Portfolio Allocation with Dynamic Risk Preferences via Reinforcement Learning
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Economics, Econometrics and Finance (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10614-023-10509-w.pdf
Reference15 articles.
1. Basak, S., & Chabakauri, G. (2010). Dynamic mean-variance asset allocation. The Review of Financial Studies, 23(8), 2970–3016.
2. Björk, T., Murgoci, A., & Zhou, X. Y. (2014). Mean-variance portfolio optimization with state-dependent risk aversion. Mathematical Finance: An International Journal of Mathematics, Statistics and Financial Economics, 24(1), 1–24.
3. Díaz, A., & Esparcia, C. (2019). Assessing risk aversion from the investor’s point of view. Frontiers in Psychology, 10, 1490.
4. Huang, S. H., Miao, Y. H., & Hsiao, Y. T. (2021). Novel deep reinforcement algorithm with adaptive sampling strategy for continuous portfolio optimization. IEEE Access, 9, 77371–77385.
5. Jiang, Z., & Liang, J. (2017). Cryptocurrency portfolio management with deep reinforcement learning. In Intelligent systems conference (IntelliSys) (pp. 905–913).
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