Forecasting credit ratings of decarbonized firms : comparative assessment of machine learning models
Year of publication: |
2022
|
---|---|
Authors: | Yu, Baojun ; Li, Changming ; Mirza, Nawazish ; Umar, Muhammad |
Published in: |
Technological forecasting & social change : an international journal. - Amsterdam : Elsevier, ISSN 0040-1625, ZDB-ID 280700-2. - Vol. 174.2022, p. 1-16
|
Subject: | Machine learning | Carbon neutrality | Credit ratings | Low carbon transitions | Künstliche Intelligenz | Artificial intelligence | Treibhausgas-Emissionen | Greenhouse gas emissions | Kreditwürdigkeit | Credit rating | Klimaschutz | Climate protection | Prognoseverfahren | Forecasting model | Lernprozess | Learning process | Emissionshandel | Emissions trading |
-
Carbon dioxide emission typology and policy implications : evidence from machine learning
Wang, Hanjie, (2023)
-
Using meta learning methods to forecast sub-sovereign credit ratings
Evelyn, Toseafa, (2019)
-
Using meta learning methods to forecast sub-sovereign credit ratings
Evelyn, Toseafa, (2018)
- More ...
-
Rubbaniy, Ghulame, (2021)
-
When interest rates rise, ESG is still relevant : the case of banking firms
Sun, Tingting, (2024)
-
Rubbaniy, Ghulame, (2021)
- More ...