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asset-liability-management

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chirindaopensource / continuous_time_rl_for_alm

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End-to-end Python implementation of Huang's (2025) continuous-time RL methodology for asset-liability management. Features model-free soft actor-critic with adaptive exploration, entropy regularization, and Euler-Maruyama SDE simulation. Includes 7 baselines (SAC/PPO/DDPG/CPPI/ACS/MBP), parallelized execution, and Wilcoxon statistical validation.

python reinforcement-learning deep-reinforcement-learning pytorch policy-gradient portfolio-optimization quantitative-finance numerical-methods optimal-control algorithmic-trading stochastic-differential-equations gymnasium actor-critic risk-management financial-engineering stochastic-control continuous-time soft-actor-critic asset-liability-management entropy-regularization
  • Updated Oct 5, 2025
  • Jupyter Notebook

yasin-is-9-year-old / continuous_time_rl_for_alm

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🤖 Leverage continuous-time reinforcement learning to optimize asset-liability management and enhance financial decision-making.

python reinforcement-learning deep-reinforcement-learning pytorch policy-gradient portfolio-optimization quantitative-finance numerical-methods optimal-control algorithmic-trading stochastic-differential-equations gymnasium risk-management stochastic-control continuous-time soft-actor-critic asset-liability-management entropy-regularization
  • Updated Jan 11, 2026
  • Jupyter Notebook

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