Machine learning techniques for cross-sectional equity returns' prediction
Year of publication: |
2023
|
---|---|
Authors: | Fieberg, Christian ; Metko, Daniel ; Poddig, Thorsten ; Loy, Thomas |
Published in: |
OR spectrum : quantitative approaches in management. - Berlin : Springer, ISSN 1436-6304, ZDB-ID 1467029-X. - Vol. 45.2023, 1, p. 289-323
|
Subject: | Finance | Machine learning | Stock return prediction | Künstliche Intelligenz | Artificial intelligence | Prognoseverfahren | Forecasting model | Kapitaleinkommen | Capital income | Kapitalmarktrendite | Capital market returns |
-
Empirical asset pricing via machine learning : evidence from the European stock market
Drobetz, Wolfgang, (2021)
-
Machine learning portfolio allocation
Pinelis, Michael, (2022)
-
Asset returns in deep learning methods : an empirical analysis on SSE 50 and CSI 300
Li, Weiping, (2020)
- More ...
-
Machine learning techniques for cross-sectional equity returns’ prediction
Fieberg, Christian, (2022)
-
Machine learning in accounting research
Fieberg, Christian, (2022)
-
Machine learning for categorization of operational risk events using textual description
Pakhchanyan, Suren, (2022)
- More ...