This project reimagines the classical Merton portfolio optimization problem using Deep Reinforcement Learning (DRL). Instead of static, closed-form allocation rules, we design an intelligent agent that dynamically adjusts exposures to risky and risk-free assets under changing market regimes.
reinforcement-learning deep-reinforcement-learning dqn gaussian-mixture-models portfolio-optimization quantitative-finance algorithmic-trading markov-decision-processes stochastic-processes drl hidden-markov-models asset-management stochastic-control regime-switching financial-machine-learning quant-finance dynamic-asset-allocation utility-optimization market-regime-detection merton-problem
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Updated
Oct 5, 2025 - Python