A volatility-guided deep reinforcement learning framework splits Dow 30 stocks into aggressive, moderate, and conservative tiers and claims higher risk-adjusted returns than benchmarks in a two-year out-of-sample test.
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Deep Reinforcement Learning for Investor-Specific Portfolio Optimization: A Volatility-Guided Asset Selection Approach
A volatility-guided deep reinforcement learning framework splits Dow 30 stocks into aggressive, moderate, and conservative tiers and claims higher risk-adjusted returns than benchmarks in a two-year out-of-sample test.