Arbeitspapier
Improving the forecasts of European regional banks' profitability with machine learning algorithms
Regional banks as savings and cooperative banks are widespread in continental Europe. In the aftermath of the financial crisis, however, they had problems keeping their profitability which is an important quantitative indicator for the health of a bank and the banking sector overall. We use a large data set of bank-level balance sheet items and regional economic variables to forecast protability for about 2,000 regional banks. Machine learning algorithms are able to beat traditional estimators as ordinary least squares as well as autoregressive models in forecasting performance.
- ISBN
-
978-3-86788-819-6
- Sprache
-
Englisch
- Erschienen in
-
Series: Ruhr Economic Papers ; No. 705
- Klassifikation
-
Wirtschaft
Forecasting Models; Simulation Methods
Large Data Sets: Modeling and Analysis
Banks; Depository Institutions; Micro Finance Institutions; Mortgages
- Thema
-
profitability
regional banking
forecasting
machine learning
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Haskamp, Ulrich
- Ereignis
-
Veröffentlichung
- (wer)
-
RWI - Leibniz-Institut für Wirtschaftsforschung
- (wo)
-
Essen
- (wann)
-
2017
- DOI
-
doi:10.4419/86788819
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Haskamp, Ulrich
- RWI - Leibniz-Institut für Wirtschaftsforschung
Entstanden
- 2017
Ähnliche Objekte (12)
Improving the Forecasts of European Regional Banks’ Profitability with Machine Learning Algorithms
Improving profitability forecasts with information on earnings quality
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Exploiting ergodicity in forecasts of corporate profitability
Essays on the suitability of machine learning algorithms for financial forecasts
Improving and interpreting machine learning algorithms with applications
Improving promotional demand forecasts in retailing
Improving precipitation forecasts using extreme quantile regression
Improving oil price forecasts by sparse VAR methods
Improving forecasts of financial models with deep learning
Improving Oil Price Forecasts by Sparse VAR Methods
Improving the Forecasts of European Regional Banks’ Profitability with Machine Learning Algorithms
Improving profitability forecasts with information on earnings quality
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Exploiting ergodicity in forecasts of corporate profitability
Essays on the suitability of machine learning algorithms for financial forecasts
Improving and interpreting machine learning algorithms with applications
Improving promotional demand forecasts in retailing
Improving precipitation forecasts using extreme quantile regression
Improving oil price forecasts by sparse VAR methods
Improving forecasts of financial models with deep learning
Improving Oil Price Forecasts by Sparse VAR Methods
Improving the Forecasts of European Regional Banks’ Profitability with Machine Learning Algorithms
Improving profitability forecasts with information on earnings quality
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Improving 3-day deterministic air pollution forecasts using machine learning algorithms
Exploiting ergodicity in forecasts of corporate profitability
Essays on the suitability of machine learning algorithms for financial forecasts
Improving and interpreting machine learning algorithms with applications
Improving promotional demand forecasts in retailing
Improving precipitation forecasts using extreme quantile regression
Improving oil price forecasts by sparse VAR methods
Improving forecasts of financial models with deep learning