Portfolio optimization by enhanced LinUCB
| Year of publication: |
2024
|
|---|---|
| Authors: | Ni, He ; Zhang, Qin ; Guo, Xingjian ; Mirza, Sultan Sikandar |
| Published in: |
Finance research letters. - New York : Elsevier Science, ISSN 1544-6123, ZDB-ID 2145766-9. - Vol. 70.2024, Art.-No. 106266, p. 1-8
|
| Subject: | Bandit learning | Contextual LinUCB | Portfolio management | Portfolio-Management | Portfolio selection | Theorie | Theory | Lernen | Learning | Lernprozess | Learning process | Mathematische Optimierung | Mathematical programming |
-
What is the value of the cross-sectional approach to deep reinforcement learning?
Aboussalah, Amine Mohamed, (2022)
-
Optimal investment in ambiguous financial markets with learning
Bäuerle, Nicole, (2024)
-
Learning to optimize contextually constrained problems for real-time decision generation
Babier, Aaron, (2025)
- More ...
-
Zhang, Qin, (2023)
-
Nowcasting Chinese GDP in a data-rich environment : lessons from machine learning algorithms
Zhang, Qin, (2023)
-
Self-Adaptive bagging approach to credit rating
Ni, He, (2022)
- More ...