Labeling and Meta-Labeling Returns for ML Prediction

Labeling and Meta-Labeling Returns for ML Prediction

This post focuses on Chapter 3 in the new book Advances in Financial Machine Learning by Marcos Lopez De Prado.  In this chapter De Prado demonstrates a workflow for improved return labeling for the purposes of supervised classification models. He introduces multiple concepts but focuses on the Triple-Barrier Labeling method, which incorporates profit-taking, stop-loss, and holding period information, and  also meta-labeling which is a technique designed to address several issues.

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How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio

How to Scrape and Parse 600 ETF Options in 10 mins with Python and Asyncio

Post Outline

  • Intro
  • Disclaimers
  • The Secret to Scraping AJAX Sites
  • The async_option_scraper script
    • first_async_scraper class
    • expirys class
    • xp_async_scraper class
    • last_price_scraper class
  • The option_parser Module
  • The Implementation Script
  • References
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