Abstract Several studies have demonstrated the high prediction accuracy of clustered credit risk modeling. In clustered modeling, borrowers are segmented based on their similarities through cluster analysis, and a separate predictive model is developed for each cluster, resulting in increased...

Real networks often exhibit nontrivial topological features that do not occur in random graphs. The need for synthesizing realistic networks has resulted in development of various network models. In this paper, we address the problem of selecting and calibrating the model that best fits a given...

This paper investigates the generalized parametric measurement methods of aggregate operational risk in compliance with the regulatory capital standards for operational risk in the New Basel Capital Accord ("Basel II"). Operational risk is commonly defined as the risk of loss resulting from...

Amid increased size and complexity of the banking industry, operational risk has a greater potential to transpire in more harmful ways than many other sources of risk. This paper provides a succinct overview of the current regulatory framework of operational risk under the New Basel Capital...

The purpose of this study is to assess model risk with respect to parameter estimation for a simple binary logistic regression model applied as a predictive model. The assessment is done by comparing the effectiveness of eleven different parameter estimation methods. The results from the...