Statistical Properties and Power Analysis of Divergence Measures for Credit Risk Model Monitoring
arXiv stat.ML2w4 min read
arXiv:2607.12407v1 Announce Type: cross Abstract: Divergence measures are essential tools for detecting distributional shifts in model monitoring, particularly crucial given the volatility of financial data. While the Population Stability Index is the most widely used measure, Jensen-Shannon Divergence and Kullback-Leibler Divergence offer distinct advantages. Jensen-Shannon Divergence handles mixture models, addresses zero-binning problems, and is symmetric, while Kullback-Leibler Divergence excels in Bayesian model comparison. This study extends the work of Yurdakul and Naranjo (2020) with t