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: This publication presents an exploratory framework that applies volatility signals—specifically the VIX and MOVE indices—to asset allocation decisions. Rather than prescribing a definitive model, the work highlights a potential pathway for linking equity and bond market risk expectations to portfolio construction. The analysis demonstrates how relative volatility between asset classes can inform dynamic weighting, opening the door to more adaptive strategies in shifting market environments. Importantly, this is not intended as a finished methodology, but as a foundation on which more experienced professionals can build. Readers with advanced backgrounds in finance, risk management, or quantitative analysis are encouraged to refine, stress-test, and extend the framework to suit their own investment contexts. By positioning the concept as a starting point rather than a conclusion, the publication invites collaboration and deeper exploration into how volatility-based metrics may enhance long-term allocation models.

Description: This article discusses techniques for modeling credit risk, including discussion of default assumptions and recovery rates.

Description: There are two main techniques for evaluating the financial impact of interest rate movements on insurance companies: duration measures and computer simulations. In many ways these approaches provide complementary viewpoints.