Machine Learning on Market Data

Features and targets from prices, the low signal to noise ratio, purged time series cross validation, and regularized regression and trees as examples.

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How this module runs

  1. 01 · IntroductionWhat it is and why it matters
  2. 02 · Key PointsThe most important points
  3. 03 · The Math + PythonFormula, step by step, code
  4. 04 · Real WorldWhere it is used, best practice, common mistakes
  5. 05 · QuestionsExercises and interview
  6. Mini projectOne small program
Mini projectNext day returns predicted and measured against a naive forecastOne small program on the topic, to run and to extend step by step.

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