Dynamic portfolio rebalancing through reinforcement learning
Portfolio managements in financial markets involve risk management strategies and opportunistic responses to individual trading behaviours. Optimal portfolios constructed aim to have a minimal risk with highest accompanying investment returns, regardless of market conditions. This paper focuses on p...
Main Authors: | Lim, Eddy Qing Yang, Cao, Qi, Quek, Cai |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/162716 |
Similar Items
-
Learning and processing framework using Fuzzy Deep Neural Network for trading and portfolio rebalancing
by: Kan, Nicole Hui Lin, et al.
Published: (2024) -
Private Risk
by: Kaufman, Gordon M., et al.
Published: (2003) -
Financial portfolio optimization: an autoregressive deep reinforcement learning algorithm with learned intrinsic rewards
by: Lim, Magdalene Hui Qi
Published: (2024) -
Portfolio Rebalancing: A Test of the Markowitz-Van Dijk Heuristic
by: Kritzman, Mark, et al.
Published: (2007) -
Big data challenges of high-dimensional continuous-time mean-variance portfolio selection and a remedy
by: Chiu, Mei Choi, et al.
Published: (2019)