A new ordinal mixed-data sampling model with an application to corporate credit rating levels
From MaRDI portal
Publication:6556109
DOI10.1016/J.EJOR.2023.10.017MaRDI QIDQ6556109
Raffaella Calabrese, Jonathan Crook, Leonie Goldmann
Publication date: 17 June 2024
Published in: European Journal of Operational Research (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- Title not available (Why is that?)
- MIDAS Regressions: Further Results and New Directions
- Regression modeling strategies. With applications to linear models, logistic regression, and survival analysis
- Evaluation of credit risk based on firm performance
- Credit risk assessment using a multicriteria hierarchical discrimination approach: a comparative analysis
- The value of text for small business default prediction: a deep learning approach
- Random effects model for credit rating transitions
- On multiple-class prediction of issuer credit ratings
- A Globally Convergent Augmented Lagrangian Algorithm for Optimization with General Constraints and Simple Bounds
- Credit scoring with macroeconomic variables using survival analysis
- Evaluating Learning Algorithms
- Unrestricted mixed data sampling (MIDAS): MIDAS regressions with unrestricted lag polynomials
This page was built for publication: A new ordinal mixed-data sampling model with an application to corporate credit rating levels
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6556109)