Firm default prediction by GNN with gravity-model informed neighbor node sampling
Year of publication: |
2024
|
---|---|
Authors: | Minakawa, Naoto ; Izumi, Kiyoshi ; Murayama, Yuri ; Sakaji, Hiroki |
Published in: |
The review of socionetwork strategies. - Tokyo : Springer Japan, ISSN 1867-3236, ZDB-ID 2471097-0. - Vol. 18.2024, 2, p. 303-328
|
Subject: | Credit risk management | Default prediction | Graph neural networks | Gravity model | Inter-firm network | Kreditrisiko | Credit risk | Neuronale Netze | Neural networks | Prognoseverfahren | Forecasting model | Insolvenz | Insolvency | Theorie | Theory | Unternehmensnetzwerk | Business network | Gravitationsmodell | Risikomanagement | Risk management | Kreditwürdigkeit | Credit rating | Stichprobenerhebung | Sampling |
-
Wavelets analysis on structural model for default prediction
Han, Lu, (2017)
-
A Deep Neural Network (DNN) based classification model in application to loan default prediction
Bayraci, Selçuk, (2019)
-
Predicting mortgage loan defaults using machine learning techniques
Krasovytskyi, Danylo, (2024)
- More ...
-
Estimation of cross-lingual news similarities using text-mining methods
Wang, Zhouhao, (2018)
-
Deep reinforcement learning in agent based financial market simulation
Maeda, Iwao, (2020)
-
Impact analysis of financial regulation on multi-asset markets using artificial market simulations
Hirano, Masanori, (2020)
- More ...