Model Risk and Uncertainty in the Financial World

Model Risk and Uncertainty in the Financial World addresses building and managing financial models while accounting for the risks and uncertainties within. The authors highlight how models can be uncertainty-laden, prone to failure and capable of sparking crises when their risks are ignored. They distil foundational concepts in economics, statistics and machine learning into an accessible read for model-builders and -users, emphasising a distinction between risk and uncertainty, and the importance of managing them differently.

Drawing on deep professional experience, Ghose and Soulellis guide readers through key themes: the limits of probability; the psychology of risk; specification and operations failures; and how the past informs lessons for the future. They argue that uncertainty can never be eliminated, but can be managed through measurement and estimation methods and a willingness to acknowledge the unknown.