Result: Structured Dictionary Learning of Rating Migration Matrices for Credit Risk Modeling
Title:
Structured Dictionary Learning of Rating Migration Matrices for Credit Risk Modeling
Authors:
Contributors:
Centre de Mathématiques Appliquées de l'Ecole polytechnique (CMAP), Institut National de Recherche en Informatique et en Automatique (Inria)-École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), BNPP, Chaire Stress Test - BNP Paribas/Ecole polytechnique/Fondation de l'X
Source:
Computational Statistics, 2024, ⟨10.1007/s00180-023-01449-y⟩
Publisher Information:
CCSD; Springer Verlag, 2024.
Publication Year:
2024
Collection:
collection:X
collection:CNRS
collection:AO-ECONOMIE
collection:INSMI
collection:X-CMAP
collection:X-DEP
collection:X-DEP-MATHA
collection:CMAP
collection:IP_PARIS
collection:CNRS
collection:AO-ECONOMIE
collection:INSMI
collection:X-CMAP
collection:X-DEP
collection:X-DEP-MATHA
collection:CMAP
collection:IP_PARIS
Subject Terms:
Original Identifier:
HAL: hal-03715954
Document Type:
Journal
article<br />Journal articles
Language:
English
ISSN:
0943-4062
1613-9658
1613-9658
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1007/s00180-023-01449-y
DOI:
10.1007/s00180-023-01449-y
Access URL:
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.hal.03715954v2
Database:
HAL
Further Information
Rating Migration Matrix is a crux to assess credit risks. Modeling and predicting these matrices are then an issue of great importance for risk managers in any financial institution. As a challenger to usual parametric modeling approaches, we propose a new structured dictionary learning model with auto-regressive regularization that is able to meet key expectations and constraints: small amount of data, fast evolution in time of these matrices, economic interpretability of the calibrated model. To show the model applicability, we present a numerical test with real data. The source code and the data are available at https://github.com/michael-allouche/ dictionary-learning-RMM.git for the sake of reproducibility of our research.