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What are the current popular approaches to leveraging AI for stock price prediction? It seems like there could be several approaches and problem formulations:

  • Supervised learning:
    • Regression: predict the stock price directly
    • Classification: predict whether the stock price goes up or down
  • Unsupervised learning: find clusters of stocks that move together
  • Reinforcement learning: let the agent directly maximize its stock market return
  • Other AI methods: rules, symbolic systems etc.

Which are most popular/performant? Are there other ways that people are using machine learning in stock trading (sentiment analysis on financial statments, news etc.).

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Your list is complete for what is considered 'popular' by most practitioners who apply AI for stock trading. Supervised learning and rule learning are at the top for accuracy. There are more academic papers published on classifiers than on regression approaches; classifiers are typically more accurate than regressors.

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