A Quantitative Risk Management Framework for Stable Value Fund Wraps

This paper introduces quantitative risk management and scenario analysis framework for asset-liability management of stable value fund wraps. Stable value funds are guaranteed return employee benefit investment options, with currently over $400 billion USD of assets under management. These investment schemes are synthesized as such to transform a volatile fund return into a more stable one and to buffer against short-term market fluctuations.Having the main objective of understanding risk scenarios from the insurer's perspective, we argue that the simplest model for participants' withdrawal, while still maintaining sufficient flexibility to detect tail scenarios, is a two-state regime-switching model. We present such a model and attempt to identify risk scenarios that may result in substantial losses for the insurer. We conclude that there are two scenarios to consider: the inflationary scenario and the yield spike scenario. We also back-test these scenarios historically during the financial crisis, the 1980 inflation period, the Great Depression period, and the 2020 pandemic.Finally, we apply the model to estimate the tail risk and study the impact of the fund's characteristics, e.g. duration and rating. Furthermore, we observe that under normal conditions, while our model suggests that there is a convex tail risk, the U.S. regulatory formulaic risk-based capital is almost always zero, which may infer an incomplete picture of U.S. insurers' actuarial risk and profitability metrics