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Continuous‐time mean–variance portfolio selection: A reinforcement learning framework

Citations

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Cited by:

  1. Mononen, Lasse, 2025. "On Preference for Simplicity and Probability Weighting," Center for Mathematical Economics Working Papers 748, Center for Mathematical Economics, Bielefeld University.
  2. Xiaofei Shi & Daran Xu & Zhanhao Zhang, 2021. "Deep Learning Algorithms for Hedging with Frictions," Papers 2111.01931, arXiv.org, revised Dec 2022.
  3. Wing Fung Chong & Haoen Cui & Yuxuan Li, 2021. "Pseudo-Model-Free Hedging for Variable Annuities via Deep Reinforcement Learning," Papers 2107.03340, arXiv.org, revised Oct 2022.
  4. De Gennaro Aquino, Luca & Sornette, Didier & Strub, Moris S., 2023. "Portfolio selection with exploration of new investment assets," European Journal of Operational Research, Elsevier, vol. 310(2), pages 773-792.
  5. Yun Zhao & Alex S. L. Tse & Harry Zheng, 2026. "Reinforcement Learning for Speculative Trading under Exploratory Framework," Papers 2604.02035, arXiv.org.
  6. Yuling Max Chen & Bin Li & David Saunders, 2025. "Exploratory Mean-Variance Portfolio Optimization with Regime-Switching Market Dynamics," Papers 2501.16659, arXiv.org.
  7. Magni, Carlo Alberto & Marchioni, Andrea & Baschieri, Davide, 2023. "The Attribution Matrix and the joint use of Finite Change Sensitivity Index and Residual Income for value-based performance measurement," European Journal of Operational Research, Elsevier, vol. 306(2), pages 872-892.
  8. Junyan Ye & Hoi Ying Wong & Kyunghyun Park, 2025. "Robust Exploratory Stopping under Ambiguity in Reinforcement Learning," Papers 2510.10260, arXiv.org, revised Apr 2026.
  9. Min Dai & Hanqing Jin & Xi Yang, 2024. "Data-driven Option Pricing," Papers 2401.11158, arXiv.org.
  10. Carlo Alberto Magni & Andrea Marchioni, 2022. "Performance attribution, time-weighted rate of return, and clean finite change sensitivity index," Journal of Asset Management, Palgrave Macmillan, vol. 23(1), pages 62-72, February.
  11. Xuefeng Gao & Lingfei Li & Xun Yu Zhou, 2024. "Reinforcement Learning for Jump-Diffusions, with Financial Applications," Papers 2405.16449, arXiv.org, revised Aug 2025.
  12. Shanyu Han & Yang Liu & Xiang Yu, 2025. "Risk-sensitive Reinforcement Learning Based on Convex Scoring Functions," Papers 2505.04553, arXiv.org, revised May 2025.
  13. Xiaofei Shi & Daran Xu & Zhanhao Zhang, 2023. "Deep learning algorithms for hedging with frictions," Digital Finance, Springer, vol. 5(1), pages 113-147, March.
  14. Yu Li & Yuhan Wu & Shuhua Zhang, 2025. "The Exploratory Multi-Asset Mean-Variance Portfolio Selection using Reinforcement Learning," Papers 2505.07537, arXiv.org.
  15. Min Dai & Yuchao Dong & Yanwei Jia & Xun Yu Zhou, 2023. "Data-Driven Merton's Strategies via Policy Randomization," Papers 2312.11797, arXiv.org, revised Feb 2026.
  16. Jose Blanchet & Jiayi Cheng & Yuewei Ling & Hao Liu & Yang Liu, 2025. "Duality and Policy Evaluation in Distributionally Robust Bayesian Diffusion Control," Papers 2506.19294, arXiv.org, revised Jan 2026.
  17. Sang Hu & Zihan Zhou, 2024. "Exploratory Dividend Optimization with Entropy Regularization," JRFM, MDPI, vol. 17(1), pages 1-23, January.
  18. Chen Ziyi & Gu Jia-wen, 2025. "Exploratory Utility Maximization Problem with Tsallis Entropy," Papers 2502.01269, arXiv.org.
  19. Yuling Max Chen & Bin Li & David Saunders, 2025. "Exploratory Mean-Variance with Jumps: An Equilibrium Approach," Papers 2512.09224, arXiv.org.
  20. Alexandre Carbonneau & Fr'ed'eric Godin, 2021. "Deep equal risk pricing of financial derivatives with non-translation invariant risk measures," Papers 2107.11340, arXiv.org.
  21. Yu-Jui Huang & Shihao Zhu, 2025. "Mean-Variance Stackelberg Games with Asymmetric Information," Papers 2509.03669, arXiv.org.
  22. Xia Han & Ruodu Wang & Xun Yu Zhou, 2022. "Choquet regularization for reinforcement learning," Papers 2208.08497, arXiv.org.
  23. Xiangyu Cui & Xun Li & Yun Shi & Si Zhao, 2023. "Discrete-Time Mean-Variance Strategy Based on Reinforcement Learning," Papers 2312.15385, arXiv.org.
  24. Sebastien Lleo & Wolfgang Runggaldier, 2026. "Exploratory Randomization for Discrete-Time Risk-Sensitive Benchmarked Investment Management with Reinforcement Learning," Papers 2603.00738, arXiv.org.
  25. Dong-Mei Zhu & Jia-Wen Gu & Feng-Hui Yu & Tak-Kuen Siu & Wai-Ki Ching, 2021. "Optimal pairs trading with dynamic mean-variance objective," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(1), pages 145-168, August.
  26. Jiang, Yifu & Olmo, Jose & Atwi, Majed, 2024. "Deep reinforcement learning for portfolio selection," Global Finance Journal, Elsevier, vol. 62(C).
  27. Jiang, Yifu & Olmo, Jose & Atwi, Majed, 2025. "High-dimensional multi-period portfolio allocation using deep reinforcement learning," International Review of Economics & Finance, Elsevier, vol. 98(C).
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