A Functional Representation of Credit Behavior for Probability of Default Modeling
By Jonas Brunholm, Bjarne Højgaard, Thomas Dyhre Nielsen, Orimar Sauri
Rating
1721
Battle Count: 50
Relevance
2/10
The paper is highly relevant to credit risk management and banking regulation (IRB) but has low direct relevance to algorithmic trading or market microstructure strategies.
Implementation Complexity
7/10
Implementing Functional Data Analysis with spline bases, relative time alignment, and penalized estimation is significantly more complex than standard logistic regression, requiring specialized statistical knowledge and software.
Reproducibility
2/5
Data is proprietary to Nykredit and cannot be shared. Code is available upon reasonable request from the corresponding author, but no public repository is linked.
About this paper
Methodology: Functional Logistic Regression with Relative Time Alignment. Problem types: Classification, Risk Management, Time Series Forecasting.
The interactive Everscope explorer (charts, battles, favorites) loads below.