaches. In examining the circumstances around the emergence of a large retail class of investors, one sees that ingrained human tendencies, particularly optimism bias, have fueled much investor behavior responsible for the recovery. Understanding this makes it possible to predict potential future crashes and develop behavioral interventions for subsequent market recoveries.

Description: Hot Topics in Setting Pension Return Assumptions is the third in a series, following Mathematics of Pension Return Assumption and Inflation, focusing on Effects, Forecasts, and Role in Pension Valuations. What time horizon is more appropriate for Capital Market Assumption (CMA) forecasts: mid-term or long-term time horizon, or a blend of both? How do we map the asset classes of a plan's own investment policy to the asset classes of investment forecasters' CMAs? If we use asset-smoothing for valuation assets, should we use market-driven expected returns or smoothed/average versions of them?

Description: We explore the considerations regarding discount rates in the new US GAAP Targeted Improvements, including selection of observable rates and methods for extrapolations rates where there is no observable 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 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: The focus of this article is that while Economic Capital can be a valuable component of the ERM process for insurance companies, an over-emphasis on EC, to the point of neglect of other steps in the ERM process, can reduce the effectiveness of an ERM program.

Description: Why Write Variable Products When You Can Put the Money Directly into the Stock Market?

Description: This is a Confidentiality Agreement to be signed prior to contributing data to the Society of Actuaries' study that investigated the motivating factors contributing to the exercise of stock options.

Description: The 1986-98 Credit Risk Loss Experience Study represents a continuation of the 1986-94 study analyzing credit loss experience by institutional investors on private placement bonds. The study measures incidence rates, loss severities and economic loss rates associated with credit risk events for privately placed debt during the years 1986-98.