Blog
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DRL Agent Deployment: What Breaks Between Training and Live
Most DRL agent deployment failures are not model failures — they are feature parity failures, and they produce no error message. Consider a DRL agent that converges cleanly: reward curves…
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What Goes in a DRL Trading Agent’s Observation Vector
Consider a PPO agent trained for 2 million steps on EURUSD 15-minute data that shows flat reward curves across all 5 seeds. Switching to SAC changes nothing. Adjusting the learning…
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Which DRL Algorithm for FX Trading — and Why the Max Drawdown Number Tells You Everything
In a 2025 benchmark on petroleum futures, DQN and PPO finished with almost the same annualized return and almost the same Sharpe ratio. Their maximum drawdowns were 22 times apart.…