Forecasting net charge-off rates of banks : what model works best?
Year of publication: |
2018
|
---|---|
Authors: | Barth, James R. ; Han, Sumin ; Joo, Sunghoon ; Lee, Kang Bok ; Maglic, Stevan ; Shen, Xuan |
Published in: |
Quantitative finance and economics. - [Springfield, Mo.] : AIMS Press, ISSN 2573-0134, ZDB-ID 2937262-8. - Vol. 2.2018, 3, p. 554-589
|
Subject: | forecasting | banking | predictive models | ridge estimator | partial least squares | Prognoseverfahren | Forecasting model | Schätztheorie | Estimation theory | Bank | Kleinste-Quadrate-Methode | Least squares method | Partielle kleinste Quadrate | Partial least squares |
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2017)
-
Google data in bridge equation models for German GDP
Götz, Thomas B., (2019)
-
What charge‐off rates are predictable by macroeconomic latent factors?
Kim, Hyeongwoo, (2023)
- More ...
-
Forecasting net charge‐off rates of banks : a PLS approach
Barth, James R., (2018)
-
Another look at the determinants of the financial condition of state pension plans
Barth, James R., (2018)
-
Bank-client cross-ownership of bank stocks : a network analysis
Barth, James R., (2022)
- More ...