Tail Risk

Tail risk, the probability of extreme, low-frequency events with potentially catastrophic consequences, is a growing area of research across diverse fields. Current efforts focus on developing robust methods for predicting and mitigating tail risk, employing techniques from extreme value theory, stochastic optimization, and reinforcement learning to model and manage these rare events. This research is crucial for improving decision-making in areas such as finance, robotics, and machine learning, where the impact of rare but severe failures can be significant. Improved understanding and management of tail risk are essential for building more resilient and reliable systems.