Deep Learning and Reinforcement Learning in Algorithmic Trading (2018–2025)

A practical survey of deep learning (LSTM/CNN/Transformers) and deep reinforcement learning (DQN/PPO/A2C) for trading across equities, futures, and crypto—what works, what breaks, and how to deploy with realistic risk controls.

Algorithmic trading workflow with robustness filters and portfolio checks

Contents

  1. Why this matters
  2. Fast reader map
  3. Deep learning for prediction
  4. Deep reinforcement learning
  5. Market-specific observations
  6. Pragmatic benchmark table
  7. Best practice for live trading
  8. Bottom line
  9. References