"Machine Learning for Algorithmic Trading" with author Stefan Jansen

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In this session of the Quantopian Book Conversations series, we welcome Stefan Jansen, author of the widely acclaimed book Machine Learning for Algorithmic Trading. Stefan shares the story behind the book’s creation, the challenges of working with financial data, and how his work bridges the gap between machine learning theory and practical application in quantitative finance.

Topics covered include:

The evolution of the book across editions

Domain-specific challenges in applying ML to finance

Reinforcement learning and synthetic data

The importance of simplicity, data quality, and domain knowledge

Insights on alternative data, high-frequency trading, and the future of algorithmic trading

Language models and the potential role of quantum computing

This in-depth conversation is a must-watch for aspiring quants, data scientists, and anyone interested in the intersection of finance and machine learning.

🔗 Stefan Jansen's book: https://www.amazon.com/Machine-Learni...

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Disclaimer
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