This paper adapts Gouriéroux and Monfort's (2021) model risk framework to property and casualty insurance, focusing on policy-level data. It addresses model risk at two levels: the impact on predictions and out-of-sample uncertainty, and the need to account for risk during model selection.
top of page
Rechercher
Posts récents
Voir tout“As analysts are primary recipients of these reports, we investigate whether and how analyst forecast properties have changed following...
This study proposes a new method for detecting insider trading. The method combines principal component analysis (PCA) with random forest...
Cyber risk classifications often fail in out-of-sample forecasting despite their in-sample fit. Dynamic, impact-based classifiers...
bottom of page
Comments