Predicting returns with machine learning across horizons, firm size, and time
Year of publication: |
2023
|
---|---|
Authors: | Cakici, Nusret ; Fieberg, Christian ; Metko, Daniel ; Zaremba, Adam |
Published in: |
The journal of financial data science. - New York, NY : Pageant Media, Ltd., ISSN 2640-3951, ZDB-ID 2957666-0. - Vol. 5.2023, 4, p. 119-144
|
Subject: | Künstliche Intelligenz | Artificial intelligence | Betriebsgröße | Firm size | Prognoseverfahren | Forecasting model | Kapitaleinkommen | Capital income |
-
Machine learning goes global : cross-sectional return predictability in international stock markets
Cakici, Nusret, (2023)
-
Abnormal returns from takeover prediction modelling : challenges and suggested investment strategies
Danbolt, Jo, (2016)
-
Machine Learning Predicts Electrospray Particle Size
Parhizkar, Maryam, (2022)
- More ...
-
Machine Learning Goes Global : Cross-Sectional Return Predictability in International Stock Markets
Cakici, Nusret, (2022)
-
Machine learning goes global : cross-sectional return predictability in international stock markets
Cakici, Nusret, (2023)
-
Do anomalies really predict market returns? : new data and new evidence
Cakici, Nusret, (2024)
- More ...